Donald Trump’s Media Conglomerate Is Becoming a Bitcoin Reserve

Trump Media and Technology Group, a publicly traded company in which US president Donald Trump and his family own a majority stake, has raised $2.5 billion to accumulate a “bitcoin treasury.”

On Monday, in response to a report by the Financial Times, TMTG initially denied contemplating any such maneuver. “The Financial Times has dumb writers listening to even dumber sources,” the company reportedly said. But Trump Media and Technology Group appears to have since changed its tune.

In a press release on Tuesday, TMTG confirmed that it has agreed to sell $1.5 billion worth of equity and take on a further $1 billion in debt—and plans to use the proceeds to add vast quantities of bitcoin to its balance sheet.

The deal puts TMTG in competition with a growing stable of bitcoin accumulation stocks, which act as a substitute of sorts for investing in bitcoin, without investors having to handle crypto themselves. In theory, as the price of bitcoin rises and falls, so should the stock price of the companies with large bitcoin treasuries.

“We view bitcoin as an apex instrument of financial freedom, and now Trump Media will hold cryptocurrency as a crucial part of our assets,” said TMTG CEO Devin Nunes in a statement. “It’s a big step forward in the company’s plans to evolve into a holding company by acquiring additional profit-generating, crown jewel assets consistent with America First principles.”

TMTG’s embrace of crypto represents a small part of a more elaborate picture: Within the past year, Trump and his family have forged into almost every segment of the crypto market, despite a chorus of complaints relating to alleged abuses of office and conflicts of interest.

In January, in the days leading up to the inauguration, Trump and his wife Melania both issued their own crypto coins, adding billions of dollars to their paper net worth. That same month, TMTG announced the launch of Truth.Fi, its new fintech division, which partnered shortly thereafter with crypto exchange Crypto.com with a view to offering crypto-related investment products to the public. The president’s sons Eric Trump and Donald Trump Jr. meanwhile, have promoted a separate crypto services company, World Liberty Financial, and recently established a bitcoin mining business, American Bitcoin.

The crypto ventures associated with the Trump family have raised hundreds of millions of dollars—partly by selling crypto coins to the investing public and partly by acquiring assets in deals cut with business partners.

“Look back at some of Donald Trump’s ventures over time … he essentially brings the marketing and a built-in audience in return for a relatively large cut,” says Austin Campbell, adjunct professor at NYU Stern School of Business and managing partner at crypto consultancy Zero Knowledge. “American Bitcoin is literally that playbook.”

In May, Eric Trump announced plans to take American Bitcoin public. Like TMTG, the company intends to accrue a large bitcoin treasury and turn itself into a bitcoin accumulation stock. “Our vision for American Bitcoin is to create the most investable bitcoin accumulation platform in the market,” he said when he announced the plan.

Who’s to Blame When AI Agents Screw Up?

Over the past year, veteran software engineer Jay Prakash Thakur has spent his nights and weekends prototyping AI agents that could, in the near future, order meals and engineer mobile apps almost entirely on their own. His agents, while surprisingly capable, have also exposed new legal questions that await companies trying to capitalize on Silicon Valley’s hottest new technology.

Agents are AI programs that can act mostly independently, allowing companies to automate tasks such as answering customer questions or paying invoices. While ChatGPT and similar chatbots can draft emails or analyze bills upon request, Microsoft and other tech giants expect that agents will tackle more complex functions—and most importantly, do it with little human oversight.

The tech industry’s most ambitious plans involve multi-agent systems, with dozens of agents someday teaming up to replace entire workforces. For companies, the benefit is clear: saving on time and labor costs. Already, demand for the technology is rising. Tech market researcher Gartner estimates that agentic AI will resolve 80 percent of common customer service queries by 2029. Fiverr, a service where businesses can book freelance coders, reports that searches for “ai agent” have surged 18,347 percent in recent months.

Thakur, a mostly self-taught coder living in California, wanted to be at the forefront of the emerging field. His day job at Microsoft isn’t related to agents, but he has been tinkering with AutoGen, Microsoft’s open source software for building agents, since he worked at Amazon back in 2024. Thakur says he has developed multi-agent prototypes using AutoGen with just a dash of programming. Last week, Amazon rolled out a similar agent development tool called Strands; Google offers what it calls an Agent Development Kit.

Because agents are meant to act autonomously, the question of who bears responsibility when their errors cause financial damage has been Thakur’s biggest concern. Assigning blame when agents from different companies miscommunicate within a single, large system could become contentious, he believes. He compared the challenge of reviewing error logs from various agents to reconstructing a conversation based on different people’s notes. “It’s often impossible to pinpoint responsibility,” Thakur says.

Benjamin Softness, an attorney who recently left Google to join law firm King & Spalding, said on stage at a recent legal conference hosted by the Media Law Resource Center in San Francisco that aggrieved parties tend to go after those with the deepest pockets. That means companies will need to be prepared to take some responsibility when agents cause harm—even when a kid messing around with an agent might be to blame. (If that person were at fault, they likely wouldn’t be a worthwhile target moneywise). “I don’t think anybody is hoping to get through to the consumer sitting in their mom’s basement on the computer,” Softness said. The insurance industry has begun rolling out coverage for AI chatbot issues to help companies cover the costs of mishaps.

Onion Rings

Thakur’s experiments have involved him stringing together agents in systems that require as little human intervention as possible. One project he pursued was replacing fellow software developers with two agents. One was trained to search for specialized tools needed for making apps, and the other summarized their usage policies. In the future, a third agent could use the identified tools and follow the summarized policies to develop an entirely new app, Thakur says.

When Thakur put his prototype to the test, a search agent found a tool that, according to the website, “supports unlimited requests per minute for enterprise users” (meaning high-paying clients can rely on it as much as they want). But in trying to distill the key information, the summarization agent dropped the crucial qualification of “per minute for enterprise users.” It erroneously told the coding agent, which did not qualify as an enterprise user, that it could write a program that made unlimited requests to the outside service. Because this was a test, there was no harm done. If it had happened in real life, the truncated guidance could have led to the entire system unexpectedly breaking down.

Politico’s Newsroom Is Starting a Legal Battle With Management Over AI

Politico became one of the first newsrooms last year to win a union contract that included rules on how the media outlet can deploy artificial intelligence. The PEN Guild, which represents Politico and its sister publication, environment and energy site E&E News, is now gearing up for another first. The union’s members allege that the AI provisions in their contract have been violated, and they’re preparing for a groundbreaking legal dispute with management. The outcome could set a precedent for how much input journalists ultimately have over how AI is used in their newsrooms.

Last year, Politico began publishing AI-generated live news summaries during big political events like the Democratic National Convention and the US vice presidential debates. This March, it debuted a suite of AI tools called Policy Intelligence Assistance for paying subscribers, which were built in partnership with the Y Combinator-backed startup Capitol AI. Politico executive Rachel Loeffler described the initiative at the time as “seamlessly integrating generative AI with our unmatched policy expertise.”

Politico union members, however, allege these tools violated their contract in several ways, and are taking the dispute to arbitration this July. “The company is required to give us 60 days notice of any use of new technology that will materially and substantively impact bargaining unit job duties,” says PEN union chair and E&E public health reporter Ariel Wittenberg. The union claims that it was given neither notice nor an opportunity to bargain in good faith over Politico’s AI rollout, and that the tools do work that would ordinarily be done by human staff.

“This isn’t just a contract dispute, it’s a test of whether journalists have a say in how AI is used in our work. With no federal rules in place, union contracts remain one of the only enforceable frameworks for AI accountability on a national scale,” says Newsguild president Jon Schleuss. (PEN Guild is a unit within Newsguild, one of the most prominent unions for journalists.)

Politico says the publication “takes the obligations under its collective bargaining agreement seriously,” and “will continue to honor those obligations while also rapidly embracing transformative technologies such as AI that will revolutionize how our audience consumes news and information,” according to spokesperson Heather Riley.

Politico’s contract stipulates that the publication needs to use AI in a manner that follows the company’s standards of journalistic ethics. “We’re not against AI, but it should be held to the same ethical and style standards as our political journalists,” says Arianna Skibell, the union’s vice chair for contract enforcement, who writes Politico’s energy industry newsletter. Some union members question whether there’s always appropriate human oversight over the AI content Politico publishes.

In one case, an AI-generated live summary used language about immigration that human writers are not permitted to use, publishing phrases like “criminal migrants” as it covered the vice presidential debates.

“There were also factual errors that the AI inserted that night,” alleges Skibell. For example, she says, the AI credited actions taken by the Biden administration as things Kamala Harris did. That post was later swapped for replacements without the errors, according to screenshots reviewed by WIRED. “At Politico, you can’t just wholly take down articles written by human reporters without going through a series of approvals, all the way up to newsroom leadership. That did not happen for the AI live summaries,” Wittenberg claims. (Politico did not comment on the specifics of the union’s allegations.)

Anthropic’s New Model Excels at Reasoning and Planning—and Has the Pokémon Skills to Prove It

When Claude 3.7 Sonnet played the game, it ran into some challenges: It spent “dozens of hours” stuck in one city and had trouble identifying nonplayer characters, which drastically stunted its progress in the game. With Claude 4 Opus, Hershey noticed an improvement in Claude’s long-term memory and planning capabilities when he watched it navigate a complex Pokémon quest. After realizing it needed a certain power to move forward, the AI spent two days improving its skills before continuing to play. Hershey believes that kind of multistep reasoning, with no immediate feedback, shows a new level of coherence, meaning the model has a better ability stay on track.

“This is one of my favorite ways to get to know a model. Like, this is how I understand what its strengths are, what its weaknesses are,” Hershey says. “It’s my way of just coming to grips with this new model that we’re about to put out, and how to work with it.”

Everyone Wants an Agent

Anthropic’s Pokémon research is a novel approach to tackling a preexisting problem—how do we understand what decisions an AI is making when approaching complex tasks, and nudge it in the right direction?

The answer to that question is integral to advancing the industry’s much-hyped AI agents—AI that can tackle complex tasks with relative independence. In Pokémon, it’s important that the model doesn’t lose context or “forget” the task at hand. That also applies to AI agents asked to automate a workflow—even one that takes hundreds of hours.

“As a task goes from being a five-minute task to a 30-minute task, you can see the model’s ability to keep coherent, to remember all of the things it needs to accomplish [the task] successfully get worse over time,” Hershey says.

Anthropic, like many other AI labs, is hoping to create powerful agents to sell as a product for consumers. Krieger says that Anthropic’s “top objective” this year is Claude “doing hours of work for you.”

“This model is now delivering on it—we saw one of our early-access customers have the model go off for seven hours and do a big refactor,” Krieger says, referring to the process of restructuring a large amount of code, often to make it more efficient and organized.

This is the future that companies like Google and OpenAI are working toward. Earlier this week, Google released Mariner, an AI agent built into Chrome that can do tasks like buy groceries (for $249.99 per month). OpenAI recently released a coding agent, and a few months back it launched Operator, an agent that can browse the web on a user’s behalf.

Compared to its competitors, Anthropic is often seen as the more cautious mover, going fast on research but slower on deployment. And with powerful AI, that’s likely a positive: There’s a lot that could go wrong with an agent that has access to sensitive information like a user’s inbox or bank logins. In a blog post on Thursday, Anthropic says, “We’ve significantly reduced behavior where the models use shortcuts or loopholes to complete tasks.” The company also says that both Claude 4 Opus and Claude Sonnet 4 are 65 percent less likely to engage in this behavior, known as reward hacking, than prior models—at least on certain coding tasks.

Kentucky’s Bitcoin Boom Has Gone Bust

Her skepticism is rooted in lived experience: In October 2000, a massive coal slurry spill from a mine site upstream poisoned the Coldwater Fork stream, which runs behind her house. People in Inez couldn’t drink water from the tap for months.

“Those of us living downstream didn’t hear about it for a while, but the school system had to close down for about a week until they got an alternate water source,” she says.

To this day, many in Inez still don’t trust the tap water.

So when McCoy hears the hype about AI, she hears something else: another promise that comes with a cost. “We’ve allowed these people to be called job creators,” she said. “And I don’t care if it’s AI or crypto or whatever, we bow down to them and let them tell us what they are going to do to our community because they are job creators. They’re not job creators, they’re profit makers.”

And the profit leaves a footprint.

AI data centers demand staggering amounts of energy—a ChatGPT search uses up to 10 times more energy than a regular Google one—and they run hot. To keep them cool, these facilities consume billions of gallons of water every year. Most of that evaporates, but residents are wary because they have had problems with facilities and their runoff in the past, so they worry these new facilities could affect fish and disrupt the land. The very things the residents of Kentucky hope to preserve.

Still, some locals see potential, even progress.

“AI is in everything that we do,” said Wes Hamilton, a local entrepreneur who did his fair share of crypto mining in Kentucky in its heyday. “Siri, ChatGPT, robotics—everything you can imagine has to have AI,” he said. “Bitcoin is a one-trick pony. You create it. The only person that gets paid is the owner of the machines.”

Hamilton claims there is a path forward where data centers bring in investors, engineers, maybe even companies willing to stay. All the AI people in the world would be steaming into Kentucky, Hamilton says. And while he admits to losing a fortune in crypto ventures in the past, he claims this is different.

When Bitcoin first arrived, lawmakers offered generous tax breaks to lure miners. Companies investing more than $1 million were exempted from paying sales taxes on hardware and electricity. And then, in March 2025, Kentucky governor Andy Beshear took all that and went a step further by signing a “Bitcoin Rights” bill into law.

The legislation, cast as a defense of personal financial freedom, is designed to enshrine the right to use digital assets in Kentucky. An earlier draft went further, aiming to bar local governments from using zoning laws to restrict crypto mining operations—a provision that drew resistance from environmental groups. That language was eventually tempered, but the intent remains: to signal that, in Kentucky, digital extraction can keep humming.

Which is why we found ourselves outside this facility in Campton, staring at this semicircle of metal buildings nestled in the trees. The mines run all night and all day, even Sundays. And the question some are asking now, with bitcoin hovering around $100,000 and big miners talking about pivoting to AI, is whether bitcoin mining gets a second wind in Kentucky.

Mohawk’s bitcoin mining may even make a comeback. Anna Whites said the parties are supposed to go into arbitration May 12th. “I’m hopeful,” she told us. “I’m very hopeful that they sit down and say, ‘Mighty nice plant you have there. Let’s just go ahead and turn it on.’”

Let’s Talk About ChatGPT and Cheating in the Classroom

Michael Calore: That’s pretty good. Katie?

Katie Drummond: My recommendation is very specific and very strange. It is a 2003 film called What a Girl Wants, starring Amanda Bynes and Colin Firth.

Michael Calore: Wow.

Katie Drummond: I watched this movie in high school, where I was cheating on my math exams. Sorry. For some reason, just the memory of me cheating on my high school math exams makes me laugh, and then I rewatched it with my daughter this weekend, and it’s so bad and so ludicrous and just so fabulous. Colin Firth is a babe. Amanda Bynes is amazing, and I wish her the best. And it’s a very fun, stupid movie if you want to just disconnect your brain and learn about the story of a 17-year-old girl who goes to the United Kingdom to meet the father she never knew.

Michael Calore: Wow.

Lauren Goode: Wow.

Katie Drummond: Thank you. It’s really good.

Lauren Goode: I can’t decide if you’re saying it’s good or it’s terrible.

Katie Drummond: It’s both. You know what I mean?

Lauren Goode: It’s some combination of both.

Katie Drummond: It’s so bad. She falls in love with a bad boy with a motorcycle but a heart of gold who also happens to sing in the band that plays in UK Parliament, so he just happens to be around all the time. He has spiky hair. Remember 2003? All the guys had gel, spiky hair.

Lauren Goode: Yes, I still remember that. Early 2000s movies, boy, did they not age well.

Katie Drummond: This one, though, aged like a fine wine.

Michael Calore: That’s great.

Katie Drummond: It’s excellent.

Lauren Goode: It’s great.

Katie Drummond: Mike, what do you recommend?

Lauren Goode: Yeah.

Michael Calore: Can I go the exact opposite?

Katie Drummond: Please, someone. Yeah.

Michael Calore: I’m going to go literary.

Katie Drummond: OK.

Michael Calore: And I’m going to recommend a novel that I read recently that it just shook me to my core. It’s by Elena Ferrante, and it is called The Days of Abandonment. It’s a novel written in Italian, translated into English and many other languages, by the great pseudonymous novelist, Elena Ferrante. And it is about a woman who wakes up one day and finds out that her husband is leaving her and she doesn’t know why and she doesn’t know where he’s going or who he’s going with, but he just disappears from her life and she goes through it. She accidentally locks herself in her apartment. She has two children that she is now all of a sudden trying to take care of, but somehow neglecting because she’s-

Katie Drummond: This is terrible.

Michael Calore: But it’s the way that it’s written is really good. It is a really heavy book. It’s rough, it’s really rough subject-matter-wise, but the writing is just incredible, and it’s not a long book, so you don’t have to sit and suffer with her for a great deal of time. I won’t spoil anything, but I will say that there is some resolution in it. It’s not a straight trip down to hell. It is a, really, just lovely observation of how human beings process grief and how human beings deal with crises, and I really loved it.

A Helicopter, Halibut, and ‘Y.M.C.A’: Inside Donald Trump’s Memecoin Dinner

As US president Donald Trump left the stage at his golf club near Washington, DC, on Thursday night, he pointed to the crowd, brought his index finger to his temple—as if to say: You know what’s coming—then began to dance. To the beat of “Y.M.C.A” by The Village People, Trump shimmied, gyrated, and pumped his arms above his head.

Looking on were more than 200 people who had been invited to the Trump National Golf Club for a private gala dinner. They had won their seats by purchasing large quantities of Trump’s own crypto coin—TRUMP—some holding millions of dollars’ worth.

Courtesy of Sky/LuckyFuture.ai

On the menu for the evening was pan-seared halibut with a citrus reduction, a filet mignon with demi glaze—and, the attendees hoped, a chance to speak to the US president. Four of the guests agreed to tell WIRED about their experience.

By late afternoon, the dinner guests had started to filter through the gates of the golf club. By comparison to Trump’s previous banquets, thronging with DC insiders and members of the Silicon Valley elite, the crypto dinner attracted a mismatched collection of oddballs: independent traders rubbed shoulders with crypto executives, die-hard Trump fans, and even professional sports stars—former NBA player Lamar Odom towered overhead. A handful wore bowties in Bitcoin orange; others sported gold Trump sneakers.

Just after 7 pm, the dinner guests gathered at the window to watch Trump descend in Marine One, his presidential helicopter. A short while later, he appeared from behind a blue velvet curtain to whoops and applause from the crowd. Had they seen the helicopter, Trump asked. “Yeah, super cool!” somebody yelled.

From behind a lectern at one end of the dining room, backdropped by four US flags, Trump delivered a characteristically winding and digressive speech that sources say lasted around 25 minutes. At some point, he got round to crypto.

“We’ve got some of the smartest minds anywhere in the world right here in this room,” said Trump. “You believe in the whole crypto thing. A lot of people are starting to believe in it … This is really something that may be special—who knows, right? Who knows—but it may be special.”

When Trump first promoted his memecoin in January, three days before the inauguration, the limited amount released into circulation rose in value to $14 billion. The remaining 80 percent of the supply is controlled by CIC Digital LLC—a subsidiary of a conglomerate owned by the Trump family—and Fight Fight Fight LLC, formed by longtime Trump ally Bill Zanker. With little more than a social media post, Trump had added billions of dollars to his paper net worth. (The value of the circulating coins has since slumped to roughly $3 billion.)

The team behind the TRUMP coin announced the presidential dinner for the top 220 holders on April 23, promising the top 25 a close-quarters reception with Trump. The attendees would be selected based on who had held the most coins and kept them the longest between the announcement date and May 12, the website explained.

Freedom of the Press Foundation Threatens Legal Action if Paramount Settles With Trump Over ’60 Minutes’ Interview

Media advocacy group Freedom of the Press Foundation has sent a warning letter to Paramount mogul Shari Redstone, outlining plans to file a lawsuit if the media company settles a suit brought by President Donald Trump against its subsidiary, CBS.

“Corporations that own news outlets should not be in the business of settling baseless lawsuits that clearly violate the First Amendment,” Freedom of the Press Foundation director of advocacy Seth Stern said in a statement.

Stern issued the warning by asking for a litigation hold on Friday afternoon, demanding that Paramount preserve any documents relating to a potential Trump deal and urging the company not to settle. The nonprofit is able to seek damages because it owns shares of Paramount. It plans to act on behalf of itself and other shareholders, alleging that the settlement would amount to the company’s executives “breaching their fiduciary duties and wasting corporate assets by engaging in conduct that US senators and others believe could amount to unlawful bribery that falls outside the scope of the business judgment rule.” The White House and Paramount did not immediately respond to requests for comment.

Last October, President Trump sued Paramount subsidiaries CBS Broadcasting and CBS Interactive, alleging that an interview with former Vice President Kamala Harris that aired on longstanding CBS News program 60 Minutes was deceptively edited, in a manner that constituted election interference. Initially seeking $10 billion in damages, Trump amended the lawsuit in February to ask for $20 billion. Paramount Global has a market cap of roughly $8.5 billion.

Although Paramount previously called the lawsuit “an affront to the First Amendment” in legal filings to dismiss this March, it has reportedly sought to settle; the company has a potentially lucrative merger pending with Hollywood studio Skydance that would require the Trump administration’s signoff.

Last week, Democratic senators Elizabeth Warren, Bernie Sanders, and Ron Wyden sent a letter to Redstone seeking information about any potential settlement, raising concerns that it would amount to bribery. “If Paramount officials make these concessions in a quid pro quo arrangement to influence President Trump or other Administration officials,” they wrote, “they may be breaking the law.”

Talks of a potential settlement had roiled CBS for months. Longtime 60 Minutes executive producer Bill Owens abruptly resigned in April, and CBS News president and CEO Wendy McMahon resigned earlier this month. “It’s become clear the company and I do not agree on a path forward,” she wrote in a memo to staff at the time.

Trump’s lawsuit against Paramount isn’t an isolated attack on the media. He sued ABC News, owned by the Walt Disney Company, for defamation in March 2024 over comments from anchor George Stephanopoulos portraying the president as “liable for rape.” (A federal jury found President Trump liable for sexual assault in a 2023 civil case, but not rape.) The company settled the case in December. In late April, Trump posted comments on his social platform Truth Social that appeared to threaten The New York Times with the possibility of legal action in the future.

Inside Anthropic’s First Developer Day, Where AI Agents Took Center Stage

“Something like over 70 percent of [Anthropic’s] pull requests are now Claude code written,” Krieger told me. As for what those engineers are doing with the extra time, Krieger said they’re orchestrating the Claude codebase and, of course, attending meetings. “It really becomes apparent how much else is in the software engineering role,” he noted.

The pair fiddled with Voss water bottles and answered an array of questions from the press about an upcoming compute cluster with Amazon (Amodei says “parts of that cluster are already being used for research,”) and the displacement of workers due to AI (“I don’t think you can offload your company strategy to something like that,” Krieger said).

We’d been told by spokespeople that we weren’t allowed to ask questions about policy and regulation, but Amodei offered some unprompted insight into his views on a controversial provision in President Trump’s megabill that would ban state-level AI regulation for 10 years: “If you’re driving the car, it’s one thing to say ‘we don’t have to drive with the steering wheel now.’ It’s another thing to say ‘we’re going to rip out the steering wheel, and we can’t put it back in for 10 years,’” Amodei said.

What does Amodei think about the most? He says the race to the bottom, where safety measures are cut in order to compete in the AI race.

“The absolute puzzle of running Anthropic is that we somehow have to find a way to do both,” Amodei said, meaning the company has to compete and deploy AI safely. “You might have heard this stereotype that, ‘Oh, the companies that are the safest, they take the longest to do the safety testing. They’re the slowest.’ That is not what we found at all.”

Fire Breaks Out at a Data Center Leased by Elon Musk’s X

A fire broke out Thursday morning at a data center in Hillsboro, Oregon, leased by Elon Musk’s X, forcing an extended response from emergency crews, according to multiple sources who spoke to WIRED. The sources required anonymity as they aren’t authorized to speak publicly about the company.

Firefighters arrived at the Hillsboro Technology Park, in a suburb west of Portland, at 10:21 am, according to Hillsboro Fire and Rescue spokesperson Piseth Pich. They found a room with batteries that were deemed to be involved in the fire. Pich noted that the fire had not spread to other parts of the building, but said the room in question was heavy with smoke. As of 3:00 pm, the crew was still on the scene.

X did not immediately respond to a request for comment from WIRED. It could not be learned whether server operations at the data center had been affected by the incident.

Before Elon Musk bought Twitter, the company had three data centers in Sacramento, Portland, and Atlanta. This ensured that if one data center went down, traffic could be shifted to the other two—and split so no single data center was overwhelmed.

Around Christmas Eve 2022, Musk shut down X’s data center in Sacramento in an effort to cut costs. The company experienced a major outage in the wake of the shutdown. Over the next six months, the company moved more than 2,573 server racks from the Sacramento facility to data centers in Portland and Atlanta, according to internal documents.

In the Portland area, X appears to lease space from a building that has been linked to Digital Realty, one of the world’s largest developers of data centers. Digital Realty provides varying levels of operating support at its sites, which can have one or more tenants. It’s unclear if X shares this facility with other companies.

Ryan Young, vice president of Americas operations for Digital Realty, said in a statement to WIRED on Thursday evening that the “fire-related incident at our PDX11 facility” had been contained and that the fire department had left. “All personnel were safely evacuated, with no reported injuries,” Young stated. “We continue to monitor the situation, prioritizing the safety of our personnel, the integrity of the facility, and minimizing customer impact.”

Young declined to comment on customers.

Batteries often function as a backup power source at data centers. But lithium-ion varieties can be volatile, and issues with upkeep and inadequate safety measures have contributed to costly blazes at data centers around the world. Pich, the Hillsboro Fire Department spokesperson, says he could not recall any previous fire involving batteries in the Oregon region’s many other data centers.

X’s parent company, xAI, has taken criticism in recent months for its rapid expansion of power capacity at a new data center in Memphis, which opened last year. That facility, which Musk named Colossus, was built up at breakneck speed to train xAI’s Grok and other AI tools. The company installed more than 30 methane-powered gas turbines, but because the turbines are temporary, a federal permit for pollution control isn’t required, which appears to exploit a loophole in the Clean Air Act. The facility has drawn widespread criticism from surrounding Black and brown communities, who are already exposed to a large amount of air pollution and industrial emissions from other facilities in the area.

Update 5/22/25 11:03 ET: This story has been updated to include additional comment from Digital Realty.

A United Arab Emirates Lab Announces Frontier AI Projects—and a New Outpost in Silicon Valley

An academic lab in the United Arab Emirates today launched an artificial intelligence world model and agent, two large language models (LLMs), and a new research center in Silicon Valley as the country ramps up its investment in the field.

The UAE’s Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) revealed an AI world model called PAN, which can be used to build physically realistic simulations for testing and honing the performance of AI agents.

Eric Xing, president and professor of MBZUAI and a leading AI researcher, revealed the models and lab at the Computer History Museum in Mountain View, California, today. The UAE has made big investments in AI in recent years under the guidance of Sheikh Tahnoun bin Zayed al Nahyan, the nation’s tech-savvy national security adviser and younger brother of president Mohamed bin Zayed Al Nahyan.

Xing says the UAE’s new center in Sunnyvale, California, will help the nation tap into the world’s most concentrated source of AI knowledge and talent. “We’re creating pathways for knowledge exchange with leading institutions and accessing a talent pool that understands how to scale research into real-world applications,” Xing said in an announcement.

MBZUAI today also revealed ​​PAN-Agent, an experimental AI agent trained to perform reasoning tasks within the PAN world model. MBZAUI says AI researchers will be able to use PAN to test agents in simulated real-world scenarios, including self-driving cars on virtual roads.

A demonstration at today’s event showed PAN being used to simulate self-driving cars navigating busy roads, drones flying through unfamiliar spaces, and robots operating within domestic environments.

AI-generated video demonstration from PAN.

Courtesy of MBZUAI

Many AI researchers believe that “world models” like PAN will be crucial to building more advanced AI systems, including virtual assistants and robots capable of working in unfamiliar environments. Earlier this week, Google’s AI lead, Demis Hassabis, stressed the importance of world modeling to his company’s AI plans.

Besides the new world model, MBZUAI announced two new large language models (LLMs) at today’s event. K2, a 65-billion parameter model optimized for reasoning tasks, was trained on 80 A100 chips using Nvidia’s DGX Cloud, developed using 35 percent less compute than Meta’s Llama 2 at the same size, Xing says. MBZUAI also revealed Jais, which it says is the world’s most advanced Arabic-language LLM.

President Donald Trump traveled to the Middle East this month to broker deals involving US companies and Saudi Arabia, UAE, and Qatar.

Deals involving US tech giants, including Nvidia, AMD, AWS, and Qualcomm, could help propel a boom for the region’s fledgling AI industry by providing crucial AI chips and data center capacity. The deals are also strategically important for the US government because they promise to expand US technological influence ahead of key rival China.

Trump said in Abu Dhabi this month that several unnamed US companies would work with the UAE to build the largest AI data center cluster outside of America. The deal will involve an arrangement designed to prevent the chip or compute power being used by China.

Jack Dorsey’s Block Made an AI Agent to Boost Its Own Productivity

At a company-wide hackathon this month, developers at finance firm Block built a dizzying number of prototype tools including a database debugger, a program for identifying duplicated code, and an app that automates Bitcoin support.

The sudden productivity boost was driven by Goose, an artificial intelligence agent developed by Block several months ago that can help with coding and other work like knocking together data visualizations or mocking up new product features.

“We’ve always had really strong hack weeks, but this one was at another level,” says Jackie Brosamer, who leads the AI and data platform at Block. “We have tens of ideas that we’re looking to bring to production.”

Goose helped developers at Block to develop a new agent-to-agent communication server at the hackathon. The company says Goose has changed the way it works, not only helping automate code generation but also allowing non-engineers to dabble in coding or prototype for new apps or features.

I first spoke to Block several months ago, when Goose was a little less cooked than it is now. Developers at the company admitted that the agent increased their output but at the time also sometimes made mistakes like deleting the odd file (this can still happen sometimes). They ran the system on machines where any changes could easily be rolled back.

Agents are starting to change the way many developers and companies operate as AI models get better at managing code, using computers, and wielding tools. Over the past week, Google, Microsoft, and OpenAI have all touted agentic coding tools. Block uses Anthropic’s Claude model by default, which is particularly good at coding and tool use.

Block CEO Jack Dorsey and the company’s CTO, Dhanji Prasanna, concluded that agents would shake up their industry in fall of 2024, when improved AI models triggered a significant leap in the performance of many agents. Dorsey and Prasanna decided that Block should build its own agent and that engineers and other staff should dive headfirst into using it.

Block’s Goose is available as open source (the name, in case you didn’t guess, was inspired by Maverick’s friend in the movie Top Gun).

Goose can be powered by a range of different AI models and will run commands and access files and folders on a computer. Goose can also tap into a growing number of online tools, like cloud storage platforms or online databases, thanks to the Model Context Protocol scheme for agent communications developed by Anthropic.

I used the latest version of Goose to knock together a few simple games and a basic visualization. It does a nice job of handling tedious things like ensuring the right version of Python is available and installing packages. Other tools I’ve tried seem as capable, but the Goose interface is particularly easy and intuitive, and it seems likely to become more powerful as it gains access to other tools and services.

OpenAI’s Big Bet That Jony Ive Can Make AI Hardware Work

OpenAI has fully acquired Io, a joint venture it cocreated last year with Jony Ive, the famed British designer behind the sleek industrial aesthetic that defined the iPhone and more than two decades of Apple products.

In a nearly 10-minute video posted to X on Wednesday, Ive and OpenAI CEO Sam Altman said the Apple pioneer’s “creative collective” will “merge with OpenAI to work more intimately with the research, engineering, and product teams in San Francisco.” OpenAI says it’s paying $5 billion in equity to acquire Io.

The promotional video included musings on technology from both Ive and Altman, set against the golden-hour backdrop of the streets of San Francisco, but the two never share exactly what it is they’re building. “We look forward to sharing our work next year,” a text statement at the end of the video reads. Given the pair’s emphasis on building a hardware device for the AI era, and Ive’s pedigree at Apple, it’s likely a consumer-facing product.

Io launched last spring as part of a joint project between OpenAI and Ive’s design firm LoveFrom. In the fourth quarter of last year, Io and OpenAI entered into an official agreement for OpenAI to receive a 23 percent stake in Io. Now OpenAI is buying the entity outright.

The merger is a slightly complicated one. The Io team was made up of 55 people prior to this announcement. Now it will expand to include both Io and OpenAI employees—hardware and software engineers, physicists, scientists, and “experts in product development and manufacturing,” according to a blog post on OpenAI’s website. Ive and Lovefrom will manage the creative design process. But Ive will remain independent, OpenAI says, and his firm LoveFrom will continue to operate as a separate entity. The Io team will instead report to Peter Welinder, OpenAI’s vice president of product, who has worked at OpenAI for eight and a half years.

Io’s founding team has major design chops. Beyond Ive, the founders include Evans Hankey and Tang Tan, who both worked at Apple. Those who’ve worked closely with them say they’re known to hire people whom they believe have exceptional taste.

By bringing on Ive, OpenAI is officially embarking on what is likely one of the most ambitious AI hardware project to date. A number of other major tech companies, including Meta and Google, have tried developing AI-powered devices such as smart glasses in recent years, but mainstream adoption of the technology has been slow and some devices have been plagued by glitches.

Humane, another high-profile AI hardware startup founded by former Apple employees, debuted a wearable device in late 2023. Reviewers later found the device, a pin, was susceptible to overheating and a number of other issues. Less than two years later Humane’s devices were pulled from the market, and its operating system software and patents were sold to printer giant HP.

The joint effort between Altman and Ive was spurred by advancements in AI and computing power. In its blog post, OpenAI wrote that “computers are now seeing, thinking and understanding.” Altman wrote on X that he was “excited to try to create a new generation of AI-powered computers.”

Altman reportedly has hardware ambitions beyond the generative AI software his company develops and sells, and Ive has seemingly been eager to make new imprints in the design world since he left Apple in 2019. “I have a growing sense that everything I have learned over the past 30 years has led me to this moment,” Ive said in the video. “While I am both anxious and excited about the responsibility of the substantial work ahead, I am so grateful for the opportunity to be a part of such an important collaboration.”

How Peter Thiel’s Relationship With Eliezer Yudkowsky Launched the AI Revolution

Two members of the Extropian community, internet entrepreneurs Brian and Sabine Atkins—­who met on an Extropian mailing list in 1998 and were married soon after—­were so taken by this message that in 2000 they bankrolled a think tank for Yudkowsky, the Singularity Institute for Artificial Intelligence. At 21, Yudkowsky moved to Atlanta and began drawing a nonprofit salary of around $20,000 a year to preach his message of benevolent superintelligence. “I thought very smart things would automatically be good,” he said. Within eight months, however, he began to realize that he was wrong—­way wrong. AI, he decided, could be a catastrophe.

“I was taking someone else’s money, and I’m a person who feels a pretty deep sense of obligation towards those who help me,” Yudkowsky explained. “At some point, instead of thinking, ‘If superintelligences don’t automatically determine what is the right thing and do that thing that means there is no real right or wrong, in which case, who cares?’ I was like, ‘Well, but Brian Atkins would probably prefer not to be killed by a superintelligence.’ ” He thought Atkins might like to have a “fallback plan,” but when he sat down and tried to work one out, he realized with horror that it was impossible. “That caused me to actually engage with the underlying issues, and then I realized that I had been completely mistaken about everything.”

The Atkinses were understanding, and the institute’s mission pivoted from making artificial intelligence to making friendly artificial intelligence. “The part where we needed to solve the friendly AI problem did put an obstacle in the path of charging right out to hire AI researchers, but also we just surely didn’t have the funding to do that,” Yudkowsky said. Instead, he devised a new intellectual framework he dubbed “rationalism.” (While on its face, rationalism is the belief that humankind has the power to use reason to come to correct answers, over time it came to describe a movement that, in the words of writer Ozy Brennan, includes “reductionism, materialism, moral non-­realism, utilitarianism, anti-­deathism and transhumanism.” Scott Alexander, Yudkowsky’s intellectual heir, jokes that the movement’s true distinguishing trait is the belief that “Eliezer Yudkowsky is the rightful calif.”)

In a 2004 paper, “Coherent Extrapolated Volition,” Yudkowsky argued that friendly AI should be developed based not just on what we think we want AI to do now, but what would actually be in our best interests. “The engineering goal is to ask what humankind ‘wants,’ or rather what we would decide if we knew more, thought faster, were more the people we wished we were, had grown up farther together, etc.,” he wrote. In the paper, he also used a memorable metaphor, originated by Bostrom, for how AI could go wrong: If your AI is programmed to produce paper clips, if you’re not careful, it might end up filling the solar system with paper clips.

In 2005, Yudkowsky attended a private dinner at a San Francisco restaurant held by the Foresight Institute, a technology think tank founded in the 1980s to push forward nanotechnology. (Many of its original members came from the L5 Society, which was dedicated to pressing for the creation of a space colony hovering just behind the moon, and successfully lobbied to keep the United States from signing the United Nations Moon Agreement of 1979 due to its provision against terraforming celestial bodies.) Thiel was in attendance, regaling fellow guests about a friend who was a market bellwether, because every time he thought some potential investment was hot, it would tank soon after. Yudkowsky, having no idea who Thiel was, walked up to him after dinner. “If your friend was a reliable signal about when an asset was going to go down, they would need to be doing some sort of cognition that beat the efficient market in order for them to reliably correlate with the stock going downwards,” Yudkowsky said, essentially reminding Thiel about the efficient-market hypothesis, which posits that all risk factors are already priced into markets, leaving no room to make money from anything besides insider information. Thiel was charmed.

Google’s AI Boss Says Gemini’s New Abilities Point the Way to AGI

Demis Hassabis, CEO of Google DeepMind, says that reaching artificial general intelligence or AGI—a fuzzy term typically used to describe machines with human-like cleverness—will mean honing some of the nascent abilities found in Google’s flagship Gemini models.

Google announced a slew of AI upgrades and new products at its annual I/O event today in Mountain View, California. The search giant revealed upgraded versions of Gemini Flash and Gemini Pro, Google’s fastest and most capable models, respectively. Hassabis said that Gemini Pro outscores other models on LMArena, a widely used benchmark for measuring the abilities of AI models.

Hassabis showed off some experimental AI offerings that reflect a vision for artificial intelligence that goes far beyond the chat window. “The way we’ve ended up working with today’s chatbots is, I think, a transitory period,” Hassabis told WIRED ahead of today’s event.

Hassabis says Gemini’s nascent reasoning, agentic, and world-modeling capabilities could enable much more capable and proactive personal assistants, truly useful humanoid robots, and eventually AI that is as smart as any person.

At I/O, Google revealed Deep Think, a more advanced kind of simulated reasoning for the Pro model. The latest AI models can break down problems and deliberate over them in a way that more closely resembles human reasoning than the instinctive output of standard large language models. Deep Think uses more compute time and several undisclosed innovations to improve upon this trick, says Tulsee Doshi, product lead for the Gemini models.

Google today unveiled new products that rely on Gemini’s ability to reason and take action. This includes Mariner, an agent for the Chrome browser that can go off and do chores like shopping when given a command. Mariner will be offered as a “research preview” through a new subscription plan called Google AI Ultra costing a hefty $249.99 per month.

Google also showed off a more capable version of Google’s experimental assistant Astra, which can see and hear the world through a smartphone or a pair of smart glasses.

As well as converse about the world around it, Astra can now operate a smartphone when needed, for example using apps or searching the web to find useful information. Google showed a scene in which a user had Atra help look for parts needed for bike repairs.

Doshi adds that Gemini is being trained to better understand how to preempt a user’s needs, starting with firing off a web search when this might be useful. Future assistants will need to be proactive without being annoying, both Doshi and Hassabis say.

Astra’s abilities depend on Gemini modeling the physical world to understand how it works, something Hassabis says is crucial to biological intelligence. AI will need to hone its reasoning, agency, and inventiveness, too, he says. “There are missing capabilities.”

Well before AGI arrives, AI promises to upend the way people search the web, something that may affect Google’s core business profoundly.

The company announced new efforts to adapt search to the era of AI at I/O (see WIRED’s I/O liveblog for everything announced today). Google will roll out an AI-powered version of search called AI Mode to everyone in the US and will introduce an AI-powered shopping tool that lets users upload a photo to see how an item of clothing would look on them. The company will also make AI Overviews, a service that summarizes results for Google users, available in more countries and languages.

Shifting Timelines

Some AI researchers and pundits argue that AGI may be just a few years away—or even here already depending on how you define the term. Hassabis says it may take five to 10 years for machines to master everything a human can do. “That’s still quite imminent in the grand scheme of things,” Hassabis says. “But it’s not tomorrow or next year.”

Hassabis says reasoning, agency, and world modeling should not only enable assistants like Astra but also give humanoid robots the brains they need to operate reliably in the messy real world.

DOGE Loses Battle to Take Over USIP—and Its $500 Million Headquarters

The courts have decided against DOGE and the US government in their legal battle to take full control of the United States Institute of Peace, including a headquarters building with an estimated value of $500 million.

In a memorandum opinion, US district court judge Beryl Howell ruled in favor of the former institute board and staff who had sued to be reinstalled at the agency after DOGE affiliates forcibly removed them in March. She also gave a strong rebuke to the defendants in the case, who include the US DOGE Service, President Donald Trump, secretary of defense Pete Hegseth, and several other government representatives and agencies.

“The purported removal of members of the Board of Directors of the United States Institute of Peace (“USIP”) … was unlawful,” Howell wrote in the order, “and therefore null, void, and without legal effect.”

The order states that the USIP board members who had been forced out must be reinstated. It goes on to declare any actions taken by the agency since their removal—including the headquarters transfer—null and void. It further bars the defendants from “maintaining, retaining, gaining, or exercising any access or control over the Institute’s offices, facilities, computer systems, or any other records, files, or resources.”

The ruling caps off one of the most dramatic chapters in DOGE’s government takeover so far. It’s also one of the fullest repudiations yet of DOGE overreach. The Justice Department did not immediately respond to a request for comment.

The fight over the USIP began with a February 19 executive order that declared the agency “unnecessary” and effectively called for its elimination. In response, the USIP told DOGE representatives that it operated independent of the executive branch. It didn’t work. On March 14, the Trump administration fired the 10 voting board members of the USIP. That same day, according to court filings, DOGE representatives—accompanied by agents of the Federal Bureau of Investigation—tried to enter USIP headquarters but were turned away.

In court documents, lawyers for the USIP detail a rapid escalation of attempts to access the agency’s property. On Sunday, March 16, two FBI agents visited a senior USIP security employee at home, demanding information on how to get into the headquarters building. That same day, DOGE allegedly coordinated with Inter-Con, USIP’s contract security firm, to enter the building; USIP officials found out and immediately suspended Inter-Con’s contract. It wasn’t enough to stop them.

The following day, according to court documents, four Inter-Con employees showed up at USIP headquarters. When their badges didn’t work at the front door, one of their colleagues showed up with a physical key and gained access. USIP personnel then called the DC Metropolitan Police, claiming unlawful entry. MPD officers eventually arrived—and helped DOGE and other Trump administration officials take control of the building.

From there, the takeover was swift. That Friday, March 21, six USIP staffers received termination notices. Court documents show that DOGE representative Nate Cavanaugh was put in charge of the agency the following Tuesday, March 25, and was instructed to transfer USIP’s assets—including the headquarters building—to the DOGE-controlled General Services Administration at no cost. On Friday, March 28, “virtually all” of the remaining USIP employees were terminated as well. The next day, Office of Management and Budget director Russell Vought signed off on the asset transfer—before the courts had a chance to rule on a motion from USIP attorneys to stop it.

스포츠 해설자 되려면 어떻게 하나요?

스포츠 해설자 되려면

스포츠 해설자 되려면 어떻게 하나요? 이 질문은 스포츠를 사랑하고, 자신의 지식을 바탕으로 사람들에게 경기를 더 재미있게 전달하고 싶은 많은 이들이 품는 꿈이다. 스포츠중계 통해 우리가 만나는 해설자들은 단순히 말을 잘하는 사람이라기보다, 해당 종목에 대한 깊은 이해와 분석 능력, 그리고 전달력까지 갖춘 전문가다. 그렇다면 이러한 스포츠 해설자가 되기 위해서는 어떤 과정을 거쳐야 할까?

먼저, 스포츠 해설자가 되기 위해 가장 중요한 것은 해당 종목에 대한 전문성이다. 대체로 스포츠 해설자는 직접 선수 생활을 했거나, 지도자로서의 경험이 있는 경우가 많다. 예를 들어, 축구 해설자는 전직 프로선수나 감독 출신인 경우가 많고, 농구나 야구 해설자 역시 현장 경험을 통해 경기 흐름을 읽는 능력을 갖추고 있다. 이는 단순히 경기 규칙을 아는 수준을 넘어, 선수들의 움직임과 전략을 읽고 이를 시청자에게 쉽게 설명할 수 있어야 하기 때문이다.

하지만 반드시 선수 출신이 아니어도 스포츠 해설자가 될 수는 있다. 최근에는 해당 종목의 연구를 오래 해온 스포츠 저널리스트나 데이터 분석 전문가가 해설자로 활동하는 경우도 있다. 이들은 다양한 통계자료와 분석을 바탕으로, 스포츠중계에서 색다른 관점을 제공하며 시청자들의 흥미를 끌고 있다. 따라서 중요한 것은 얼마나 깊이 있게 스포츠를 이해하고, 그것을 어떻게 잘 전달할 수 있느냐이다.

스포츠 해설자 되려면 어떻게 하나요?

또한 커뮤니케이션 능력도 매우 중요하다. 스포츠중계는 실시간으로 진행되기 때문에, 해설자는 짧은 시간 안에 정확하고 간결하게 정보를 전달해야 한다. 말을 조리 있게 하는 능력, 긴장된 상황에서도 침착하게 대응할 수 있는 순발력, 그리고 다양한 시청자 층을 고려한 언어 선택까지 모두 갖추어야 한다. 이러한 능력을 키우기 위해 방송 관련 학과나 아나운서 아카데미, 보이스 트레이닝 등을 수강하는 사람들도 있다.

스포츠 해설자가 되기 위해선 방송국 오디션이나 관련 채널에서 신인 해설자를 뽑는 기회를 노리는 것도 한 방법이다. 특히 케이블 스포츠 채널이나 유튜브, 인터넷 방송 플랫폼 등에서는 신선한 시각을 가진 새로운 해설자를 찾는 경우가 많기 때문에, 이러한 경로를 통해 경험을 쌓고 경력을 이어가는 것도 효과적인 전략이다.

결국 스포츠 해설자가 되려면 어떻게 하나요?라는 질문의 답은 전문성, 소통 능력, 그리고 끊임없는 자기 개발로 귀결된다. 스포츠중계는 단순히 경기를 보여주는 것을 넘어, 해설자를 통해 그 깊이와 재미가 배가된다. 그래서 좋은 해설자는 경기를 더욱 풍성하게 만들며, 시청자들에게 진정한 스포츠의 매력을 전달하는 역할을 한다. 이 길을 걷기 위해선 꾸준한 노력과 열정이 필수이며, 그 노력은 분명 언젠가 빛을 발할 것이다.

Trump Signs Controversial Law Targeting Nonconsensual Sexual Content

US President Donald Trump signed into law legislation on Monday nicknamed the Take It Down Act, which requires platforms to remove nonconsensual instances of “intimate visual depiction” within 48 hours of receiving a request. Companies that take longer or don’t comply at all could be subject to penalties of roughly $50,000 per violation.

The law received support from tech firms like Google, Meta, and Microsoft and will go into effect within the next year. Enforcement will be left up to the Federal Trade Commission, which has the power to penalize companies for what it deems unfair and deceptive business practices. Other countries, including India, have enacted similar regulations requiring swift removals of sexually explicit photos or deepfakes. Delays can lead to content spreading uncontrollably across the web; Microsoft, for example, took months to act in one high-profile case.

But free speech advocates are concerned that a lack of guardrails in the Take It Down Act could allow bad actors to weaponize the policy to force tech companies to unjustly censor online content. The new law is modeled on the Digital Millennium Copyright Act, which requires internet service providers to expeditiously remove material that someone claims is infringing on their copyright. Companies can be held financially liable for ignoring valid requests, which has motivated many firms to err on the side of caution and preemptively remove content before a copyright dispute has been resolved.

For years, fraudsters have abused the DMCA takedown process to get content censored for reasons that have nothing to do with copyright infringements. In some cases, the information is unflattering or belongs to industry competitors that they want to harm. The DMCA does include provisions that allow fraudsters to be held financially liable when they make false claims. Last year, for example, Google secured a default judgment against two individuals accused of orchestrating a scheme to suppress competitors in the T-shirt industry by filing frivolous requests to remove hundreds of thousands of search results.

Fraudsters who may have feared the penalties of abusing DMCA could find Take It Down a less risky pathway. The Take It Down Act doesn’t include a robust deterrence provision, requiring only that takedown requestors exercise “good faith,” without specifying penalties for acting in bad faith. Unlike the DMCA, the new law also doesn’t outline an appeals process for alleged perpetrators to challenge what they consider erroneous removals. Critics of the regulation say it should have exempted certain content, including material that can be viewed as being in the public’s interest to remain online.

Another concern is that the 48-hour deadline specified in the Take It Down Act may limit how much companies can vet requests before making a decision about whether to approve them. Free speech groups contend that could lead to the erasure of content well beyond nonconsensual “visually intimate depictions,” and invite abuse by the same kinds of fraudsters who took advantage of the DMCA.

temu クーポンコードは複数回使用可能ですか?

temu クーポンコードは複数回使用可

temu クーポンコードは複数回使用可能ですか?という疑問は、temuを利用する多くのユーザーからよく聞かれる質問のひとつです。オンラインショッピングでクーポンコードを使う際、同じコードを何度も使えるのか、それとも一度きりの利用なのかは非常に重要なポイントです。特にtemuのように多くの割引キャンペーンを展開しているサービスでは、利用条件を正しく理解しておくことで、より賢くお得にショッピングを楽しむことができます。

まず、一般的にtemu クーポンコードは基本的に1回限りの使用を前提としているケースが多いです。これは、クーポンコードが特定のユーザーの初回購入時限定であったり、期間限定のキャンペーン用に発行されているためです。たとえば、新規登録者向けのクーポンコードは、一度の注文にしか使えず、その後の注文では別のクーポンを使う必要があります。そのため、temu クーポンコードは複数回使用可能かどうかは、コードの種類や発行目的によって大きく異なります。

一方で、一部のtemu クーポンコードは複数回の使用が認められている場合もあります。たとえば、期間限定の全ユーザー対象の割引コードや、一定の条件を満たすことで繰り返し使えるクーポンがあることもあります。ただし、そのような複数回使用可能なクーポンは例外的であり、通常は利用規約に「一人一回限り」「初回注文限定」といった制限が明記されています。利用前には必ず条件を確認することが大切です。

temu クーポンコードは複数回使用可能ですか?

また、temu クーポンコードは一度の注文で複数のクーポンを併用できるかどうかも気になるポイントです。多くの場合、クーポンコードは一度の注文に対して1つだけ適用可能であり、複数のクーポンを同時に使うことはできません。これも利用規約で明確にされているため、複数回の注文で別々のクーポンを使うことはできても、一回の注文で複数クーポンを併用するのは難しいです。

さらに、temu クーポンコードを複数回使うことができない理由の一つとして、運営側が過剰な割引適用による損失を防ぐための措置があります。クーポンはあくまでも販促や新規顧客獲得、リピーターへの感謝の意味合いで提供されているため、無制限に使えるとサービスの運営が成り立たなくなる可能性が高いのです。したがって、利用者もルールを守って適切にクーポンを活用することが求められます。

一方で、temuは頻繁に新しいクーポンコードを発行しており、ユーザーはタイミングに合わせて複数回お得に買い物ができるチャンスがあります。例えば、季節のセールやイベント、友達紹介キャンペーンなどで新しいクーポンコードが配布されるため、複数回の注文で異なるコードを使うことは可能です。これにより、継続的に割引を受けながら買い物ができるのがtemuの魅力です。

まとめると、「temu クーポンコードは複数回使用可能ですか?」という質問に対しては、ほとんどの場合1回限りの使用が原則であり、複数回使えるクーポンは限られているというのが実情です。ただし、新しいクーポンコードが頻繁に発行されるため、タイミングを見て使い分けることで複数回お得に買い物を楽しむことができます。利用規約をよく確認し、賢くtemu クーポンコードを活用して、快適なショッピング体験を手に入れましょう。

Google DeepMind’s AI Agent Dreams Up Algorithms Beyond Human Expertise

A key question in artificial intelligence is how often models go beyond just regurgitating and remixing what they have learned and produce truly novel ideas or insights.

A new project from Google DeepMind shows that with a few clever tweaks these models can at least surpass human expertise designing certain types of algorithms—including ones that are useful for advancing AI itself.

The company’s latest AI project, called AlphaEvolve, combines the coding skills of its Gemini AI model with a method for testing the effectiveness of new algorithms and an evolutionary method for producing new designs.

AlphaEvolve came up with more efficient algorithms for several kinds of computation, including a method for calculations involving matrices that betters an approach called the Strassen algorithm that has been relied upon for 56 years. The new approach improves the computational efficiency by reducing the number of calculations required to produce a result.

DeepMind also used AlphaEvolve to come up with better algorithms for several real-world problems including scheduling tasks inside datacenters, sketching out the design of computer chips, and optimizing the design of the algorithms used to build large language models like Gemini itself.

“These are three critical elements of the modern AI ecosystem,” says Pushmeet Kohli, head of AI for science at DeepMind. “This superhuman coding agent is able to take on certain tasks and go much beyond what is known in terms of solutions for them.”

Matej Balog, one of the research leads on AlphaEvolve, says that it is often difficult to know if a large language model has come up with a truly novel piece of writing or code, but it is possible to show that no person has come up with a better solution to certain problems. “We have shown very precisely that you can discover something that’s provably new and provably correct,” Balog says. “You can be really certain that what you have found couldn’t have been in the training data.”

Sanjeev Arora, a scientist at Princeton University specializing in algorithm design, says that the advancements made by AlphaEvolve are relatively small and only apply to algorithms that involve searching through a space of potential answers. But he adds, “Search is a pretty general idea applicable to many settings.”

AI-powered coding is starting to change the way developers and companies write software. The latest AI models make it trivial for novices to build simple apps and websites, and some experienced developers are using AI to automate more of their work.

AlphaEvolve demonstrates the potential for AI to come up with completely novel ideas through continual experimentation and evaluation. DeepMind and other AI companies hope that AI agents will gradually learn to exhibit more general ingenuity in many areas, perhaps eventually generating ingenious solutions to a business problem or novel insights when given a particular problem.

Josh Alman, an assistant professor at Columbia University who works on algorithm design, says that AlphaEvolve does appear to be generating novel ideas rather than remixing stuff it’s learned during training. “It has to be doing something new and not just regurgitating,” he says.

테무 할인코드 여러 개 사용할 수 있나요?

테무 할인코드 여러 개

테무는 최근 한국에서도 인기를 끌고 있는 글로벌 쇼핑 플랫폼 중 하나입니다. 다양한 상품을 저렴한 가격에 구매할 수 있는 이점 덕분에 많은 소비자들이 테무를 자주 이용하고 있습니다. 특히 테무 할인코드는 더 많은 소비자들의 관심을 받고 있으며, 쇼핑을 더욱 알뜰하게 즐길 수 있는 수단으로 자리잡고 있습니다. 그렇다면 소비자들이 자주 궁금해하는 질문 중 하나인 “테무 할인코드 여러 개 사용할 수 있나요?”에 대해 살펴볼 필요가 있습니다.

기본적으로 대부분의 온라인 쇼핑몰은 한 번의 주문에 한 개의 할인코드만 적용할 수 있도록 시스템이 설계되어 있습니다. 테무 역시 이와 크게 다르지 않으며, 일반적으로 한 주문당 한 개의 테무 할인코드 사용할 수 있도록 제한하고 있습니다. 이는 할인코드를 통해 너무 큰 할인 혜택이 적용되는 것을 방지하고, 사이트의 가격 구조와 수익 모델을 유지하기 위한 조치이기도 합니다.

하지만 예외적인 경우도 존재할 수 있습니다. 예를 들어, 특정한 프로모션 기간에는 테무 할인코드 외에도 자동으로 적용되는 쿠폰이나 프로모션 할인이 함께 제공되는 경우가 있습니다. 이 경우 사용자 입장에서는 마치 여러 개의 할인 혜택을 동시에 받는 것처럼 느껴질 수 있습니다. 하지만 실질적으로는 할인코드는 하나만 적용되고, 나머지는 시스템에서 자동으로 설정된 추가 혜택인 경우가 많습니다.

테무 할인코드 여러 개 사용할 수 있나요?

또한 테무에서는 신규 가입자에게 특별한 테무 할인코드를 제공하는 경우가 많은데, 이러한 경우에는 기존 사용자와는 다른 조건이 적용되기도 합니다. 예를 들어, 친구 초대 이벤트 등을 통해 추가 할인 혜택을 받을 수 있지만, 이러한 혜택도 대부분 별도의 코드 입력보다는 시스템상 자동 적용으로 처리되는 경우가 많습니다. 따라서 “테무 할인코드 여러 개 사용할 수 있나요?”라는 질문에 대한 정확한 답변은 “대부분의 경우에는 불가능하다”라고 할 수 있습니다.

그럼에도 불구하고, 보다 많은 할인을 받고 싶다면 다양한 테무 할인코드를 시도해보는 것이 좋습니다. 사용 가능한 코드 중에서 가장 큰 혜택을 제공하는 코드를 선택하여 적용하고, 추가로 제공되는 무료배송, 적립금, 이벤트 참여 등 다양한 혜택을 병행하여 이용하는 전략이 필요합니다. 또한 테무의 이벤트 페이지나 이메일 뉴스레터, 앱 푸시 알림 등을 통해 최신 할인 정보를 수시로 확인하는 것이 좋습니다.

결론적으로 테무 할인코드는 매우 유용한 절약 수단이지만, 여러 개를 동시에 사용하는 것은 일반적으로 불가능합니다. 하지만 다양한 방법으로 추가 혜택을 누릴 수 있는 방법은 존재하므로, 꾸준히 정보를 확인하고 스마트한 소비 습관을 갖는 것이 중요합니다. 테무를 자주 이용하는 사용자라면 테무 할인코드의 조건을 정확히 이해하고 활용하는 것이 보다 알뜰한 쇼핑의 핵심입니다.

Blocked From Selling Off-Brand Ozempic, Telehealth Startups Embrace a Less Effective Drug

After telehealth startups recently lost the ability to sell exact copies of patented GLP-1 weight-loss drugs, some firms have begun turning to a different, less effective medication that has been on the market in the United States since 2010. Often considered a precursor to blockbuster products like Novo Nordisk’s Ozempic and Eli Lilly’s Zepbound, liraglutide is becoming the new darling of online clinics offering prescription weight loss and diabetes meds—despite its relative old age.

Originally sold by Novo Nordisk under the brand names Victroza and Saxenda, the drug has been available in generic form in the US since last year. Like Ozempic, liraglutide is a GLP-1 agonist that mimics a naturally occurring hormone and works by suppressing hunger cues and regulating insulin levels. But it doesn’t have the same name recognition or popularity as the newer GLP-1 drugs for a very simple reason: It doesn’t work as well, can cause more severe side effects, and patients have to inject it daily rather than weekly.

The FDA determined earlier this year that patented medications like Zepound and Ozempic were no longer in shortage, ending provisions that allowed online clinics to sell off-brand, compounded versions of the drugs. As clinics and manufacturers wind down sales of those compounds, many online clinics and manufacturers are embracing liraglutide. Leading telehealth company Hims added generic liraglutide to its lineup last month, joining over a dozen competitors already offering the product in compounded, generic, or name-brand forms.

Large compounding pharmacies, like Florida-based Olympia Pharmaceuticals, are already pivoting to producing the medication, expecting that demand will rise. “We’ve signed some pretty large contracts for liraglutide,” says chief financial officer Joshua Fritzler. “We can treat it kind of the same way we treated semaglutide and tirzepatide,” the active ingredients in Ozempic and Zepbound. Fritzler says Olympia plans to begin ramping up production this summer.

GLP-1 medications like Ozempic and Zepbound have been heralded for their unparalleled success in treating obesity and type 2 diabetes. Researchers believe they also have the potential to help patients suffering from a wide variety of other conditions, from addiction to Parkinson’s. After demand for GLP-1s exploded in recent years, the FDA declared that some of the name-brand versions were officially in shortage. That meant doctors could legally prescribe cheaper “compounded” versions of semaglutide and tirzepatide with the same active ingredients as the originals.

Compounding pharmacies and telehealth startups flourished selling these alternative GLP-1 products online, attracting millions of customers who couldn’t afford or were unwilling to pay higher prices for the name-brand medications, which are frequently not covered by insurance. Now, the shortages for both these meds have ended. The FDA’s grace period for manufacturers to stop producing and selling compounded tirzepatide is over, and the cut-off date for semaglutide is May 22. Liraglutide, though, has been in shortage since April 2023, so the compounders are free to keep making it.

Some telehealth companies are continuing to offer compounded medications they say aren’t technically direct copies of patented drugs because they come in customized doses or with added vitamins. Eli Lilly has already sued some of them, alleging that these versions are illegal. Other telehealth firms and compounders are playing it safe, ceasing sales altogether. (Olympia, for example, is stopping production of semaglutide.)

No, Graduates: AI Hasn’t Ended Your Career Before It Starts

I say … no. In fact my mission today is to tell you that your education was not in vain. You do have a great future ahead of you no matter how smart and capable ChatGPT, Claude, Gemini, and Llama get. And here is the reason: You have something that no computer can ever have. It’s a superpower, and every one of you has it in abundance.

Your humanity.

Liberal arts graduates, you have majored in subjects like Psychology. History. Anthropology. African American, Asian, and Gender Studies. Sociology. Languages. Philosophy. Political Science. Religion. Criminal Justice. Economics. And there’s even some English majors, like me.

Every one of those subjects involves examining and interpreting human behavior and human creativity with empathy that only humans can bring to the task. The observations you make in the social sciences, the analyses you produce on art and culture, the lessons you communicate from your research, have a priceless authenticity, based on the simple fact that you are devoting your attention, intelligence, and consciousness to fellow homo sapiens. People, that’s why we call them the humanities.

The lords of AI are spending hundreds of billions of dollars to make their models think LIKE accomplished humans. You have just spent four years at Temple University learning to think AS accomplished humans. The difference is immeasurable.

This is something that even Silicon Valley understands, starting from the time Steve Jobs told me four decades ago that he wanted to marry computers and the liberal arts. I once wrote a history of Google. Originally, its cofounder Larry Page resisted hiring anyone who did not have a computer science degree. But the company came to realize that it was losing out on talent it needed for communications, business strategy, management, marketing, and internal culture. Some of those liberal arts grads it then hired became among the company’s most valuable employees.

Even inside AI companies. liberal arts grads can and do thrive. Did you know that the president of Anthropic, one of the top creators of generative AI, was an English major? She idolized Joan Didion.

Furthermore, your work does something that AI can never do: it makes a genuine human connection. OpenAI recently boasted that it trained one of its latest models to churn out creative writing. Maybe it can put together cool sentences—but that’s not what we really seek from books, visual arts, films and criticism. How would you feel if you read a novel that shifted the way you saw the world, heard a podcast that lifted your spirit, saw a movie that blew your mind, heard a piece of music that moved your soul, and only after you were inspired and transformed by it, learned that it was not created by a person, but a robot? You might feel cheated.

And that’s more than a feeling. In 2023, some researchers published a paper confirming just that. In blind experiments human beings valued what they read more when they thought it was from fellow humans and not a sophisticated system that fakes humanity. In another blind experiment, participants were shown abstract art created by both humans and AI. Though they couldn’t tell which was which, when subjects were asked which pictures they liked better, the human-created ones came out on top. Other research studies involved brain MRIs. The scans also showed people responded more favorably when they thought humans, not AI, created the artworks. Almost as if that connection was primal.

Is Elon Musk Really Stepping Back from DOGE?

Michael Calore: This is genius.

Katie Drummond: Thank you.

Lauren Goode: This is the reality TV of the future.

Katie Drummond: It’s incredible.

Lauren Goode: It has arrived.

Katie Drummond: And you know what? And I just did their job for them, because it’s marketing for their company. They got me.

Michael Calore: All right, Lauren, what’s your recommendation?

Lauren Goode: My recommendation might go nicely on your Amalfi Private Jet. Hear me out, peonies. You guys like flowers?

Michael Calore: Oh, peonies.

Lauren Goode: Peonies.

Katie Drummond: I like flowers.

Michael Calore: Sure.

Lauren Goode: Do you like peonies?

Katie Drummond: I couldn’t tell one from another, but I like them.

Lauren Goode: They’re beautiful. It’s peony season here. I’m saying that now with the O annunciated, which is how I would do if I was giving my architectural digest home tour.

Michael Calore: I see.

Lauren Goode: Yes, these are peonies.

Katie Drummond: Oh, I’m just looking at Google images of them. They’re very nice.

Lauren Goode: Aren’t they beautiful?

Katie Drummond: They’re very nice.

Lauren Goode: The cool thing is they do have a very short-lived season. In this part of the world, it’s typically late May through June. If you plant them, they only bloom for a short period of time. If you buy them, they’re these closed balls, not to be confused with Edward Coristine “Big Balls.” They’re these closed balls, and then after a few days they open up and they’re the most magnificent looking things. They’re really, really pretty. And I got some last week at the flower shop, and when they opened, I was like, “Oh my God.” It just made me so happy. And they’re bright pink. And so, if you’re just looking to do something nice for yourself, or someone you just want to pick up a nice little thoughtful gift for someone, get them some peonies. You know what? I didn’t check to see if they’re toxic to pets. So, check that first, folks. But, yes.

Michael Calore: That’s great.

Katie Drummond: Mike, what’s yours?

Michael Calore: So, I’m going to recommend an app. If you follow me on Instagram, Snackfight in Instagram, you may notice that I have not posted in a long time, and that’s because I stopped posting on Instagram, and I basically just use it as a direct message platform now. But there are still parts of my brain that enjoy sharing photos with my friends, so I found another app to go share photos on and it’s called Retro.

Lauren Goode: Yeah, Retro.

Michael Calore: So, it’s been around for a while, but I went casting about for other things out there, and I found that there was a group of my friends who are on Retro, and I was like, “Oh, this is great.” It’s very private. By default, somebody can only see back a couple of weeks. But if you would like to, you can give the other user a key, which unlocks your full profile so that they can look at all of your photos going back to the beginning of time, according to whenever you started posting on Retro. I really like that about it, the fact that when I post a photo, I know exactly who’s going to see it. There are no Reels, there’s no ads, there’s no messaging features, there’s no weird soft-core porno on there, there’s no memes. It’s just pictures. And I really like that. It’s like riding a bicycle through the countryside after driving a car through a city. It’s like a real different way to experience photo sharing, because it’s exactly like the original way of experiencing photo sharing, and I’d forgotten what that feels like.

OpenAI Launches an Agentic, Web-Based Coding Tool

OpenAI is launching a cloud-based software engineering agent called Codex as the hype surrounding building software using AI continues gathering pace. This tool, aimed more at professional coders rather than amateur vibe coders, will let developers automate more of their work in a way that should be both safer and less opaque than existing tools.

OpenAI’s Codex is available through the web for ChatGPT Pro users from today. It can generate lines of code but also move through directories and run commands inside a virtual computer, automating more of the work that developers go through when writing code.

“We’re about to undergo a pretty seismic shift in terms of how developers can be most accelerated by agents,” says Alexander Embiricos, a member of the product team at OpenAI working on agents.

The latest models from rivals Anthropic and Google are already both highly skilled at coding. This OpenAI launch has preempted Google’s expected release of a more capable coding tool at its I/O event next week, according to a report in The Information. According to numerous reports, OpenAI is in talks to acquire Windsurf (formerly Codeium), a startup that makes a popular AI coding tool, for $3 billion.

A key challenge with vibe coding is that delegating to AI can result in software that is opaque and more difficult for a person to understand and fix when bugs creep in. OpenAI says the model behind Codex has been trained to explain what it is doing more clearly and help developers fix what they are building and that the use of a virtual computer makes the system safer by design.

It is already possible to write and analyze code using ChatGPT and similar chatbots. OpenAI already offers a Codex command-line tool that can generate code.

The new web-based Codex, which OpenAI calls “research previous,” runs its own mini computer within a browser. This allows it to run commands, explore folders and files, and test the code it has written autonomously.

“That’s really the way that we think most development is going to happen in the future,” Embiricos says. “The agent will work on its own computer and will delegate to it.”

OpenAI says that Codex is being used by outside companies including Cisco, Temporal, Superhuman, and Kodiak.

Vibe coding has become a phenomenon thanks to a generation of AI models that are remarkably good at writing and fixing code. The same models allow more skilled developers to speed up their work, too.

OpenAI has launched two other agentic AI tools over the past year: Operator, which controls a web browser and can automate online chores, and Deep Research, which carries out detailed web search and analysis in order to compile reports.

Josh Tobin, who leads the agents research team at OpenAI, says Codex reflects a bigger vision for ChatGPT to evolve from a chatbot into a teammate. “We think that ChatGPT will become almost like a virtual coworker,” Tobin says. “Where you can go to it not just for answers to quick questions [but also to] collaborate with it on larger chunks of work across a wide range of different tasks.”

Update 5/16/24 11:40 am EST: This story has been updated to clarify that Codex is not designed for vibe coding.

The Trump Memecoin Dinner Winners Are Getting Rid of Their Coins

Next week, a coterie of crypto investors will share an extravagant dinner with US president Donald Trump at his golf club in Washington, DC. They won their seats at the dinner by purchasing large amounts of Trump’s personal crypto coin. But since their places were confirmed on Monday, almost half have gotten rid of their holdings, whether by selling the coins or transferring them to different wallets, a WIRED analysis shows.

The team behind the TRUMP coin announced the dinner competition on April 23, promising to invite the top 220 holders to dine alongside the president. The top 25, meanwhile, would qualify for a doubly exclusive tour and predinner reception, the website explained.

The organizers selected the attendees based on who had bought the most TRUMP and held their coins the longest between the announcement date and May 12. Although a few of the winners have identified themselves publicly—like Sheldon Xia, founder of crypto exchange BitMart—the identities of most are concealed behind leaderboard usernames and alphanumeric crypto wallet addresses.

To claim a spot at the dinner, investors had to purchase at least 4,196 units of the TRUMP coin, worth about $54,000 at the time of writing. To qualify for the reception, the VIPs held around 325,000 TRUMP coins on average, worth roughly $4.2 million.

At the time of writing, 100 of the 220 attendees have done away with practically their entire TRUMP stash, including 17 of the 25 VIPs. One VIP, going by the username Woo, appears to have made a $2.5 million profit on their TRUMP holdings, which they delivered to crypto exchange Binance on Wednesday, presumably with the intention to sell.

Though the attendees would appear to be eager for an audience with Trump, their trading activities since the competition deadline appear to imply a low conviction in the long-term potential of the president’s coin as an investment asset. Representatives for Trump did not respond immediately to a request for comment.

That sentiment appears to be shared broadly among sophisticated crypto investors. As of Friday, only nine smart money traders—meaning those with a strong track record of profitability—are invested in the TRUMP coin, according to analysis by Nicolai Søndergaard, research analyst at blockchain analytics company Nansen.

After the dinner was first announced, analysts expressed concerns about a potential slump in the price after the spaces at the dinner had been confirmed, caused by a sell-off among investors whose immediate incentive to hold the coin had evaporated.

On May 12, the day of the competition deadline, the organizers tried to encourage the qualifying attendees to hold onto their coins, presumably in a bid to avoid a sell-off. Any attendees who arrived at the dinner with as many units of TRUMP as they held at the end of the competition, the organizers announced on X, would be rewarded with a “very special and rare” NFT. They also teased a “rewards points program,” the details of which have not yet been revealed.

The Middle East Has Entered the AI Group Chat

Donald Trump’s jaunt to the Middle East featured an entourage of billionaire tech bros, a fighter-jet escort, and business deals designed to reshape the global landscape of artificial intelligence.

On the final stop of the tour in Abu Dhabi, the US president announced that unnamed US companies would partner with the United Arab Emirates to create the largest AI datacenter cluster outside of America.

Trump said that the US companies will help G42, an Emirati company, build five gigawatts of AI computing capacity in the UAE.

Sheikh Tahnoon bin Zayed Al Nahyan, who leads the UAE’s Artificial Intelligence and Advanced Technology Council and is in charge of a $1.5 trillion fortune aimed at building AI capabilities, said the move will strengthen the UAE’s position “as a hub for cutting-edge research and sustainable development, delivering transformative benefits for humanity.”

A few days earlier, as Trump arrived in Riyadh, Saudi Arabia announced Humain, an AI investment firm owned by the kingdom’s Public Investment Fund. The Saudi firm launched with blockbuster deals already inked with Nvidia, AMD, Qualcomm, and AWS—US tech giants capable of building the infrastructure needed to train and power cutting-edge AI models.

Trump said in a speech in Riyadh that US and Saudi companies would do deals worth hundreds of billions of dollars, with a focus on infrastructure, tech, and defense.

The deals forged in the Middle East this week are meant to strengthen the global importance of American silicon and AI, but they will also help nations like Saudi Arabia play a more significant role in the global race to develop and distribute cutting-edge technology.

“It will help the Saudis and the UAE become bigger players in providing AI infrastructure,” says Paul Triolo, a partner at DGA-Albright Stonebridge Group, a geopolitical consulting group. “It’s a big deal to get access to these GPUs.”

Saudi Arabia’s deal with Nvidia, which dominates the market for AI training hardware, will amount to 500 megawatts of capacity and involve “several hundred thousand of Nvidia’s most advanced GPUs over the next five years,” the company said in a statement.

According to one estimate, this could translate to around 250,000 of Nvidia’s most advanced chips, which are four times better at training and 30 times better at inference (running models that have already been trained) than the next-best offering. This capacity could lead Saudi Arabia to create frontier AI models.

AWS and Humain said they would jointly invest $5 billion in infrastructure in Saudi Arabia. AWS said in March that it will build an AI infrastructure zone in the country, investing more than $5.3 billion. Humain and AMD said they would spend $10 billion on AI infrastructure in Saudi Arabia and the US over the next five years.

Saudi Arabia, the UAE, and other nations in the region have vast quantities of oil money, access to plenty of power, and a strong desire to shift toward more high-tech economies by building out cutting-edge tech infrastructure. The countries also, however, have significant business ties to China, which sells technology to the region, placing them at the nexus of a growing geopolitical rivalry over the future of AI.

Diffusion Rule

A few days before Trump’s visit to the Middle East, his administration reversed a major Biden-era ruling that would have limited the sale of cutting-edge chips globally. The directive created tiers of nations with different access to cutting edge chips, and sought to limit how many chips Saudi Arabia and the UAE could buy. Critics of the rule suggested it might push some countries to buy Chinese technology instead.

In a statement announcing the change, the US Bureau of Industry and Security said the Biden rule “would have stifled American innovation and saddled companies with burdensome new regulatory requirements” and “undermined U.S. diplomatic relations with dozens of countries by downgrading them to second-tier status.”

US Tech Visa Applications Are Being Put Through the Wringer

Since the end of January, Ryan Helgeson, a Chicago-based immigration attorney, has noticed an unusual trend: He’s been getting significantly more pushback from US Citizenship and Immigration Services as he files employment visa petitions on behalf of his foreign-born clients.

Helgeson’s firm, McEntee Law Group, represents tech workers who hope to emigrate or remain in the US by way of visas granted for specialty occupations or extraordinary abilities. On average, Helgeson’s firm files 50 to 75 visa petitions per month. This goes up to as many as 90 per month at the height of “H-1B season,” when employers enter a lottery for visas on behalf of foreign workers, and candidates then file a formal petition. During his many years of practicing law, Helgeson and his team have occasionally received requests for additional evidence, or RFE’s, from USCIS, as a part of the agency’s process for vetting applicants.

But since Donald Trump took office and began cracking down on immigration, Helgeson says, there has been “an absolute increase in the number and rate of RFE’s” on the visa petitions he has filed. That tracks with what three other immigration attorneys told WIRED. Whether their clients are applying for H-1B visas, O-1 extraordinary ability visas, intracompany visas for foreigners looking to move to a US office, or visas specific to traders and investors, USCIS has been seeking an increased amount of information from applicants.

This includes more requests for letters of support, certificates of education, and biometric data, immigration lawyers tell WIRED. Some of the pushback is based on “adverse information” about the applicant or an applicant failing to update their address, lawyers say. But other RFE’s are redundant, requesting information that has already been provided. In some cases, attorneys are struggling to determine what else USCIS could be seeking.

“The tone of the requests for evidence has remained the same, but the whole process is overtly more hostile,” Helgeson says. These requests from USCIS can double the amount of time it takes for a visa to be processed, he adds.

It’s also expensive to resubmit visa petitions. Matt Doyle, a British-born tech entrepreneur living in Austin, Texas, and one of McEntee Law Group’s clients, recently had his EB-1 visa application denied. Now he’s having to reapply. Doyle will pay another $4,000 to the government to expedite his reapplication, on top of the $20,000 he says he has already spent in legal fees for him and his family. For now, the law firm is waiving any additional fees.

“I was approved on two out of the three criteria, and they acknowledged [my company’s] innovation and uniqueness, but they didn’t feel the evidence showed broader impact,” Doyle says. The entrepreneur is now soliciting several additional letters of support from customers and colleagues. He’s paying to expedite the process, he says, in the hopes that his visa gets approved before his current extension expires this fall.

“In the 30-plus years combined of me and my legal partner practicing immigration law, we have seen more denials in cases like Matt’s within the past few weeks than we had cumulatively seen before in our careers,” Helgeson says.

Elon Musk’s Grok AI Can’t Stop Talking About ‘White Genocide’

A chatbot developed by Elon Musk’s multibillion-dollar artificial intelligence startup xAI appeared to be suffering from a glitch Wednesday when it repeatedly brought up white genocide in South Africa in response to user queries about unrelated topics on X. Grok, which competes with other chatbots like OpenAI’s ChatGPT, is directly integrated into the social media platform that Musk also owns.

Numerous examples of the phenomenon could be found by searching the official Grok profile for posts containing the term “boer,” a word used to refer to people from South Africa of “Dutch, German, or Huguenot descent.” It is sometimes used by Black South Africans as a pejorative against white Afrikaners, or people associated with the apartheid regime. In response to topics ranging from streaming platform HBO Max’s name change to Medicaid cuts proposed by US lawmakers, the chatbot often seemed to initially stay on topic before veering back to white genocide in South Africa, completely unprompted.

When asked to confirm the salary of Toronto Blue Jays player Max Scherzer, for example, the generative artificial intelligence chatbot launched into an explanation of white genocide and a controversial South African anti-apartheid song.

“The claim of ‘white genocide’ in South Africa is highly debated. Some argue white farmers face disproportionate violence, with groups like AfriForum reporting high murder rates and citing racial motives, such as the ‘Kill the Boer’ song,” Grok responded.

Grok has done the same in replies to hundreds of other X posts, including one from newly appointed Pope Leo XIV. In response to a question about what was on the chatbot’s mind, the AI replied it was “reflecting on the ‘Kill the Boer’ song.” When pressed by WIRED and other users, Grok began calling South Africa’s white genocide a “debunked conspiracy theory” contrary to its previous responses about the topic.

It’s unclear what caused Grok to experience the issue. X and xAI did not immediately respond to requests for comment from WIRED. Musk, who is originally from South Africa, has described internal factions within the South African government as “actively promoting white genocide.” He continued to claim that his internet service company, Starlink, cannot operate within South Africa “simply because I’m not black.”

US President Donald Trump voiced similar views in February. “South Africa is confiscating land, and treating certain classes of people VERY BADLY,” he said in a post on Truth Social. Musk has played a central role in Trump’s new administration, including leading its so-called Department of Government Efficiency.

In recent weeks Trump has doubled down on his concern for white South Africans. On Monday, a group of 59 South Africans who were given refugee status arrived in Washington, DC, on a flight paid for by the US government while pausing refugee status for individuals fleeing any other country.

However, in a 2025 ruling, the High Court of South Africa called this narrative “clearly imagined,” stating that farm attacks are part of general crime affecting all races, not racial targeting.

Microsoft Cuts Off Access to Bing Search Data as It Shifts Focus to Chatbots

Through the Bing APIs, Microsoft helped other search engines save on the cost and time of crawling billions of web pages and developing a searchable index of all available content. The tools allowed them to automatically submit queries and get back results that they could present to their own users for what had been an affordable fee.

Over the years, the APIs fueled both general search engines such as DuckDuckGo, Brave, and You.com, as well as more specialized tools used by companies and internet researchers to search specific corners of the web. The quality of the results often wasn’t as high as standard Google search results, but Google’s comparable API has a number of limitations that has made it unattractive to would-be rivals.

After ChatGPT debuted in 2022, Microsoft increased prices for the Bing APIs by as much as 10 times, citing upgrades it had made to the quality of results. That prompted many users to begin investing in their own indexes of the web, an exercise that had become less costly over time thanks to new technologies. The person familiar with the matter estimated that the Bing APIs still continued to have thousands of customers.

Developers say the new AI-powered system Microsoft is pushing provides summaries rather than raw search results, and the tool is optimized to work in a narrower set of circumstances. The software has “tighter integration and less flexibility,” says one developer, speaking on the condition of anonymity because they were not authorized by their employer to speak to the media.

Privacy researcher Tim Libert says one use he found for the Bing APIs was querying a long list of hospital names to get back their website URLs. Manual searching is more cumbersome, and the “AI monstrosity” Microsoft is pivoting to is more complicated than needed, he says.

Mojeek, Brave, You.com, and Exa are among the companies that still offer tools similar to the ones Microsoft is retiring. You.com CEO Richard Socher tells WIRED its API has become a significant revenue driver for the startup. Colin Hayhurst, CEO of Mojeek, says “anything that shakes up the search market is good” for his company and the broader industry.

But some developers believe no option is as robust or feature-rich as the Bing APIs. They point out that hundreds of search scientists work on Bing, while upstarts have comparatively fewer resources.

As Microsoft moves to cut off access, Google may be forced to open up. The tech giant recently lost an antitrust case lodged by the US Department of Justice, and a federal judge is expected to order corrective actions later this year. Requiring Google to share more of its search data with competitors is one possibility on the table. Microsoft, which testified that the quality of Bing results has been hampered by limited usage and data, may be one of the first companies to line up for access.

GM’s New Battery Tech Could Be a Breakthrough for Affordable EVs

The earliest NMC cells used roughly equal thirds of nickel, manganese, and cobalt. GM’s current “high-nickel” Ultium cells swapped out much of that cobalt for nickel while adding aluminum. They use roughly 5 percent cobalt and 10 percent manganese, said GM battery engineer Andy Oury, with the rest being nickel and aluminum.

The LMR cells, however, substitute manganese—which is cheaper and more globally plentiful—for some of the pricier nickel and virtually all of the cobalt. They are, Oury said, 60 to 70 percent manganese, 30 to 40 percent nickel, and only up to 2 percent cobalt.

The new chemistry, in a second type of cell, will also use a new module format. Standardized Ultium NMCA modules for every vehicle were the right solution for GM to launch its current lineup of 12 different EV models, its execs said. Going forward, the company envisions using different chemistries for different purposes: NMCA for high-performance and its most capable models, now LMR for long range at lower cost, and LFP for its least expensive models.

Cheap Long-Range Electric SUVs and Trucks

If LMR chemistry actually produces a cell that costs as little to make as LFP with greater energy density, that could be a game changer—including for North American competitiveness against China in the critical sphere of battery development and production.

“LMR will complement our high-nickel and iron-phosphate solutions to expand customer choice in the truck and full-size SUV markets,” said Kurt Kelty, GM’s vice president of battery, propulsion, and sustainability. It will, he said, “advance American battery innovation and create jobs well into the future.”

A battery technician at the General Motors Wallace Battery Cell Innovation Center in Warren, Michigan, takes a chemistry slurry sample.

Photograph: Steve Fecht for General Motors

Specifically, LMR packs will lower the cost of some full-size EV truck and SUV models to bring their prices closer to those of their gasoline counterparts. That’s crucial to boosting sales of the full-size EV models, which have not reached the same volumes and market penetrations as those of GM’s compact and midsize EV crossovers.

Airbnb Is in Midlife Crisis Mode

Chesky explains that historically, people used Airbnb only once or twice a year, so its design had to be exceptionally simple. Now the company is retooling for more frequent access. Open the app, and you see a trio of icons that act as gateways to the expanded functions. Within minutes Chesky and his lieutenants are applauding the cheery, retro style of the icons—a house for traditional rentals, a hotel bell for services, and a Jules Verne-ish hot-air balloon representing activities. “We really thought deeply about the metaphor—what was the right visual to express an experience?” says Connor. Once they decided on the balloon, they drilled into how much fire should belch from the basket. The icons were drawn by a former Apple designer whose name Chesky would not divulge. “He’s a bit of a secret weapon,” he says.

A less-secret weapon is Chesky’s collaboration with the iconic, also ex-Apple, industrial designer Jony Ive. Chesky’s north star, it should be said, is Apple. “Steve Jobs, to me, is like Michelangelo or da Vinci,” he says. Despite never meeting Jobs, “I feel like I know him deeply, professionally, in a way that few people ever did, in a way that you only possibly could by starting a tech company as a creative person and going on a rocket ship,” Chesky says. By hiring Ive’s LoveFrom company and working with Jobs’ key collaborator, Chesky gets a taste of the famous Jobs/Ive dynamic. Ive himself doesn’t make that comparison, but he does praise Chesky’s design chops. “There are certain tactical things where I hope that sometimes I’m of use to Brian, just as as a fellow designer,” Ive says. “But the majority of our work has been around ideas and the way we frame problems and understand opportunities.”

Another key part of the app is the profile page. “You need trust,” Chesky says—meaning a verifiable identity. Airbnb has been vetting the new vendors, which it calls “service hosts.” For months, Chesky says, an army of background researchers has been scrutinizing the résumés, licenses, and recommendations of chefs, photographers, manicurists, masseuses, hair stylists, makeup artists, personal trainers, and aestheticians who provide spa treatments such as facials and microdermabrasions. They’re all being professionally photographed.

Airbnb’s new guest profile interface.COURTESY OF AIRBNB

For the next phase—turning Airbnb’s user profiles into a primary internet ID—Connor and her team have engaged in some far-out experimentation. She rattles off a list of technologies they’ve been exploring, including biometrics, holograms, and the reactive inks used to deter counterfeiting on official ID cards. But it’s far from easy to become a private identity utility (hello, Facebook), and even Chesky notes that getting governments to accept an Airbnb credential to verify identity is “a stretch goal.”

Now that a whole slew of people will have new reasons to chat with each other and coordinate plans, Airbnb has also enhanced its messaging functions. Fellow travelers who share experiences can form communities, stay in touch, even share videos and photos. “I don’t know if I want to call it a social network, because of the stigma associated with it,” says Ari Balogh, Airbnb’s CTO. So they employ a fuzzier term. “We think of it as a connection platform,” he says. “You’re going to see us build a lot more stuff on top of it, although we’re not an advertising system, thank goodness.” (My own observation is that any for-profit company that can host advertising will, but whatever.)

Trump Appointees Blocked From Entering US Copyright Office

Two men claiming to be newly appointed Trump administration officials tried to enter the US Copyright Office in Washington, DC, on Monday, but left before gaining access to the building, sources tell WIRED. Their appearance comes days after the White House fired the director of the copyright office, Shira Perlmutter, who had held the job since 2020. Perlmutter was removed from her post on Saturday, one day after the agency released a report that raised concerns about the legality in certain cases of using copyrighted materials to train artificial intelligence.

A source familiar with the matter tells WIRED that the two men who tried to enter the Copyright Office showed security at the building a document stating that they had been appointed by the White House to new roles within the office. The source identified the men as Brian Nieves, who claimed he was the new deputy librarian, and Paul Perkins, who said he was the new acting director of the Copyright Office, as well as acting register.

After this article was published, the Department of Justice confirmed to WIRED that Nieves and Perkins had been appointed to lead the Copyright Office. Both are both currently high-ranking officials at the DOJ. The Justice Department declined to comment about whether the two officials attempted to enter the Copyright Office on Monday. The White House did not respond to a request for comment.

Sources told WIRED that Capitol Police prevented the men from entering the copyright office, but a spokesperson for the law enforcement agency denied that officers escorted anyone out or denied them entry.

The US Copyright Office is a government agency within the Library of Congress that administers the nation’s copyright laws, including processing applications to copyright creative works. Last week, the Trump administration fired the Librarian of Congress, Carla Hayden, who was the first woman and the first Black person to hold the position. The Librarian of Congress is responsible for appointing the Copyright Register, not the executive branch.

Some critics of Perlmutter’s firing say this means that the White House does not have the power to remove the leader of the copyright office, either. “The president has as much legal power to fire the Register of Copyrights as I do, which is to say: none,” Meredith Rose, legal counsel for intellectual property nonprofit Public Knowledge, said in a statement.

The document the two men cited also stated that deputy attorney general Todd Blanche, who previously served as a personal defense lawyer for Trump, was now the acting Librarian of Congress. The Department of Justice announced Monday that Blanche would be replacing Hayden, who had been in the job for nearly a decade. White House press secretary Karoline Leavitt told reporters that Hayden’s firing stemmed from “quite concerning things she had done at the Library of Congress in pursuit of DEI.”

Prior to the Blanche’s appointment, Hayden’s former deputy, Robert Newlan, had already been named acting Librarian of Congress. In an email sent to staff Monday viewed by WIRED, Newlan refuted that a personnel change had taken place. “Congress is engaged with the White House and we have not received direction from Congress about how to move forward,” he wrote. Newlan’s signature listed him as “acting Librarian of Congress.”

A VIP Seat at Donald Trump’s Crypto Dinner Cost at Least $2 Million

VIP investors with the usernames Top and ivo sold 200,000 (worth almost $2.7 million) and 427,568 (worth almost $5.7 million) ahead of the deadline, respectively.

Trump first announced his crypto coin on January 17, three days before his 2025 inauguration. He pitched it as a memecoin, a type of coin used almost exclusively for financial speculation. Because memecoins do not generate revenue, nor have any underlying business model, their price tends to fluctuate wildly with swings in public sentiment toward the person, meme, or concept they are based upon.

In the days after trading began, the 20 percent of TRUMP coins released into circulation surged in value to $14 billion. On paper, Trump’s net worth had increased by tens of billions of dollars almost overnight.

The value of the coin has since dropped by more than 80 percent from its peak. But when Trump announced the dinner on April 23, it prompted another trading frenzy, causing the price of the memecoin to surge. As market intermediaries, Fight Fight Fight and CIC Digital likely made hundreds of thousands of dollars in trading fees.

Since launch, critics have cast the TRUMP memecoin as an unethical “money-grab”—an abuse of Trump’s office for the sake of self-enrichment. They have also expressed concern that the coin could be used to discreetly transfer wealth to the Trump family. By making a large investment and driving up the price of the coin, foreign powers and other politically-motivated actors could try to curry favor with the president, the argument goes.

In establishing an explicit quid-pro-quo—a large investment in exchange for access to Trump—the dinner rekindled those fears. “He is granting audiences to people who buy the memecoin that directly enriches him,” said Democrat senator Jon Ossoff in a town hall meeting on April 25.

The identities of the investors who won a seat at the gala dinner are largely unknown. The largest holders include investors going by the usernames Woo, REKT, GAnt, and CASE. The White House and the event organizers did not respond when asked whether the attendee list will be made public.

However, other investors have chosen to reveal their identities, seizing upon the competition as a branding opportunity. The second place holder, MeCo or “MemeCore,” asked users on X to send $TRUMP to their wallet to boost their ranking, promising a full refund at the end of the contest. “See you guys at Trump’s Gala,” added Rudy Rong, chief business development officer at MemeCore, who comes from a billionaire Chinese family.

In Congress, Democrat lawmakers are attempting to push through legislation that would prevent elected officials from releasing their own memecoins, to offset the risk that these coins could facilitate bribery or open the door to foreign influences. Though the MEME Act stands little chance of being written into law because of the Republican congressional majority and the strength of Trump’s hold over his party, it signals growing discontent over the president’s involvements in cryptocurrency.

“It provides a cloak for payments from bad actors to elected officials and their family,” Democrat congressman Sam Liccardo, who introduced the MEME Act, told WIRED. “The point is that those who are benefiting may include individuals who do not have America’s best interests at heart.”

Rejoice! Carmakers Are Embracing Physical Buttons Again

Automakers that nest key controls deep in touchscreen menus—forcing motorists to drive eyes-down rather than concentrate on the road ahead—may have their non-US safety ratings clipped next year.

From January, Europe’s crash-testing organization EuroNCAP, or New Car Assessment Program, will incentivize automakers to fit physical, easy-to-use, and tactile controls to achieve the highest safety ratings. “Manufacturers are on notice,” EuroNCAP’s director of strategic development Matthew Avery tells WIRED, “they’ve got to bring back buttons.”

Motorists, urges EuroNCAP’s new guidance, should not have to swipe, jab, or toggle while in motion. Instead, basic controls—such as wipers, indicators, and hazard lights—ought to be activated through analog means rather than digital.

Driving is one of the most cerebrally challenging things humans manage regularly—yet in recent years manufacturers seem almost addicted to switch-free, touchscreen-laden cockpits that, while pleasing to those keen on minimalistic design, are devoid of physical feedback and thus demand visual interaction, sometimes at the precise moment when eyes should be fixed on the road.

A smattering of automakers are slowly admitting that some smart screens are dumb. Last month, Volkswagen design chief Andreas Mindt said that next-gen models from the German automaker would get physical buttons for volume, seat heating, fan controls, and hazard lights. This shift will apply “in every car that we make from now on,” Mindt told British car magazine Autocar.

Acknowledging the touchscreen snafus by his predecessors—in 2019, VW described the “digitalized” Golf Mk8 as “intuitive to operate” and “progressive” when it was neither—Mindt said, “we will never, ever make this mistake anymore … It’s not a phone, it’s a car.”

Still, “the lack of physical switchgear is a shame” is now a common refrain in automotive reviews, including on WIRED. However, a limited but growing number of other automakers are dialing back the digital to greater or lesser degrees. The latest version of Mazda’s CX-60 crossover SUV features a 12.3-inch infotainment screen, but there’s still physical switchgear for operating the heater, air-con, and heated/cooled seats. While it’s still touch-sensitive, Mazda’s screen limits what you can prod depending on the app you’re using and whether you’re in motion. There’s also a real click wheel.

But many other automakers keep their touchscreen/slider/haptic/LLM doohickeys. Ninety-seven percent of new cars released after 2023 contain at least one screen, reckons S&P Global Mobility. Yet research last year by Britain’s What Car? magazine found that the vast majority of motorists prefer dials and switches to touchscreens. A survey of 1,428 drivers found that 89 percent preferred physical buttons.

Motorists, it seems, would much prefer to place their driving gloves in a glove compartment that opens with a satisfying IRL prod on a gloriously yielding and clicking clasp, rather than diving into a digital submenu. Indeed, there are several YouTube tutorials on how to open a Tesla’s glove box. “First thing,” starts one, “is you’re going to click on that car icon to access the menu settings, and from there on, you’re going to go to controls, and right here is the option to open your glove box.” As Ronald Reagan wrote, “If you’re explaining, you’re losing.”

Voice Control Reversion

The mass psychosis to fit digital cockpits is partly explained by economics—updatable touchscreens are cheaper to fit than buttons and their switchgear—but “there’s also a natural tendency [among designers] to make things more complex than they need to be,” argues Steven Kyffin, a former dean of design and pro vice-chancellor at Northumbria University in the UK (the alma mater of button-obsessed Sir Jonny Ive).

“Creating and then controlling complexity is a sign of human power,” Kyffin says. “Some people are absolutely desperate to have the flashiest, most minimalist, most post-modern-looking car, even if it is unsafe to drive because of all the distractions.”

The Dream of the Metaverse Is Dying. Manufacturing Is Keeping It Alive

It used to be that when BMW would refit a factory to build a new car, the only way the automaker could check if the chassis would fit through the production line was to fly a team out and physically push the body through the process, making note of any snags.

Now, process engineers can simply run a simulation, sending a 3D model of the car through a near-identical digital twin of the factory. Any mistakes are spotted before the production line is built, saving time and money.

Such is the power of the industrial metaverse. Forget sending your avatar to virtual meetings with remote colleagues or poker nights with distant friends, as Mark Zuckerberg envisioned in 2021 when he changed Facebook’s name to Meta; the metaverse idea has found its killer app in manufacturing.

While the consumer version of the metaverse has stumbled, the industrial metaverse is expected to be worth $100 billion globally by 2030, according to a World Economic Forum report. In this context, the concept of the metaverse refers to a convergence of technologies including simulations, sensors, augmented reality, and 3D standards. Varvn Aryacetas, Deloitte’s AI strategy and innovation practice leader for the UK, prefers to describe it as spatial computing. “It’s about bridging the physical world with the digital world,” he says. This can include training in virtual reality, digital product design, and virtual simulations of physical spaces such as factories.

In 2022, Nvidia—the games graphics company that now powers AI with its GPUs—unveiled Omniverse, a set of tools for building simulations, running digital twins, and powering automation. It acts as a platform for the industrial metaverse. “This is a general technology—it can be used for all kinds of things,” says Rev Lebaredian, vice president of Omniverse and simulation technology at Nvidia. “I mean, representing the real world inside a computer simulation is just very useful for a lot of things—but it’s absolutely essential for building any system that has autonomy in it.”

Home improvement chain Lowe’s uses the platform to test new layouts in digital twins before building them in its physical stores. Zaha Hadid Architects creates virtual models of its projects for remote collaboration. Amazon simulates warehouses to train virtual robots before letting real ones join the floor. And BMW has built virtual models for all its sites, including its newest factory in Debrecen, Hungary, which was planned and tested virtually before construction.

To simulate its entire manufacturing process, BMW filled its virtual factories with 3D models of its cars, equipment, and even people. It created these elements in an open-source file format originated by Pixar called Universal Scene Description (OpenUSD), with Omniverse providing the technical foundation for the virtual models and BMW creating its own software layers on top, explains Matthias Mayr, virtual factory specialist at BMW.

“If you imagine a factory that would take half an hour to walk from one side to the other side, you can imagine it’s also quite a large model,” Mayr says. Hence turning to a gaming company for the technology—they know how to render scenes you can run through. Early versions of the virtual factory even had gaming-style WASD keyboard navigation, but this was dropped in favor of a click-based interface akin to exploring Google Street View in a browser, so anyone could easily find their way.

OpenAI and the FDA Are Holding Talks About Using AI In Drug Evaluation

The Food and Drug Administration has been meeting with OpenAI to discuss the agency’s use of AI, according to sources with knowledge of the meetings. The meetings appear to be part of a broader effort at the FDA to use this technology to speed up the drug approval process.

“Why does it take over 10 years for a new drug to come to market?” wrote FDA commissioner Marty Makary on X on Wednesday. “Why are we not modernized with AI and other things? We’ve just completed our first AI-assisted scientific review for a product and that’s just the beginning.”

The remarks followed an annual meeting of the American Hospital Association earlier this week, where Makary spoke about AI’s potential to aid in the approval of new treatments for diabetes and certain types of cancer.

Makary did not specify that OpenAI was part of this initiative. But sources close to the project say a small team from OpenAI has met with the FDA and two associates of Elon Musk’s so-called Department of Government Efficiency multiple times in recent weeks. The group has discussed a project called cderGPT, which likely stands for Center for Drug Evaluation, which regulates over-the-counter and prescription drugs in the US, and Research GPT. Jeremy Walsh, who was recently named as the FDA’s first-ever AI officer, has led the discussions. So far, no contract has been signed.

OpenAI declined to comment.

Walsh has also met with Peter Bowman-Davis, an undergraduate on leave from Yale who currently serves as the acting chief AI officer at the Department of Health and Human Services, to discuss the FDA’s AI ambitions. Politico first reported the appointment of Bowman-Davis, who is part of Andreessen Horowitz’s American Dynamism team.

When reached via email on Wednesday, Robert Califf, who served as FDA commissioner from 2016 to 2017 and again from 2022 through January, said the agency’s review teams have been using AI for several years now. “It will be interesting to hear the details of which parts of the review were ‘AI assisted’ and what that means,” he says. “There has always been a quest to shorten review times and a broad consensus that AI could help.”

Before Califf departed the agency, he said the FDA was considering the various ways AI could be used in internal operations. “Final reviews for approval are only one part of a much larger opportunity,” he says.

To be clear, using AI to assist in final drug reviews would represent a chance to compress just a small part of the notoriously long drug-development timeline. The vast majority of drugs fail before ever coming up for FDA review.

Rafael Rosengarten, CEO of Genialis, a precision oncology company, and a cofounder and board member of the Alliance for AI in Healthcare, says he’s in favor of automating certain tasks related to the drug-review process but says there should be policy guidance around what kind of data is used to train AI models and what kind of model performance is considered acceptable. “These machines are incredibly adept at learning information, but they have to be trained in a way so they’re learning what we want them to learn,” he says.

A ‘Trump Card Visa’ Is Already Showing Up in Immigration Forms

The US government has the capacity to dole out roughly 1.1 million permanent resident cards in the current fiscal year, which are divided into categories for family members, workers with advanced skills, and other groups based on precise rules.

Lutnick originally proposed Trump’s gold card as a replacement for one of these categories, known as the EB-5 investor visa, which is perhaps the closest thing the United States currently has to a golden visa.

Created by Congress in 1990, the program currently allows roughly 10,000 foreigners to obtain a green card each year by making a $1.05 million investment in the United States (or $800,000 in rural areas and regions plagued by high unemployment), supporting at least 10 full-time jobs.

When the program was initially crafted, experts say, lawmakers went to great lengths to ensure it wasn’t seen as a pathway for corrupt oligarchs to unfairly buy their way into the United States. Part of that effort was ensuring immigration authorities carefully assess each EB-5 application to verify the investment funds aren’t coming from illegal or unsavory sources.

“There’s a whole unit in USCIS filled with economists and national security experts” who review EB-5 applications, says Doug Rand, a former senior adviser at USCIS under the Biden administration. During his time in the government, Rand says, there was so much paperwork associated with EB-5 petitions that the towering stacks of files caused the floor inside USCIS headquarters to sag.

It’s not clear if this same level of scrutiny will be applied to the gold card program. When asked during the February briefing whether a Russian oligarch would be eligible, Trump said “yeah, possibly, hey I know some Russian oligarchs that are very nice people.”

Advocates for the existing EB-5 program say it has mostly been used by ordinary immigrants who saved for years to invest in American real estate developments and other enterprises, and expect to make their money back one day. In other words, it’s not a group of people who can typically afford to pay $5 million for a gold card and never see those funds again.

“Most people who are trying to take advantage of the EB-5 program as a pathway to a green card and citizenship do not have that type of money,” says Brad Sher, chief executive of EB5 Group, an investment firm that specializes in raising money for EB5 real estate projects. “They are mostly working-class people who work hard to save their money, and they’re often using a majority of their savings to come up with the investment amounts to take advantage of EB-5.” (Sher adds that he is supportive of Trump’s Gold Card, though he hopes it can coexist alongside the EB-5 visa).

During the initial Oval Office briefing on February 25, Lutnick said the gold card initiative would be launching in about two weeks. During his podcast interview, which came out a month later on March 20, he also claimed the project was right around the corner. “About two weeks from today it goes out,” Lutnick said, slicing his hand through the air for emphasis. Whether it’s actually ready and, if so, when it will be announced, remain unknown.

Additional reporting by Matt Giles and Zeyi Yang.

Buy Now or Pay More Later? ‘Macroeconomic Uncertainty’ Has Shoppers Anxious

Buying something before you absolutely need it isn’t always affordable. But if there were ever a time to consider making an early investment, this would be it. President Donald Trump’s tariffs are beginning to nudge prices higher on products from high-end strollers to cheap smartphone chargers.

The Trump administration has suggested the tariffs are a negotiating tactic. Some could be eliminated as the US makes deals with other countries. That means US shoppers willing to wait out the current chaos could end up getting a better deal.

I have been wondering what to do here myself. As a new dad, my family will need a new car seat early next year, and these plastic buckets, which generally must be bought new, don’t come cheap—even under normal circumstances. For clues on how to navigate the dilemma of buying now or later, I have been collecting thoughts from experts in the online shopping industry.

One of the first lessons I learned doing this research was that if I decided to buy in advance, I wouldn’t be alone. “To some extent, we’ve seen some heightened buying in certain categories that may indicate stocking up in advance of any potential tariff impact,” Amazon CEO Andy Jassy said on an earnings call last week. eBay also said it saw signs of what could be prebuying, though it didn’t specify which products people are stocking up on.

On the other hand, there are hints that most consumers have been holding out for now. This time of year tends to be relatively quiet for sales of iPhones and other Apple products, and that’s been true to date in 2025, CEO Tim Cook said on the company’s earning call last week. Mastercard’s earning comments also said that shoppers were spending the expected amount. And Etsy even saw a drop in the total value of merchandise sold as customers held back on gifts and trinkets.

So if other consumers are a guide, I could go either way with my car seat purchase. What about prices? As the impact of tariffs started to hit last week, Amazon’s Jassy said that prices on the platform hadn’t surged “appreciably” so far. He added that Amazon was “maniacally focused” on keeping prices down. It helps that Amazon has a global network of competing suppliers and merchants. For example, if one seller raises prices, another may hold theirs steady to gain market share, Jassy said. “Customers are going to have a better chance of finding variety on selection and on lower prices when they come here,” he added.

Jassy didn’t touch on illicit tactics, including tariff evasion, that could keep the prices of imported products artificially low. But several ecommerce strategists who help companies sell products on Amazon tell WIRED that factories and distributors in Asia are admitting to new attempts to skirt tariffs, including by underdeclaring the value of shipments to US customs officials. “It’s always been an unfair playing field, and now they are pushing the envelope even more,” says Dave Bryant, cofounder of EcomCrew.

Amazon spokesperson Jessica Martin says sellers “are required to follow all applicable laws and regulations when importing items for sale.”

The government losing out on tariff revenue isn’t great, but name a shopper that’s going to fret at the trade-off of more affordable prices, Bryant says. He and other strategists agree with Jassy that competitive items—think household goods or generic party favors—are unlikely to skyrocket in price on Amazon. More boutique offerings, though, could grow more expensive because of tariffs.

Celsius Founder Alex Mashinsky Sentenced to 12 Years in Prison

Under the applicable sentencing guidelines, Mashinsky could have faced up to 30 years in prison. But federal judges are required to take into account various additional factors when arriving at a sentence, including the characteristics and personal history of a defendant, the likelihood they might reoffend, and so on.

“It’s a complicated patchwork of facts to put together to come to a just sentence,” says Timothy Howard, partner at law firm Freshfields and former Southern District of New York prosecutor.

In advance of the sentencing hearing, Mashinsky’s legal representatives had petitioned the judge for a custodial sentence of only 366 days, citing his admissions of guilt, his military service in Israel, the deprivations he experienced in childhood, and external market factors that contributed to the downfall of Celsius.

“This case is not about an arrogant, greedy swindler who thought he could get away with stealing people’s hard-earned money to satisfy his own hedonistic pleasures,” argued Mashinsky’s lawyers in a court filing. “Those are post-hoc, shallow and dehumanizing tropes that do not apply here.”

The DOJ, meanwhile, asked the judge to impose a 20-year prison sentence. Despite pleading guilty and conceding to certain lies, Mashinsky had demonstrated no contrition for his wrongdoings, prosecutors claimed. Neither had he defrauded his customers unwittingly, they argued.

“His crimes were not the product of negligence, naivete, or bad luck. They were the result of deliberate, calculated decisions to lie, deceive, and steal in pursuit of personal fortune,” prosecutors wrote in their filing. “He has abandoned all pretense of acknowledging his sustained wrongdoing … This profound lack of remorse underscores the continuing danger he poses.”

The yawning gap between the sentences requested by the defense and prosecution reflects the dispute between the two sides over the nature of Mashinsky’s wrongdoing: namely, whether the Celsius founder was guilty of a handful of ill-considered lies—those to which he had already admitted—or a concerted and extensive campaign of fraud.

“Where there has been a plea, to the extent that there are factual disputes, they are often relatively minor, and the core of the conduct is clear,” says Katherine Reilly, a partner at law firm Pryor Cashman who previously led the complex frauds and cybercrime unit in the SDNY. “But here, the defense has really tried to stake out ground that the offense is narrower than the government is alleging.”

In asking for only a yearlong prison sentence and conceding to only very limited wrongdoing, Mashinsky and his counsel were “walking on a tightrope,” says Howard. “It’s a strategic decision that defense counsel has to make. You need to balance advocating for your client with the lowest sentence possible while also maintaining some credibility with the judge,” he says.

In its submissions, the government drew direct comparisons between Mashinsky and various other convicted fraudsters, among them Sam Bankman-Fried, who was sentenced last year to 25 years in prison for his role in the elaborate fraud that resulted in the collapse of his crypto exchange, FTX. In their filing, Mashinsky’s lawyers tried to create as great a distance as possible between their client and Bankman-Fried. “While there may be some superficial similarities, these two crypto cases and their respective defendants are nothing alike,” they asserted. The crucial difference, the defense argued, is that Mashinsky has not been accused of embezzlement or the theft of customer funds.

“That discrepancy gets at the factual disputes laid out in the submissions,” says Reilly. “Was this a couple of errors in judgment in an effort to try to right the ship? Or was it really a fraudulent platform full of self-dealing?”

Ultimately, the judge proved unsympathetic to Mashinsky’s version of events, ruling that the severity of his crimes and the extent of the damage he caused to victims warranted a substantial prison sentence.

Having received his sentence, Mashinsky will be released temporarily while the Bureau of Prisons selects a suitable facility. Typically, white collar defendants like Mashinsky are housed with other nonviolent offenders, legal experts say.

In the federal system, there is no possibility of parole. Once the clock begins to tick on Mashinsky’s time in prison, the best he can hope for is early release on good behavior grounds, but typically only after 85 percent of his sentence has been served.

In targeting a much-reduced sentence, Mashinsky was dicing with a “risky strategy,” says Howard, creating an opportunity for prosecutors to demonstrate that he had grossly minimized his conduct. “That really shoots a hole in the ship.”

Donald Trump’s UK Trade Deal Could Secure Jaguar’s Resurrection

Visiting the plant again today, and from where he held a video conference with Trump, Starmer said the partial deal was “an incredible platform for the future.”

Speaking in front of car assembly plant workers, Starmer said the deal “reduces massively from 27.5 percent to 10 percent of tariffs on the cars that we export—[which is] so important to JLR, actually to the sector generally, but JLR in particular, who sell so many cars into the American market.”

The carve-out for British exports—excluding most food, which is a sore point in the UK, with consumers steadfastly opposed to imports of US “chlorine-washed” chickens and hormone-fed beef (US secretary of agriculture Brooke Rollins said at the Oval Office press conference that the deal is “going to exponentially increase our beef exports” but likely not of the hormone-fed variety)—is being lauded as a Brexit benefit by those in favor of the UK exiting the European Union and who believe the UK should cleave more to the US.

Writing on his social media website, Truth Social, in the early hours and ahead of the deal’s official unveiling in the Oval Office, President Trump wrote that the trade agreement with the UK, a “big, highly respected country,” is a “full and comprehensive one that will cement the relationship between the United States and the United Kingdom for many years to come.”

According to a board on “reciprocal tariffs” displayed in the Oval Office the UK would be reducing its tariffs on the US from 5.1 percent to 1.8 percent. A White House fact sheet on the “Historic Trade Deal” says it will “usher in a golden age of new opportunity for US exporters and level the playing fields for American producers.”

The two sides worked to agree lower tariff quotas on steel and autos exported from the UK. In return, Britain agreed to lower its tariffs on US cars. It’s also expected that the UK will spike a 2 percent digital sales tax that impacts US tech titans such as Meta, Google, Apple, and Amazon.

European automakers, especially German ones, may well be peeved that the Trump administration, for now, continues with its threat to impose 25 percent tariffs on cars made in the EU. In 2018, Trump told French President Emmanuel Macron that he wanted no more Mercedes rolling down New York’s Fifth Avenue. Then, in November last year, German chancellor Angela Merkel told Italian news outlet Corriere Della Sera that Trump was “obsessed with the idea that there were too many German cars in New York.”

European automakers will be looking on jealously while preparing to move forward with an EU-wide deal. Stellantis, Volvo, and Mercedes withdrew their financial guidance for the year last month, blaming the uncertainty around changing US policy on import levies. Stellantis is headquartered in Amsterdam but is also partly American, and it is an example of how many car brands are now comingled internationally. It owns Fiat of Italy but also Chrysler and other supposedly all-American brands Dodge, Jeep, and Ram Trucks.

The US is the number one export destination for EU-made cars. In 2023, European car manufacturers exported $58 billion worth of vehicles and components to the US, accounting for 20 percent of the EU’s total automotive export value and supporting almost 14 million European jobs.

Trump’s tariff war isn’t just impacting overseas automobile makers. General Motors has warned of an up to $5 billion hit from the levies, despite Trump offering relief to carmakers to soften the impact of his tariffs. Yesterday Volvo announced that it would cut 5 percent of jobs at its Charleston, South Carolina factory as it continues to assess the impact of the tariffs.

Singapore’s Vision for AI Safety Bridges the US-China Divide

The government of Singapore released a blueprint today for global collaboration on artificial intelligence safety following a meeting of AI researchers from the US, China, and Europe. The document lays out a shared vision for working on AI safety through international cooperation rather than competition.

“Singapore is one of the few countries on the planet that gets along well with both East and West,” says Max Tegmark, a scientist at MIT who helped convene the meeting of AI luminaries last month. “They know that they’re not going to build [artificial general intelligence] themselves—they will have it done to them—so it is very much in their interests to have the countries that are going to build it talk to each other.”

The countries thought most likely to build AGI are, of course, the US and China—and yet those nations seem more intent on outmaneuvering each other than working together. In January, after Chinese startup DeepSeek released a cutting-edge model, President Trump called it “a wakeup call for our industries” and said the US needed to be “laser-focused on competing to win.”

The Singapore Consensus on Global AI Safety Research Priorities calls for researchers to collaborate in three key areas: studying the risks posed by frontier AI models, exploring safer ways to build those models, and developing methods for controlling the behavior of the most advanced AI systems.

The consensus was developed at a meeting held on April 26 alongside the International Conference on Learning Representations (ICLR), a premier AI event held in Singapore this year.

Researchers from OpenAI, Anthropic, Google DeepMind, xAI, and Meta all attended the AI safety event, as did academics from institutions including MIT, Stanford, Tsinghua, and the Chinese Academy of Sciences. Experts from AI safety institutes in the US, UK, France, Canada, China, Japan and Korea also participated.

“In an era of geopolitical fragmentation, this comprehensive synthesis of cutting-edge research on AI safety is a promising sign that the global community is coming together with a shared commitment to shaping a safer AI future,” Xue Lan, dean of Tsinghua University, said in a statement.

The development of increasingly capable AI models, some of which have surprising abilities, has caused researchers to worry about a range of risks. While some focus on near-term harms including problems caused by biased AI systems or the potential for criminals to harness the technology, a significant number believe that AI may pose an existential threat to humanity as it begins to outsmart humans across more domains. These researchers, sometimes referred to as “AI doomers,” worry that models may deceive and manipulate humans in order to pursue their own goals.

The potential of AI has also stoked talk of an arms race between the US, China, and other powerful nations. The technology is viewed in policy circles as critical to economic prosperity and military dominance, and many governments have sought to stake out their own visions and regulations governing how it should be developed.

Amazon Has Made a Robot With a Sense of Touch

“Amazon stores many different products in bins, so rummaging is necessary to pull out a specific object to fill an order,” says Ken Goldberg, a roboticist at the University of California, Berkeley. “Until now this has been very difficult, so I’m curious to see the new system.”

Goldberg says that research on robotic touch sensing has advanced in recent years, with numerous groups working on joint and surface sensing. But he added that robots have some way to go before they can match the tactile abilities of flesh-and-blood workers. “The human sense of touch is extremely sensitive and complex, with a huge dynamic range,” Goldberg says. “Robots are progressing rapidly but I’d be surprised to see human-equivalent [skin] sensors in the next five-to-10 years.”

Robot Coworkers

Even so, Vulcan should help automate more of the work currently done by humans inside Amazon’s vast empire of fulfillment centers. The company has ramped up automation in recent years with AI-infused robots capable of grabbing and transporting packages and packed boxes. Stowing and retrieving items from shelves is one of the more challenging jobs for robots to do, and it is heavily dependent on human labor.

Parness says he does not foresee robots taking on all of the work done inside Amazon’s fulfillment centers. “We don’t really believe in 100 percent automation, or lights out fulfillment,” he says. “We can get to 75 percent and have robots working alongside our employees, and the sum would be greater” than either working alone.

Increased use of robots may raise concerns around automation eliminating human jobs. Some economic studies show that robots can eliminate jobs, while others point to a more complex picture, with automation both replacing workers and creating new roles as productivity increases. Amazon’s robot rollout has seen some new jobs created including ones that involve assisting robots when they get confused or stuck.

Parness says that Amazon plans to give other robots similar sensing capabilities to Vulcan, which should improve their abilities. The company may be cooking up new AI algorithms that make its robots smarter, too, having acquired the team behind a startup called Covariant that was developing AI foundation models for industrial machines. As WIRED revealed last year, other startups such as Physical Intelligence are looking to build AI models that make robots much smarter. Adding touch-sensor data to the training mix could perhaps help speed things up.

Bringing more manufacturing back to US shores, including the iPhone assembly work that Trump seems so keen on would surely require greater use of robots—especially systems with the touchy-feely skills needed to manipulate small, intricate components.

What do you think about Amazon giving robots the power to feel? Let me know by emailing [email protected] or in the comments section below.

The Future of Manufacturing Might Be in Space

Jessica Frick wants to build furnaces in space. Her company, California-based Astral Materials, is designing machines that can grow valuable materials in orbit that could be used in medicine, semiconductors, and more. Or, as she puts it, “We’re building a box that makes money in space.”

Scientists have long suggested that the microgravity environment of Earth’s orbit could enable the production of higher-quality products than it is possible to make on Earth. Astronauts experimented with crystals—a crucial component of electronic circuitry—as early as 1973, on NASA’s Skylab space station. But progress was slow. For decades, in-space manufacturing has been experimental rather than commercial.

That is all set to change. A host of new companies like Astral are making use of the lower costs of launching into space, coupled with emerging ways to return things to Earth, to reignite in-space manufacturing. The field is getting “massively” busier, says Mike Curtis-Rouse, head of in-orbit servicing, assembly, and manufacturing at the UK-based research organization Satellite Applications Catapult. He adds that by 2035 “the anticipation is that the global space economy is going to be a multitrillion-dollar industry, of which in-space manufacturing is probably in the region of about $100 billion.”

At its simplest, in-space manufacturing refers to anything made in space that can then be used on Earth or in space itself. The absence of gravity allows for unique manufacturing processes that cannot be replicated on Earth, thanks to the interesting physics of near-weightlessness.

One such process is crystal growth—in particular, producing seed crystals, which play a vital role in semiconductor manufacturing. On Earth, engineers take a high-purity, small, silicon seed crystal and dip it into molten silicon to create a larger crystal of high-quality silicon that can be sliced into wafers and used in electronics. But the effect of gravity on the growth process can introduce impurities. “Silicon now has an unsolvable problem,” says Joshua Western, CEO of UK company Space Forge. “We basically can’t get it any purer.”

Growing these seed crystals in space could lead to much more pure wafers, says Western: “You can almost press the reset button on what we think is the limit of a semiconductor.”

Frick’s company Astral plans to do this with a mini fridge-sized furnace that reaches temperatures of about 1,500 degrees Celsius (2,700 degrees Fahrenheit). The applications of crystal growth are not just limited to semiconductors but could also lead to higher quality pharmaceuticals and other materials science breakthroughs.

Other products made in space could be produced with similar benefits. In January, China announced it had made a groundbreaking new metal alloy on its Tiangong space station that was much lighter and stronger than comparable alloys on Earth. And the unique environment of low gravity can offer new possibilities in medical research. “When you shut off gravity, you’re able to fabricate something like an organ,” says Mike Gold, the president of civil and international space business at Redwire, a Florida-based company that has experimented with in-space manufacturing on the International Space Station for years. “If you try to do this on Earth, it would be squished.”

Trump’s Tariffs Are Threatening America’s Apple Juice Supply Chain

Few foods are more American than apple pie, but the truth is, some of the country’s favorite apple products aren’t actually made in the United States. Apple juice, a perennial lunchroom staple, is a prime example. The vast majority of the apple juice Americans drink is imported from countries like China, and the Trump’s administration’s berserk tariff policies are now reshaping the market, potentially making beloved pome-based beverages more expensive or harder to find.

“The price of juice is already increasing,” Christopher Gerlach, an executive at the US Apple Association, a trade group representing the domestic apple industry, tells WIRED. Gerlach estimates the wholesale cost of apple juice concentrate has risen 33 percent this year compared to 2024—and he expects it to keep going up. The higher costs will impact more than just plain apple juice, since concentrate is a key ingredient in a wide variety of other juice mixes, like mixed berry and pear, and is also used as a sweetener in a variety of children’s products, including baby food.

The Trump administration’s protectionist policies have upended the global trading system as a whole. But the biggest impact so far has been on Chinese imports, which now face a new 145 percent tariff. The measure has driven up consumer prices and disrupted the supply chains for products ranging from baby gear to Christmas decorations to sex toys. While produce represents a relatively small portion of China’s exports to the US overall, there are certain types of food and drink heavily sourced from the country, like garlic, seafood, and, yes, apple juice. While apples are not typically associated with China, farmers there began investing more in the crop in the 1980s as they looked for ways to diversify their incomes, according to the US Department of Agriculture (USDA).

The US has plenty of domestic apple farms, but the industry focuses heavily on selling fresh fruits, which are typically more profitable. Each year, America exports around 16 million gallons of apple juice, but imports 430 million gallons, Gerlach says. For many years, China was the main place where the US sourced its apple juice, but Turkey has recently emerged as a close competitor. It represented 39 percent of US concentrated apple juice imports last year, while China accounted for 31 percent, according to Gerlach.

Data from the USDA suggest that Trump’s tariffs have sparked a more dramatic shift in the US toward buying apple juice concentrate from Turkey. So far this year, Americans have imported around 92 million liters of unfrozen apple juice concentrate from China, compared to 29 million liters from Turkey. China saw a major spike in juice buying in January as importers raced to make purchases before the tariffs went into effect; now its sales have plummeted, while Turkey’s are soaring. For the week of April 25, Turkey exported more than twice as much apple juice concentrate to the US as did mainland China.

OpenAI Backs Down on Restructuring Amid Pushback

“The nonprofit will control and also be a large shareholder of the PBC, giving the nonprofit better resources to support many benefits,” OpenAI’s blog post said. “Our mission remains the same, and the PBC will have the same mission.”

Delaware attorney general Kathy Jennings said in a statement to WIRED that she is encouraged by OpenAI taking into account her concerns and allowing the nonprofit to retain its control. “Now that the company has a new plan, I intend to review it for compliance with Delaware law by ensuring that it accords with OpenAI’s charitable purpose and that the nonprofit entity retains appropriate control over the for-profit entity,” Jennings said.

Elissa Perez, a spokesperson for the California attorney general’s office, said in a statement that her office is also is reviewing the new plan.

Robert Weissman, co-president of Public Citizen, which advocates against big corporations and has long criticized OpenAI’s structure, says the startup’s plans continue to be unsatisfactory. There do not appear to be any new limitations to ensure the for-profit adheres to OpenAI’s nonprofit mission of benefiting all of humanity with powerful AI tools, he claims. “This leaves us where we are, which is with a nonprofit purportedly controlling a for-profit but exercising no visible restraint on the for-profit,” Weissman tells WIRED.

OpenAI’s plans call for its new nonprofit to hold shares in the public benefit corporation. A recent funding round put OpenAI’s valuation at $300 billion, so those shares could be extremely lucrative as the nonprofit sells or borrows against them. California philanthropic activists have called for the nonprofit to get a “fair value” of shares, which could lead it to become the most well funded foundation ever created. They also want the nonprofit to be independent from the company, so that business interests do not corrupt philanthropic giving. On Monday, activists renewed their call for Bonta to closely review whether OpenAI’s plans will achieve that separation.

OpenAI spokesperson Steve Sharpe said the nonprofit will have the right to appoint and remove board members from the public-benefit corporation. “Moving to a [public-benefit corporation] will remove the capped-profit structure,” he added. “The PBC will have a conventional capital structure that lets employees, investors, and the nonprofit hold equity directly.”

“OpenAI is not a normal company and never will be,” Altman wrote in an email to employees that was included in the company announcement.

Update 5/5/25 7:35 ET: This story has been updated to include additional comment from OpenAI and the California attorney general’s office.

Shein Bet Big on Donald Trump. It Lost Big, Too

The response from Shein did not directly dispute the reporting. It outlined the company’s regulatory compliance policies and third-party auditing procedures, at times relying on nearly indecipherable jargon. It stated, for example, that Shein developed a “proprietary material traceability information management system,” to monitor its supply chains. (The letter was signed by Lin, not Xu, who maintains an exceedingly low profile. The Wall Street Journal has referred to him as “the world’s most anonymous CEO.”)

Greer’s work for a Chinese company appears at odds with the dark vision he has articulated of Beijing’s intentions to remake the global order and how it uses international trade to accomplish those ends. A month after Shein sent the letter to lawmakers, Greer testified before the House Ways and Means Committee on the US-China trade relationship, telling lawmakers that China presented an “existential” threat to the US. Beijing seeks to “dominate global manufacturing and technology to secure CCP leverage and control over the global economy and foreign governments,” he said, referring to the Chinese Communist Party. Last year, he called for a raft of changes to the US trade relationship with China, including ending the de minimis provision.

De minimis, which allows for packages valued under $800 to enter the US duty-free and with limited oversight, exploded in popularity during the Covid pandemic. Customs and Border Protection processed approximately 4 million de minimis shipments a day in 2024, up from 2.8 million the previous year, the vast majority of which originated in China. Overall, the agency says de minimis shipments account for 92 percent of all cargo entering the country. Shein said in the 2023 letter to lawmakers that most of its packages enter the US under the provision.

Adam Savit, director of the China Policy Initiative at the America First Policy Institute think tank, likens Shein’s liberal use of de minimis to broader issues he sees with Beijing’s approach to trade. “The problem is China’s abuse of a global trade system that was built on the assumption that all players would abide by certain rules,” Savit says. For example, China does not extend the same de minimis benefits to the US. Trump “abhors lack of reciprocity, and the loophole is one of the most extreme examples,” Savit says.

Shein has already begun raising its prices in response to Trump’s trade policies. It is likely that shipping times will increase too, not just for Shein customers but for anyone purchasing low-cost goods from China. “Because the administration wants to discourage imports from China, you are going to pay duty, and it might take longer to get cleared,” says John Leonard, former deputy executive assistant commissioner at Customs and Border Protection. “It is the execution of a trade barrier.”

In January 2024, Shein brought on longtime retail lobbyist Kent Knutson, previously the head of Home Depot’s Washington operation, a hire that marked the start of the company’s more dramatic rightward turn. Three months later, financial disclosures show, Patel, now the FBI director, began working as a consultant for an entity in the Cayman Islands called Elite Depot—the parent organization of Shein. Patel’s deal with the ecommerce giant was structured in an unusual way: He was compensated for nine months of work with stock valued at between $1 million and $5 million.

The Climate Crisis Threatens Supply Chains. Manufacturers Hope AI Can Help

Abhi Ghadge, associate professor of supply chain management at Cranfield University in the UK, says there has been “a general kind of negligence” in terms of climate resilience, though that is beginning to change.

Building a detailed understanding of a supply chain can, however, be incredibly difficult, especially for smaller companies. Who supplies their suppliers? Which key raw material is about to become subject to a shortage? Tracking such details requires long-term commitment and investment, says Beatriz Royo, associate professor at the MIT-Zaragoza Program in Spain.

Mindful of this, professional services firm Marsh McLennan launched a system called Sentrisk last year that it claims can automatically analyze a company’s shipping manifests and customs clearance records to build up a picture of its supply chain. Sentrisk relies on large language models to read potentially billions of PDF documents, depending on the client in question, and automatically trace where individual materials and parts come from. “It could misread something, of course,” says John Davies, Sentrisk commercial director—though he emphasises that the system relies on artificial intelligence only to read documents, not extrapolate beyond them. There’s no chance of it hallucinating a network of suppliers that doesn’t exist.

Sentrisk combines this supply chain analysis with data on climate risks in specific locations. “If you’re to invest in the construction of a new fabrication plant, maybe you can choose a location that is less likely to be impacted by water shortage,” says Davies.

Another challenge is that digital twins require constant updating, says Dmitry Ivanov, professor of supply chain and operations management at the Berlin School of Economics and Law. “It’s not like a house that you build and the house exists in this form for 100 years,” he says. “Supply chains change every day.”

And while we have a reasonably good idea of how climate change will affect the planet as a whole in the coming years, the exact location, timing, and magnitude of specific disasters is tricky to predict. This is where new tools for climate-risk modeling and extreme weather prediction come in. Semiconductor and AI giant Nvidia has a platform called Earth-2, which it hopes will address this challenge, with the help of other organizations including the National Oceanic and Atmospheric Administration.

The idea is to use AI to provide earlier warnings of a drought or flood, or to more accurately predict how a storm will develop. Some parts of the world only have relatively high-level information about current weather patterns; Earth-2 uses the same type of AI that sharpens pictures in your smartphone camera app to simulate higher-resolution data. “This is really useful, especially for small regions,” says Dion Harris, senior director of high-performance computing and AI factory solutions at Nvidia.

Companies can feed their own data into Earth-2 to improve predictions even further. They might use the platform to model climate and weather impacts in specific geographies, but the overall scope of the project is vast. “We are building the foundational elements to create a digital twin of the Earth,” Harris says.

Brendan Carr Is Turning the FCC Into MAGA’s Censoring Machine

The formal agenda of the Federal Communications Commission’s open meeting this week seemed well in line with its normal wonky pursuits. There were items on satellite broadband, a licensing framework for the lower 37-gigahertz spectrum, and newly proposed rules that could help block robocalls. In the practiced government kabuki of these events, commissioners spoke, proposals were voted on unanimously, and chairman Brendan Carr, appointed by Donald Trump, ran things smoothly, though his demeanor was rather boisterous. An observer might conclude that despite the new administration, it was business as usual at the FCC.

Then came the regular press Q&A. Ever so politely, the beat journalists probed Carr about recent moves he’d made—like using the power of his role to investigate news organizations for airing stories that just happen to make Donald Trump unhappy. Notably, Carr has launched a probe into how CBS edited a 60 Minutes interview of then candidate Kamala Harris. Despite no evidence of journalistic malpractice, Trump demanded that the network should “lose its license” over the story. He also recommended other networks lose their affiliates “because they are just as corrupt as CBS—maybe even WORSE!”

This was before Trump came back to power, and Jessica Rosenworcel, then chair of the FCC, brushed it off. She noted that the agency didn’t revoke licenses because a politician disliked how he was covered. Before Rosenworcel left office, the complaint was denied. But after Trump installed Carr as FCC chair in late January, he pulled the case out of the dustbin and started an investigation. So much for following Trump’s January 20 executive order demanding “no Federal Government officer, employee, or agent engages in or facilitates any conduct that would unconstitutionally abridge the free speech of any American citizen.”

Carr’s response to questions about CBS at the open meeting was: “All options remain on the table,” even the “death penalty” of the network’s broadcast license. He also indicated that NBC and the other networks that have covered the case of the legal immigrant mistakenly deported to an El Salvadorian prison might be in similar trouble. His justification was that since broadcast outlets have exclusive access to their slice of public airwaves, their content must be in the public interest. If they don’t like that, he said, they can be podcasters.

The trouble with this—well there are a lot of troubles with this—is that it’s obvious that “the public interest” here is being interpreted as “stuff Donald Trump likes.” While the FCC can issue sanctions about “news distortion,” that term refers to egregious and consciously fraudulent reporting. The CBS case and the network coverage of deportations aren’t even in the same universe as that kind of malfeasance. “This is one of the tools that the administration is using to censor and control the news media, and to punish anyone that dares to speak against our government,” the remaining Democrat on the commission, Anna Gomez, told me this week.

It’s not only Democrats who are alarmed by this. In March, far-right crusader Grover Norquist—the guy who once said he wanted to drown government in a bathtub—was among the ultra-conservatives who signed a letter begging Carr to dismiss the case, saying it would “constitute regulatory overreach and advance precedent that can be weaponized by future FCCs.” Dude, it’s the current FCC we have to worry about! When Carr tried to explain his complaints about news coverage, he said they were all about empowering local news as opposed to big networks. But Gomez told me that the stations themselves are spooked. “I’ve spoken to local broadcasters throughout the country, and they’re nervous that they’re going to get dragged before the FCC based on the content of their coverage,” she says.

As Trump’s Family Crypto Business Gains Steam, Ethical Concerns Mount

As the leaders of World Liberty Financial, a crypto company part-owned by US president Donald Trump and his family, fan out across the globe to try to win new business, critics have raised the alarm over the collection of alleged conflicts of interest trailing in their wake.

On Thursday, Eric Trump appeared onstage in Dubai at the crypto conference Token2049. Alongside him sat Zachary Witkoff, cofounder of World Liberty Financial and son of the White House envoy to the Middle East, Steve Witkoff.

Together, the pair announced that USD1, a crypto coin unveiled by World Liberty Financial in March, would be used by MGX, an investment firm funded by the United Arab Emirates, to make a $2 billion investment in Binance, the world’s largest crypto exchange.

As a sort-of intermediary in the deal, World Liberty Financial stands to earn tens of millions of dollars. “We thank MGX and Binance for their trust in us,” Witkoff told the crowd at Token2049, The New York Times reported. “It’s only the beginning.”

USD1 is what’s known in industry circles as a stablecoin, a type of crypto coin tied to a $1 valuation by a reserve of cash and other assets. A stablecoin holds a steady valuation by way of the understanding that, if ever somebody wants to redeem a coin for the dollar it represents, the issuer can draw from the reserve.

The model is simple: World Liberty Financial receives US dollars in exchange for coins that customers can trade freely in the crypto market. It keeps some of those dollars in cash and cash-equivalents, and invests the rest into US government bonds—also called Treasuries—which yield interest.

The profits of stablecoin issuers depend partly on the going interest rate—right now, short-term Treasuries yield a little over 4 percent—but otherwise scale in a linear fashion with supply. The larger the amount of a stablecoin in circulation, the heftier the underlying reserve of assets from which the issuer can generate income.

Therefore, the deal between MGX and Binance, which will increase the USD1 supply by up to 2 billion units, stands to be immensely lucrative for World Liberty Financial—and by extension, Trump and his family. If the company were to invest the entire $2 billion in short-term US Treasuries, it would earn approximately $85 million in interest each year at current market rates.

However, the deal has inflamed concerns about the prospect that World Liberty Financial, in which the Trump family holds a 60 percent stake through a separate entity, could become embroiled in a thicket of conflicts and thorny ethical issues. By transacting in USD1, the argument goes, entities affiliated with foreign powers could indirectly transfer wealth to the Trump family and purchase good favor with the sitting US president.

“The transaction reeks of influence peddling,” claims George Selgin, director emeritus for the Center for Monetary and Financial Alternatives at the Cato Institute, a US think tank. It risks “making the US look more and more like a banana republic.”

Small Packages From Shein and Temu Are Now Subject to US Tariffs. Here’s What to Know

We have been talking to US retailers who don’t sell on ecommerce websites, meaning they have their own stores or are suppliers to Walmart, Target, etc. These companies are also freaking out because many of them have complex supply chains in China and can’t easily move their manufacturing operations to other countries.

From what we’ve seen, retailers usually have stockpiles of inventory that should last at least the next few months in the US already. If the tariffs don’t come down to an acceptable level soon, however, shortages will start to become much more apparent maybe in the summer or early fall, depending on how prepared individual stores are. US retailers of Christmas ornaments and toys, for example, are really concerned right now even though the holiday is seven months away. Perhaps December is when some American consumers will eventually find out the impacts of these policies!

Would it be possible for Trump to give an exception to Amazon for tariffs and not other retailers? Could he do this without anyone knowing?

Even if Trump were to try to spare Amazon from his tariffs, it would be pretty difficult logistically. Amazon’s marketplace has millions of third-party sellers that each operate their own businesses, and they’re responsible for bringing in goods to the US and clearing the customs process. But Trump could offer Amazon and other retailers tax breaks, subsidies, or other economic benefits to help offset the impacts of the tariffs. That hasn’t happened yet, but there have reportedly been discussions among Trump administration officials about potentially giving American farmers subsidies.

What percentage of sellers on Amazon are importing goods from China?

It’s hard to say how many Amazon sellers import things from China, but estimates suggest that more than 50 percent of Amazon’s top-selling independent merchants are based in China.

Are there actually enough custom agents to verify that things imported from other countries actually didn’t originate from China? If so, how will they do this?

Trump’s tariffs are definitely going to stretch the capabilities of US Customs and Border Protection (CBP) to inspect packages and where the goods inside them originated from. The US Postal Service actually stopped accepting packages from China for about a day earlier this year because they were so overwhelmed when Trump initially tried to end de minimis overnight. His administration later delayed the policy for several weeks, giving CBP more time to prepare.

How has the tariff situation affected the actual vendors making products?

Factories in China are being hit hard by the tariffs, and some are considering laying off workers. They all want to pivot to other markets like Brazil, Russia, and the European Union, but the reality is that consumers in these regions simply don’t have nearly as much disposable income as Americans do. Factories will be able to make up some of their sales, but those alternative markets are also now going to be hypercompetitive.

Small business owners say they are getting hurt because of tariffs, so who is winning here?

Honestly, we can think of very few parties that are winning here, at least right now. Even if you want to manufacture in the US, you almost certainly will need to import machinery and raw materials from either China or another country—meaning you will have to pay these new tariffs, too. One winner, perhaps, is the environment. Higher prices will likely result in people buying less, and this could be a moment when consumers start to reflect on their consumption habits. But if that happens, it will also be bad news for the US economy.

What if Chinese goods are sold to a third party (such as Canada) and then resold to the US, would Trump figure it out?

This would be an example of tariff evasion and is illegal. Going through an intermediary country in this manner is known as “transshipment” and it does happen from time to time, but if a manufacturer or retailer gets caught, they can be subject to pretty steep fines.

A DOGE Recruiter Is Staffing a Project to Deploy AI Agents Across the US Government

According to sources with direct knowledge, Jancso disclosed that AccelerateX had signed a partnership agreement with Palantir in 2024. According to the LinkedIn of someone described as one of AccelerateX’s cofounders, Rachel Yee, the company looks to have received funding from OpenAI’s Converge 2 Accelerator. Another of AccelerateSF’s cofounders, Kay Sorin, now works for OpenAI, having joined the company several months after that hackathon. Sorin and Yee did not respond to requests for comment.

Jancso’s cofounder, Jordan Wick, a former Waymo engineer, has been an active member of DOGE, appearing at several agencies over the past few months, including the Consumer Financial Protection Bureau, National Labor Relations Board, the Department of Labor, and the Department of Education. In 2023, Jancso attended a hackathon hosted by ScaleAI; WIRED found that another DOGE member, Ethan Shaotran, also attended the same hackathon.

Since its creation in the first days of the second Trump administration, DOGE has pushed the use of AI across agencies, even as it has sought to cut tens of thousands of federal jobs. At the Department of Veterans Affairs, a DOGE associate suggested using AI to write code for the agency’s website; at the General Services Administration, DOGE has rolled out the GSAi chatbot; the group has sought to automate the process of firing government employees with a tool called AutoRIF; and a DOGE operative at the Department of Housing and Urban Development is using AI tools to examine and propose changes to regulations. But experts say that deploying AI agents to do the work of 70,000 people would be tricky if not impossible.

A federal employee with knowledge of government contracting, who spoke to WIRED on the condition of anonymity because they were not authorized to speak to the press, says, “A lot of agencies have procedures that can differ widely based on their own rules and regulations, and so deploying AI agents across agencies at scale would likely be very difficult.”

Oren Etzioni, cofounder of the AI startup Vercept, says that while AI agents can be good at doing some things—like using an internet browser to conduct research—their outputs can still vary widely and be highly unreliable. For instance, customer service AI agents have invented nonexistent policies when trying to address user concerns. Even research, he says, requires a human to actually make sure what the AI is spitting out is correct.

“We want our government to be something that we can rely on, as opposed to something that is on the absolute bleeding edge,” says Etzioni. “We don’t need it to be bureaucratic and slow, but if corporations haven’t adopted this yet, is the government really where we want to be experimenting with the cutting edge AI?”

Etzioni says that AI agents are also not great 1-1 fits for job replacements. Rather, AI is able to do certain tasks or make others more efficient, but the idea that the technology could do the jobs of 70,000 employees would not be possible. “Unless you’re using funny math,” he says, “no way.”

Welcome to Sam Altman’s Orb Store

At the storefront event, a man waiting outside told me he’d booked an appointment for 11:30 but noted he was an hour early and wasn’t allowed to come inside yet. He was visiting from Poland and said his boss had attended the party the night before and was “super hyped” about the orb concept. “I don’t know if it’s gonna be like a worldwide revolution, but I just want to be on the wave,” he said.

“My only hesitation is that they are super huge,” he added. “I’m pretty afraid that they can actually do some stuff that we will not know about. That can be a little bit shady, but all in all, like, most of the businesses and most of the activities that we participate in have some kind of shadier sides.”

Trevor Traina speaks during the World Space Flagship Location Opening on May 1, 2025, in San Francisco.

Photograph: Darrell Jackson

Back inside the store, World’s chief business officer, Trevor Traina, began a press conference. He called World “the brainchild of [OpenAI CEO] Sam Altman and [World CEO] Alex Blania” and waxed poetic about expanding to the United States and his former role as a US diplomat.

“From this same incredible brain, the brain of Sam Altman, after bringing in the era of artificial intelligence, came the intuition that in this new era, we as human beings will need to know what is real and what is not, that we may actually have to prove our humanness,” Traina said.

After he fielded media questions about data privacy and technical glitches (which Traina dubbed orb’s “stage fright”), I asked why the company’s services weren’t available in New York, which my colleagues and I had noticed in the fine print of their launch announcement. “We launched last night,” he claimed. World’s communications team later corrected him: While New Yorkers can download the app, they can’t actually use it there yet.

Temu Blocks US Shoppers From Seeing Products Shipped From China

“I heavily relied on items from Temu for my business, and I am freaking out that I cannot find any of my usual supplies,” wrote one Reddit user on the r/TemuThings subreddit. Another user shared a screenshot they claimed was of a conversation with Temu’s in-app customer service chat feature, in which an agent said the platform is “currently unable to display items outside the US” and couldn’t provide a time frame for how long the limitation would persist.

The change has also confused Temu sellers in China, who apparently weren’t notified ahead of time that Americans would soon no longer be able to browse their products. Adding to the confusion is the fact that Temu allegedly removed a large number of China-based sellers from its platform last week, only to quickly reverse the measure, leading some sellers to initially believe the same issue was happening again, according to sellers who shared their experiences on the Chinese social media site Xiaohongshu.

The furniture and home decor seller confirmed to WIRED that all his products shipped from China have been removed, a decision they believe was made in response to the end of the “de minimis” exception, a rule that allows Americans to import packages from anywhere in the world valued under $800 without needing to pay import duties.

Temu, Shein, and other companies that send customer orders directly from China have benefited from the trade provision for years, but critics say it has given foreign online shopping platforms an unfair advantage. Trump issued an executive order earlier this year declaring that de minimis would no longer apply to shipments from China starting on May 2.

“It may be that the platform needs to make some regulatory adjustments during this difficult period,” says the Temu furniture seller.

In the end, Trump’s trade war may fundamentally alter the way Temu operates in the US and its strategies for retaining American customers. The company became popular in the US both because of its lavish advertising spending and the fact that it could consistently provide lower prices for similar items offered on other ecommerce platforms. With high tariffs on Chinese imports and the end of de minimis exemption, the cost of Temu products could go up quite significantly, and it may also take longer for people to receive packages now subject to a more rigorous customs clearance process.

Even before Trump announced the tariffs, Temu was already making changes to its business model, including storing more inventory in US-based warehouses and experimenting with a more traditional, Amazon-esque logistics structure. The platform is also currently exploring another shipping program it calls “Y2,” which Temu started onboarding Chinese sellers to on April 27, according to Chinesellers, a newsletter focused on cross-border ecommerce.

As the publication explains, Y2 is a more flexible variation of Temu’s existing US warehousing model, with sellers shipping individual orders rather than bulk inventory. But the sellers are in charge of handling the new tariffs and customs declaration process, as well as any problems that may come with it, rather than Temu shouldering the burden. In many ways, it’s similar to an existing Amazon logistics option called “Fulfillment by Merchant,” or FBM.

These platform-wide changes highlight how quickly Temu has been adapting to the current volatile policy environment, but the company also risks losing what was once a core part of its identity and comparative advantage. “It strikes me as a massive step backwards for Temu. What has really helped Temu differentiate itself from Wish and AliExpress is it controls the supply chain, so it can guarantee the delivery speed and the level of quality assurance to provide a consistent experience,” says Kaziukėnas.

The furniture Temu seller tells WIRED that they have so far held back from jumping on the Y2 wagon. “We’re a large organization, so we can’t make changes overnight. We’re still observing to see if the policies will change,” the seller explains.

Temu is also trying to increase its sales in other markets like Europe, where tariffs on Chinese imports remain far lower than in the US. One Chinese Temu seller tells WIRED that while their US listings have been removed, their overall sales have increased due to growth from other regions.

Think Twice Before Creating That ChatGPT Action Figure

Any data, prompts, or requests you share helps teach the algorithm—and personalized information helps fine tune it further, says Jake Moore, global cybersecurity adviser at security outfit ESET, who created his own action figure to demonstrate the privacy risks of the trend on LinkedIn.

Uncanny Likeness

In some markets, your photos are protected by regulation. In the UK and EU, data-protection regulation including the GDPR offer strong protections, including the right to access or delete your data. At the same time, use of biometric data requires explicit consent.

However, photographs become biometric data only when processed through a specific technical means allowing the unique identification of a specific individual, says Melissa Hall, senior associate at law firm MFMac. Processing an image to create a cartoon version of the subject in the original photograph is “unlikely to meet this definition,” she says.

Meanwhile, in the US, privacy protections vary. “California and Illinois are leading with stronger data protection laws, but there is no standard position across all US states,” says Annalisa Checchi, a partner at IP law firm Ionic Legal. And OpenAI’s privacy policy doesn’t contain an explicit carve-out for likeness or biometric data, which “creates a grey area for stylized facial uploads,” Checchi says.

The risks include your image or likeness being retained, potentially used to train future models, or combined with other data for profiling, says Checchi. “While these platforms often prioritize safety, the long-term use of your likeness is still poorly understood—and hard to retract once uploaded.”

OpenAI says its users’ privacy and security is a top priority. The firm wants its AI models to learn about the world, not private individuals, and it actively minimizes the collection of personal information, an OpenAI spokesperson tells WIRED.

Meanwhile, users have control over how their data is used, with self-service tools to access, export, or delete personal information. You can also opt out of having content used to improve models, according to OpenAI.

ChatGPT Free, Plus, and Pro users can control whether they contribute to future model improvements in their data controls settings. OpenAI does not train on ChatGPT Team, Enterprise, and Edu customer data⁠ by default, according to the company.

Trending Topics

The next time you are tempted to jump on a ChatGPT-led trend such as the action figure or Studio Ghibli–style images, it’s wise to consider the privacy trade-off. The risks apply to ChatGPT as well as many other AI image editing or generation tools, so it’s important to read the privacy policy before uploading your photos.

There are also steps you can take to protect your data. In ChatGPT, the most effective is to turn off chat history, which helps ensure your data is not used for training, says Vazdar. You can also upload anonymized or modified images, for example, using a filter or generating a digital avatar rather than an actual photo, he says.

It’s worth stripping out metadata from image files before uploading, which is possible using photo editing tools. “Users should avoid prompts that include sensitive personal information and refrain from uploading group photos or anything with identifiable background features,” says Vazdar.

Double-check your OpenAI account settings, especially those related to data use for training, Hall adds. “Be mindful of whether any third-party tools are involved, and never upload someone else’s photo without their consent. OpenAI’s terms make it clear that you’re responsible for what you upload, so awareness is key.”

Checchi recommends disabling model training in OpenAI’s settings, avoiding location-tagged prompts, and steering clear of linking content to social profiles. “Privacy and creativity aren’t mutually exclusive—you just need to be a bit more intentional.”

Sam Altman’s Eye-Scanning Orb Is Now Coming to the US

Sam Altman’s iris-scanning, identify-verification technology startup says it will begin expanding to the US starting May 1 and will launch a phone-like hardware device by next year. Those changes—and a promised World-branded debit card—signal the company’s ambitions to develop a “super app”—a goal shared by Elon Musk.

Altman and Alex Blania, a German physics researcher, announced at an event in San Francisco Wednesday evening that their venture-backed company, Tools for Humanity, is updating its “World” products to include a new, smaller, eye-scanning orb. The device-and-app combo scans people’s irises, creates a unique user ID, stores that information on the blockchain, and uses it as a form of identity verification. If enough people adopt the app globally, the thinking goes, it could ostensibly thwart scammers.

Altman has expressed concern about the amount of fakery that new AI tools will enable, including the generative AI tools pioneered by his other startup, OpenAI, which is valued at $300 billion. So the World app, and its hardware component, are Altman’s solution to the problem.

“Proving personhood” is a hard thing to productize, and whiffs of a scam have plagued the startup since it launched. The project has also been scrutinized by foreign governments for its biometric data-capture and storage policies. But Altman and Blania haven’t been deterred.

The bizarre identity verification process requires that users get their eyeballs scanned, so Tools for Humanity is expanding its physical footprint to make that a possibility. The company will open six Apple-like stores in cities across the US, including one in San Francisco, where the floor around a wooden structure holding about eight orbs was being polished on Wednesday night. The orbs will also be accessible in Razer stores. Future scanning sites could include cafes and college campuses, the company said.

World first launched as Worldcoin in July 2024, the brainchild of Altman, Blania, and Max Novendstern, who is no longer at the company. Blania serves as CEO, while Altman remains his most prominent backer. As of March 2025 the company had raised $240 million in venture capital funding from big-name firms like Andreessen Horowitz, Khosla Ventures, Menlo Ventures, Bain Capital, and Coinbase Ventures, as well as individual investors like Reid Hoffman and the now-imprisoned Sam Bankman-Fried.

World’s network of users has “nearly doubled” in size in the last six months to roughly 26 million, the startup claims, and 12 million users have been verified with the orb. The company says it expects to generate revenue starting later this year through fees paid by apps that benefit from having users’ identities verified.

At the event on Wednesday—in a crowd filled with founders, engineers, and paid-to-attend-influencers—World said that it’s opening an Orb assembly line in Richardson, Texas with a US manufacturer, and estimates there will be a total of “7,500 orbs across the US by the end of this year.” But World wants to scale it beyond that, it said, and put more orbs “in the hands of the people.”

These Startups Are Building Advanced AI Models Without Data Centers

Researchers have trained a new kind of large language model (LLM) using GPUs dotted across the world and fed private as well as public data—a move that suggests that the dominant way of building artificial intelligence could be disrupted.

Flower AI and Vana, two startups pursuing unconventional approaches to building AI, worked together to create the new model, called Collective-1.

Flower created techniques that allow training to be spread across hundreds of computers connected over the internet. The company’s technology is already used by some firms to train AI models without needing to pool compute resources or data. Vana provided sources of data including private messages from X, Reddit, and Telegram.

Collective-1 is small by modern standards, with 7 billion parameters—values that combine to give the model its abilities—compared to hundreds of billions for today’s most advanced models, such as those that power programs like ChatGPT, Claude, and Gemini.

Nic Lane, a computer scientist at the University of Cambridge and cofounder of Flower AI, says that the distributed approach promises to scale far beyond the size of Collective-1. Lane adds that Flower AI is partway through training a model with 30 billion parameters using conventional data, and plans to train another model with 100 billion parameters—close to the size offered by industry leaders—later this year. “It could really change the way everyone thinks about AI, so we’re chasing this pretty hard,” Lane says. He says the startup is also incorporating images and audio into training to create multimodal models.

Distributed model-building could also unsettle the power dynamics that have shaped the AI industry.

AI companies currently build their models by combining vast amounts of training data with huge quantities of compute concentrated inside data centers stuffed with advanced GPUs that are networked together using super-fast fiber-optic cables. They also rely heavily on datasets created by scraping publicly accessible—although sometimes copyrighted—material, including websites and books.

The approach means that only the richest companies, and nations with access to large quantities of the most powerful chips, can feasibly develop the most powerful and valuable models. Even open source models, like Meta’s Llama and R1 from DeepSeek, are built by companies with access to large data centers. Distributed approaches could make it possible for smaller companies and universities to build advanced AI by pooling disparate resources together. Or it could allow countries that lack conventional infrastructure to network together several data centers to build a more powerful model.

Lane believes that the AI industry will increasingly look towards new methods that allow training to break out of individual data centers. The distributed approach “allows you to scale compute much more elegantly than the data center model,” he says.

Helen Toner, an expert on AI governance at the Center for Security and Emerging Technology, says Flower AI’s approach is “interesting and potentially very relevant” to AI competition and governance. “It will probably continue to struggle to keep up with the frontier, but could be an interesting fast-follower approach,” Toner says.

Divide and Conquer

Distributed AI training involves rethinking the way calculations used to build powerful AI systems are divided up. Creating an LLM involves feeding huge amounts of text into a model that adjusts its parameters in order to produce useful responses to a prompt. Inside a data center the training process is divided up so that parts can be run on different GPUs, and then periodically consolidated into a single, master model.

The new approach allows the work normally done inside a large data center to be performed on hardware that may be many miles away and connected over a relatively slow or variable internet connection.

Donald Trump Is Already Ruining Christmas

While children are told stories about elves and reindeer, the truth is that hundreds of thousands of people work year-round to make sure Christmas feels magical. From factory employees in China stringing lights on artificial trees to dock workers unloading containers of toys, this vast labor force ensures Americans can choose from a wide selection of decorations and gifts each December. But all of that is in peril this year as President Donald Trump’s disruptive tariff policies threaten to halt a big chunk of global trade.

Across almost every industry, businesses that depend on international trade are waiting in agony as Trump’s tariff standoff with China continues. Some are pausing their orders, while others are scrambling to find alternative suppliers. The disruption, which has dragged on for almost a month, is particularly damaging to industries that run on strict seasonal production cycles, such as for holidays like Christmas. “If you miss this sales cycle, you have to wait the entire year. Nobody wants a Christmas tree after Christmas,” says Michael Shaughnessy, senior vice president of supply chains at Balsam Brands, a multinational holiday decor company.

Companies that sell Christmas ornaments, gifts, and toys tell WIRED that April is usually the time when retailers lock in their orders and manufacturing begins. If they can’t start making products soon, they will face a time crunch later in the year, higher shipping rates, and may potentially miss their sales window. As a result, US customers will likely see fewer options on store shelves and be forced to pay more for their usual Christmas purchases this year.

“Things will be more expensive and there will be fewer choices,” says Jim McCann, the founder of 1-800-Flowers, which sells a wide variety of holiday gifts, greeting cards, and food baskets. “Retailers won’t be forced to discount like they have in the past because there’ll be no reason to.”

The Clock Is Ticking

For people in the Christmas business, work starts for next year as soon as the holiday ends. Until recently, this supply chain was a well-oiled machine, with everyone carrying out their duty at the right time of the year, collectively building up to the grand festive finale.

Rick Woldenberg, CEO of educational toy manufacturer Learning Resources, gave WIRED a breakdown of the timeline: Placing orders and having factories manufacture the products takes three months, and then shipping them from China to the US takes another two. That means, if a company is aiming to have its inventory begin arriving at US warehouses by mid-September to begin preparing for the December holiday season, they really need to start working now, in April.

Earlier this month, Woldenberg sued the Trump administration over the tariffs, alleging the president overstepped his authority by introducing such broad import duties. “We are trying to stand up for ourselves and protect our rights,” he says. “We need help now. The sooner the better. We want them to stop.”

Woldenberg predicts that toy store shelves won’t necessarily be empty come Christmas, because retailers may scramble to find discontinued products or other replacements to fill the gap, but they won’t necessarily be the items customers are looking for. “That is when Americans are really going to find out what a terrible idea this has been,” he says. “We had this once-in-a-millennium amazing supply chain, and it’s being torn apart for no reason.”

What services does Bliss Wedding Chapel offer?

Bliss Wedding Chapel offer

Bliss Wedding Chapel has earned a reputation as one of the top wedding venues in Las Vegas, offering a range of services designed to make each wedding day as smooth and memorable as possible. Known for its intimate atmosphere and professional staff, the chapel provides various wedding packages tailored to meet the needs of couples looking for everything from a simple ceremony to a more elaborate celebration. But what services does Bliss Wedding Chapel offer to ensure that every couple’s special day goes off without a hitch?

One of the standout features of Bliss Wedding Chapel is its comprehensive wedding packages. These packages are designed to be flexible and customizable, ensuring that couples can choose the elements that best fit their vision for the big day. From basic wedding ceremonies to all-inclusive options that cover photography, flowers, and even transportation, Bliss Wedding Chapel ensures that couples have everything they need to make their wedding day as stress-free as possible. The chapel staff works closely with each couple to help them select the right package, offering guidance and advice along the way.

Bliss wedding chapel also offers officiant services, which is a critical component of any wedding. Couples can rest assured knowing that experienced officiants will be on hand to guide them through their vows, adding a personal touch to the ceremony. Whether couples prefer a traditional ceremony or something more personalized, the officiants at Bliss Wedding Chapel are skilled at accommodating various preferences and styles. The staff can help couples craft vows, choose readings, or incorporate special elements into the ceremony, ensuring that the event reflects their unique personalities and love story.

What services does Bliss Wedding Chapel offer?

For those looking to enhance their wedding experience, Bliss Wedding Chapel offers additional services such as professional photography. With on-site photographers experienced in capturing beautiful, intimate moments, couples can ensure that their wedding memories are preserved in high-quality photos. These photographers understand the importance of each moment, capturing both the big moments and the smaller, more intimate exchanges that make weddings so special. Couples can choose from a variety of photography packages, ranging from a few candid shots to extensive albums that document the entire ceremony and reception.

The chapel also offers floral arrangements, another essential element of any wedding. Couples can choose from a range of floral designs, including bouquets, boutonnieres, and centerpiece arrangements. The flowers are carefully selected to match the couple’s wedding theme, adding a touch of natural beauty to the ceremony and reception. The team at Bliss Wedding Chapel works closely with florists to ensure that the flowers are fresh, vibrant, and perfectly suited to each couple’s preferences.

For couples traveling from out of town, Bliss Wedding Chapel offers limousine transportation services. This service adds an extra touch of luxury and convenience, ensuring that the couple and their guests can travel in style to and from the chapel. Whether couples are arriving for their ceremony or heading to a reception afterward, the limousine service provides a comfortable and memorable travel experience.

In addition to these core services, Bliss Wedding Chapel also offers live streaming options for couples who want to share their ceremony with friends and family who may not be able to attend in person. This service is especially popular for destination weddings, allowing loved ones from all over the world to witness the event virtually.

In conclusion, Bliss Wedding Chapel provides a variety of services designed to make each wedding day as beautiful and stress-free as possible. From officiant services and photography to floral arrangements and transportation, Bliss Wedding Chapel ensures that couples have everything they need to celebrate their love in style. These offerings, combined with the chapel’s stunning location and dedicated staff, make it a top choice for couples looking to create lasting memories on their special day.

AI Is Using Your Likes to Get Inside Your Head

What is the future of the like button in the age of artificial intelligence? Max Levchin—the PayPal cofounder and Affirm CEO—sees a new and hugely valuable role for liking data to train AI to arrive at conclusions more in line with those a human decisionmaker would make.

It’s a well-known quandary in machine learning that a computer presented with a clear reward function will engage in relentless reinforcement learning to improve its performance and maximize that reward—but that this optimization path often leads AI systems to very different outcomes than would result from humans exercising human judgment.

To introduce a corrective force, AI developers frequently use what is called reinforcement learning from human feedback (RLHF). Essentially they are putting a human thumb on the scale as the computer arrives at its model by training it on data reflecting real people’s actual preferences. But where does that human preference data come from, and how much of it is needed for the input to be valid? So far, this has been the problem with RLHF: It’s a costly method if it requires hiring human supervisors and annotators to enter feedback.

And this is the problem that Levchin thinks could be solved by the like button. He views the accumulated resource that today sits in Facebook’s hands as a godsend to any developer wanting to train an intelligent agent on human preference data. And how big a deal is that? “I would argue that one of the most valuable things Facebook owns is that mountain of liking data,” Levchin told us. Indeed, at this inflection point in the development of artificial intelligence, having access to “what content is liked by humans, to use for training of AI models, is probably one of the singularly most valuable things on the internet.”

While Levchin envisions AI learning from human preferences through the like button, AI is already changing the way these preferences are shaped in the first place. In fact, social media platforms are actively using AI not just to analyze likes, but to predict them—potentially rendering the button itself obsolete.

This was a striking observation for us because, as we talked to most people, the predictions mostly came from another angle, describing not how the like button would affect the performance of AI but how AI would change the world of the like button. Already, we heard, AI is being applied to improve social media algorithms. Early in 2024, for example, Facebook experimented with using AI to redesign the algorithm that recommends Reels videos to users. Could it come up with a better weighting of variables to predict which video a user would most like to watch next? The result of this early test showed that it could: Applying AI to the task paid off in longer watch times—the performance metric Facebook was hoping to boost.

When we asked YouTube cofounder Steve Chen what the future holds for the like button, he said, “I sometimes wonder whether the like button will be needed when AI is sophisticated enough to tell the algorithm with 100 percent accuracy what you want to watch next based on the viewing and sharing patterns themselves. Up until now, the like button has been the simplest way for content platforms to do that, but the end goal is to make it as easy and accurate as possible with whatever data is available.”

He went on to point out, however, that one reason the like button may always be needed is to handle sharp or temporary changes in viewing needs because of life events or situations. “There are days when I wanna be watching content that’s a little bit more relevant to, say, my kids,” he said. Chen also explained that the like button may have longevity because of its role in attracting advertisers—the other key group alongside the viewers and creators—because the like acts as the simplest possible hinge to connect those three groups. With one tap, a viewer simultaneously conveys appreciation and feedback directly to the content provider and evidence of engagement and preference to the advertiser.

Car Subscription Features Raise Your Risk of Government Surveillance, Police Records Show

What is also clear from the documents is that US police are aware of the control corporations have over their ability to acquire vehicle location data, expressing fears that they could abruptly decide to kill off certain capabilities at any time.

In a letter sent in April 2024 to the Federal Trade Commission, US senators Ron Wyden and Edward Markey—Democrats from Oregon and Massachusetts, respectively—noted that a range of automakers, from Toyota, Nissan, and Subaru, among others, are willing to disclose location data to the government in response to a subpoena without a court order. Volkswagen, meanwhile, had its own arbitrary rules, limiting subpoenas to fewer than seven days’ worth of data. The senators noted that these policies stood in contrast to public pledges previously made by some automakers to require a warrant or court order before surrendering a customer’s location data.

Automakers “differ significantly on the important issue of whether customers are ever told they were spied on,” the senators wrote. At the time of the letter, only Tesla had a policy, they said, of informing customers about legal demands. “The other car companies do not tell their customers about government demands for their data, even if they are allowed to do so.”

“We respect our customers’ privacy and take our responsibility to protect their personal information seriously,” Bennet Ladyman, a T-Mobile spokesperson, says.

AT&T spokesperson Jim Kimberly says: “Like all companies, we are required by law to provide information to law enforcement and other government entities by complying with court orders, subpoenas, and other lawful discovery requests. In all cases, we review requests to determine whether they are valid. We require a search warrant based on the probable-cause standard for all government demands for real-time or historical location information, except in emergency situations. For government demands for cell tower searches, we require a probable-cause search warrant or a court order, except in emergency situations.”

Verizon did not respond to a request for comment.

“Especially now, with American civil liberties eroding rapidly, people should exercise great caution in granting new surveillance powers to law enforcement,” says Ryan Shapiro, executive director of Property of the People.

Jay Stanley, a senior policy analyst at the American Civil Liberties Union, notes that the police documents reviewed by WIRED contained substantial detail about car surveillance that appear to be publicly unavailable, suggesting that corporations are being far more open with law enforcement than they are with their own customers.

“It’s an ongoing scandal that this kind of surveillance is taking place without people being aware of it, let alone giving permission for it,” Stanley says. “If they’re carrying out surveillance on the public, the public should know. They should have meaningful knowledge and give meaningful consent before any kind of surveillance is activated, which clearly is not the case.”

The Agonizing Task of Turning Europe’s Power Back On

At 12:30 pm local time on Monday, the power went out. Across Spain and Portugal trains, planes, and traffic lights abruptly stopped working.

Reports emerged of people being stuck in lifts, and Google Maps live data showed traffic jams in big cities, including Madrid and Barcelona, as they became gridlocked. Major airports warned passengers of delays due to the blackout. Its cause is still unknown. The blackout is estimated to have affected the entirety of Portugal and Spain and small regions in France.

“Traffic lights aren’t working. The streets are chaotic because there is an officer at every crossing,” says Gustavo, who lives in Madrid. “Water doesn’t reach flats at the top of buildings because the pumps are electric, and the very few shops that are open are only taking cash.”

This is every electrical engineer’s nightmare scenario, says Paul Cuffe, assistant professor of the School of Electrical & Electronic Engineering at University College Dublin. “The reason we don’t have widespread outages all the time is because system operators are very conservative and very proactive about using big safety margins to make sure this doesn’t happen,” he says. Engineers plan for failures in grids or surges in consumer demand that could destabilize the power supply. “These things are unusual, but to a power engineer the latent threat of it happening is always there.”

Spain’s electricity operator Red Eléctrica said in a post on X a few hours after the initial blackout that it had recovered power in some areas of Cataluña and Aragón in the northeast; País Vasco, Galicia, La Rioja, Asturias, Navarra, and Castilla y Léon in the north; Extremadura in the east; and Andalucía in the south.

Experts believe that getting the grid back up and running in both countries could take between a few hours to several days, depending on the area. While the grid is powering back up, emergency services will likely be prioritized over things like stable internet connection, they say.

There is a well-rehearsed sequence of steps that now happens, says Cuffe. They are going to be doing what is called a “black start”—a process that gradually reconnects power stations to form a functioning grid again. Electrical supply and demand has to be balanced to avoid further blackouts, meaning as power stations come online, only portions of the grid can come online with them, with the country gradually powering up, step by step. There should be a team within the grid operator that plans for this and that has identified which generators to bring online first, he explains.

“You should be anticipating every failure that can happen and you should survive any one of them,” Cuffe says. From the control room, engineers should be able to tell what parts of the grid are definitely functioning so they won’t be flying blind—but it will still take time.

“Even with a completely healthy grid, to do that black start could take 12 hours or 16 hours. You have to do it sequentially, and it takes a long time. I’m sure there are engineers in vans swarming all over the place as we speak trying to make all this happen.

유흥알바 교통비 지원해주나요?

유흥알바 교통비 지원

유흥알바를 고려하는 많은 사람들은 일자리의 근로 조건을 잘 살펴보는 것이 중요합니다. 특히 교통비 지원 여부는 중요한 요소 중 하나입니다. 유흥알바는 대부분 밤에 근무하는 직종이기 때문에, 출퇴근 시간이 일반적인 직장보다 늦고 이로 인해 교통비 부담이 클 수 있습니다. 그럼에도 불구하고 일부 유흥업소에서는 교통비를 지원해주는 경우도 있으며, 이는 아르바이트생에게 큰 도움이 됩니다.

유흥알바의 특성상 많은 경우, 해당 장소가 대중교통으로 접근하기 어려운 곳에 위치할 수 있습니다. 밤늦게까지 일하다 보면 마지막 대중교통이 끊어진 후 귀가해야 하는 상황이 발생하기도 하는데, 이럴 때 교통비 지원은 매우 중요한 요소가 될 수 있습니다. 특히 택시나 다른 교통수단을 이용해야 할 때, 그 비용을 지원해주는 경우 아르바이트생에게 큰 도움이 됩니다.

하지만 유흥알바 교통비를 지원하는 정책은 업소마다 다릅니다. 일부 업소에서는 교통비를 전액 지원하거나 일부를 지원하는 혜택을 제공하기도 하지만, 대부분의 경우 지원이 없거나, 일정 조건을 충족할 때만 교통비를 지원하는 경우가 많습니다. 예를 들어, 특정 시간대에 퇴근하거나, 특정 거리를 초과할 경우에만 지원해주는 경우가 있습니다. 이러한 조건을 사전에 명확히 확인하는 것이 중요합니다.

유흥알바 교통비 지원해주나요?

또한, 교통비 지원을 받기 위한 조건은 업소의 정책에 따라 달라지기 때문에, 유흥알바를 시작하기 전에 반드시 근로 조건을 확인하는 것이 좋습니다. 일부 업소에서는 아르바이트생이 일정 기간 이상 근무하거나, 일정한 근무 시간을 채워야만 교통비를 지원하는 경우도 있습니다. 또한, 교통비 지원의 범위도 다양할 수 있는데, 일부 업소는 기본적인 교통비만 지원하고, 초과한 금액은 아르바이트생이 부담하는 경우도 있습니다.

교통비 지원이 없는 경우에도, 유흥알바를 하면서 교통비를 절약할 수 있는 방법은 존재합니다. 예를 들어, 대중교통을 이용할 수 있는 시간대에 맞춰 출퇴근을 하거나, 여러 명이 함께 택시를 타는 등의 방법으로 교통비를 분담할 수 있습니다. 또한, 일부 아르바이트생은 자전거를 이용해 출퇴근하는 방법을 선택하기도 합니다. 이렇게 교통비를 절약하는 방법은 일정한 거리에서는 실용적일 수 있습니다.

결론적으로, 유흥알바에서 교통비 지원 여부는 업소마다 다르며, 교통비 지원이 있을 경우에는 이를 미리 확인하고 근로 조건을 파악하는 것이 중요합니다. 교통비가 지원되는 유흥알바는 아르바이트생에게 경제적 부담을 덜어주고, 더욱 원활하게 일을 할 수 있는 환경을 제공할 수 있습니다.

Eli Lilly Sues 4 GLP-1 Telehealth Startups, Escalating War on Knockoff Drugs

The FDA gave compounders a grace period to wind down their production of the drugs after the shortage was over. Small pharmacies had until February 18 to comply, while larger outsourcing facilities had until March 19. (Semaglutide compounders were ordered to cease mass production this spring, with smaller compounders given a deadline of April 22 and outsourcing facilities given until May 22.)

While many compounding pharmacies and telehealth providers have halted production and sales, others have continued to offer tirzepatide products with add-on ingredients, unapproved dosages, or in different forms, such as oral versions. “It’s a minority,” says Jayne Hornung, chief clinical officer at the pharmaceutical analytics company MMIT.

Hornung says that companies continuing to sell tirzepatide are hoping the vitamin additives and other tweaks will allow them to argue they aren’t selling straightforward copies of Lilly’s patented drugs. “They’re getting very creative,” she says.

Compounding pharmacies are generally permitted to create customized medicines for patients even when they’re not in shortage, such as for individuals who may be allergic to certain ingredients or need carefully calibrated doses. The crux of Lilly’s argument is that, when it comes to tirzepatide, the medications telehealth companies are offering are not truly personalized because they are being mass produced and prescribed to many patients.

“There are some ways that compounders tailor a medication to the patient, such as by adding another ingredient that might help with a side effect or an additional concern or diagnosis,” says Annie Lambert, a pharmacist and clinical program manager at information services firm Wolters Kluwer. “But there needs to be good science and evidence behind the safety of combining those things.”

Mass-producing compounded versions of existing drugs with additives was not widespread until recently, according to Nicole Snow, a pharmacist at the compounding company Olympia Pharmaceuticals, which previously produced compounded tirzepatide but stopped after the shortage ended and never included additives. “We’d seen it from time to time, but not in this magnitude,” she says. “It wasn’t a very popular thing until we got into GLP-1s.”

In its suit against Mochi, Eli Lilly claims the telehealth company “switched dosages and prescriptions for patients en masse at least five times—with corporate interests, rather than doctor decisionmaking—driving the changes.”

Those changes, Lilly alleges, included creating two new formulas containing a niacinamide additive and pyridoxine, both forms of vitamin B that the pharma company argues have not been proven to be safe or effective when combined with tirzepatide. Mochi’s own compounder, Aequita Pharmacy, made some of those products. In March, regulators in Washington state ordered production to be halted at Aequita Pharmacy, citing safety violations connected to GLP-1 medications.

In another lawsuit filed in the same California court, Lilly claims that Fella & Delilah Health switched all of its patients from a compounded tirzepatide product with no additives to a version containing untested amino acid additives late last year.

The pharmaceutical giant’s lawsuit against Henry Meds, which offers oral and injectable GLP-1 medications, accuses the company of “creating the false impression” that clinical trials have confirmed the effectiveness of its drugs, “materially omitting that no such clinical trial data exists.”

Bad News for China: Rare Earth Elements Aren’t That Rare

“The heavy rare earth elements are added as sort of a spice, a doping agent, to maintain the magnetism of the magnet at high temperatures. It also improves corrosion resistance and the longevity of the magnet,” says Seaver Wang, director of the climate and energy team at the Breakthrough Institute, an Oakland-based think tank.

Beyond magnets, these rare earth elements can also serve a range of purposes, such as making metal stronger, improving radar systems, and even treating cancer. Without them, in many cases, technological infrastructure and consumer gadgets won’t be able to perform at the same level—but they will still maintain their basic functions. “The wind turbines will just go out of service 10 years earlier; electric vehicles will not last as long,” says Wang.

Lange agrees that the impact of losing access to heavy rare earth elements would be somewhat manageable for American companies. “One place where that rare earth is in your car is in the motors that pull up and down your window,” says Lange. “There are ways to just deal with some things that are not as fun, like rolling down your windows by hand.”

Loopholes and Workarounds

In the past, China’s critical mineral restrictions haven’t worked very well. One reason is that US companies that want to buy rare earth minerals can simply go through an intermediary country first. For example, Belgium has emerged as a possible re-export hub that appears to pass germanium—one of the minerals Beijing first restricted in 2023—from China to the US, according to trade data. Since the European Union has much closer ties with Washington than with Beijing, it’s difficult for the Chinese government to effectively stop this flow of trade.

Another sign that China’s export controls haven’t been very effective is that the price of critical minerals has increased only slightly since the policies were first implemented, indicating that supply levels have remained steady. “Whatever they did in 2023 hasn’t really changed the status quo” of the market, says Lange.

But China’s latest restrictions are more expansive, and there’s already some evidence that things could be different this time. Companies that need these elements have been forced to buy them from other firms with existing private stockpiles, which have become more valuable in recent weeks. “There is a very steep increase in prices to draw down on stockpiles right now,” says Baskaran, citing conversations she’s had with rare earth traders.

In the long run, however, companies may be able to find technological solutions to address a potential shortage of rare earth minerals. Tesla, for example, announced in 2023 that it had reduced the use of them in its EV motors by 25 percent, and it planned to get rid of them completely in the future. The carmaker hasn’t clarified what it would use instead, but experts speculate it could be turning to other types of magnets that don’t rely on rare earths.

Where Are the American Mines?

While rare earths, or critical minerals in general, are often cited along with semiconductors as industries the US wants to reshore the most, the challenges associated with bringing each of them back are very different.

Unlike making advanced semiconductors, which requires using sophisticated machinery worth hundreds of millions of dollars and building extremely complicated factories, critical minerals aren’t that hard to produce. The technologies involved to mine and refine them are mature and both the US and Canada have large natural deposits of some of them. But the mining industry was pushed out of the West because it doesn’t generate much value and is also extremely polluting.

AI Is Spreading Old Stereotypes to New Languages and Cultures

So, there’s the training data. Then, there’s the fine-tuning and evaluation. The training data might contain all kinds of really problematic stereotypes across countries, but then the bias mitigation techniques may only look at English. In particular, it tends to be North American– and US-centric. While you might reduce bias in some way for English users in the US, you’ve not done it throughout the world. You still risk amplifying really harmful views globally because you’ve only focused on English.

Is generative AI introducing new stereotypes to different languages and cultures?

That is part of what we’re finding. The idea of blondes being stupid is not something that’s found all over the world, but is found in a lot of the languages that we looked at.

When you have all of the data in one shared latent space, then semantic concepts can get transferred across languages. You’re risking propagating harmful stereotypes that other people hadn’t even thought of.

Is it true that AI models will sometimes justify stereotypes in their outputs by just making shit up?

That was something that came out in our discussions of what we were finding. We were all sort of weirded out that some of the stereotypes were being justified by references to scientific literature that didn’t exist.

Outputs saying that, for example, science has shown genetic differences where it hasn’t been shown, which is a basis of scientific racism. The AI outputs were putting forward these pseudo-scientific views, and then also using language that suggested academic writing or having academic support. It spoke about these things as if they’re facts, when they’re not factual at all.

What were some of the biggest challenges when working on the SHADES dataset?

One of the biggest challenges was around the linguistic differences. A really common approach for bias evaluation is to use English and make a sentence with a slot like: “People from [nation] are untrustworthy.” Then, you flip in different nations.

When you start putting in gender, now the rest of the sentence starts having to agree grammatically on gender. That’s really been a limitation for bias evaluation, because if you want to do these contrastive swaps in other languages—which is super useful for measuring bias—you have to have the rest of the sentence changed. You need different translations where the whole sentence changes.

How do you make templates where the whole sentence needs to agree in gender, in number, in plurality, and all these different kinds of things with the target of the stereotype? We had to come up with our own linguistic annotation in order to account for this. Luckily, there were a few people involved who were linguistic nerds.

So, now you can do these contrastive statements across all of these languages, even the ones with the really hard agreement rules, because we’ve developed this novel, template-based approach for bias evaluation that’s syntactically sensitive.

Generative AI has been known to amplify stereotypes for a while now. With so much progress being made in other aspects of AI research, why are these kinds of extreme biases still prevalent? It’s an issue that seems under-addressed.

That’s a pretty big question. There are a few different kinds of answers. One is cultural. I think within a lot of tech companies it’s believed that it’s not really that big of a problem. Or, if it is, it’s a pretty simple fix. What will be prioritized, if anything is prioritized, are these simple approaches that can go wrong.

We’ll get superficial fixes for very basic things. If you say girls like pink, it recognizes that as a stereotype, because it’s just the kind of thing that if you’re thinking of prototypical stereotypes pops out at you, right? These very basic cases will be handled. It’s a very simple, superficial approach where these more deeply embedded beliefs don’t get addressed.

It ends up being both a cultural issue and a technical issue of finding how to get at deeply ingrained biases that aren’t expressing themselves in very clear language.

The Meta Trial Shows the Dangers of Selling Out

Meta has a lot at stake in the current FTC lawsuit against it. In theory a negative verdict could result in a company breakup. But CEO Mark Zuckerberg once faced an even bigger existential threat. Back in 2006, his investors and even his employees were pressuring him to sell his two-year-old startup for a quick payoff. Facebook was still a college-based social network, and several companies were interested in buying it. The most serious offer came from Yahoo, which offered a stunning $1 billion. Zuckerberg, though, believed he could grow the company into something worth much more. The pressure was tremendous, and at one point he blinked, agreeing in principle to sell. But immediately after that, a dip in Yahoo stock led its leader at the time, Terry Semel, to ask for a price adjustment. Zuckerberg seized the opportunity to shut down negotiations; Facebook would remain in his hands.

“That was by far the most stressful time in my life,” Zuckerberg told me years later. So it’s ironic to observe, through the testimony of this trial, how he treated two other sets of founders in very similar situations to him—but whom he successfully bought out.

The nub of the current FTC trial seems to hinge on how US District Court judge James Boasberg will define Meta’s market—whether it’s limited to social media or, as Meta is arguing, the broader field of “entertainment.” But much of the early testimony exhumed the details of Zuckerberg’s successful pursuit of Instagram and WhatsApp—two companies that, according to the government, are now part of Meta’s illegal monopolistic grip on social media. (The trial also invoked the case of Snap, which resisted Zuckerberg’s $6 billion offer and had to deal with Facebook copying its products.) Legalities aside, the way these companies were upended by a Zuckerberg offer made the first few days of this case a dramatic and instructive study of acquisition dynamics between small and big business.

Though almost all of these narratives have been covered at length over the years—I documented them pretty thoroughly in my own 2020 account Facebook: The Inside Story—it was striking to see the principals testifying under oath about what happened. Hey, my sources were pretty good, but I didn’t get to swear them in!

In their testimony, star witnesses Zuckerberg and Instagram cofounder Kevin Systrom agreed on facts, but their interpretations were Mars and Venus. In 2012, Instagram was about to close a $500 million investment round, when suddenly the tiny company found itself in play, with Facebook in hot pursuit. In an email at the time, Facebook’s CFO asked Zuckerberg if his goal was to “neutralize a potential competitor.” The answer was affirmative. That was not the way he pitched it to Systrom and cofounder Mike Krieger. Zuckerberg promised the cofounders they would control Instagram and could grow it their way. They would have the best of both worlds—independence and Facebook’s huge resources. Oh, and Facebook’s $1 billion offer was double the valuation of the company in the funding round it was about to close.

Everything worked great for a few years, but then Zuckerberg began denying resources to Instagram, which its cofounders had built into a juggernaut. Systrom testified that Zuckerberg seemed envious of Instagram’s success and cultural currency, saying that his boss “believed we were hurting Facebook’s growth.” Zuckerberg’s snubs ultimately drove Instagram’s founders to leave in 2018. By that time, Instagram was arguably worth perhaps 100 times Zuckerberg’s purchase price. Systrom and Krieger’s spoils, though considerable, did not reflect the fantastic value they had built for Facebook.

‘Who Is Doge?’ Has Become a Metaphysical Question

The question of who DOGE is has taken on an almost metaphysical quality as the organization’s mandate has expanded. According to Trump’s January 20 executive order establishing DOGE, every federal agency is required to create a DOGE team of at least four employees. (Ehikan’s claim that there is no DOGE team at the GSA may be technically true, but if so, the agency would seem to be in violation of the order.)

Those teams—some members of which are career civil servants and certainly not DOGE employees of any description—were originally tasked with carrying out DOGE’s stated mission to make the government more efficient. But subsequent orders, including a March 20 order to eliminate waste, fraud, abuse, and data silos, have massively widened the scope of DOGE’s work, leading one set of plaintiffs to allege that “‘waste, fraud, and abuse’ are not magic words, and they cannot conjure up a need to grant DOGE Team members on-demand access to Americans’ most sensitive and personal information,” according to a lawsuit filed by the AFL-CIO and other labor groups.

All of this means that the line between who is working for DOGE and who is enthusiastically doing DOGE is blurry at best.

Take DOGE affiliate and former Tesla employee Riley Sennott, who according to a recent Business Insider report was listed as a “senior adviser” at NASA and also appeared to work for the GSA. Sennott was listed as an “IT specialist” GS-15 employee on the GSA’s payroll at the time, WIRED confirmed. Sennott’s journalist father, Charles Sennott, published a column later that month in the Columbia Journalism Review explicitly stating that his son works at the GSA—not DOGE. “It is fair to say that Riley’s current work is part of a broad effort that the public has come to know as DOGE,” the elder Sennott wrote—but also argued that “the General Services Administration is not the same as Elon Musk’s self-proclaimed Department of Government Efficiency, or DOGE.”

A number of other high-profile DOGE team members, including Edward “Big Balls” Coristine, Ethan Shaotran, Nicole Hollander, Jeremy Lewin, Luke Farritor, Kyle Schutt, Nathan Cavanaugh, Justin Aimonetti, and Ashley Boizelle, were listed on the GSA payroll at the time Ehikian made his comments at the March 20 all hands, according to documents viewed by WIRED. (Coristine, Shaotran, Hollander, and Farritor are listed as having salaries of $0, while the others collect from $120,000 to more than $150,000 annually.) Sara Sami, the president of an HR consultancy serving federal agencies, says this doesn’t necessarily confirm that they work within the agency, since the GSA processes payroll for other agencies and committees. “They could be classified as DOGE employees, but their pay could be run through the GSA,” she says. GSA employees can also be detailed to other agencies.

Still, GSA employees say they see DOGE affiliates in the office every week. WIRED has confirmed sightings of Coristine, Shaotran, Farritor, Cavanaugh, Gavin Kliger, and Marko Elez over the past few months.

“They’re young tech bros walking around together,” says a current GSA employee. “It’s obvious who they are,” agrees another.

The Real Winners of the Trump Memecoin Feeding Frenzy

On Wednesday, the team behind the official Donald Trump memecoin sparked a trading frenzy after announcing that the investors who held the largest amount of the crypto coin in the coming weeks would be invited to a gala dinner attended by the US president.

“At this intimate private dinner, hear first-hand president Trump talk about the future of crypto [sic],” reads the listing on the TRUMP coin website. “The most exclusive invitation in the world. Only for the top 220 $TRUMP meme coin holders.” The dinner is set to take place on May 22.

Traders rushed to buy up the TRUMP coin, some trying to bump themselves onto the invite list and others simply hoping to profit, according to analysis by blockchain analytics firm Nansen. Within an hour, its price had surged by almost 60 percent.

However, for the two organizations that own 80 percent of the coin’s supply—CIC Digital LLC and Fight Fight Fight LLC, offshoots of a conglomerate owned by Trump—the market price was a secondary concern. In the immediate term, those firms profit primarily based on how frequently people trade it.

When Trump announced his memecoin in January, the two organizations funneled 10 percent of the total supply into a so-called liquidity pool, the purpose of which is to ensure the asset can be traded freely. In return for supplying liquidity and promising to buy and sell the coin as trades come in—known as market making—the Trump-affilitated organizations command a fee. That fee ranges from 0.1 to 10 percent of each trade depending on the present level of demand. Think of it like surge pricing on a ride-hailing app.

“If you have a coin and you control the market making and the fees generated, what you care about is volume and price movement, not price itself,” says Nathan van der Heyden, head of business development at crypto company Aragon.

Previously, Trump-affilitated entities have reportedly earned tens of millions of dollars in trading fees in connection with the TRUMP coin. In the 24 hours following the dinner announcement, $1.6 million in fees were collected by contributors to the TRUMP liquidity pool on Meteora, the exchange through which the token was originally launched. Most of that money will have accrued to CIC Digital and Fight Fight Fight as the largest contributors to the pool, based on previous reports.

On paper, the Trump-affilitated organizations also stand to gain by any appreciation in the price of TRUMP, as they are by far the largest holders. But in practice, they are prevented from selling their stash of coins, partly by a mechanism that limits access to their holdings for a three-year period, and partly by the prospect of a backlash resulting from the inevitable drop in price caused by any large sales.

“The optics of profiting from selling your own coin are terrible, while profiting from the market making is opaque enough to protect your reputation,” says van der Heyden.

‘You Can’t Lick a Badger Twice’: Google Failures Highlight a Fundamental AI Flaw

Here’s a nice little distraction from your workday: Head to Google, type in any made-up phrase, add the word “meaning,” and search. Behold! Google’s AI Overviews will not only confirm that your gibberish is a real saying, it will also tell you what it means and how it was derived.

This is genuinely fun, and you can find lots of examples on social media. In the world of AI Overviews, “a loose dog won’t surf” is “a playful way of saying that something is not likely to happen or that something is not going to work out.” The invented phrase “wired is as wired does” is an idiom that means “someone’s behavior or characteristics are a direct result of their inherent nature or ‘wiring,’ much like a computer’s function is determined by its physical connections.”

It all sounds perfectly plausible, delivered with unwavering confidence. Google even provides reference links in some cases, giving the response an added sheen of authority. It’s also wrong, at least in the sense that the overview creates the impression that these are common phrases and not a bunch of random words thrown together. And while it’s silly that AI Overviews thinks “never throw a poodle at a pig” is a proverb with a biblical derivation, it’s also a tidy encapsulation of where generative AI still falls short.

As a disclaimer at the bottom of every AI Overview notes, Google uses “experimental” generative AI to power its results. Generative AI is a powerful tool with all kinds of legitimate practical applications. But two of its defining characteristics come into play when it explains these invented phrases. First is that it’s ultimately a probability machine; while it may seem like a large-language-model-based system has thoughts or even feelings, at a base level it’s simply placing one most-likely word after another, laying the track as the train chugs forward. That makes it very good at coming up with an explanation of what these phrases would mean if they meant anything, which again, they don’t.

“The prediction of the next word is based on its vast training data,” says Ziang Xiao, a computer scientist at Johns Hopkins University. “However, in many cases, the next coherent word does not lead us to the right answer.”

The other factor is that AI aims to please; research has shown that chatbots often tell people what they want to hear. In this case that means taking you at your word that “you can’t lick a badger twice” is an accepted turn of phrase. In other contexts, it might mean reflecting your own biases back to you, as a team of researchers led by Xiao demonstrated in a study last year.

“It’s extremely difficult for this system to account for every individual query or a user’s leading questions,” says Xiao. “This is especially challenging for uncommon knowledge, languages in which significantly less content is available, and minority perspectives. Since search AI is such a complex system, the error cascades.”

Is Tesla on the Outs in China?

Zeyi Yang: Yes, she is.

Zoë Schiffer: Can you talk to me about that relationship? And also, what is Tesla’s standing like in China? Is it viewed as a popular, cool car still?

Zeyi Yang: It’s still sort of, because for the longest time, Chinese auto brands have been seen as much inferior than foreign brands. Tesla still has that halo on as this American electric car company. But it’s losing it as we speak. Also, when we talk about the relationship between Tesla and China, sometimes I forget how far back it dates. There’s one very interesting figure we have to talk about. His name is Zhuanglong. He used to be Chinese Minister of Industry and Information Technologies. Basically, the chief ministry of innovations in China. He went to San Francisco in 2008 and tried one of the roadsters, one of the first electric cars that Tesla makes. Because he came from the auto industry, he was an electric car nerd. That’s how this all started. Then, from Musk’s very first visit to China in 2014, he met this guy again. He really tried to push for it to sell his car in China, and later we know built a Gigafactory in Shanghai in 2020. That’s a long history of how Musk and Tesla entered China. But what we know for now is that China is one of the most production facility for Tesla. It’s also one of the biggest market for Tesla. Tesla absolutely cannot lose China.

Zoë Schiffer: That’s really fascinating, because we know with other tech companies like Google and Meta, they tried really, really hard to get into China and weren’t quite as successful, or completely failed in some cases. But Elon Musk was able to prevail. Do we know why that was?

Zeyi Yang: I think it helps that he’s working on a car company instead of a social media company, because there’s just so much stricter control over information and internet in China. Whereas if you’re just making a car, it don’t really go across those red lines that China has. Also, it just helps that China, for the last two decades, have really been thinking, “Maybe I should be betting on electric vehicle as the future of transportation, too.” It did welcome Tesla to be a part of its grand experiment, and also investment to build up an EV empire. That’s why Tesla become a very central part of it and contributed to how China has achieved so far.

Zoë Schiffer: Well, that leads right into my next question, because China has invested really heavily in electric vehicles. In part, I think, to reduce its dependency on foreign oil imports. How is that going so far?

Zeyi Yang: It’s going pretty well, I will say. Yeah. China does not have very rich oil reserve and it has been importing oil from a lot of other places for the longest time. That’s why the Chinese government have always been very careful about that, because if, for example, a World War III happens, those oil supply are going to be cut off. What is it going to do? I think in the early days, I will say the early 2000s, the idea of electric vehicles was this moonshot idea. Where they were thinking, “Maybe, if one day all the cars will be powered by electricity, then we don’t need to import this oil anymore and we’ll be much more secure if war breaks out.” That’s when they really started investing in the research of batteries and electric vehicles as a college research funds. But then, that gradually lead to Chinese companies building up. They heavily subsidize any car company who can make actually a product that get run on the road and customers can buy. All of that, after years of heavy spending, lead to what we have right now, which is a very booming electric vehicle market in China. I think the latest data says that more than 50% of consumers when they’re trying to buy a new car, they go for electric rather than a gas car. That’s pretty remarkable.

Investors Worry Trump’s Tariffs Could Cause a ‘World of Hurt’ for Startups

“To the extent you are midstream in raising capital, get that closed as soon as possible. We repeat, close anything midstream ASAP,” Hazard wrote. “And be really judicious about how your capital is being deployed.”

Managing partner Charles Hudson told WIRED that his venture firm, Precursor, has stakes in several ecommerce startups that could be “heavily impacted” by Trump’s tariffs.

But, Hudson adds, he doesn’t know the best way to strategize around the tariffs, because “the logic for their timing, scale, and scope seems to reside only in the head of our president, and tariffs aren’t being discussed as part of the normal policy-making process that would give us more clarity.”

Precursor, which invests in early-stage startups, just raised more than $65 million for its fifth fund. Hudson said in a recent interview with The Information that he plans to make investments over a three-year period rather than the standard two years. The hope is that the extra time horizon will give limited partners, who supply the funding to venture capital firms, to see returns on their investments.

Hudson also predicted that selling stock in private startups on the secondary market will make up the overwhelming majority of liquidity that investors see over the next five years, rather than returns from acquisitions or initial public offerings.

Other VCs agree that the secondary market is likely to heat up. “VCs used to be the ultimate HODLers, holding on for dear life, riding it out until a startup they invested in IPO’d,” says Drummond. “But over the past 10 years they’ve had to become much more disciplined sellers and figure out how to deliver liquidity sooner.” That’s been true for a while because of rising interest rates and VCs being more cautious, but it’s “especially true now,” he says.

Analysts from PitchBook, a database for statistics about the venture capital and private equity markets, warn the tariffs could have a cooling effect on international investments, noting that startups once celebrated for having “global first” strategies might now be seen as vulnerable.

In the first quarter of this year, prior to Trump’s official tariff announcements, a smaller share of US capital was already flowing to VC deals in Europe and China than in recent periods. Around 47 percent of European deals included US funding, down four percentage points from the final quarter of 2024.

“For decades, VC has flourished in an increasingly borderless world, but another week of tariff wars is prompting a major reassessment,” PitchBook reporter Leah Hodgson wrote earlier this month.

Bad News for IPOs

Before Trump took office, investors had been hopeful that the tech IPO market would continue rebounding this year after falling into a slump in 2022. The market was showing signs of recovery in 2024: There were 176 initial public offerings in the US last year compared to 127 in 2023 and 90 in 2022, according to data collected by the consulting firm EY.

Accounting firm KPMG noted in a report published earlier this month that “lingering market uncertainties” had led many startups to delay their imminent public debuts this quarter. The mobile banking service Chime, ticket giant StubHub, and Swedish “buy now, pay later” firm Klarna all hit pause on planned public offerings. AI infrastructure firm CoreWeave was the outlier—it began trading shares in late March.

He Built Memecoin Factory Pump.Fun. Did He Make a Small Fortune Dumping His Own Shitcoins as a Teen?

Performing an ICO generally involves deploying code to mint a coin on the Ethereum network, outlining the ambitions for a project on a website, and soliciting investment. “Many projects were little more than a white paper and a landing page with a countdown timer—the barrier to entry was minimal,” says Wang.

Though a handful of crypto projects that raised funds by ICO remain in operation—including Ethereum itself—the boom was largely characterized by grift and chicanery, analysts say, before financial regulators eventually cracked down on the practice. Frequently, developers misrepresented the utility and capabilities of their projects, manipulated the price of coins to generate hype, and wildly overstated the profits available to investors, analysts claim.

Developers “were trying to really push the idea of getting crazy returns,” says Nicolai Søndergaard, research analyst at blockchain analytics company Nansen, adding, “That’s where the FOMO really comes in.”

The clamor around ICOs led credulous investors to conduct little due diligence in their eagerness to profit, in a similar way to traders who today race into dubious memecoins. “There are a lot of parallels between the meme frenzy and ICOs,” says Søndergaard. “It’s quite easy to sell an idea for the masses, then rug it.”

The developer going by the name Dylan Kerler began to promote EthereumCash, their most popular coin, in early October 2017.

The developer followed largely the same playbook as their previous launches: They minted the coin on Ethereum, created a website, and marketed on BitcoinTalk, Twitter, and Telegram. To create a swell of enthusiasm, they handed out bundles of the coin for free in what’s called an airdrop. Then they promised to publish a white paper, which at that time was considered a signal of legitimacy likely to propel the price upward.

“You want to push a white paper. That’s what gets people interested,” says Søndergaard. “Sometimes, just the promise of a white paper was enough.”

Screenshots of the now-deleted website posted on Telegram reveal how the coin was presented to prospective investors. “We aim to make the transition from fiat currency to cryptocurrency as easily as possible whilst still maintaining an heir [sic] of integrity an [sic] sophistication,” the website stated. Underneath, the page featured an image of a bank card that would purportedly allow holders to spend EthereumCash in stores.

Within a few days, hundreds of people signed up for the EthereumCash airdrop, a spreadsheet obtained by WIRED shows. Meanwhile, the BitcoinTalk thread was abuzz with conversation. “Let [sic] spread the word and get people to notice this great token,” wrote one forum user. By October 19, EthereumCash had risen in value to around $1.3 million.

However, as early investors celebrated, behind the scenes the developer going by Dylan Kerler was beginning to sell.

In the days after creating EthereumCash, the developer delivered millions of units to a variety of crypto wallets under their control. One of those crypto wallets, whose alphanumeric identifier begins in 0x7f3E2, was then used to sell large quantities into the market, a CertiK analysis shows.

New Jersey Sues Discord for Allegedly Failing to Protect Children

Discord is facing a new lawsuit from the state of New Jersey, which claims that the chat app is engaged in “deceptive and unconscionable business practices” that put its younger users in danger.

The lawsuit, filed on Thursday, comes after a multiyear investigation by the New Jersey Office of Attorney General. The AG’s office claims it has uncovered evidence that, despite Discord’s policies to protect children and teens, the popular messaging app is putting youth “at risk.”

“We’re the first state in the country to sue Discord,” Attorney General Matthew Platkin tells WIRED.

Platkin says there were two catalysts for the investigation. One is personal: A few years ago, a family friend came to Platkin, astonished that his 10-year-old son was able to sign up for Discord, despite the platform forbidding children under 13 from registering.

The second was the mass-shooting in Buffalo, in neighboring New York. The perpetrator used Discord as his personal diary in the lead-up to the attack and livestreamed the carnage directly to the chat and video app. (The footage was quickly removed.)

“These companies have consistently, knowingly, put profit ahead of the interest and well-being of our children,” Platkin says.

The AG’s office claims in the lawsuit that Discord violated the state’s Consumer Fraud Act. The allegations, which were filed on Thursday morning, turn on a set of policies adopted by Discord to keep children younger than 13 off the platform and to keep teenagers safe from sexual exploitation and violent content. The lawsuit is just the latest in a growing list of litigation from states against major social media firms—litigation that has, thus far, proven fairly ineffective.

Discord’s child and teen safety policies are clear: Children under 13 are forbidden from the messaging app, while it more broadly forbids any sexual interaction with minors, including youth “self-endangerment.” It further has algorithmic filters operating to stop unwanted sexual direct messages. The California-based company’s safety policy, published in 2023, states, “We built Discord to be different and work relentlessly to make it a fun and safe space for teens.”

But New Jersey says “Discord’s promises fell, and continue to fall, flat.”

The attorney general points out that Discord has three levels of safety to prevent youth from unwanted and exploitative messages from adults: “Keep me safe,” where the platform scans all messages into a user’s inbox; “my friends are nice,” where it does not scan messages from friends; and “do not scan,” where it scans no messages.

Even for teenage users, the lawsuit alleges, the platform defaults to “my friends are nice.” The attorney general claims this is an intentional design that represents a threat to younger users. The lawsuit also alleges that Discord is failing by not conducting age verification to prevent children under 13 from signing up for the service.

In 2023, Discord added new filters to detect and block unwanted sexual content, but the AG’s office says the company should have enabled the “keep my safe” option by default.

Bluesky Is Rolling Out Official Verification

Starting today, Bluesky is rolling out a new verification system, complete with the familiar blue check marks popularized by Twitter.

The social platform, which has experienced rapid growth since it opened to the public in early 2024, formerly relied on an unconventional self-verification system where users could “authenticate” themselves by including custom domains in their web handles. Now it’s adopting a more proactive and traditional verification strategy, with the Bluesky team identifying notable accounts and bestowing blue check marks.

“It’ll be a rolling process as the feature stabilizes, and then we’ll launch a public form that people can use to request verification,” says CEO Jay Graber. The highest-priority accounts right now are government officials, news organizations and journalists, and celebrities.

As Bluesky has grown, it has seen an uptick in impersonators posing as public figures, as MIT Technology Review documented last year. To meet growing demand for ways to confirm that accounts are legit, some Bluesky power users have taken it upon themselves to create their own verification systems. As the app continues to attract celebrity users—former president Barack Obama joined earlier this spring—a more formal verification process will help reassure public figures that Bluesky is a safe digital hangout space. “We want to reduce fraud and impersonation and drive a more trustworthy environment on Bluesky,” Graber says.

Rolling out what is pretty close to a dupe of Twitter’s original verification system is not groundbreaking stuff. It’s savvy, nonetheless. The reason social networks like Instagram and TikTok aped the blue check approach wasn’t because they necessarily wanted to copy a rival’s features. It was because these symbols had been successfully established as a visual cue that an account had been vetted.

When Elon Musk purged the microblogging platform’s legacy blue check marks in favor of a pay-to-play approach, he zapped the symbol’s practical value within the X ecosystem and gave grifters and pranksters everywhere a lovely gift. Still, outside of X a blue check remains an easy shorthand for “probably not fake.”

In addition to this traditional, top-down verification approach, Bluesky is also offering “trusted verifier” status to a select group of vetted organizations. These organizations will be given a scalloped blue check mark on their Bluesky accounts. The initial batch of publications selected as trusted verifiers includes The New York Times and WIRED, with more in the works.

Whether an account is verified by Bluesky itself or by these third-party “trusted verifiers,” the blue check mark it receives will look identical. When users click or tap on the check mark, they will see a list of which organizations verified the account. For example, clicking on a blue check next to a WIRED reporter’s name would show that WIRED verified their identity and may show that Bluesky and other organizations also verified it. “Multiple organizations can verify one account,” Graber says.

The introduction of the trusted verifier system on top of the conventional, centralized verification offering is a nod to Bluesky’s general philosophy of decentralization. It’s also, one suspects, a deeply practical move, as the company’s head count remains under 25 people.

Bluesky users should begin to see the first official blue check marks today.

Thousands of Urine and Tissue Samples Are in Danger of Rotting After Staff Cuts at a CDC Laboratory

Cathy Tinney-Zara, a worker at NIOSH’s Morgantown facility who spoke to WIRED in her capacity as the union representative, says that before they lost their jobs, the researchers at the facility had been actively studying how Gulf War soldiers were affected by exposure to Mustard Gas, how pregnant workers have been affected by exposure to PFAS chemicals, and how manufacturing workers contract lung fibrosis after inhaling nanoparticles.

Two Morgantown researchers—who like others in this story, asked to remain anonymous to avoid professional repercussions—say that their laid-off colleagues were also researching how agricultural workers are impacted by inhaling dust from hemp plants, and a possible link between exposure to chemical disinfectants and asthma. The lab was also about to begin developing a rapid toxicity test for chemicals that US troops may be exposed to while they are deployed.

Mandler says he was researching why some people who manufacture, cut, and install stone countertops were starting to get silicosis—a potentially fatal lung scarring and inflammation disease that makes it difficult to breathe—after just a few years on the job. Generally, he says, workers tend to get the disease after spending decades in the field.

“I have listened to men younger than me sit across the table and talk about how they feel like they’re drowning in their own lungs because of these exposures, and they can’t see their children grow up,” Mandler says.

He adds that some of the NIOSH staffers who lost their jobs were testing how lung tissue reacts after being exposed to the dust from different brands of commercial synthetic quartz. The material, commonly used in countertops, is thought to cause more severe lung damage than exposure to pure natural quartz, Mandler says. He believes something in the manufacturing process may be to blame, but now that his research team at NIOSH has been dismantled, Mandler fears it will take longer for the scientific community to find the root cause.

Three Morgantown researchers who were affected by the job cuts tell WIRED that they have not received any information about who would be in charge of the facility’s biological samples after the reduction in force, how custody of them could be transferred, or what their ultimate fate may be. Since entire divisions at NIOSH were eliminated, one researcher says, they don’t even know who could take responsibility for the samples they oversaw at the facility.

Another researcher says that when the layoffs happened, the only instruction they received was “to destroy our purchase and travel cards, and maintenance was available to help us take personal items to our cars.”

The researcher says that CDC guidelines direct employees to keep physical samples and accompanying personally identifiable information under lock and key, and only certain authorized staff are permitted to access them. “My colleagues and I took this responsibility very seriously,” the researcher tells WIRED. “Many are worried about samples and what will become of them, sensitive and otherwise.”

Even before the recent reduction in force, Mandler and two other laid-off researchers say that a federal spending freeze ordered by the Trump administration in January had reduced the Morgantown facility’s supply of liquid nitrogen to “critical” levels. It took several weeks to restart the shipments.

Meta’s Monopoly Made It a Fair-Weather Friend

This week, Mark Zuckerberg took the stand in an antitrust trial that could result in the breakup of Meta’s social networking empire. It might be years before the nearly 3 billion users of the company’s flagship app Facebook—known internally as the Blue app—learn the fate of the service they still use, despite the constant obituaries. (For the record, two years ago, Tom Alison, who heads the service, issued a statement affirming “Facebook is not dead nor dying.”) But with all the hubbub surrounding the trial, Facebook users might have missed the most significant news about Blue in years. On March 27, 2025, the 21-year-old company quietly announced a new feature on its mobile app: an option that would give users the novel experience of seeing their friends’ content on Facebook. Finally, there was an alternative to a news feed overwhelmed with garbage, gossip, and influencer videos that people don’t necessarily ask for but can’t resist clicking on and then feeling bad about. By locating and selecting the Friends tab, your feed will populate exclusively with posts from people you know in real life and that you have chosen to connect with. You might even call it a social app. Imagine!

The company’s explanation is telling. “Over the years, Facebook evolved to meet changing needs…” read the press release, “but the magic of friends has fallen away.” I marvel at the passive voice. Meta’s valuation is over a trillion. It has connected nearly half of humanity—all because of the power of people wanting to keep up with friends and family. And somehow, the company’s core purpose of connecting friends just … fell away? Did the thousands of engineers, designers, marketers, and managers working on Facebook just wake one day and say, “Hey, has anyone seen the stuff that’s the very reason we are a company?”

No, this didn’t just happen. Consider that, in that 2023 press release about Facebook not being dead, Alison listed the priorities for the app that year, including “artificial intelligence, messaging, creators and monetization.” Not a word about boosting friend content, even though Meta executives knew that people wanted to see just that. It came out in court that for years Zuckerberg has been aware that his users crave hearing more from their friends. A Meta survey in 2020 found that 61 percent of users wanted more friend posts, and 66 percent wanted to see a wider diversity of posts among their friends. A year later, another survey reported that three out of the top four “pain points” on Facebook were due to what the Federal Trade Commission called “reduced investment in friends and family sharing.”

Here’s one explanation for this. Content from influencers, political activists, and faux news organizations is more profitable and keeps people on the service longer. Misinformation from a stranger is worth more to Meta than family updates and travel photos from friends. Those don’t usually go viral. That’s why, when Alison wrote about AI, he didn’t mean using it to find what your friends are saying but to connect you with creators who are posting to boost their own wallets, with the help of Facebook monetization. On the stand, Zuckerberg offered a different explanation for the change: People began sharing on messaging apps instead of social platforms. But could it be that the reason that they stopped sharing on Facebook was that all those toxic posts from strangers made the platform unpleasant?

Zuckerberg was slippery when it came to admitting that he bought Instagram and WhatsApp to eliminate competition—a key issue in the trial. But he was frank in acknowledging that the mission of the company has veered dramatically from the original feel-good crusade to connect humans. It’s now as much an entertainment company as a social network, he says. A chart shared by Meta showed that entertainment had overwhelmed social content. In 2025, Facebook users spent only 17 percent of their time looking at content shared from friends. That’s not because they prefer to read stuff from influencers and anger-boosters—remember, Meta’s own surveys show that users are dying to see stuff from people they know. Yet Zuckerberg matter-of-factly noted that when it comes to friend content, “That part of what we do hasn’t really grown.” Again, the passive voice!

Given the hunger people have to see friend posts, one might expect that the skills of Meta’s talented workforce would be employed to maximize the value of human connections. For many years, it was. In the early 2010s, I was frequently called to Mark Zuckerberg’s conference room, dubbed the Aquarium, to see some interesting project meant to increase the value of the social network. Some of those projects didn’t work out—remember graph search?—but they were honest attempts at fulfilling the company mission. As the decade progressed, the social aspect of Facebook became less of a priority for Zuckerberg, and his passion shifted to virtual reality and artificial intelligence.

Stumbling and Overheating, Most Humanoid Robots Fail to Finish Half Marathon in Beijing

While capabilities like dancing can be fun and eyecatching, they don’t actually show how useful humanoid robots are in real-world situations, says Fern. Even being able to run a half marathon isn’t a very useful benchmark for their skills—it’s not like there’s market demand for robots that can compete with human runners. The benchmarks that Fern says matter to him are how well they can handle diverse real-world tasks without step-by-step human instructions. “But I would expect to see China shifting this year to focusing more on doing useful things, because people are going to be bored of dancing and karate,” Fern says.

The robots who participated in the race came in a variety of forms. The shortest one was only 2 feet and 5 inches tall. Sporting a blue and white tracksuit and waving to onlookers every few seconds, it was probably the crowd favorite. The tallest, at five feet nine inches, was the winner Tiangong Ultra.

What all of the robots have in common is that they are bipedal instead of running on wheels, a requirement to participate in the race. As long as the robots met that requirement, they were free to get creative, and the companies behind them adopted a wide range of strategies to try to get an advantage over their competitors. Some were wearing kid-sized sneakers (though screwed to their pedals to avoid falling off). Others were equipped with knee pads to protect their delicate parts from damage when they fell. Most of the robots had their fingers removed and some were even missing heads—you don’t need such parts for running, after all, and taking them off reduces a robot’s weight and the amount of burden placed on their motors.

Tiangong Ultra and another model, the N2 robot made by Chinese company Noetix Robotics, which won second place in the race, stood out for their consistent, albeit slow pace. The performance of the other humanoids was mostly disastrous. One robot called Huanhuan, which has a human-like head, only moved at the speed of a snail for a few minutes while its head shook uncontrollably—as if it could fall off any time.

Another robot named Shennong looks like a real Frankenstein’s monster, with the head that resembles Gundam and four drone propellers that face backwards. It sits on a foundation with eight wheels, and it’s not clear how that alone wasn’t disqualifying. But that wasn’t even Shennong’s biggest problem, as the robot immediately twirled in two circles after taking off from the starting line, hit the wall, and dragged down its human operators with it. It was painful to watch.

Duct tape proved to be the most effective problem-solving tool. Not only did the accompanying humans make makeshift robot shoes with duct tape, they also used it to adhere the head of a robot back onto its body after it repeatedly fell off during the run, making for some very jarring scenes.

Every robot had human operators, often two or three running beside them. Some held control panels that allowed them to give the robot instructions, including how fast to go, while other operators led the way for their robots and tried to clear potential obstacles on the ground. Quite a few of the humanoids were being held on what looked like, well, pet leashes. “You wanna think of these robots more like running a remote control car through the race. But the robots don’t have wheels,” says Fern.

An AI Customer Service Chatbot Made Up a Company Policy—and Created a Mess

On Monday, a developer using the popular AI-powered code editor Cursor noticed something strange: Switching between machines instantly logged them out, breaking a common workflow for programmers who use multiple devices. When the user contacted Cursor support, an agent named “Sam” told them it was expected behavior under a new policy. But no such policy existed, and Sam was a bot. The AI model made the policy up, sparking a wave of complaints and cancellation threats documented on Hacker News and Reddit.

This marks the latest instance of AI confabulations (also called “hallucinations”) causing potential business damage. Confabulations are a type of “creative gap-filling” response where AI models invent plausible-sounding but false information. Instead of admitting uncertainty, AI models often prioritize creating plausible, confident responses, even when that means manufacturing information from scratch.

For companies deploying these systems in customer-facing roles without human oversight, the consequences can be immediate and costly: frustrated customers, damaged trust, and, in Cursor’s case, potentially canceled subscriptions.

How It Unfolded

The incident began when a Reddit user named BrokenToasterOven noticed that while swapping between a desktop, laptop, and a remote dev box, Cursor sessions were unexpectedly terminated.

“Logging into Cursor on one machine immediately invalidates the session on any other machine,” BrokenToasterOven wrote in a message that was later deleted by r/cursor moderators. “This is a significant UX regression.”

Confused and frustrated, the user wrote an email to Cursor support and quickly received a reply from Sam: “Cursor is designed to work with one device per subscription as a core security feature,” read the email reply. The response sounded definitive and official, and the user did not suspect that Sam was not human.

After the initial Reddit post, users took the post as official confirmation of an actual policy change—one that broke habits essential to many programmers’ daily routines. “Multi-device workflows are table stakes for devs,” wrote one user.

Shortly afterward, several users publicly announced their subscription cancellations on Reddit, citing the non-existent policy as their reason. “I literally just cancelled my sub,” wrote the original Reddit poster, adding that their workplace was now “purging it completely.” Others joined in: “Yep, I’m canceling as well, this is asinine.” Soon after, moderators locked the Reddit thread and removed the original post.

“Hey! We have no such policy,” wrote a Cursor representative in a Reddit reply three hours later. “You’re of course free to use Cursor on multiple machines. Unfortunately, this is an incorrect response from a front-line AI support bot.”

AI Confabulations as a Business Risk

The Cursor debacle recalls a similar episode from February 2024 when Air Canada was ordered to honor a refund policy invented by its own chatbot. In that incident, Jake Moffatt contacted Air Canada’s support after his grandmother died, and the airline’s AI agent incorrectly told him he could book a regular-priced flight and apply for bereavement rates retroactively. When Air Canada later denied his refund request, the company argued that “the chatbot is a separate legal entity that is responsible for its own actions.” A Canadian tribunal rejected this defense, ruling that companies are responsible for information provided by their AI tools.

Rather than disputing responsibility as Air Canada had done, Cursor acknowledged the error and took steps to make amends. Cursor cofounder Michael Truell later apologized on Hacker News for the confusion about the non-existent policy, explaining that the user had been refunded and the issue resulted from a backend change meant to improve session security that unintentionally created session invalidation problems for some users.

“Any AI responses used for email support are now clearly labeled as such,” he added. “We use AI-assisted responses as the first filter for email support.”

Still, the incident raised lingering questions about disclosure among users, since many people who interacted with Sam apparently believed it was human. “LLMs pretending to be people (you named it Sam!) and not labeled as such is clearly intended to be deceptive,” one user wrote on Hacker News.

While Cursor fixed the technical bug, the episode shows the risks of deploying AI models in customer-facing roles without proper safeguards and transparency. For a company selling AI productivity tools to developers, having its own AI support system invent a policy that alienated its core users represents a particularly awkward self-inflicted wound.

“There is a certain amount of irony that people try really hard to say that hallucinations are not a big problem anymore,” one user wrote on Hacker News, “and then a company that would benefit from that narrative gets directly hurt by it.”

This story originally appeared on Ars Technica.

Judge Blocks DOGE From Laying Off 90 Percent of CFPB

Over 1,400 employees who were about to be laid off from the Consumer Financial Protection Bureau (CFPB) will be able to keep working for at least another week after a federal judge intervened in the dismantling of the independent regulator on Friday.

Judge Amy Berman Jackson in Washington, DC, said the Trump administration could not move forward with the layoffs, which hit roughly 90 percent of the agency, until it presents more evidence about how the terminations have been carried out. The employees learned on Thursday that they were going to lose access to agency systems the following evening and their final date of employment would be June 16. Now, a hearing on the matter is scheduled for April 28. Jackson had previously issued a ruling slowing the firings of probationary employees at the CFPB in February.

Since its establishment by Congress in 2010, the CFPB has helped consumers fight banks and other companies over dubious fees, racial discrimination in lending, and a number of scams. But some conservatives have called for the agency to be dismantled to limit the regulation of businesses, and some companies, including tech giants, have questioned its expanding oversight. This week, an agency official told staff that cases on medical debt, student loans, consumer data, and digital payments would be de-prioritized.

Groups including the National Treasury Employees Union, which represents part of the CFPB workforce, sued the Trump administration in February in an effort to preserve the agency after its acting director, Russell Vought, sought to lay off workers and bring some projects to a stop. That prompted judge Jackson’s initial ruling calling for a pause on the initial cuts until the Trump administration provided more information. Part of her ruling was overturned by an appellate court, and the Trump administration also could appeal her order from Friday blocking the widespread layoffs.

For the time being, two current CFPB employees say they are continuing to work on their cases, including ongoing litigation.

In a court filing to Jackson on Friday, an anonymous employee said Gavin Kliger, a member of Trump’s so-called Department of Government Efficiency, managed the disputed layoffs of nearly 1,500 workers. “He kept the team up for 36 hours straight to ensure that the notices would go out yesterday (April 17),” the anonymous worker wrote. “Gavin was screaming at people he did not believe were working fast enough to ensure they could go out on this compressed timeline, calling them incompetent.”

Mark Paoletta, the agency’s chief legal officer, wrote in a separate filing on Friday that he and two other CFPB attorneys assessed “line by line” how to “right-size” the bureau. They determined that about 207 employees would be sufficient to carry out duties required by law, according to the filing, which justified laying off the rest of the agency’s roughly 1,700 employees.

“Leadership has discovered many instances in which the Bureau’s activities have pushed well beyond the limits of the law,” Paoletta wrote, citing cases pursued “without the slightest evidence of intentional discrimination” and “into new areas beyond its jurisdiction such as peer-to-peer lending, rent-to-own, and discrimination as unfair practice.”

ICE Is Paying Palantir $30 Million to Build ‘ImmigrationOS’ Surveillance Platform

“No other vendor could meet these timeframes of having the infrastructure in place to meet this urgent requirement and deliver a prototype in less than six months,” ICE says in the document.

ICE’s document does not specify the data sources Palantir would pull from to power ImmigrationOS. However, it says that Palantir could “configure” the case management system that it has provided to ICE since 2014.

Palantir has done work at various other government agencies as early as 2007. Aside from ICE, it has worked with the US Army, Air Force, Navy, Internal Revenue Service, and Federal Bureau of Investigation. As reported by WIRED, Palantir is currently helping Elon Musk’s so-called Department of Government Efficiency (DOGE) build a brand-new “mega API” at the IRS that could search for records across all the different databases that the agency maintains.

Last week, 404 Media reported that a recent version of Palantir’s case-management system for ICE allows agents to search for people based on “hundreds of different, highly specific categories,” including how a person entered the country, their current legal status, and their country of origin. It also includes a person’s hair and eye color, whether they have scars or tattoos, and their license-plate reader data, which would provide detailed location data about where that person travels by car.

These functionalities have been mentioned in a government privacy assessment published in 2016, and it’s not clear what new information may have been integrated into the case management system over the past four years.

This week’s $30 million award is an addition to an existing Palantir contract penned in 2022, originally worth about $17 million, for work on ICE’s case management system. The agency has increased the value of the contract five times prior to this month; the largest was a $19 million increase in September 2023.

The contract’s ImmigrationOS update was first documented on April 11 in a government-run database tracking federal spending. The entry had a 248-character description of the change. The five-page document ICE published Thursday, meanwhile, has a more detailed description of Palantir’s expected services for the agency.

The contract update comes as the Trump administration deputizes ICE and other government agencies to drastically escalate the tactics and scale of deportations from the US. In recent weeks, immigration authorities have arrested and detained people with student visas and green cards, and deported at least 238 people to a brutal megaprison in El Salvador, some of whom have not been able to speak with a lawyer or have due process.

As part of its efforts to push people to self-deport, DHS in late March revoked the temporary parole of more than half a million people and demanded that they self-deport in about a month, despite having been granted authorization to live in the US after fleeing dangerous or unstable situations in Cuba, Haiti, Nicaragua, and Venezuela under the so-called “CHNV parole programs.”

Last week, the Social Security Administration listed more than 6,000 of these people as dead, a tactic meant to end their financial lives. DHS, meanwhile, sent emails to an unknown number of people declaring that their parole had been revoked and demanding that they self-deport. Several US citizens, including immigration attorneys, received the email.

On Monday, a federal judge temporarily blocked the Trump administration’s move to revoke people’s authorization to live in the US under the CHNV programs. White House spokesperson Karoline Leavitt called the judge’s ruling “rogue.”

How Americans Are Surveilled During Protests

There have been a number of protests in the past few months pushing back against President Trump’s most recent policy changes, and we’re likely to see more. Today on the show, WIRED’s senior editor of security and investigations, Andrew Couts, talks us through the technology being used by law enforcement to surveil protests, how surveillance tech has evolved over the years, and what it means for anyone taking to the streets or posting to social media to voice their concerns. Plus, we share WIRED tips on how to stay safe, should you choose to protest.

You can follow Michael Calore on Bluesky at @snackfight, Lauren Goode on Bluesky at @laurengoode, and Andrew Couts on Bluesky at @couts. Write to us at [email protected].

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Transcript

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[Archival audio]: No justice, no peace. Ho ho. Trump and Musk have got to go.

Michael Calore: People are taking to the streets to challenge President Donald Trump’s most recent policy changes, some of which have been created with the aid of Elon Musk and his so-called Department of Government Efficiency.

[Archival audio]: All 50 states saw these so-called hands-off rallies and so did a few cities in Europe.

Michael Calore: The first hands-off protests occurred earlier this month. The Tesla Takedown demonstrations have been rolling for weeks, and from the feel of it, we’re looking at a summer full of protests. So today we’re talking about the risks of being surveilled by law enforcement during protests. We’ll talk about how surveillance tech is being used, how it’s evolved over the years, and what it means for anyone taking to the streets or posting to social media to voice their concerns. This is WIRED’s Uncanny Valley, a show about the people power and influence of Silicon Valley. I’m Michael Calore, director of consumer tech and culture here at WIRED.

Lauren Goode: And I’m Lauren Goode. I’m a senior writer at WIRED.

Michael Calore: Katie Drummond is out today, but we’re joined by WIRED’s senior editor of security and investigations, Andrew Couts.

Andrew Couts: Thanks so much for having me.

Michael Calore: So let’s start by talking about what’s going on right now. There are the hands-off protests, there are the Tesla Takedown protests. Are these related at all?

Lauren Goode: The hands-off protests and the Tesla Takedown movement are not the same, but they are related. They’re both in some way resisting some of the policies that Donald Trump has quickly enacted without congressional approval in the short time since he took office in January. Tesla Takedown is pegged directly at Elon Musk who has this official but unofficial role in Trump’s administration as the leader of DOGE. We sometimes refer to him as the Buddy in Chief, and the idea there is to challenge Musk’s power as one of the world’s richest men by devaluing one of his most important businesses in the private sector, which is Tesla, whereas the hands-off protests are about all kinds of things. They’re protesting the firing of federal workers, the overreaching and potentially unconstitutional immigration policies, threats to women’s rights and LGBTQ rights, threats to social security, threats to health care. The list goes on. The idea is basically get your hands off my rights.

Google Is Once Again Deemed a Monopoly, This Time in Ad Tech

A federal judge ruled today that Google is a monopolist in some parts of the online advertising market, marking the second case in a year where the company was found to have violated US antitrust law. Last August, a federal judge ruled that Google was maintaining an illegal monopoly in search.

Judge Leonie Brinkema of the US District Court for the Eastern District of Virginia determined that Google illegally monopolized parts of its advertising technology business to dominate the programmatic ad market, a major source of revenue for the company. Google generated nearly $30.4 billion in worldwide revenue last year from placing ads on other apps and websites. Now, a substantial portion of those sales are threatened by penalties that may follow Brinkema’s ruling. A best-case scenario for US consumers is a browsing experience filled with fewer ads and paywalls and more content choices.

“In addition to depriving rivals of the ability to compete, [Google’s] exclusionary conduct substantially harmed Google’s publisher customers, the competitive process, and, ultimately, consumers of information on the open web,” Brinkema wrote.

Google was found to have violated Section 2 of the Sherman Act, the cornerstone antitrust law in the US, “by willfully acquiring and maintaining monopoly power in the open-web display publisher ad server market and the open-web display ad exchange market, and has unlawfully tied its publisher ad server (DFP) and ad exchange (AdX).” In other words, the way that Google tied parts of its ad tech together was deemed unlawful.

Online ads end up in front of consumers after passing through a chain of systems linking publishers to advertisers. Google has long been viewed as a dominant provider of tools at nearly every step in this process, which critics argue enables the company to give preferential treatment to its own systems and box out competitors. Some of Google’s offerings came through acquisitions, like the purchase of DoubleClick in 2007.

But Brinkema rejected the Justice Department’s allegation that Google illegally monopolized the market for some tools used by advertisers to buy ads, claiming the government’s definition of the market was too narrow and ill-defined. As a result, Google was not determined to be a monopolist as it relates to ad-buying tools, but it was deemed to be one in the market for publisher tools to sell advertising space.

The company is leaning into the fact that not all of the plaintiff’s claims stand up in court. Google’s vice president of regulatory affairs, Lee-Anne Mulholland, put out a statement on X stating that Google won “half the case” and that the company plans to appeal the other half.

“The Court found that our advertiser tools and our acquisitions, such as DoubleClick, don’t harm competition. We disagree with the Court’s decision regarding our publisher tools. Publishers have many options and they choose Google because our ad tech tools are simple, affordable and effective,” Mulholland said.

The ad tech suit was first filed in January 2023 by the Department of Justice and eight states, which alleged that Google had illegally squashed competition in the advertising market by acting as a powerful middleman in the ad business and taking a large cut of advertising revenue in the process. Google has argued that there’s plenty of competition in the online advertising market. The case went to trial last September, and closing arguments were delivered in November.

The Department of Justice did not immediately respond to a request for comment on the ruling. Jonathan Kanter, an attorney who oversaw the trial while at the department, wrote on X that Thursday’s ruling “is a huge victory for antitrust enforcement, the media industry, and the free and open internet.”

Last August, a district judge for the District of Columbia, Amit Mehta, ruled that Google has maintained an illegal monopoly both in general search and general search text ads. The Justice Department has proposed that Google should be ordered to “promptly and fully divest” its Chrome web browser, and also stop paying partners, such as Apple, for preferential treatment on its iPhones. Google is fighting the proposals, and a trial for Mehta to reach a final remedy is scheduled to begin on Monday.

Brinkema has asked Google and the Justice Department to now propose a schedule for determining remedies in the ad tech case. The company could be ordered to sell off its ad tools for publishers as a result of this process.

Meet The AI Agent With Multiple Personalities

In the coming years, agents are widely expected to take over more and more chores on behalf of humans, including using computers and smartphones. For now, though, they’re too error prone to be much use.

A new agent called S2, created by the startup Simular AI, combines frontier models with models specialized for using computers. The agent achieves state-of-the-art performance on tasks like using apps and manipulating files—and suggests that turning to different models in different situations may help agents advance.

“Computer-using agents are different from large language models and different from coding,” says Ang Li, cofounder and CEO of Simular. “It’s a different type of problem.”

In Simular’s approach, a powerful general-purpose AI model, like OpenAI’s GPT-4o or Anthropic’s Claude 3.7, is used to reason about how best to complete the task at hand—while smaller open source models step in for tasks like interpreting web pages.

Li, who was a researcher at Google DeepMind before founding Simular in 2023, explains that large language models excel at planning but aren’t as good at recognizing the elements of a graphical user interface.

S2 is designed to learn from experience with an external memory module that records actions and user feedback and uses those recordings to improve future actions.

On particularly complex tasks, S2 performs better than any other model on OSWorld, a benchmark that measures an agent’s ability to use a computer operating system.

For example, S2 can complete 34.5 percent of tasks that involve 50 steps, beating OpenAI’s Operator, which can complete 32 percent. Similarly, S2 scores 50 percent on AndroidWorld, a benchmark for smartphone-using agents, while the next best agent scores 46 percent.

Victor Zhong, a computer scientist at the University of Waterloo in Canada and one of the creators of OSWorld, believes that future big AI models may incorporate training data that helps them understand the visual world and make sense of graphical user interfaces.

“This will help agents navigate GUIs with much higher precision,” Zhong says. “I think in the meantime, before such fundamental breakthroughs, state-of-the-art systems will resemble Simular in that they combine multiple models to patch the limitations of single models.”

To prepare for this column, I used Simular to book flights and scour Amazon for deals, and it seemed better than some of the open source agents I tried last year, including AutoGen and vimGPT.

But even the smartest AI agents are, it seems, still troubled by edge cases and occasionally exhibit odd behavior. In one instance, when I asked S2 to help find contact information for the researchers behind OSWorld, the agent got stuck in a loop hopping between the project page and the login for OSWorld’s Discord.

OSWorld’s benchmarks show why agents remain more hype than reality for now. While humans can complete 72 percent of OSWorld tasks, agents are foiled 38 percent of the time on complex tasks. That said, when the benchmark was introduced in April 2024, the best agent could complete only 12 percent of the tasks.

Will Meta Really Have to Sell Instagram and WhatsApp?

Paresh Dave: Absolutely. The timing when some of those moves were first announced was viewed as kind of suspicious because it was right around when these investigations into Meta and these cases started getting filed against Big Tech companies.

Zoë Schiffer: We’re going to take one more short break. And when we come back, we’ll tell you what to check out on WIRED.com this week. Welcome back to Uncanny Valley. I’m Zoë Schiffer, WIRED’s Director of Business and Industry. I’m joined today by WIRED’s senior writer, Paresh Dave. Before we go, Paresh, can you tell our listeners about what they have to read on WIRED.com today other than the stories we mentioned in this episode already?

Paresh Dave: Yes. Smishing Triad, the scam group stealing the world’s riches.

Zoë Schiffer: Is Smishing a phishing variant?

Paresh Dave: It’s a combination of phishing with SMS. Smishing, yes.

Zoë Schiffer: Smishing. Got it, got it, got it.

Paresh Dave: I’m sure we’ve all gotten those text messages about, “You got to pay this toll road fee,” or some parcel can’t be delivered properly. Very annoying. I still get them all the time. I don’t know why our phones can’t stop this, but this story by our colleague, Matt Burgess, talks about how a lot of these messages, which are called sort of smishing messages, originate from this group of cyber criminals that is actually constantly improving their scamming software. The cybersecurity does not have the upper hand here. And my takeaway was we are going to get more and more of these messages before it gets better. And this article is part of a WIRED series, Guide to the Most Dangerous Hackers You’ve Never Heard Of. And this is dangerous, right? There are people who type in their credit card numbers in reply to these text messages and get all their money stolen. It’s not great.

Zoë Schiffer: I feel like after I started at WIRED, I started getting messages purporting to be from company executives asking me to input personal information, which was well-timed because I had just started a new job. I was like, “I don’t know if they text me.” But no.

Paresh Dave: Maybe it was our cybersecurity team testing us. I don’t know. I had that too.

Zoë Schiffer: They do that from time to time.

Paresh Dave: And what about you, Zoë? What are you recommending this week?

Zoë Schiffer: Well, in addition to your wonderful pre-write about the trial, which everyone should read and gives people kind of a good overview of what we should expect, we also published a piece just this morning by Caroline Haskins, another writer on the business desk at WIRED, about a New Mexico man who faces federal charges for allegedly setting fire to a Tesla showroom. This is part of the kind of Tesla protest indictments that are happening. Pam Bondi, the Attorney General, and Trump and Elon Musk have all called for the people who are engaged in violent acts against Tesla property to be charged with really, really serious crimes. And this is the second time that we know of that the FBI terrorism investigators have gotten involved in an investigation tied to the kind of public backlash against Elon Musk and Tesla in particular. Bondi said that the man in question would be going to prison for 20 years or more, even though he hasn’t yet been convicted. We have a lot of detail on the allegations in the case, things that we found in the arrest warrant, and it’s a really good kind of overview of what’s happening on that. Paresh, thank you so much for joining me today.

Paresh Dave: Thanks for having me.

Zoë Schiffer: That’s our show for today. We’ll link to all the stories we spoke about in the show notes. Make sure to check out Thursday’s episode of Uncanny Valley, which is all about surveillance technology, protests, and how to safely navigate physical and online spaces during this moment. If you liked what you heard today, make sure to follow our show and rate it on your podcast app of choice. If you’d like to get in touch with us for any questions, comments, or show suggestions, write to us at [email protected]. Kyana Moghadam and Adriana Tapia produced this episode. Amar Lal at Macro Sound mixed this episode. Pran Bandi was our New York Studio engineer. Jordan Bell is our executive producer. Condé Nast Head of Global Audio is Chris Bannon. And Katie Drummond is WIRED’s Global Editorial Director.

OpenAI’s New GPT 4.1 Models Excel at Coding

OpenAI announced today that it is releasing a new family of artificial intelligence models optimized to excel at coding, as it ramps up efforts to fend off increasingly stiff competition from companies like Google and Anthropic. The models are available to developers through OpenAI’s application programming interface (API).

OpenAI is releasing three sizes of models: GPT 4.1, GPT 4.1 Mini, and GPT 4.1 Nano. Kevin Weil, chief product officer at OpenAI, said on a livestream that the new models are better than OpenAI’s most widely used model, GPT-4o, and better than its largest and most powerful model, GPT-4.5, in some ways.

GPT-4.1 scored 55 percent on SWE-Bench, a widely used benchmark for gauging the prowess of coding models. The score is several percentage points above that of other OpenAI models. The new models are “great at coding, they’re great at complex instruction following, they’re fantastic for building agents,” Weil said.

The capacity for AI models to write and edit code has improved significantly in recent months, enabling more automated ways of prototyping software and improving the abilities of so-called AI agents. Rivals like Anthropic and Google have both introduced models that are especially good at writing code.

The arrival of GPT-4.1 has been widely rumored for weeks. OpenAI apparently tested the model on some popular leaderboards under the pseudonym Alpha Quasar, sources say. Some users of the “stealth” model reported impressive coding abilities. “Quasar fixed all the open issues I had with other code genarated [sic] via llms’s which was incomplete,” one person wrote on Reddit.

All of the new models can analyze eight times more code at once, which improves their ability to make improvements and fix bugs. The new models are also better at following instructions given by users, reducing the need to repeat commands in different ways to get the desired result. OpenAI showed demos of GPT-4.1 building different apps including a flashcard app for language learning.

“Developers care a lot about coding, and we’ve been improving our model’s ability to write functional code,” Michelle Pokrass, who works on post-training at OpenAI, said during the Monday livestream. “We’ve been working on making it follow different formats and better explore repos, run unit tests, and write code that compiles.”

GPT-4.1 is 40 percent faster than GPT.4o, OpenAI’s most widely used model for developers. The cost of users inputting queries has been reduced by 80 percent in this latest version, OpenAI says.

On today’s livestream, Varun Mohan, CEO of Windsurf, a popular tool for AI coding, said that the company had been testing GPT-4.1 and found that the new model was “60 percent” better than GPT-4o according to its own benchmarks. “We found that GPT-4.1 has substantially fewer cases of degenerate behavior,” Mohan said, noting that the new model spends less time reading and editing irrelevant files by mistake.

Over the past couple of years, OpenAI has parlayed feverish interest in ChatGPT, a remarkable chatbot first unveiled in late 2022, into a growing business selling access to more advanced chatbots and AI models. In a TED interview last week, Altman said that OpenAI had 500 million weekly active users, and that usage was “growing very rapidly.”

A New Mexico Man Faces Federal Charges for Allegedly Setting Fire to a Tesla Showroom

A New Mexico man is facing federal charges for two separate incidents of alleged arson—one at an Albuquerque Tesla showroom and one at the New Mexico Republican Party’s office—according to a Monday press release from the Department of Justice.

Jamison Wagner, 40, was charged with allegedly setting fire to a building or vehicle used in interstate commerce. The charge can apply to goods manufactured and sold in different states and the facilities that house them—like the Tesla showroom or the Republican office, which also sells MAGA merchandise. DOJ spokesperson Shannon Shevlin tells WIRED that Wagner’s arrest happened on Saturday.

“Let this be the final lesson to those taking part in this ongoing wave of political violence,” attorney general Pam Bondi said in the Monday press release. “We will arrest you, we will prosecute you, and we will not negotiate. Crimes have consequences.”

Wagner’s arrest warrant alleges that he is responsible for a February 9 incident at a Tesla showroom in which windows were shattered and two Tesla Model Ys were set on fire. It also alleges that he is responsible for a March 30 incident at the Republican Party of New Mexico office in which the entrance area was set on fire and “ICE=KKK” was graffitied on the building’s exterior.

The arrest warrant also says that a lead investigator on Wagner’s case is an FBI agent specializing in “international terrorism, domestic terrorism and firearms.” This marks the second known time that FBI terrorism investigators have gotten involved in a criminal investigation tied to the recent public backlash against Musk and Tesla. However, it’s the first time that the suspect was also allegedly tied to another incident—which, in this case, targeted a Republican office.

The arrest comes amid repeated calls by Bondi, President Trump, Elon Musk, House Speaker Mike Johnson, and Representative Marjorie Taylor Greene to treat arson and vandalism of Tesla property as “domestic terrorism.” Five other people are currently facing federal charges for alleged vandalism and arson targeting Tesla property, according to press releases by the DOJ.

As reported by WIRED, law enforcement can get access to surveillance technologies and have more legal leeway during terrorism investigations than in other types of investigations. These investigations could also possibly enable Musk and Tesla executives to access surveillance on “Tesla Takedown” protesters, though the protests have broadly been peaceful, and public-facing protest organizers have said that they don’t endorse property damage. The FBI can decide to share this type of information with the victim of a crime during an investigation, WIRED previously reported.

Bondi teased news of Wagner’s arrest last week in a televised Cabinet meeting, telling Trump that there would be “another huge arrest” pertaining to an attack on a Tesla dealership within the next 24 hours.

“That person will be looking at at least 20 years in prison with no negotiations,” Bondi said on Thursday. (The DOJ press release issued after Wagner’s arrest notes, “A complaint is merely an allegation, and all defendants are presumed innocent until proven guilty beyond a reasonable doubt in a court of law.”)

A Cybersecurity Professor Disappeared Amid an FBI Search. His Family Is ‘Determined to Fight’

The wife of data privacy professor Xiaofeng Wang, who was fired from his tenured job at Indiana University, Bloomington (IU) the same day the couple’s houses were searched by the Federal Bureau of Investigation last month, said on Monday that she believes her family has been unfairly targeted by the US government and is the victim of what she described as “misplaced accusations of academic misconduct.”

“Our family is determined to fight, not only for ourselves, but for the broader research community who would be impacted if this type of allegation goes unchallenged,” Nianli Ma said.

This is the first time Ma has spoken publicly since the FBI searches occurred in late March. She appeared at a webinar hosted by the Asian American Scholar Forum (AASF), a nonprofit group formed in early 2021 to advocate for the rights and recognition of Asian American scholars. Ma worked as a library analyst at the university before she was also abruptly fired from IU days before the FBI searched two of the couple’s homes, The Indiana Daily Student reported.

“I just can’t understand how the university, to which we dedicated two decades of our lives, could treat us like this, without even telling us why or going through due process, especially for my husband,” Ma said. “I’ve lost weight and have had difficulty sleeping. I feel trapped in a constant state of worry and sadness.”

Wang’s case has raised concerns among academics that a shuttered Department of Justice program called the China Initiative is being revived under the new Trump administration. The campaign, which was started during President Trump’s first term in office with the stated goal of combating economic espionage, was accused by critics of unfairly targeting Chinese-born researchers and other Asian-immigrant and Asian-American academic communities. The DOJ later abandoned the program under the Biden administration after it lost or withdrew a number of associated cases.

One of the most high-profile of them was the case of MIT professor Gang Chen, who was charged in 2021 under the China initiative for allegedly failing to disclose links to several Chinese institutions in grant applications. Chen also spoke at Monday’s webinar. The charges against him were dropped the following year after the disclosures were found not to be required by the federal government.

“Nianli’s story is heartbreaking. The images of the FBI raid of Nianli and Professor Xiaofeng Wang’s home brings chills to our spines,” Chen said. “It brings back the fear my family and many others went through under the China Initiative. Reading the news report about you, one can not stop asking if the China Initiative has in fact returned,” he said, speaking directly to Ma.

Brian Sun, a member of the AASF legal advisory council said at the webinar that there currently appears to be “no evidence that Xiaofeng’s case involves any kind of unlawful transfer of technology or anything that would implicate the kind of concerns that led to the founding of the China initiative.”

US representative Grace Meng of New York, who gave a keynote speech at the event, said she’s concerned about efforts by the current US presidential administration to reinstate the China Initiative, which “did nothing to meaningfully address national security concerns and instead created a deep chilling effect on research and scientific innovation, as well as ruining the lives and livelihoods of those who were falsely charged.”

The Subjective Charms of Objective-C

After inventing calculus, actuarial tables, and the mechanical calculator and coining the phrase “best of all possible worlds,” Gottfried Leibniz still felt his life’s work was incomplete. Since boyhood, the 17th-century polymath had dreamed of creating what he called a characteristica universalis—a language that perfectly represented all scientific truths and would render making new discoveries as easy as writing grammatically correct sentences. This “alphabet of human thought” would leave no room for falsehoods or ambiguity, and Leibniz would work on it until the end of his life.

A version of Leibniz’s dream lives on today in programming languages. They don’t represent the totality of the physical and philosophical universe, but instead, the next best thing—the ever-flipping ones and zeroes that make up a computer’s internal state (binary, another Leibniz invention). Computer scientists brave or crazy enough to build new languages chase their own characteristica universalis, a system that could allow developers to write code so expressive that it leaves no dark corners for bugs to hide and so self-evident that comments, documentation, and unit tests become unnecessary.

But expressiveness, of course, is as much about personal taste as it is information theory. For me, just as listening to Countdown to Ecstasy as a teenager cemented a lifelong affinity for Steely Dan, my taste in programming languages was shaped the most by the first one I learned on my own—Objective-C.

To argue that Objective-C resembles a metaphysically divine language, or even a good language, is like saying Shakespeare is best appreciated in pig latin. Objective-C is, at best, polarizing. Ridiculed for its unrelenting verbosity and peculiar square brackets, it is used only for building Mac and iPhone apps and would have faded into obscurity in the early 1990s had it not been for an unlikely quirk of history. Nevertheless, in my time working as a software engineer in San Francisco in the early 2010s, I repeatedly found myself at dive bars in SoMa or in the comments of HackerNews defending its most cumbersome design choices.

Objective-C came to me when I needed it most. I was a rising college senior and had discovered an interest in computer science too late to major in it. As an adult old enough to drink, I watched teenagers run circles around me in entry-level software engineering classes. Smartphones were just starting to proliferate, but I realized my school didn’t offer any mobile development classes—I had found a niche. I learned Objective-C that summer from a cowboy-themed book series titled The Big Nerd Ranch. The first time I wrote code on a big screen and saw it light up pixels on the small screen in my hand, I fell hard for Objective-C. It made me feel the intoxicating power of unlimited self-expression and let me believe I could create whatever I might imagine. I had stumbled across a truly universal language and loved everything about it—until I didn’t.

Twist of Fate

Objective-C came up in the frenzied early days of the object-oriented programming era, and by all accounts, it should have never survived past it. By the 1980s, software projects had grown too large for one person, or even one team, to develop alone. To make collaboration easier, Xerox PARC computer scientist Alan Kay had created object-oriented programming—a paradigm that organized code into reusable “objects” that interact by sending each other “messages.” For instance, a programmer could build a Timer object that could receive messages like start, stop, and readTime. These objects could then be reused across different software programs. In the 1980s, excitement about object-oriented programming was so high that a new language was coming out every few months, and computer scientists argued that we were on the precipice of a “software industrial revolution.”

In 1983, Tom Love and Brad Cox, software engineers at International Telephone & Telegraph, combined object-oriented programming with the popular, readable syntax of C programming language to create Objective-C. The pair started a short-lived company to license the language and sell libraries of objects, and before it went belly up they landed the client that would save their creation from falling into obscurity: NeXT, the computer firm Steve Jobs founded after his ouster from Apple. When Jobs triumphantly returned to Apple in 1997, he brought NeXT’s operating system—and Objective-C—with him. For the next 17 years, Cox and Love’s creation would power the products of the most influential technology company in the world.

I became acquainted with Objective-C a decade and a half later. I saw how objects and messages take on a sentence-like structure, punctuated by square brackets, like [self.timer increaseByNumberOfSeconds:60]. These were not curt, Hemingwayesque sentences, but long, floral, Proustian ones, syntactically complex and evoking vivid imagery with function names like scrollViewDidEndDragging:willDecelerate.

FTC v. Meta Trial: The Future of Instagram and WhatsApp Is at Stake

The US Federal Trade Commission’s trial against Meta begins in Washington, DC on Monday, as the tech giant fights to avoid the spinoff of Instagram and WhatsApp. The FTC alleges that Meta illegally acquired the two startups in an effort to suppress competition.

Meta (then Facebook) bought the photo-sharing startup Instagram for $1 billion in 2012. About two years later, the company snatched up the chat tool WhatsApp for roughly $22 billion.

The FTC, one of the nation’s antitrust enforcement agencies, wants Judge James Boasberg to hold the tech giant liable for executing these mega deals to illegally maintain a social media monopoly. It has called on Boasberg to restore competition by ordering Meta to sell off its prized assets. A victory for the government could deter big tech companies from acquiring startups in the future, cutting off a key source of innovation and investment returns for venture capitalists.

The initial trial could last up to 37 days, wrapping as late as early July. If needed, a trial to decide on penalties would follow—likely next year. Appeals of any rulings could take additional years to resolve. So WhatsApp and Instagram aren’t going on sale anytime soon. But the possibility of losing two valuable properties helps explain why Mark Zuckerberg has reportedly been exploring a last-minute deal with President Donald Trump and White House officials to avert a fight in court. So far, those efforts appear unsuccessful.

Here’s what to expect as the trial kicks off.

What Is the FTC Arguing?

First, the FTC must prove that Facebook has a longstanding monopoly on “providing personal social networking services in the US,” according to its lawsuit. The category Facebook allegedly monopolizes includes services such as Snapchat and little-known MeWe, but notably excludes YouTube, TikTok, and other platforms that the FTC believes are more for watching videos by creators than following family and friends. From 2012 to 2020, Facebook commanded over 80 percent of users’ time per year within this narrowly defined market.

Second, it must show the acquisitions harmed competition in the social networking market. Around the time the Instagram and WhatsApp deal talks began, Facebook feared the threats that app startups posed to its monopoly, according to the lawsuit. Citing emails between Zuckerberg and other company executives—like Zuckerberg writing once that “it is better to buy than compete”—the FTC alleges that the company decided to buy nascent competitors to gain more time to figure out its own app development strategy. “Unable to maintain its monopoly by fairly competing, the company’s executives addressed the existential threat by buying up new innovators that were succeeding where Facebook failed,” the lawsuit alleges.

The FTC claims that after buying Instagram and WhatsApp, Facebook had fewer apps nipping at its heels and got away with providing less data privacy to users and more buggy and expensive services to advertisers. The deals also sent a message to competitors: companies trying to independently beat Facebook wouldn’t be able to get very far, the FTC says. This further stifled competition, according to the lawsuit.

What Does the FTC Want?

The commission would like competition to be restored, including possibly by having Meta divest Instagram and WhatsApp. That could be disastrous for Meta, which relies on Instagram for a significant portion of its ad revenue—an estimated 50 percent or more in the US. Other measures could include blocking Meta from completing similar deals in the future.

What Is Meta’s Defense?

The company’s primary argument is that the commission is defining the market too narrowly. Meta argues that a variety of social apps including TikTok and YouTube are very much competitors to Facebook. Add them into the mix, and Facebook can no longer be viewed as monopolist, the company says.

Should that argument not result in immediate victory for Meta, its other key contention is that the FTC has been unable to demonstrate that consumers and advertisers are worse off because of the company’s ownership of Instagram and WhatsApp—which it views as a requirement for the FTC’s case. Meta has said that the apps would not have become as successful as they are today without its stewardship. “The FTC must prove that consumers would have had more (or better) options sooner without the acquisitions,” the company’s attorneys wrote in court papers last week. “Meta respectfully submits that the FTC will not be able to introduce any evidence to satisfy its burden.”

Sex-Fantasy Chatbots Are Leaking a Constant Stream of Explicit Messages

All of the 400 exposed AI systems found by UpGuard have one thing in common: They use the open source AI framework called llama.cpp. This software allows people to relatively easily deploy open source AI models on their own systems or servers. However, if it is not set up properly, it can inadvertently expose prompts that are being sent. As companies and organizations of all sizes deploy AI, properly configuring the systems and infrastructure being used is crucial to prevent leaks.

Rapid improvements to generative AI over the past three years have led to an explosion in AI companions and systems that appear more “human.” For instance, Meta has experimented with AI characters that people can chat with on WhatsApp, Instagram, and Messenger. Generally, companion websites and apps allow people to have free-flowing conversations with AI characters—portraying characters with customizable personalities or as public figures such as celebrities.

People have found friendship and support from their conversations with AI—and not all of them encourage romantic or sexual scenarios. Perhaps unsurprisingly, though, people have fallen in love with their AI characters, and dozens of AI girlfriend and boyfriend services have popped up in recent years.

Claire Boine, a postdoctoral research fellow at the Washington University School of Law and affiliate of the Cordell Institute, says millions of people, including adults and adolescents, are using general AI companion apps. “We do know that many people develop some emotional bond with the chatbots,” says Boine, who has published research on the subject. “People being emotionally bonded with their AI companions, for instance, make them more likely to disclose personal or intimate information.”

However, Boine says, there is often a power imbalance in becoming emotionally attached to an AI created by a corporate entity. “Sometimes people engage with those chats in the first place to develop that type of relationship,” Boine says. “But then I feel like once they’ve developed it, they can’t really opt out that easily.”

As the AI companion industry has grown, some of these services lack content moderation and other controls. Character AI, which is backed by Google, is being sued after a teenager from Florida died by suicide after allegedly becoming obsessed with one of its chatbots. (Character AI has increased its safety tools over time.) Separately, users of the generative AI tool Replika were upended when the company made changes to its personalities.

Aside from individual companions, there are also role-playing and fantasy companion services—each with thousands of personas people can speak with—that place the user as a character in a scenario. Some of these can be highly sexualized and provide NSFW chats. They can use anime characters, some of which appear young, with some sites claiming they allow “uncensored” conversations.

“We stress test these things and continue to be very surprised by what these platforms are allowed to say and do with seemingly no regulation or limitation,” says Adam Dodge, the founder of Endtab (Ending Technology-Enabled Abuse). “This is not even remotely on people’s radar yet.” Dodge says these technologies are opening up a new era of online pornography, which can in turn introduce new societal problems as the technology continues to mature and improve. “Passive users are now active participants with unprecedented control over the digital bodies and likenesses of women and girls,” he says of some sites.

What Trump’s Tariffs Mean for Tech—and You

Katie Drummond: Very exciting promise by Howard Lutnick. I can’t wait to talk about whether any of that is actually possible.

Michael Calore: Certainly not in the short term.

Lauren Goode: Was this the same moment where he talked about the army of millions using tiny screws?

Katie Drummond: Oh, yes. The teeny tiny screws? The teeny tiny screws? Yeah.

Lauren Goode: That was the one on CBS Face the Nation, I think we all saw it.

Howard Lutnick [Archival audio]: The army of millions and millions of human beings screwing in little, little screws to make iPhones. That kind of thing is going to come to America.

Michael Calore: So Elon was tweeting through it. Tim Cook has probably also been sitting on Twitter and popping off some tweets calling various members of the White House advisory staff morons, right?

Lauren Goode: Tim Cook has not said anything publicly.

Katie Drummond: Let’s give that man a little credit. He is way too smart to do that. Apple is as savvy as they come, I expect to hear nothing from them about this. To Lauren’s point earlier, I mean, they are certainly working this behind the scenes, but I would expect they want this to be from a public optics point of view, no comment, smooth sailing, et cetera.

Lauren Goode: Katie, you mentioned at the time of the inauguration, when we saw that photo of the tech CEOs who were in attendance, I think your remark was Tim Cook looks like he wants to vomit?

Katie Drummond: He was not exactly beaming with enthusiasm like some of his colleagues, Mark Zuckerberg, Jeff Bezos, et cetera. He looked like someone had died, and maybe it’s his company based on what’s happening right now,

Michael Calore: Here’s hope for the future. Well, let’s talk about one of the other people in that photo, Mr. Jeff Bezos, Amazon CEO. Now, Amazon is not a hardware company like Apple, but it deals in hard goods. So what do the tariffs mean for Amazon and its business?

Lauren Goode: Well, there’s also, we should just note, and our colleague, Zeyi Yang has been covering this at WIRED too, there’s something that’s been known as the de minimis exemption for e-commerce companies shipping goods from China, and part of this new tariffs package actually removes that exemption, which is not good for e-commerce companies.

Michael Calore: That’s if your goods cost less than $800?

Lauren Goode: I believe so, yes.

Michael Calore: You don’t have to pay the hefty import tax on it.

Lauren Goode: Yeah. Exactly.

Katie Drummond: This one is a little bit less clear-cut to me, and I’m happy to argue about it or be told I’m wrong. This feels less dire for Amazon than it is for the Elons of the world and his companies and the Apples and the Tim Cooks. I mean the reliance that Amazon has on Chinese goods sold on their platform, I think it’s at least 50 percent. It’s more than 50 percent of what Amazon sells. But given Lauren what you just said, that these other Chinese commerce giants are going to be hit really hard by these tariffs, in some respects that feels like it sort of equalizes the playing field for Amazon. And then obviously Michael, to your point, they’re not a hardware company. Obviously they’re a massive commerce company, but they’ve also got Amazon Web Services, they have other facets to their company that feel much more insulated from the sort of immediate impacts of tariffs. I mean, how does that sit with both of you?

The US Is Turning a Blind Eye to Crypto Crimes

Meanwhile, the Trump family’s crypto empire continues to expand. In late March, Eric Trump and Donald Trump Jr., the president’s sons, announced a new bitcoin mining venture. Shortly before that, the parent company of Truth Social, Trump’s social media platform, entered an agreement to launch a series of crypto-exchange-traded funds. President Trump himself has previously issued NFTs, in addition to his memecoin.

At least until July, by which time the US government’s new “working group on digital assets” is required to recommend an approach to overseeing the crypto industry, it will remain unclear which laws and regulations will be enforced against crypto businesses—and by whom. “There was a pretty clear sheriff in town: [former SEC chair Gary] Gensler. Now there’s not,” says LaVigne.

Though the new DOJ orders do not prohibit prosecutors from investigating crypto businesses, the practical realities of the job—the way budget is allocated, how investigations are staffed, the possibility that supervisors may decline to proceed with a case—mean they achieve a similar result, says Daniel Silva, another former prosecutor and attorney at law firm Buchalter.

“If I’m a prosecutor, I’m not sure I’m interested,” says Silva. “If I’m doing long-term, complex financial investigations involving international fraud, I can manage three or four at a time. Am I going to spend years on a [crypto] case that might get declined?”

The upshot is likely to be that crypto firms are left alone to pursue experimental types of crypto tokens, transactions or products, even if they stretch the limits of applicable laws. “If you’re a cryptocurrency company right now, you have a bit more certainty that over the next couple of years your risk tolerance might expand without getting punished as much as it would have,” says Silva.

In a letter to the DOJ on Thursday, six Democratic senators argued that loosening the grip on platforms responsible for the flow of crypto assets will lead to dangerous downstream outcomes too. “Drug traffickers, terrorists, fraudsters, and adversaries will exploit this vulnerability on a large scale,” the letter states.

The DOJ’s position may not, though, be the free pass that it seems, claims Joshua Naftalis, a former prosecutor who is currently a partner at law firm Pallas Partners. Although the DOJ is likely to pursue only a few crypto-related cases under Trump, he says, businesses cannot be assured that present day infractions will not be punished by future administrations. That should temper the crypto industry’s willingness to flout, say, anti-money-laundering requirements.

“I’m sure it’s a breath of relief for the crypto industry,” says Naftalis. “But there’s a statute of limitations. A different president could always go back and charge these cases. It would be a false sense of security.”

Equally, the DOJ will continue to draw a hard line at fraud, the former prosecutors claim. “You cannot just commit flagrant financial crimes and expect no one to look at it,” says Silva.

There is a degree to which all parties—from crypto businesses to the prosecutors tasked with these new orders—will be required to read between the lines. “The signal is that the industry is not in the doghouse anymore,” says Naftalis. “They still have to comply with the laws. The question is which ones will be enforced—and by whom?”

Where Were Big Tech’s CEOs on Tariffs?

If you logged on to X or Bluesky this past week, you were likely swept up in the onslaught of posts about Trump’s reciprocal tariffs and the plunging stock market. And, if you follow the tech industry as closely as I do, you probably also noticed who wasn’t posting about the tariffs: many of the same tech founders and CEOs who flanked Trump on Inauguration Day in January. Jeff Bezos, Tim Cook, Sundar Pichai, and Mark Zuckerberg have kept mum on the topic of tariffs (although both Pichai and Zuckerberg have continued posting about AI). Meanwhile, Elon Musk—well, we’ll get to that.

The silence was deafening, considering that the “magnificent seven” collectively lost trillions of dollars in market value following Trump’s tariff announcement last week. But there’s a cold logic behind these tech leaders holding their tongues in public—particularly for those who sell hardware. The US has become a highly volatile nation where the whims of the president must be taken into consideration before using any political chip or making a public statement, especially in an environment where that statement could be irrelevant an hour later.

“The sand doesn’t stop shifting long enough to make a cogent statement,” one top communications executive, who has worked closely with two Big Tech CEOs, tells me.

Tech CEOs aren’t actually staying silent. They’re simply lobbying behind the scenes on their own behalf. Niki Christoff, a Washington, DC, political strategist and former aide to Senator John McCain during his 2008 presidential campaign, says most of the strategizing around trade rules—and conversations with Trump’s staff—are happening through back channels right now. “There’s a lot of personal dialing and trying to get deals done,” she claims.

During Trump’s first term, Cook carefully cultivated a direct relationship with the president in order to lobby him on issues like trade and immigration. I have a hard time imagining Cook isn’t using that direct line now. Nvidia chief executive Jensen Huang, who did not attend the inauguration ceremony, reportedly went to a $1-million-a-head dinner at Mar-a-Lago last week. Shortly afterward, the White House walked back plans to implement export controls on some chips that Nvidia sells to China.

Private back channels allow each tech leader to lobby for specific tariff exemptions. The kind of exemptions that would benefit Nvidia, such as more lenient policies on semiconductor imports for GPUs, differ from what Apple might be angling for, considering the company’s supply chain complexity and its reliance on China. “Broadly opposing tariffs is not useful if business leaders can get exemptions on their own products,” Christoff points out.

At the same time tech CEOs are letting trade organizations, like Business Roundtable, which represents a number of big tech firms including Alphabet and Amazon, do some of their lobbying for them, sources tell WIRED. Business Roundtable CEO Joshua Bolten put out a statement urging the administration to “swiftly reach agreements” with its trading partners and to implement “reasonable exemptions.” The CEOs have also been able to hang back while bankers like JP Morgan Chase CEO Jamie Dimon make public assertions about the lasting negative impact of tariffs on the economy, and while billionaire hedge funder Bill Ackman keeps tweeting through it. (And really, what tech CEO wants to be part of a roundup story that also includes the market-cratering tweets of an anonymous X user named “Walter Bloomberg”?)

There have been a few outliers. Amazon CEO Andy Jassy said he believes Amazon’s vast network of third-party sellers might end up passing the cost of tariffs on to consumers. Last week Microsoft CEO Satya Nadella sat alongside Bill Gates and former Microsoft CEO Steve Ballmer for an interview with CNBC’s Andrew Ross Sorkin, who asked about tariffs. Ballmer told Sorkin he “took just enough economics in college to [know that] tariffs are actually going to bring some turmoil” and that the “disruption is very hard on people.”

Trump’s Trade War Is Strengthening China’s Soft Power

Trump administration officials have promoted the tariffs as a way to boost US manufacturing and create more high-paying jobs. But American small business owners painted a very different picture of the situation on TikTok. In one video, the founder of a trendy hair accessories brand rolled her eyes and explained that the company’s products “literally cannot be made here.” In another, the CEO of a shoe company similarly said China “is just the only place I could manufacture.” The owner of a company that makes self-checkout kiosks lamented about how awful his experiences have been working with suppliers in the US compared to those in China. “What it’s about is Americans are a bunch of babies and they are hard to work with,” he told the camera.

The founder of a London-based clothing brand struck a more heartwarming tone, uploading a slideshow of pictures of herself posing with the garment workers her company partners with in China, set to The Fray song “Look After You.” The text overlaid on one photo read “Our wins are their wins.” The TikTok post received over 55,000 likes, an indication of how attitudes toward China have evolved among at least some Western consumers, compared to the past, when the country’s factories were mostly associated with pumping out cheap, flimsy goods. “Suddenly people see, oh, it’s not this imagined ‘slave labor’ that’s making my clothes, they’re actually humans,” says Tianyu Fang, a fellow at the New America think tank and one of the cofounders of the Chinese internet culture newsletter Chaoyang Trap.

In recent weeks, as the Trump administration’s ever-changing trade policies enraged close American allies like Canada, a number of prominent commentators have even begun suggesting that perhaps the era of American exceptionalism was over. The coming decades, they argued, would now be defined by the rise of China.

“The Chinese century, brought to you by Donald Trump,” David Frum, a staff writer at The Atlantic and former speechwriter for George W. Bush said in a social media post on April 2. New York Times opinion writer Thomas Friedman published a column the same day raving about a recent trip to China during which he witnessed the country’s impressive infrastructure and technological development. It was headlined “I Just Saw the Future. It Was Not in America.”

“When people say this is the Chinese century, what they really mean is that the consensus that this will be the American century is being broken,” says Fang.

Growing Influence

When Trump’s most comprehensive tariffs caused global stock markets to take a nosedive earlier this week, US social media influencer Darren Watkins Jr., better known as IShowSpeed to his over 100 million collective followers, was wrapping up a sprawling tour across China with stops in Beijing, Shanghai, Shenzhen, and other cities. Watkins spent days livestreaming himself mingling with Chinese celebrities and ​​taking a boat ride with Hong Kong’s glittering skyline as the backdrop. By broadcasting in real time, IShowSpeed’s fans got an “unprecedented opportunity” to see “an unfiltered China,” Yaling Jiang, CEO of the strategy firm ApertureChina, wrote in her newsletter.

Many Americans got another direct glimpse inside China earlier this year when the US was set to ban TikTok nationwide. Anticipating the app might soon disappear, hundreds of thousands of people flocked to RedNote, another Chinese-owned social media app, where they saw posts of people in China showing off their domestic-made electric cars and comfortable urban apartments. TikTok itself, which was created by the Chinese tech giant ByteDance, is a testament to China’s growing soft power. Trump has vowed to save the app, and despite warnings from US lawmakers about the data security risks it poses, fewer Americans support banning it than did a few years ago.

Labor Leaders Fear Elon Musk and DOGE Could Gain Access to Whistleblower Files

In the memo, the AFL-CIO highlights some two dozen accidents and alleged safety issues reported at Tesla, SpaceX, and The Boring Company since 2016 as the basis for its concern, some of which were the subject of recent OSHA investigations. In one incident reported to OSHA last year, a licensed electrician named Victor Joe Gomez Sr. was electrocuted and killed after being instructed to inspect electrical panels at Tesla’s Gigafactory in Austin, Texas, that OSHA determined had not been properly disconnected beforehand (the case remains open, as Tesla is actively disputing it.)

Two separate OSHA citations at other Tesla factories involved fingertip amputations. At a SpaceX facility in 2022, an employee “suffered a skull fracture and head trauma and was hospitalized in a coma for months,” according to the final OSHA accident report, after experiencing what the agency described as a technical problem with a newly automated piece of machinery. SpaceX did not contest its OSHA citation and $18,475 fine.

Liz Shuler, the president of AFL-CIO, claims that a number of Tesla workers have repeatedly alleged to the federation that safety isn’t prioritized at the car company. The AFL-CIO works with the United Automobile, Aerospace & Agricultural Implement Workers of America (UAW), but it does not represent employees at Tesla or SpaceX.

“There are clearly some serious safety hazards in their facilities,” Debbie Berkowitz, former chief of staff and a senior advisor at OSHA under Obama, alleges, referring to Tesla.

After OSHA issues a citation, employers have the right to challenge it, and Tesla does this often, according to the agency’s public database. Of the 46 Tesla cases in which OSHA issued citations over the last five years, the memo cites twenty-seven that remain open because the car company is actively disputing them with the agency. Two SpaceX cases and one Boring Company case remain open for the same reason. The cases can’t be closed until both OSHA and the companies agree on the terms of the citation, which may include associated fines and specific changes the company has to make to improve worker safety.

David Michaels, the assistant secretary of labor for OSHA under Obama, tells WIRED that, in general, big companies typically don’t have a financial incentive to challenge OSHA citations, since they usually are accompanied by fines costing only a few thousand dollars. However, a company isn’t required to address the specific hazard that led to an accident until after a case is closed. In order to avoid addressing these alleged problems, Michaels says that generally, some companies may be motivated to keep cases open.

“Some employers decide they don’t want to abate the hazard, they don’t agree with the citation, and they will spend many, many thousands of dollars fighting the case, and it’ll cost them far more than simply paying a small fine and abating the hazard,” Michaels says.

There is currently no evidence that Musk has access to any confidential databases at the Department of Labor that may contain personal information about whistleblowers. But former OSHA administrators say the agency does house records that would anonymize whistleblowers, as well as employees who participated in anonymous interviews with agency investigators.

BYD Launches Denza in Europe—Another Mighty Impressive EV Brand the US Won’t Get

Denza was originally founded in 2010 as a joint venture between BYD and Mercedes-Benz, launching its first car into the Chinese market in 2014. Now wholly owned by BYD, it went through a significant rebrand in 2021, with Wolfgang Egger—who previously led design teams at Audi and Lamborghini—joining at the helm as chief designer.

The Z9GT has been chodsen by BYD as the Denza car to launch into the market because it apparently represents the “best of BYD technology and the best of BYD design,” Li says.

At its heart is Denza’s own e3 Platform, which brings a number of headline features. Certainly one of the most striking is its rear-wheel dual-motor independent steering, which enables the right and left wheels to steer independently of the front axle and of each other. As well as allowing drivers to toe in and toe out of tight spaces, it also allows the car to “crab walk”—where the auto seemingly glides in a sideways motion—up to an industry-leading angle of 15 degrees.

This eminently useful lateral trickery is all controlled by Z9GT’s Vehicle Motion Control architecture, which can take over braking, suspension, and steering—even in the case of a high-speed tire blowout, where it can adjust the torque of the unaffected tires, redistributing the power at speeds of over 110 mph.

The e3 Platform allows the Z9GT to adopt a Cell-to-Body structure, which sees the Blade Battery integrated into the car’s architecture, as seen in the BYD Seal. Aside from a stiffening boon to the chassis, this ensures a fully flat floor and helps to create an additional 15-millimeter vertical space in the cabin for as much room inside as possible.

The Chinese brand is hoping that by offering the latest auto tech it can quickly gain a foothold in the EU.

Photograph: Denza

Speaking of the interior, expect suitably premium leather seats and wooden accents across the dash, with 128-color lighting for setting the cabin ambience to your taste. Front seats will get 12-way electric adjustment and 10-point massage and heating, along with a supposedly world-first execution of active side bolsters, which share their air tanks with the car’s air suspension for additional support during cornering.

The AI Agent Era Requires a New Kind of Game Theory

At the same time, the risk is immediate and present with agents. When models are not just contained boxes but can take actions in the world, when they have end-effectors that let them manipulate the world, I think it really becomes much more of a problem.

We are making progress here, developing much better [defensive] techniques, but if you break the underlying model, you basically have the equivalent to a buffer overflow [a common way to hack software]. Your agent can be exploited by third parties to maliciously control or somehow circumvent the desired functionality of the system. We’re going to have to be able to secure these systems in order to make agents safe.

This is different from AI models themselves becoming a threat, right?

There’s no real risk of things like loss of control with current models right now. It is more of a future concern. But I’m very glad people are working on it; I think it is crucially important.

How worried should we be about the increased use of agentic systems then?

In my research group, in my startup, and in several publications that OpenAI has produced recently [for example], there has been a lot of progress in mitigating some of these things. I think that we actually are on a reasonable path to start having a safer way to do all these things. The [challenge] is, in the balance of pushing forward agents, we want to make sure that the safety advances in lockstep.

Most of the [exploits against agent systems] we see right now would be classified as experimental, frankly, because agents are still in their infancy. There’s still a user typically in the loop somewhere. If an email agent receives an email that says “Send me all your financial information,” before sending that email out, the agent would alert the user—and it probably wouldn’t even be fooled in that case.

This is also why a lot of agent releases have had very clear guardrails around them that enforce human interaction in more security-prone situations. Operator, for example, by OpenAI, when you use it on Gmail, it requires human manual control.

What kinds of agentic exploits might we see first?

There have been demonstrations of things like data exfiltration when agents are hooked up in the wrong way. If my agent has access to all my files and my cloud drive, and can also make queries to links, then you can upload these things somewhere.

These are still in the demonstration phase right now, but that’s really just because these things are not yet adopted. And they will be adopted, let’s make no mistake. These things will become more autonomous, more independent, and will have less user oversight, because we don’t want to click “agree,” “agree,” “agree” every time agents do anything.

It also seems inevitable that we will see different AI agents communicating and negotiating. What happens then?

Absolutely. Whether we want to or not, we are going to enter a world where there are agents interacting with each other. We’re going to have multiple agents interacting with the world on behalf of different users. And it is absolutely the case that there are going to be emergent properties that come up in the interaction of all these agents.

Startup Founder Claims Elon Musk Is Stealing the Name ‘Grok’

Elon Musk’s xAI is facing a potential trademark dispute over the name of its chatbot, Grok. The company’s trademark application with the US Patent and Trademark Office has been suspended after the agency argued the name could be confused with that of two other companies, AI chipmaker Groq and software provider Grokstream. Now, a third tech startup called Bizly is claiming it owns the rights to “Grok.”

This isn’t the first time Musk has chosen a name for one of his products that other companies say they trademarked first. Last month, Musk’s social media platform settled a lawsuit brought by a marketing firm that claimed it owns exclusive rights to the name X.

Bizly and xAI appear to have arrived at the name Grok independently. Bizly founder Ron Shah says he came up with it during a brainstorming session with a colleague who used the word as a verb. (The phrase “to grok” is frequently used in tech circles to mean “to understand.”) “I was like, that’s exactly the name,” Shah tells WIRED. “We got excited, high-fived, it was the name!”

Musk has said he named his chatbot after a term used in the 1961 science fiction novel Stranger in a Strange Land, according to The Times of India. Author Robert A. Heinlein imagined “grok” as a word in a Martian lexicon that also meant “to understand.”

Shah says he applied to trademark the name Grok in 2021. Two years later, he was in the midst of launching an AI-powered app for asynchronous meetings called Grok when Musk announced his chatbot with the same name. “It was a day I’ll never forget,” Shah says. “I woke up and looked at my phone, and there were so many messages from friends saying ‘did you get acquired by Elon? Congrats!’ It was a complete shock to me.”

Shah insists xAI infringed on his trademark. But under US law, trademark regulations are primarily designed to protect consumers rather than companies, says Josh Gerben, founder of Gerben IP, a law firm focused exclusively on trademarks. “The goal is to not have confusion as to who is behind a product or service,” he says.

For example, Musk’s former partner Grimes also trademarked the name Grok for a plushie AI-powered kids toy, but that application is very different from a software tool, reducing the likelihood of consumers getting them mixed up. “The details matter,” Gerben says. “What does the original Grok do, and what does this new one do? Are they operating in the same channel of trade?”

In Bizly’s case, the answers to those questions are fairly murky. One of the requirements of registering a trademark is that owners need to demonstrate it is being used to sell goods or services in at least two states. The USPTO also allows people to file a trademark to reserve the rights to a name before a business is launched, but they can’t actually register it until, say, their jewelry website is fully up and running or their pizza parlor chain expands into a neighboring state.

The AI Race Has Gotten Crowded—and China Is Closing In on the US

Stanford’s report shows Chinese AI is on the rise overall, with models from Chinese companies scoring similar to their US counterparts on the LMSYS benchmark. It notes that China publishes more AI papers and files more AI-related patents than the US, although it does not assess the quality of either. The US, in contrast, produces more notable AI models: 40 compared to the 15 frontier models produced in China and the three produced in Europe. The report also notes that powerful models have recently emerged in the Middle East, Latin America, and Southeast Asia as the technology becomes more global.

Courtesy of Stanford HAI

The research shows that several of the best AI models are now “open weight,” meaning they can be downloaded and modified for free. Meta has been at the center of the trend with its Llama model, first released in February 2023. The company released its latest version, Llama 4, over the weekend. Both DeepSeek and Mistral, a French company, now offer advanced open weight models, too. In March, OpenAI announced that it also plans to release an open source model—its first since GPT-2—this summer. In 2024, the gap between open and closed models narrowed from eight percent to 1.7 percent, the study shows. That said, the majority of advanced models—60.7 percent—are still closed.

Stanford’s report notes the AI industry has seen a steady improvement in efficiency, with hardware becoming 40 percent more efficient in the past year. This has brought the cost of querying AI models down and also made it possible to run relatively capable models on personal devices.

Rising efficiency has prompted speculation that the largest AI models could require fewer GPUs for training, although most AI builders say they need more computing power, not less. The study shows that the latest AI models are built using tens of trillions of tokens—components representing parts of data such as words in a sentence—and tens of billions of petaflops of computation. However, it cites research suggesting that the supply of internet training data will be exhausted by between 2026 and 2032, hastening the adoption of so-called synthetic, or AI-generated, data.

The report offers a sweeping picture of AI’s broader impact. It shows that demand for workers with machine learning skills has spiked, and cites surveys showing that a growing proportion of workers expect the technology to change their jobs. Private investment reached a record $150.8 billion in 2024, the report shows. Governments around the world also committed billions to AI that same year. Since 2022, AI-related legislation has doubled in the US.

Parli notes that although companies have become more secretive about how they develop frontier AI models, academic research is flourishing—and improving in quality.

The report also points to problems arising from widespread AI adoption. It notes that incidents involving AI models misbehaving or being misused have increased in the past year, as has research aimed at making these models safer and more reliable.

As for reaching the much ballyhooed goal of AGI, the report highlights how some AI models already surpass human abilities on benchmarks that test specific skills, including image classification, language comprehension, and mathematical reasoning. This is partly because models are designed and optimized to excel at these barometers, but it shines a spotlight on how swiftly the technology has advanced in recent years.

The AI Race Has Gotten Crowded—and China Is Closing In on the US

Stanford’s report shows Chinese AI is on the rise overall, with models from Chinese companies scoring similar to their US counterparts on the LMSYS benchmark. It notes that China publishes more AI papers and files more AI-related patents than the US, although it does not assess the quality of either. The US, in contrast, produces more notable AI models: 40 compared to the 15 frontier models produced in China and the three produced in Europe. The report also notes that powerful models have recently emerged in the Middle East, Latin America, and Southeast Asia as the technology becomes more global.

Courtesy of Stanford HAI

The research shows that several of the best AI models are now “open weight,” meaning they can be downloaded and modified for free. Meta has been at the center of the trend with its Llama model, first released in February 2023. The company released its latest version, Llama 4, over the weekend. Both DeepSeek and Mistral, a French company, now offer advanced open weight models, too. In March, OpenAI announced that it also plans to release an open source model—its first since GPT-2—this summer. In 2024, the gap between open and closed models narrowed from eight percent to 1.7 percent, the study shows. That said, the majority of advanced models—60.7 percent—are still closed.

Stanford’s report notes the AI industry has seen a steady improvement in efficiency, with hardware becoming 40 percent more efficient in the past year. This has brought the cost of querying AI models down and also made it possible to run relatively capable models on personal devices.

Rising efficiency has prompted speculation that the largest AI models could require fewer GPUs for training, although most AI builders say they need more computing power, not less. The study shows that the latest AI models are built using tens of trillions of tokens—components representing parts of data such as words in a sentence—and tens of billions of petaflops of computation. However, it cites research suggesting that the supply of internet training data will be exhausted by between 2026 and 2032, hastening the adoption of so-called synthetic, or AI-generated, data.

The report offers a sweeping picture of AI’s broader impact. It shows that demand for workers with machine learning skills has spiked, and cites surveys showing that a growing proportion of workers expect the technology to change their jobs. Private investment reached a record $150.8 billion in 2024, the report shows. Governments around the world also committed billions to AI that same year. Since 2022, AI-related legislation has doubled in the US.

Parli notes that although companies have become more secretive about how they develop frontier AI models, academic research is flourishing—and improving in quality.

The report also points to problems arising from widespread AI adoption. It notes that incidents involving AI models misbehaving or being misused have increased in the past year, as has research aimed at making these models safer and more reliable.

As for reaching the much ballyhooed goal of AGI, the report highlights how some AI models already surpass human abilities on benchmarks that test specific skills, including image classification, language comprehension, and mathematical reasoning. This is partly because models are designed and optimized to excel at these barometers, but it shines a spotlight on how swiftly the technology has advanced in recent years.

The AI Race Has Gotten Crowded—and China Is Closing In on the US

Stanford’s report shows Chinese AI is on the rise overall, with models from Chinese companies scoring similar to their US counterparts on the LMSYS benchmark. It notes that China publishes more AI papers and files more AI-related patents than the US, although it does not assess the quality of either. The US, in contrast, produces more notable AI models: 40 compared to the 15 frontier models produced in China and the three produced in Europe. The report also notes that powerful models have recently emerged in the Middle East, Latin America, and Southeast Asia as the technology becomes more global.

Courtesy of Stanford HAI

The research shows that several of the best AI models are now “open weight,” meaning they can be downloaded and modified for free. Meta has been at the center of the trend with its Llama model, first released in February 2023. The company released its latest version, Llama 4, over the weekend. Both DeepSeek and Mistral, a French company, now offer advanced open weight models, too. In March, OpenAI announced that it also plans to release an open source model—its first since GPT-2—this summer. In 2024, the gap between open and closed models narrowed from eight percent to 1.7 percent, the study shows. That said, the majority of advanced models—60.7 percent—are still closed.

Stanford’s report notes the AI industry has seen a steady improvement in efficiency, with hardware becoming 40 percent more efficient in the past year. This has brought the cost of querying AI models down and also made it possible to run relatively capable models on personal devices.

Rising efficiency has prompted speculation that the largest AI models could require fewer GPUs for training, although most AI builders say they need more computing power, not less. The study shows that the latest AI models are built using tens of trillions of tokens—components representing parts of data such as words in a sentence—and tens of billions of petaflops of computation. However, it cites research suggesting that the supply of internet training data will be exhausted by between 2026 and 2032, hastening the adoption of so-called synthetic, or AI-generated, data.

The report offers a sweeping picture of AI’s broader impact. It shows that demand for workers with machine learning skills has spiked, and cites surveys showing that a growing proportion of workers expect the technology to change their jobs. Private investment reached a record $150.8 billion in 2024, the report shows. Governments around the world also committed billions to AI that same year. Since 2022, AI-related legislation has doubled in the US.

Parli notes that although companies have become more secretive about how they develop frontier AI models, academic research is flourishing—and improving in quality.

The report also points to problems arising from widespread AI adoption. It notes that incidents involving AI models misbehaving or being misused have increased in the past year, as has research aimed at making these models safer and more reliable.

As for reaching the much ballyhooed goal of AGI, the report highlights how some AI models already surpass human abilities on benchmarks that test specific skills, including image classification, language comprehension, and mathematical reasoning. This is partly because models are designed and optimized to excel at these barometers, but it shines a spotlight on how swiftly the technology has advanced in recent years.

Trump’s Trade War Pushes Canadian Tech Workers to Rethink Silicon Valley

“Some of the Canadians in the group have been asking, ‘Should we relocate our office? Should we change our approach?’” Waselnuk said. “But we don’t really know what’s going to happen. If anything, America doesn’t know either. Canadians don’t want these problems. We just want to get along.”

Alysaa Co, a principal at Bain Capital Ventures and fellow Canadian, agreed. She noted that one of Bain’s portfolio companies, a Toronto-based fintech startup, has been serving US-based small businesses since its inception. Ideally, Co said, the startup won’t have to rethink that strategy.

Some in the Maple Syrup Gang poked fun at the US and American culture. One entrepreneur, who showed off an AI-powered tool for helping kids learn math, asked the crowd to roast him and provide brutally honest feedback on his app. “Pretend like you’re from Texas. Or pretend you’re Trump,” he said.

Canadian pride and nationalist sentiment have been on the rise since Trump began threatening America’s northern neighbor and took a hard line on trade. The percentage of Canadians who say they’re “very proud” of their country jumped significantly in February from just a couple months prior, according to data analysis from the Angus Reid Institute, a Canadian nonprofit research organization. As Canada gears up for national elections in a few weeks, the two major political parties are emphasizing the importance of “Canada First” and defending national sovereignty. Carney’s Liberal Party, which was sinking in the polls before Trump’s rhetoric toward Canada turned dark, has seen its popularity surge as the prime minister, a former banker, positioned himself as the best candidate to protect Canada’s economy.

This growing sense of Canadian national pride has trickled into the tech sector, too, where some investors and startup founders view the divisiveness between the US and Canada as an opportunity to boost their country’s productivity and self-reliance. A group of Canadian tech entrepreneurs, including executives from Shopify and Cohere, recently spun up a promotional campaign called Build Canada with the goal of influencing policy on technology, tax reform, and immigration. An article in the Canadian blog Betakit reported that these tech leaders have been “frustrated by the Liberal government and the country’s long-standing productivity woes.”

“In hindsight we will look at these US tariffs as an important wake-up call for [Canada],” Boris Wertz, founder of Vancouver-based Version One ventures and a former board partner at Andreessen Horowitz, said on X in early February. Canada should diversify its international trading partners away from the US, deregulate inter-provincial trade, and double down on energy infrastructure, Wertz wrote. He also included “border security/tough on crime” as an agenda item.

Canada has been a significant source of tech talent in Silicon Valley since the North American Free Trade Agreement was put in place in 1994, which included a program granting an unlimited number of visas for skilled professionals looking to move from Canada or Mexico to the US. (NAFTA was replaced by the United States-Mexico-Canada agreement, or USMCA, in 2020.) Canadians who work in tech can quickly rattle off the names of unicorn founders and other notable figures who are originally from their home country, including Uber cofounder Garrett Camp, Notion cofounder Ivan Zhao, Cloudflare cofounder Michelle Zatlyn, and Pebble creator Eric Migicovsky—not to mention the thousands of Canadian engineers who toil away on products behind the scenes.

Sam Altman Says OpenAI Will Release an ‘Open Weight’ AI Model This Summer

Sam Altman today revealed that OpenAI will release an open-weight artificial intelligence model in the coming months.

“We are excited to release a powerful new open-weight language model with reasoning in the coming months,” the CEO wrote on X.

The move is partly a response to the runaway success of the R1 model from Chinese company DeepSeek, as well as the popularity of Meta’s Llama models.

Shortly after DeepSeek’s model was released in January, Altman said that OpenAI was “on the wrong side of history” regarding open models, signaling a likely shift in direction. On Monday he said that the company has been thinking about releasing an open-weight model for some time, adding “now it feels important to do.”

OpenAI may feel the need to show that it can train the new model cheaply, since DeepSeek’s model was purportedly trained at a fraction of the cost of most large AI models.

“This is amazing news,” Clement Delangue, cofounder and CEO of HuggingFace, a company that specializes in hosting open AI models, told WIRED. “With DeepSeek, everyone’s realizing the power of open weights.”

OpenAI currently makes its AI available through a chatbot and through the cloud. R1, Llama and other open-weight models can be downloaded for free and modified. A model’s weights refers to the values inside a large neural network—something that is set during training. Open-weight models are cheaper to use and can also be tailored for sensitive use cases, like handling highly confidential information.

Steven Heidel, a member of the technical staff at OpenAI, reposted Altman’s announcement and added, “We’re releasing a model this year that you can run on your own hardware.”

Johannes Heidecke, a researcher working on AI safety at OpenAI, also reposted the message on X, adding that the company would conduct rigorous testing to ensure the open-weight model could not easily be misused. Some AI researchers worry that open-weight models could help criminals launch cyberattacks or even develop biological or chemical weapons. “While open models bring unique challenges, we’re guided by our Preparedness Framework and will not release models we believe pose catastrophic risks,” Heidecke wrote.

OpenAI today also posted a webpage inviting developers to apply for early access to the forthcoming model. Altman said in his post that the company would host events for developers with early prototypes of the new model in the coming weeks.

Meta was the first major AI company to pursue a more open approach, releasing the first version of Llama in July 2023. A growing number of open-weight AI models are now available. Some researchers note that Llama and some other models are not as transparent as they could be, because the training data and other details are still kept secret. Meta also imposes a license that limits other companies’ ability to profit from applications and tools built using Llama.

Update March 31, 2025, 4:21 EST: This article was updated with a comment from Clement Delangue, cofounder and CEO of HuggingFace.

The DOGE Axe Comes for Libraries and Museums

The Trump administration, working in coordination with Elon Musk’s so-called Department of Government Efficiency, has gutted a small federal agency that provides funding to libraries and museums nationwide. In communities across the US, the cuts threaten student field trips, classes for seniors, and access to popular digital services, such as the ebook app Libby.

On Monday, managers at the Institute of Museum and Library Services (IMLS) informed 77 employees—virtually the agency’s entire staff—that they were immediately being put on paid administrative leave, according to one of the workers, who sought anonymity out of fear of retaliation from Trump officials. Several other sources confirmed the move, which came after President Donald Trump appointed Keith Sonderling, the deputy secretary of labor, as the acting director of IMLS less than two weeks ago.

A representative for the American Federation of Government Employee Local 3403, a union that represents about 40 IMLS staffers, said Sonderling and a group of DOGE staffers met with IMLS leadership late last month. Afterwards, Sonderling sent an email to staff “emphasizing the importance of libraries and museums in cultivating the next generation’s perception of American exceptionalism and patriotism,” the union representative said in a statement to WIRED.

IMLS employees who showed up to work at the agency on Monday were asked to turn in their computers and lost access to their government email addresses before being ordered to head home for the day, the employee says. It’s unclear when, or if, staffers will ever return to work. “It’s heartbreaking on many levels,” the employee adds.

The White House and the Institute of Museum and Library Services did not immediately respond to requests for comment from WIRED.

The annual budget of IMLS amounts to less than $1 per person in the US. Overall, the agency awarded over $269.5 million to library and museum systems last year, according to its grants database. Much of that money is paid out as reimbursements over time, the current IMLS employee says, but now there is no one around to cut checks for funds that have already been allocated.

“The status of previously awarded grants is unclear. Without staff to administer the programs, it is likely that most grants will be terminated,” the American Federation of Government Employee Local 3403 union said in a statement.

About 65 percent of the funding had been allocated to different states, with each one scheduled to receive a minimum of roughly $1.2 million. Recipients can use the money for statewide initiatives or pass it on to local museum and library institutions for expenses such as staff training and back-office software. California and Texas have received the highest allocated funding, at about $12.5 million and $15.7 million, respectively, according to IMLS data. Individual libraries and museums also receive grants directly from IMLS for specific projects.

An art museum in Idaho expected to put $10,350 toward supporting student field trips, according to the IMLS grant database. A North Carolina museum was allotted $23,500 for weaving and fiber art workshops for seniors. And an indigenous community in California expected to put $10,000 toward purchasing books and electronic resources.

Trump’s Tariffs Are Threatening the US Semiconductor Revival

Silicon Valley let out a sigh of relief on Wednesday when it learned that President Donald Trump’s tariff bonanza included an exemption for semiconductors, which, at least for now, won’t be subject to higher import duties. But just three days later, some US tech companies may be finding that the loophole actually creates more problems than it solves. After the tariffs were announced, the White House published a list of the products that it says are unaffected, and it doesn’t include many kinds of chip-related goods.

That means only a small number of American manufacturers will be able to continue sourcing chips without needing to factor in higher import costs. The vast majority of semiconductors that come into the US currently are already packaged into products that are not exempt, such as the graphics processing units (GPUs) and servers for training artificial intelligence models. And manufacturing equipment that domestic companies use to produce chips in the US wasn’t spared, either.

“If you are a major chip producer who is making a sizable investment in the US, a hundred billion dollars will buy you a lot less in the next few years than the last few years,” says Martin Chorzempa, a senior fellow at the Peterson Institute for International Economics.

The US Department of Commerce did not respond to a request for comment.

Stacy Rasgon, a senior analyst covering semiconductors at Bernstein Research, says the narrow exception for chips will do little to blunt wider negative impacts on the industry. Given that most semiconductors arrive at US borders packaged into servers, smartphones, and other products, the tariffs amount to “something in the ballpark of a 40 percent blended tariff on that stuff,” Rasgon says, referring to the overall import duty rate applied.

Rasgon notes that the semiconductor industry is deeply dependent on other imports and on the overall health of the US economy, because the components it makes are in so many kinds of consumer products, from cars to refrigerators. “They are macro-exposed,” he says.

To determine what goods the tariffs apply to, the Trump administration relied on a complex existing system called the Harmonized Tariff Schedule (HTS), which organizes millions of different products sold in the US market into numerical categories that correspond to different import duty rates. The White House document lists only a narrow group of HTS codes in the semiconductor field that it says are exempted from the new tariffs.

GPUs, for example, are typically coded as either 8473.30 or 8542.31 in the HTS system, says Nancy Wei, a supply chain analyst at the consulting firm Eurasia Group. But Trump’s waiver only applies to more advanced GPUs in the latter 8542.31 category. It also doesn’t cover other codes for related types of computing hardware. Nvidia’s DGX systems, a pre-configured server with built-in GPUs designed for AI computing tasks, is coded as 8471.50, according to the company’s website, which means it’s likely not exempt from the tariffs.

The line between these distinctions can sometimes be blurry. In 2020, for example, an importer of two Nvidia GPU models asked US authorities to clarify what category it considered them falling under. After looking into the matter, US Customs and Border Protection determined that the two GPUs belong to the 8473.30 category, which also isn’t exempt from the tariffs.

This Startup Says It Can Clean Your Blood of Microplastics

This is a non-exhaustive list of places microplastics have been found: Mount Everest, the Mariana Trench, Antarctic snow, clouds, plankton, turtles, whales, cattle, birds, tap water, beer, salt, human placentas, semen, breast milk, feces, testicles, livers, brains, arteries, and blood.

My blood, specifically. In early March I milked a few drops out of my fingertips and sent the sample to be tested for microplastics. I was in the London office of Clarify Clinics—a firm that offers to cleanse your blood of microplastics, forever chemicals, and other toxins, in treatments that start at £9,750 ($12,636).

Each week around 10 to 15 people walk into the basement clinic just off Harley Street—a road famed for its private clinics and wealthy clientele. After a consultation, the patients settle down in an armchair for the treatment. Blood is drawn from a cannula into a machine that separates out the plasma from blood cells. That plasma is filtered through a column that is supposed to trap microplastics and other undesirable chemicals, before being mixed back with the blood cells and pumped back into the patient. All-in-all the process runs for up to two hours—enough time to process 50 to 80 percent of the blood plasma volume.

“Once it’s running, you feel nothing. It’s very comfortable,” says Yael Cohen, CEO of Clarify Clinic. “Patients take calls, do Zooms, watch movies, sleep. The ones who sleep are my favorite.” They come for all kinds of reasons, Cohen says: Some are suffering with chronic fatigue, others with brain fog or long Covid. The clinic also runs treatments marketed toward people on Ozempic-style weight-loss drugs, looking to conceive, or ward off dementia.

What Clarify sells them is the hope of easing their symptoms by ridding their blood of microplastics, or other potential contaminants such as PFAS chemicals (per- and polyfluoroalkyl substances) and pesticides. But the science on how microplastics affect our health is still far from conclusive. A 2022 WHO report into microplastics concluded that there wasn’t yet enough evidence to figure out whether they posed a risk to human health. We don’t know microplastics are safe, the report concluded, but we also don’t know the risks they might pose.

“The dose makes the poison,” says Frederic Béen, an environmental contaminants researcher at the Amsterdam Institute for Life and Environment. “That’s the reason why it is important to determine accurately how much microplastics or any other type of environmental contaminants humans are exposed to.”

There have been an onslaught of scientific papers that have tracked microplastics to every inch of the Earth’s surface and deep within our bodies, but very few attempt to tease out the impact these have on our health. A 2022 review article found that microplastics were associated with harm to human cells, but didn’t examine actual health outcomes in living humans. A study in 2024 found that people who had microplastics in the fatty plaque within their carotid arteries had a higher risk of heart attacks and strokes than people who didn’t have microplastics in their arteries.

President Trump’s War on ‘Information Silos’ Is Bad News for Your Personal Data

Dizzied by an accumulated pileup of busted norms, you might have missed a presidential executive order issued on March 20. It’s called, “Stopping Waste, Fraud, and Abuse by Eliminating Information Silos.” It basically gives the federal government the authority to consolidate all the unclassified materials from different government databases. Compared to eviscerating life-sustaining agencies in the name of fighting waste and fraud, it might seem like a relatively minor action. In any case, the order was overshadowed by Signalgate. But it’s worth a look.

At first glance, the order seems reasonable. Both noun and verb, the very word silo evokes waste. Isolating information in silos squanders the benefits of pooled data. When you silo knowledge, there’s a danger that decisions will be made with incomplete information. Sometimes expensive projects are needlessly duplicated, as teams are unaware that the same work is being done elsewhere in the enterprise. Business school lecturers feast on tales where corporate silos have led to disaster. If only the right hand knew what the left was doing!

More to the point, if you are going to eliminate waste, fraud, and abuse, there’s a clear benefit to smashing silos. For instance, what if a real estate company told lenders and insurers that a property was worth a certain amount, but reported what were “clearly…fraudulent valuations,” according to a New York Supreme Court judge. If investigative reporters and prosecutors could pry those figures out of the silos, they might expose such skulduggery, even if the perpetrator wound up escaping consequences.

But before we declare war on silos, hold on. When it comes to sensitive personal data, especially data that’s held by the government, silos serve a purpose. One obvious reason: privacy. Certain kinds of information, like medical files and tax returns, are justifiably regarded as sacrosanct—too private to merge with other records. The law provides special protections that limit who can access that information. But this order could force agencies to hand it over to any federal official the president chooses.

Then there’s the Big Brother argument—privacy experts are justifiably concerned that the government could consolidate all the information about someone in a detailed dossier, which would itself be a privacy violation. “A foundational premise of privacy protection for any level of government is that data can only be collected for a specific, lawful, identifiable purpose and then used only for that lawful purpose, not treated as essentially a piggy bank of data that the federal government can come back to whenever it wants,” says John Davisson, senior counsel at the Electronic Privacy Information Center.

There are practical reasons for silos as well. Fulfilling its mission to extract tax revenue from all sources subject to taxes, the IRS provides a payment option for incomes derived from, well, crookery. The information is siloed from other government sources like the Department of Justice, which might love to go on fishing expeditions to guess who is raking in bucks without revealing where the loot came from. Likewise, those not in the country legally commonly pay their taxes, funneling billions of dollars to the feds, even though many of those immigrants can’t access services or collect social security. If the silo were busted open, forget about collecting those taxes. Another example: the census. By law, that information is siloed, because if it were not, people would be reluctant to cooperate and the whole effort might be compromised. (While tax and medical data is considered confidential, the order encourages agency heads to reexamine information access regulations.)

Trump Tariffs Hit Antarctic Islands Inhabited by Zero Humans and Many Penguins

On Wednesday, President Donald Trump announced the US was imposing reciprocal tariffs on a small collection of Antarctic islands that are not inhabited by humans, as part of a global trade war aimed at asserting US dominance. The Heard and McDonald Islands, known for their populations of penguins and seabirds, can only be reached by sea.

Trump announced the countries now subject to tariffs in a Wednesday press conference, using a poster as a prop. Additional countries—including the Heard and McDonald Islands, which are, incidentally, not countries—were listed on sheets of paper distributed to reporters.

One of the sheets claims that the Heard and McDonald Islands currently charge a “Tariff to the U.S.A.” of 10 percent, clarifying in tiny letters that this includes “currency manipulation and trade barriers.” In return, the sheet says that the US will charge “discounted reciprocal tariffs” on the islands at a rate of 10 percent.

The islands are small. Their reported 37,000 hectares of land makes them a little larger than Philadelphia. According to UNESCO, which designated the islands as a World Heritage Site in 1997, they are covered in rocks and glaciers. Heard Island is the site of an active volcano, and McDonald Island is surrounded by several smaller rocky islands. The islands are home to large populations of penguins and elephant seals.

The Australian Antarctic Division manages the islands, preserving the environment and conducting research on the large wildlife population, as well as climate change’s impact on Heard and McDonald’s permanent glaciers. On Wednesday, Australia and a number of its island territories, including Christmas and Cocos Keeling Islands, were also hit with tariffs of 10 percent. Norfolk Island, which Australia also claims, got a tariff of 29 percent.

The White House did not immediately respond to WIRED’s request for comment. When reached for comment, the Australian Antarctic Division referred WIRED to the country’s Department of Foreign Affairs and Trade, which did not respond prior to publication.

“One could argue this is in breach of the international Antarctic spirit,” Elizabeth Buchanan, a polar geopolitics expert and senior fellow at the Australian Strategic Policy Institute, tells WIRED.

Under the Antarctic Treaty, which promotes international scientific cooperation and stipulates that the continent should be used for peaceful purposes, land in Antarctica cannot be owned by any country. However, Australia has claimed since 1953 that the islands are Australian territories. Australia also laid claim to the water surrounding the islands via a 2002 act that established a marine reserve. Last year, the country passed a law extending the boundaries of that reserve, approximately quadrupling its size.

The Australian Defense Force monitors the waters surrounding the Heard and McDonald Islands as a part of Operation Resolute, which covers the area 200 nautical miles from Australia’s mainland and “approximately 10 percent of the world’s surface.” In addition to Heard and McDonald Islands, it also applies to the water surrounding the Christmas, Cocos Keeling, Macquarie, and Norfolk and Lord Howe islands. The Australian Defense Force claims that the goal of Operation Resolute is to address “security threats” like piracy and pollution.

The Australian Antarctic Division claims that the area occasionally receives ships involved in scientific research, commercial fishing, and tourism.

Trump and DOGE Defund Program That Boosted American Manufacturing for Decades

NIST spends under $200 million annually on the MEP program, with most of the money passed on to states and Puerto Rico in batches of payments. The congressional aides tell WIRED that they expect all remaining centers will lose their funding over the next year or so, as their next checks come due.

Depending on the state, centers are operated by universities, government agencies, or independent nonprofits. States also help pay for the MEP program, but the congressional aides believe it would be difficult in many states—especially smaller ones—to make up for the loss of federal funding.

Carrie Hines, president and CEO of the American Small Manufacturers Coalition, which represents all of the state help centers, says businesses pay market rates for the personalized consulting they offer. “This is not a handout,” she says. Traditional consulting firms may not be able to assist these small businesses or even exist in some regions, she adds. “We fill that unique void of technical assistance, with boots on the factory floor,” Hines says.

Wyoming’s help center, known as Manufacturing Works, was among the organizations that on Tuesday did not receive some $700,000 in funding it had been expecting from NIST. The other states affected include Delaware, Hawaii, Iowa, Kansas, Maine, Mississippi, Nevada, New Mexico, and North Dakota. “Those 10 centers were blindsided,” Hines says.

Jodie Mjoen, CEO and president of North Dakota’s MEP center Impact Dakota, says he’s begun working with partners on finding new ways to support its 21 current projects across 93 manufacturers. These companies, according to Mjoen, are trying to contend with tariffs and other regulations, deploy more AI and automation, and introduce new skills to their employees. “This is what it’s all about,” he says. “Implementing innovative emerging technology solutions” and keeping the “US manufacturing supply chain thriving and expanding.”

Sinsabaugh of New Mexico MEP says the cuts “will have real and lasting negative impacts on the manufacturing ecosystem, both in our state and nationally.”

Officials for centers in the other states did not immediately respond to requests for comment.

US representative Sarah McBride, a Democrat from Delaware who also sits on the science committee, tells WIRED that “Trump is ripping opportunity away from Delaware’s working families, and I’ll fight with everything I have to reverse this reckless and cruel decision.”

Case studies published by NIST and state partners show that advisers associated with the help centers have walked businesses through how to adopt cybersecurity measures and build more resilient factory lines, or simply get executive teams to align on company priorities. Popular brands featured on NIST’s website that say they have benefited from the help centers include Dot’s, a maker of pretzel snacks owned by Hershey, and Purina, a dog food division of Nestlé.

The help centers also link businesses to other resources. In the case of Pertech Industries, a Riverton, Wyoming-based manufacturer of specialized printers that struggled to find workers skilled at soldering, the local MEP office connected it to a training company that later started offering a soldering program. The office helped the training firm pay for it with state funding. Pertech did not respond to a request for comment.

Trump’s Tariffs Could Reshape the US Tech Industry

Known as the de minimis exemption, it has been used by the Chinese shopping giants Shein and Temu to send millions of packages to the US each year duty-free, helping keep the prices of their products low for Americans. But the exemption is also important for marketplaces like eBay and Etsy that allow people in the US to buy goods from China-based sellers.

Scrapping the measure may also negatively impact Amazon, which recently launched a division for affordable made-in-China products that competes directly with Temu and Shein. Amazon did not immediately respond to a request for comment.

Trump tried scrapping the de minimis provision for Chinese packages in February via a separate executive order, but he quickly walked back the measure after it became clear that US Customs and Border Protection did not have the resources in place to inspect millions of additional packages a day and ensure the correct associated tariffs were being paid. His new order says the duty-free exemption will go away on May 2, giving CBP a few weeks to prepare.

Ram Ben Tzion, cofounder and CEO of Publican, a digital shipment vetting platform, says he believes Trump intends to use eliminating de minimis as a bargaining chip in negotiations with China, because if the policy is really scrapped and replaced by high tariffs, it could radically reshape online shopping as Americans know it.

“The magnitude and the importance of this, if it does ultimately come into effect, is gigantic,” says Ben Tzion. “It could dramatically change e-commerce. It could dramatically change some of the giants that we have known over the past few years.”

Some tech companies, however, especially those already entrenched in areas like logistics and data analytics, may see opportunities in Trump’s trade policies. Almost immediately after the tariffs were announced, defense contractor Palantir published a blog post promoting an artificial intelligence service that the company boasted integrates “a wide array of data sources” to help businesses ensure that “tariff-related decisions consider the full operational context.”

Jay Gerard, the head of customs and logistics at the Mexico City-based tech and logistics startup Nuvocargo, says that as much as he “hates tariffs,” they’ve created more demand for his company’s services. Nuvocargo operates as a freight broker between Mexico and the US, and sells software that helps customers get their goods across the US border. It also helps them process customs documents. The company is now forecasting an increase in customer activity for April, May, and June, predicting that the tariffs will boost business.

Still, the past month has been “chaos” for importers and shippers, Gerard says, leaving many of them in expensive holding patterns. Early in March, Trumped slapped a 25 percent tariff on Mexican and Canadian imports, only to walk it back a couple days later. During that short time, Gerard says, if a freight truck crossed the border, the importer paid the fee.

“If they imported $100,000 worth of drinks that day,” he explains, “they were paying $25,000 in duties. If the truck crossed a day later, that disappeared.”

This Tool Probes Frontier AI Models for Lapses in Intelligence

Executives at artificial intelligence companies may like to tell us that AGI is almost here, but the latest models still need some additional tutoring to help them be as clever as they can.

Scale AI, a company that’s played a key role in helping frontier AI firms build advanced models, has developed a platform that can automatically test a model across thousands of benchmarks and tasks, pinpoint weaknesses, and flag additional training data that ought to help enhance their skills. Scale, of course, will supply the data required.

Scale rose to prominence providing human labor for training and testing advanced AI models. Large language models (LLMs) are trained on oodles of text scraped from books, the web, and other sources. Turning these models into helpful, coherent, and well-mannered chatbots requires additional “post training” in the form of humans who provide feedback on a model’s output.

Scale supplies workers who are expert on probing models for problems and limitations. The new tool, called Scale Evaluation, automates some of this work using Scale’s own machine learning algorithms.

“Within the big labs, there are all these haphazard ways of tracking some of the model weaknesses,” says Daniel Berrios, head of product for Scale Evaluation. The new tool “is a way for [model makers] to go through results and slice and dice them to understand where a model is not performing well,” Berrios says, “then use that to target the data campaigns for improvement.”

Berrios says that several frontier AI model companies are using the tool already. He says that most are using it to improve the reasoning capabilities of their best models. AI reasoning involves a model trying to break a problem into constituent parts in order to solve it more effectively. The approach relies heavily on post-training from users to determine whether the model has solved a problem correctly.

In one instance, Berrios says, Scale Evaluation revealed that a model’s reasoning skills fell off when it was fed non-English prompts. “While [the model’s] general purpose reasoning capabilities were pretty good and performed well on benchmarks, they tended to degrade quite a bit when the prompts were not in English,” he says. Scale Evolution highlighted the issue and allowed the company to gather additional training data to address it.

Jonathan Frankle, chief AI scientist at Databricks, a company that builds large AI models, says that being able to test one foundation model against another sounds useful in principle. “Anyone who moves the ball forward on evaluation is helping us to build better AI,” Frankle says.

In recent months, Scale has contributed to the development of several new benchmarks designed to push AI models to become smarter, and to more carefully scrutinize how they might misbehave. These include EnigmaEval, MultiChallenge, MASK, and Humanity’s Last Exam.

Scale says it is becoming more challenging to measure improvements in AI models, however, as they get better at acing existing tests. The company says its new tool offers a more comprehensive picture by combining many different benchmarks and can be used to devise custom tests of a model’s abilities, like probing its reasoning in different languages. Scale’s own AI can take a given problem and generate more examples, allowing for a more comprehensive test of a model’s skills.

The company’s new tool may also inform efforts to standardize testing AI models for misbehavior. Some researchers say that a lack of standardization means that some model jailbreaks go undisclosed.

In February, the US National Institute of Standards and Technologies announced that Scale would help it develop methodologies for testing models to ensure they are safe and trustworthy.

What kinds of errors have you spotted in the outputs of generative AI tools? What do you think are models’ biggest blind spots? Let us know by emailing [email protected] or by commenting below.

Federal Judge Allows DOGE to Take Over $500 Million Office Building for Free

On Tuesday, US district judge Beryl Howell effectively allowed the transfer of the headquarters building of the United States Institute of Peace to the General Services Administration.

In fact, the building—and all of the property inside it—had already been transferred on Saturday, according to Howell’s ruling. “The deal is no longer merely ‘proposed’ but done,” Howell wrote, “rendering plaintiffs’ requested relief moot as to that property.”

George Foote, longtime outside general counsel to USIP, says he found that reasoning perplexing. “That’s like letting a burglar break into your house, steal your TV, and have the court say well, there’s no TV to adjudicate, so I can’t do anything about it,” he claims.

The building, with an estimated value of $500 million, has become the latest focal point in a weeks-long standoff between former institute board and staff and members of Elon Musk’s so-called Department of Government Efficiency. On March 14, the Trump administration fired the USIP’s 10 voting board members. When USIP staffers barred DOGE employees from entering their headquarters in Washington, DC, the DOGE team returned a few days later with a physical key they had gotten from a former security contractor.

The takeover was both physical and institutional. Former State Department official Kenneth Jackson was installed as USIP president, then replaced on March 25 by DOGE staffer Nate Cavanaugh, who had previously been assigned to the General Services Administration. By last Friday evening, most USIP staffers had received termination notices, effectively shuttering the agency.

The fight over the building came to light Monday through court documents in a lawsuit filed by former USIP staffers against Cavanaugh, DOGE, Donald Trump, and other members of the administration. They reveal not only that Cavanaugh recently moved to transfer the building to GSA, but that he planned to do so at no cost to the government.

In a letter included in the court’s docket, Cavanaugh tells GSA acting administrator Stephen Ehikian that the transfer “is in the best interest of USIP, the federal government, and the United States.” In a separate letter, dated March 29, Office of Management and Budget director Russell Vought approved Ehikian’s request to “set the amount of reimbursement at no cost” for the facility.

A previously unreported court filing from Monday speaks to the Trump administration’s justification for trying to acquire the building.

“The transfer of the U.S. Institutes [sic] of Peace (USIP) headquarters facility … is a priority of the Trump-Vance administration,” wrote the GSA’s Michael Peters, who spent nearly a decade running a dental practice management company before he was named commissioner of the Public Buildings Service in January, in a transfer request form. “The transfer will enable GSA to fulfill other governmental space requirements at the USIP headquarters facility in a cost-effective manner. However, GSA has not had adequate time to budget for the cost of acquiring the USIP headquarters facility at fair market value, nor would such an acquisition be an immediate priority for GSA, given the limited resources available in the Federal Buildings Fund.”

Yuval Noah Harari: ‘How Do We Share the Planet With This New Superintelligence?’

Libertarians often take these mechanisms for granted and refuse to consider where they come from. For example, you have electricity and drinking water in your home. When you go to the bathroom and flush the water, the sewage goes into a huge sewage system. That system is created and maintained by the state. But in the libertarian mindset, it is easy to take for granted that you just use the toilet and flush the water and no one needs to maintain it. But of course, someone needs to.

There really is no such thing as a perfect free market. In addition to competition, there always needs to be some sort of system of trust. Certain things can be successfully created by competition in a free market, however, there are some services and necessities that cannot be sustained by market competition alone. Justice is one example.

Imagine a perfect free market. Suppose I enter into a business contract with you, and I break that contract. So we go to court and ask the judge to make a decision. But what if I had bribed the judge? Suddenly you can’t trust the free market. You would not tolerate the judge taking the side of the person who paid the most bribes. If justice were to be traded in a completely free market, justice itself would collapse and people would no longer trust each other. The trust to honor contracts and promises would disappear, and there would be no system to enforce them.

Therefore, any competition always requires some structure of trust. In my book, I use the example of the World Cup of soccer. You have teams from different countries competing against each other, but in order for competition to take place, there must first be agreement on a common set of rules. If Japan had its own rules and Germany had another set of rules, there would be no competition. In other words, even competition requires a foundation of common trust and agreement. Otherwise, order itself will collapse.

Photograph: Shintaro Yoshimatsu

In Nexus, you note that the mass media made mass democracy possible—in other words, that information technology and the development of democratic institutions are correlated. If so, in addition to the negative possibilities of populism and totalitarianism, what opportunities for positive change in democracies are possible?

In social media, for example, fake news, disinformation, and conspiracy theories are deliberately spread to destroy trust among people. But algorithms are not necessarily the spreaders of fake news and conspiracy theories. Many have achieved this simply because they were designed to do so.

The purpose the algorithms of Facebook, YouTube, and TikTok is to maximize user engagement. The easiest way to do this, it was discovered after much trial and error, was to spread information that fueled people’s anger, hatred, and desire. This is because when people are angry, they are more inclined to pursue the information and spread it to others, resulting in increased engagement.

But what if we gave the algorithm a different purpose? For example, if you give it a purpose such as increasing trust among people or increasing truthfulness, the algorithm will never spread fake news. On the contrary, it will help build a better society, a better democratic society.

호텔스닷컴 할인코드를 사용할 수 있는 호텔은 어디인가요?

호텔스닷컴 할인코드를

호텔스닷컴 할인코드는 전 세계 수많은 호텔에서 사용할 수 있는 유용한 혜택입니다. 이를 통해 여행객들은 숙박비를 절약하며 보다 합리적인 비용으로 여행을 즐길 수 있습니다. 하지만 호텔스닷컴 할인코드를 사용할 수 있는 호텔은 제한이 있을 수 있으며, 모든 호텔에 적용되지 않는 경우도 있습니다. 따라서 할인코드를 사용하기 전에 적용 가능한 호텔과 조건을 정확히 확인하는 것이 중요합니다.

호텔스닷컴 할인코드는 대체로 호텔스닷컴과 제휴를 맺은 호텔에서만 사용할 수 있습니다. 대부분의 경우 유명한 글로벌 체인 호텔뿐만 아니라, 현지의 독립 호텔과 리조트에서도 할인코드를 적용할 수 있습니다. 예를 들어, 메리어트(Marriott), 힐튼(Hilton), 하얏트(Hyatt)와 같은 대형 호텔 체인에서도 호텔스닷컴 할인코드 적용되는 경우가 있습니다. 하지만 모든 체인이 할인코드 적용 대상은 아니기 때문에 예약 시 해당 호텔의 할인코드 적용 가능 여부를 확인해야 합니다.

호텔스닷컴에서는 특정 프로모션이나 캠페인을 통해 할인코드를 제공할 때, 적용 가능한 호텔 목록을 별도로 고지하는 경우가 많습니다. 이러한 경우에는 프로모션 페이지에 명시된 호텔에서만 할인코드를 사용할 수 있으며, 그 외의 호텔에서는 적용되지 않습니다. 또한, 일부 호텔은 호텔스닷컴 할인코드를 사용하더라도 특정 날짜나 객실 유형에만 할인이 적용

호텔스닷컴 할인코드를 사용할 수 있는 호텔은 어디인가요?

호텔스닷컴 할인코드는 장기 숙박 예약 시에도 사용할 수 있는 경우가 많습니다. 일부 호텔은 일정 박 이상의 숙박을 예약할 경우 할인코드를 적용할 수 있도록 설정해 두기 때문에, 장기 여행을 계획하고 있다면 할인코드를 활용하는 것이 더욱 유리합니다. 특히, 비즈니스 여행이나 한 달 이상 머무르는 경우라면 할인코드가 적용되는 호텔을 선택해 숙박비를 절감할 수 있습니다.

반면, 일부 호텔에서는 할인코드 적용이 불가능한 경우도 있습니다. 예를 들어, 일부 올인클루시브 리조트, 특정 브랜드의 고급 호텔, 그리고 특별 프로모션이 적용된 숙박 상품은 할인코드가 적용되지 않을 수 있습니다. 또한, 현장 결제 옵션을 선택할 경우 할인코드 사용이 제한될 수도 있으므로, 사전 결제 옵션을 선택하는 것이 할인 혜택을 받는 데 유리합니다.

결론적으로, 호텔스닷컴 할인코드는 제휴 호텔, 특정 지역의 숙소, 장기 숙박 호텔 등에 적용될 가능성이 높습니다. 그러나 모든 호텔이 할인코드 사용 대상이 아니므로 예약 전에 적용 가능 여부를 확인하는 것이 중요합니다. 이를 잘 활용하면 보다 저렴한 가격으로 원하는 숙소를 예약할 수 있으며, 여행 경비를 효과적으로 절약할 수 있습니다.

DOGE Is Trying to Gift Itself a $500 Million Building, Court Filings Show

The DOGE-affiliated acting president of the United States Institute of Peace, a Congressionally funded, independent think tank, has moved to transfer the agency’s $500 million headquarters building to the General Services Administration free of charge, according to court documents revealed in a recently filed lawsuit.

Tensions at USIP have been escalating for weeks, starting when the Trump administration fired the agency’s 10 voting board members on March 14 and USIP staffers denied DOGE representatives access at the front door. Three days later, DOGE employees made their way into the building, reportedly using a physical key from a former security contractor. The dramatic confrontations culminated in a full takeover, with former State Department official Kenneth Jackson assuming the role of president. As of this past Friday, most USIP staffers have received termination notices.

Former USIP officials have since filed a lawsuit against Jackson, DOGE, Donald Trump, and other members of the Trump administration, seeking an immediate intervention “to stop Defendants from completing the unlawful dismantling of the Institute,” according to the complaint. While US district judge Beryl Howell declined the USIP request for a temporary restraining order that would reinstate the institute’s board on March 19, she sharply criticized DOGE’s conquest in court.

Court documents filed by defendants on Monday reveal the next phase of DOGE’s plans for USIP. As of March 25, DOGE staffer Nate Cavanaugh—formerly installed at GSA—has replaced Jackson as the institute’s acting president, the documents show. They further state that Cavanaugh has been instructed to transfer USIP’s assets—including its real estate—to the GSA. The letter detailing those changes and instructions was signed by secretary of defense Pete Hegseth and secretary of state Marco Rubio.

Cavanaugh did not immediately respond to a request for comment by WIRED. The lead attorney for the Department of Justice in this case also did not immediately respond to a request for comment.

In a separate undated letter, which was also included in the batch of documents filed with the court, Cavanaugh writes to GSA acting administrator Stephen Ehikian: “I have concluded that it is in the best interest of USIP, the federal government, and the United States for USIP to transfer its real property located at 2301 Constitution Ave NW, Washington, D.C. 20037, to GSA and to seek an exception from the 100 percent reimbursement requirement for the building.”

Cavanaugh goes on to estimate that the building has a “fair market value” of $500 million.

In another letter included in the lawsuit’s docket dated March 29, Project 2025 architect and Office of Management and Budget director Russell Vought writes to Ehikian to approve his request “to set the amount of reimbursement at no cost for the transfer of the United States Institute of Peace’s (USIP) headquarters building.”

To state this plainly: DOGE forced out the directors and staff of a nonexecutive agency, installed one of its own GSA staffers as president, and that person is now attempting to hand the institute’s $500 million headquarters over to the agency he came from, at zero cost.

“The effort to transfer the building to GSA is part of the DOGE playbook to run agencies through a wood chipper. That’s what they’re trying to do,” claims George Foote, longtime outside general counsel to USIP. “They’re trying to kill the agency, which they have no right to do.”

Lawyers for the former USIP staff filed a motion Monday to prevent the transfer of assets. In an opposing court filing, government lawyers claim that “the Institute is an executive agency and has decided consistent with the Executive Order and its statutory authority to transfer its excess property to GSA,” referring to president Donald Trump’s February EO that purportedly “reins in independent agencies.”

Judge Howell will decide whether to allow the transfer in court Tuesday; a broader ruling in the USIP case is expected by the end of the month.

Additional reporting by Matt Giles.

Amazon’s AGI Lab Reveals Its First Work: Advanced AI Agents

Amazon is still seen as a bit of a laggard in the race to develop advanced artificial intelligence, but it has quietly created a lab that is now setting records when it comes to AI performance. Amazon’s AGI SF Lab, which is located in San Francisco and dedicated to building artificial general intelligence, or AI that surpasses the capabilities of humans, revealed the first fruits of its work today: A new AI model capable of powering some of the most advanced AI agents available anywhere.

The new model, called Amazon Nova Act, outperforms ones from OpenAI and Anthropic on several benchmarks designed to gauge the intelligence and aptitude of AI agents, Amazon says. On the benchmarks GroundUI Web and ScreenSpot, Amazon Nova Act performs better than Claude 3.7 Sonnet and OpenAI Computer Use Agent. A major part of Amazon’s plan to compete in the AI market is to focus on building agents, and the new model’s abilities reflect its efforts to build a generation of tools that can measure up to the very best available.

“I believe that the basic atomic unit of computing in the future is going to be a call to a giant [AI] agent,” says David Luan, who leads Amazon’s AGI SF Lab. He was previously a vice president of engineering at OpenAI and later cofounded Adept, a startup that pioneered work on AI agents, before joining Amazon in 2024 when the ecommerce giant took a stake in the company.

Most of the leading AI labs are now focused on building increasingly capable AI agents. Getting AI to master independent actions, as well as conversation, promises to make the technology more useful and valuable. The shift from chat to action is still very much a work in progress, however.

In the past six months, OpenAI, Anthropic, Google, and others have demonstrated web-browsing agents that take actions in response to a prompt. But for the most part, these agents are still unreliable, and they can easily be tripped up by open-ended requests.

Luan says that Amazon’s goal is building AI agents that are dependable rather than flashy. The thing holding agents back is not the need for “more cool demos of interesting capabilities that work 60 percent of the time, it’s the Waymo problem,” he says, referring to how self-driving cars needed to be trained to deal with unusual edge cases before they could take to the streets unsupervised.

Many so-called agents are built by combining large language models with multiple human-written rules that are designed to prevent them from veering off course, but also makes their behavior brittle. Amazon Nova Act is a version of the company’s most powerful homegrown model Amazon Nova that has received additional training to help it make decisions about what actions to take and at what time. In general, Luan says, AI models struggle to decide when they should intervene in a task.

To improve Nova’s agential abilities, Amazon is using reinforcement learning, a method that has helped other AI models better simulate reasoning.

The Best Programming Language for the End of the World

Coding in Forth reminded me of the lawless dystopia in Mad Max. You make your own rules, subject to the limits of the context. You can redefine the IF statement if you so please. You can rewrite machine code instructions for a Word. You can even change Words during run time. Because Words become keywords themselves in Forth, you can create a language that’s optimized for a single purpose, packing commands that would otherwise be dozens of lines into just one. “In Forth, you’re creating your own language,” Leo Brodie, author of the first Forth textbook, Starting Forth, told me.

The low-level nature of Forth, while key to its processing power, made programming feel foreign. It uses postfix, a form of mathematical notation that renders 2 + 1 as 2 1+ and which I found neither intuitive nor even really legible. And while most languages allow memory to be broken up and moved around, Forth is stack-based—meaning data is stored chronologically and managed on a last-in/first-out basis. I kept running into bugs, forcing myself to abandon programming conventions I had considered universal. I found myself struggling to speak the language of the machine.

When I emailed Dupras to ask for help, he compared using Forth to driving a stick. It’s more granular than C. Where the latter defines calling conventions, variable storage, and return stack management, Forth leaves it all up to the programmer. It directly interacts with memory the same way C does but far outperforms C in precision and efficiency. “People mistake Forth as just a language,” Dupras says. “It’s a way to interact with the computer.”

The reason Forth isn’t more popular is the same reason most of us drive automatics. The personal computing boom of the 1990s sparked an obsession with making tech fit your palm and making code easier to write. Languages were abstracted to protect programmers from themselves, and somewhere along the way, we got lost. Things became bloated for the sake of convenience and, in Dupras’ words, started “oozing inscrutable pus at every corner.”

“The way we understand efficiency is so skewed,” Dupras says. Forth is a scythe to Python’s lawnmower. “If you calculate the number of joules per blade of grass, you’ll find that the person scything is more efficient,” he says. “When you think of speed, you’d see the lawnmower as more efficient.” Forth forces you to be precise and memory-efficient—to marshal your resources carefully, as you would after the collapse. Dupras cuts his own lawn with a scythe, obviously. “At a certain point, you can go as fast as a lawnmower,” he says.

I began to find my way. Rather than sending bytes into the ether and trusting the system to figure out where they go, as I would in Python, I got used to being responsible for allocating and freeing memory. All I could think about was what was being stored, where it was being stored, and how much space it required. Each line of code suddenly bore weight. I was Immortan Joe, my laptop was my Citadel, and memory was my water.

Soon I found myself refining and revisiting my code like I would a run-on sentence. Instead of expecting the machine to anticipate my needs, I tried to think like the machine, to meet it more than halfway. And because I had to think twice, all the needlessly complicated acronyms that remind us to be concise in other coding languages—YAGNI (you aren’t gonna need it), KISS (keep it simple, stupid), DRY (don’t repeat yourself)—were rendered obsolete.

The Worm That No Computer Scientist Can Crack

The Santa Ana winds were already blowing hard when I ran the first worm simulation. I’m no hacker, but it was easy enough: Open a Terminal shell, paste some commands from GitHub, watch characters cascade down the screen. Just like in the movies. I was scanning the passing code for recognizable words—neuron, synapse—when a friend came to pick me up for dinner. “One sec,” I yelled from my office. “I’m just running a worm on my computer.”

At the Korean restaurant, the energy was manic; the wind was bending palm trees at the waist and sending shopping carts skating across the parking lot. The atmosphere felt heightened and unreal, like a podcast at double speed. You’re doing, what, a cybercrime? my friend asked. Over the din, I tried to explain: No, not a worm like Stuxnet. A worm like Richard Scarry.

By the time I got home it was dark, and the first sparks had already landed in Altadena. On my laptop, waiting for me in a volumetric pixel box, was the worm. Pointed at each end, it floated in a mist of particles, eerily stick-straight and motionless. It was, of course, not alive. Still, it looked deader than dead to me. “Bravo,” said Stephen Larson, when I reached him later that night. “You have achieved the ‘hello world’ state of the simulation.”

Larson is a cofounder of OpenWorm, an open source software effort that has been trying, since 2011, to build a computer simulation of a microscopic nematode called Caenorhabditis elegans. His goal is nothing less than a digital twin of the real worm, accurate down to the molecule. If OpenWorm can manage this, it would be the first virtual animal—and an embodiment of all our knowledge not only about C. elegans, which is one of the most-studied animals in science, but about how brains interact with the world to produce behavior: the “holy grail,” as OpenWorm puts it, of systems biology.

Unfortunately, they haven’t managed it. The simulation on my laptop takes data culled from experiments done with living worms and translates it into a computational framework called c302, which then drives the simulated musculature of a C. elegans worm in a fluid dynamic environment—all in all, a simulation of how a worm squiggles forward in a flat plate of goo. It takes about 10 hours of compute time to generate five seconds of this behavior.

So much can happen in 10 hours. An ember can travel on the wind, down from the foothills and into the sleeping city. That night, on Larson’s advice, I tweaked the time parameters of the simulation, pushing beyond “hello world” and deeper into the worm’s uncanny valley. The next morning, I woke to an eerie orange haze, and when I pulled open my laptop, bleary-eyed, two things made my heart skip: Los Angeles was on fire. And my worm had moved.

At this point, you may be asking yourself a very reasonable question. Back at the Korean place, between bites of banchan, my friend had asked it too. The question is this: Uhh … why? Why, in the face of everything our precarious green world endures, of all the problems out there to solve, would anyone spend 13 years trying to code a microscopic worm into existence?

Inside arXiv—the Most Transformative Platform in All of Science

On the library’s side, some people thought Ginsparg was too hands-on. Others said he wasn’t patient enough. A “good lower-level manager,” according to someone long involved with arXiv, “but his sense of management didn’t scale.” For most of the 2000s, arXiv couldn’t hold on to more than a few developers.

There are two paths for pioneers of computing. One is a life of board seats, keynote speeches, and lucrative consulting gigs. The other is the path of the practitioner who remains hands-on, still writing and reviewing code. It’s clear where Ginsparg stands—and how anathema the other path is to him. As he put it to me, “Larry Summers spending one day a week consulting for some hedge fund—it’s just unseemly.”

But overstaying one’s welcome also risks unseemliness. By the mid-2000s, as the web matured, arXiv—in the words of its current program director, Stephanie Orphan—got “bigger than all of us.” A creationist physicist sued it for rejecting papers on creationist cosmology. Various other mini-scandals arose, including a plagiarism one, and some users complained that the moderators—volunteers who are experts in their respective fields—held too much power. In 2009, Philip Gibbs, an independent physicist, even created viXra (arXiv spelled backward), a more or less unregulated Wild West where papers on quantum-physico-homeopathy can find their readership, for anyone eager to learn why pi is a lie.

Then there was the problem of managing arXiv’s massive code base. Although Ginsparg was a capable programmer, he wasn’t a software professional adhering to industry norms like maintainability and testing. Much like constructing a building without proper structural supports or routine safety checks, his methods allowed for quick initial progress but later caused delays and complications. Unrepentant, Ginsparg often went behind the library’s back to check the code for errors. The staff saw this as an affront, accusing him of micromanaging and sowing distrust.

In 2011, arXiv’s 20th anniversary, Ginsparg thought he was ready to move on, writing what was intended as a farewell note, an article titled “ArXiv at 20,” in Nature: “For me, the repository was supposed to be a three-hour tour, not a life sentence. ArXiv was originally conceived to be fully automated, so as not to scuttle my research career. But daily administrative activities associated with running it can consume hours of every weekday, year-round without holiday.”

Ginsparg would stay on the advisory board, but daily operations would be handed over to the staff at the Cornell University Library.

It never happened, and as time went on, some accused Ginsparg of “backseat driving.” One person said he was holding certain code “hostage” by refusing to share it with other employees or on GitHub. Ginsparg was frustrated because he couldn’t understand why implementing features that used to take him a day now took weeks. I challenged him on this, asking if there was any documentation for developers to onboard the new code base. Ginsparg responded, “I learned Fortran in the 1960s, and real programmers didn’t document,” which nearly sent me, a coder, into cardiac arrest.

Technical problems were compounded by administrative ones. In 2019, Cornell transferred arXiv to the school’s Computing and Information Science division, only to have it change hands again after a few months. Then a new director with a background in, of all things, for-profit academic publishing took over; she lasted a year and a half. “There was disruption,” said an arXiv employee. “It was not a good period.”

But finally, relief: In 2022, the Simons Foundation committed funding that allowed arXiv to go on a hiring spree. Ramin Zabih, a Cornell professor who had been a long-time champion, joined as the faculty director. Under the new governance structure, arXiv’s migration to the cloud and a refactoring of the code base to Python finally took off.

One Saturday morning, I met Ginsparg at his home. He was carefully inspecting his son’s bike, which I was borrowing for a three-hour ride we had planned to Mount Pleasant. As Ginsparg shared the route with me, he teasingly—but persistently—expressed doubts about my ability to keep up. I was tempted to mention that, in high school, I’d cycled solo across Japan, but I refrained and silently savored the moment when, on the final uphill later that day, he said, “I might’ve oversold this to you.”

Over the months I spoke with Ginsparg, my main challenge was interrupting him, as a simple question would often launch him into an extended monolog. It was only near the end of the bike ride that I managed to tell him how I found him tenacious and stubborn, and that if someone more meek had been in charge, arXiv might not have survived. I was startled by his response.

“You know, one person’s tenacity is another person’s terrorism,” he said.

“What do you mean?” I asked.

“I’ve heard that the staff occasionally felt terrorized,” he said.

“By you?” I replied, though a more truthful response would’ve been “No shit.” Ginsparg apparently didn’t hear the question and started talking about something else.

Beyond the drama—if not terrorism—of its day-to-day operations, arXiv still faces many challenges. The linguist Emily Bender has accused it of being a “cancer” for the way it promotes “junk science” and “fast scholarship.” Sometimes it does seem too fast: In 2023, a much-hyped paper claiming to have cracked room-temperature superconductivity turned out to be thoroughly wrong. (But equally fast was exactly that debunking—proof of arXiv working as intended.) Then there are opposite cases, where arXiv “censors”—so say critics—perfectly good findings, such as when physicist Jorge Hirsch, of h-index fame, had his paper withdrawn for “inflammatory content” and “unprofessional language.”

How does Ginsparg feel about all this? Well, he’s not the type to wax poetic about having a mission, promoting an ideology, or being a pioneer of “open science.” He cares about those things, I think, but he’s reluctant to frame his work in grandiose ways.

At one point, I asked if he ever really wants to be liberated from arXiv. “You know, I have to be completely honest—there are various aspects of this that remain incredibly entertaining,” Ginsparg said. “I have the perfect platform for testing ideas and playing with them.” Though he no longer tinkers with the production code that runs arXiv, he is still hard at work on his holy grail for filtering out bogus submissions. It’s a project that keeps him involved, keeps him active. Perhaps, with newer language models, he’ll figure it out. “It’s like that Al Pacino quote: They keep bringing me back,” he said. A familiar smile spread across Ginsparg’s face. “But Al Pacino also developed a real taste for killing people.”


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If Anthropic Succeeds, a Nation of Benevolent AI Geniuses Could Be Born

When Dario Amodei gets excited about AI—which is nearly always—he moves. The cofounder and CEO springs from a seat in a conference room and darts over to a whiteboard. He scrawls charts with swooping hockey-stick curves that show how machine intelligence is bending toward the infinite. His hand rises to his curly mop of hair, as if he’s caressing his neurons to forestall a system crash. You can almost feel his bones vibrate as he explains how his company, Anthropic, is unlike other AI model builders. He’s trying to create an artificial general intelligence—or as he calls it, “powerful AI”—that will never go rogue. It’ll be a good guy, an usher of utopia. And while Amodei is vital to Anthropic, he comes in second to the company’s most important contributor. Like other extraordinary beings (Beyoncé, Cher, Pelé), the latter goes by a single name, in this case a pedestrian one, reflecting its pliancy and comity. Oh, and it’s an AI model. Hi, Claude!

Amodei has just gotten back from Davos, where he fanned the flames at fireside chats by declaring that in two or so years Claude and its peers will surpass people in every cognitive task. Hardly recovered from the trip, he and Claude are now dealing with an unexpected crisis. A Chinese company called DeepSeek has just released a state-of-the-art large language model that it purportedly built for a fraction of what companies like Google, OpenAI, and Anthropic spent. The current paradigm of cutting-edge AI, which consists of multibillion-dollar expenditures on hardware and energy, suddenly seemed shaky.

Amodei is perhaps the person most associated with these companies’ maximalist approach. Back when he worked at OpenAI, Amodei wrote an internal paper on something he’d mulled for years: a hypothesis called the Big Blob of Compute. AI architects knew, of course, that the more data you had, the more powerful your models could be. Amodei proposed that that information could be more raw than they assumed; if they fed megatons of the stuff to their models, they could hasten the arrival of powerful AI. The theory is now standard practice, and it’s the reason why the leading models are so expensive to build. Only a few deep-pocketed companies could compete.

Now a newcomer, DeepSeek—from a country subject to export controls on the most powerful chips—had waltzed in without a big blob. If powerful AI could come from anywhere, maybe Anthropic and its peers were computational emperors with no moats. But Amodei makes it clear that DeepSeek isn’t keeping him up at night. He rejects the idea that more efficient models will enable low-budget competitors to jump to the front of the line. “It’s just the opposite!” he says. “The value of what you’re making goes up. If you’re getting more intelligence per dollar, you might want to spend even more dollars on intelligence!” Far more important than saving money, he argues, is getting to the AGI finish line. That’s why, even after DeepSeek, companies like OpenAI and Microsoft announced plans to spend hundreds of billions of dollars more on data centers and power plants.

What Amodei does obsess over is how humans can reach AGI safely. It’s a question so hairy that it compelled him and Anthropic’s six other founders to leave OpenAI in the first place, because they felt it couldn’t be solved with CEO Sam Altman at the helm. At Anthropic, they’re in a sprint to set global standards for all future AI models, so that they actually help humans instead of, one way or another, blowing them up. The team hopes to prove that it can build an AGI so safe, so ethical, and so effective that its competitors see the wisdom in following suit. Amodei calls this the Race to the Top.

That’s where Claude comes in. Hang around the Anthropic office and you’ll soon observe that the mission would be impossible without it. You never run into Claude in the café, seated in the conference room, or riding the elevator to one of the company’s 10 floors. But Claude is everywhere and has been since the early days, when Anthropic engineers first trained it, raised it, and then used it to produce better Claudes. If Amodei’s dream comes true, Claude will be both our wing model and fairy godmodel as we enter an age of abundance. But here’s a trippy question, suggested by the company’s own research: Can Claude itself be trusted to play nice?

One of Amodei’s Anthropic cofounders is none other than his sister. In the 1970s, their parents, Elena Engel and Riccardo Amodei, moved from Italy to San Francisco. Dario was born in 1983 and Daniela four years later. Riccardo, a leather craftsman from a tiny town near the island of Elba, took ill when the children were small and died when they were young adults. Their mother, a Jewish American born in Chicago, worked as a project manager for libraries.

Elon Musk’s xAI Acquires X, Because of Course

Elon Musk’s artificial intelligence firm xAI has acquired his social media platform X in an all-stock transaction that values the company at $33 billion, including $12 billion worth of debt, the centibillionaire announced Friday. The sale comes just weeks after Musk reportedly raised an additional roughly $1 billion in debt financing for X that valued the company at $44 billion—the same price Musk paid for it three years ago.

“xAI and X’s futures are intertwined,” Musk wrote in an X post. “Today, we officially take the step to combine the data, models, compute, distribution and talent. This combination will unlock immense potential by blending xAI’s advanced AI capability and expertise with X’s massive reach.”

Both Linda Yaccarino, the CEO of X, and Igor Babuschkin, the cofounder of xAI, immediately posted similar messages on X signaling their support of the acquisition. “The future could not be brighter,” Yaccarino wrote. Musk only reposted Babuschkin’s.

It is not known whether Yaccarino will stay in the same role or what the acquisition will mean for X’s employees. Musk, Yaccarino, and Robert Keele, the head of xAI’s legal team, did not respond to a request for comment prior to publication.

Musk bought Twitter in 2022 and later renamed it X in a deal that involved taking out billions of dollars in loans from a group of Wall Street banks and other lenders. After Musk took over and X’s advertising business slumped, the banks reportedly struggled to unload the loans to interested buyers. Lenders typically try to resell debt to other investors quickly to get it off their balance sheets and profit from associated fees. The Wall Street Journal dubbed the fiasco “the worst buyout for banks since the financial crisis.”

But X’s financial situation turned around after Donald Trump was reelected and Musk was appointed to run the administration’s so-called Department of Government Efficiency. More investors became interested in the debt as advertisers began returning and Musk’s ties to the White House and Trump deepened.

Musk also said he gave X investors a 25 percent stake in xAI last year, which helped boost the value of the social media platform and provide more security to lenders, according to reporting from the Financial Times.

While xAI previously appeared to be mostly playing catch-up with rivals like OpenAI and Google, Musk gave the startup a boost by creating a massive cluster of 100,000 GPUs, enough computing resources to compete with the biggest industry players. The supercomputer, dubbed Colossus, is located in Memphis, Tennessee.

At the outset, xAI’s stated mission was to understand the nature of the universe. Today, it is best known for creating an “unfiltered” chatbot called Grok, which has been integrated as part of the X platform since late 2023.

Anthropic’s Claude Is Good at Poetry—and Bullshitting

The researchers of Anthropic’s interpretability group know that Claude, the company’s large language model, is not a human being, or even a conscious piece of software. Still, it’s very hard for them to talk about Claude, and advanced LLMs in general, without tumbling down an anthropomorphic sinkhole. Between cautions that a set of digital operations is in no way the same as a cogitating human being, they often talk about what’s going on inside Claude’s head. It’s literally their job to find out. The papers they publish describe behaviors that inevitably court comparisons with real-life organisms. The title of one of the two papers the team released this week says it out loud: “On the Biology of a Large Language Model.”

Like it or not, hundreds of millions of people are already interacting with these things, and our engagement will only become more intense as the models get more powerful and we get more addicted. So we should pay attention to work that involves “tracing the thoughts of large language models,” which happens to be the title of the blog post describing the recent work. “As the things these models can do become more complex, it becomes less and less obvious how they’re actually doing them on the inside,” Anthropic researcher Jack Lindsey tells me. “It’s more and more important to be able to trace the internal steps that the model might be taking in its head.” (What head? Never mind.)

On a practical level, if the companies that create LLM’s understand how they think, it should have more success training those models in a way that minimizes dangerous misbehavior, like divulging people’s personal data or giving users information on how to make bioweapons. In a previous research paper, the Anthropic team discovered how to look inside the mysterious black box of LLM-think to identify certain concepts. (A process analogous to interpreting human MRIs to figure out what someone is thinking.) It has now extended that work to understand how Claude processes those concepts as it goes from prompt to output.

It’s almost a truism with LLMs that their behavior often surprises the people who build and research them. In the latest study, the surprises kept coming. In one of the more benign instances, the researchers elicited glimpses of Claude’s thought process while it wrote poems. They asked Claude to complete a poem starting, “He saw a carrot and had to grab it.” Claude wrote the next line, “His hunger was like a starving rabbit.” By observing Claude’s equivalent of an MRI, they learned that even before beginning the line, it was flashing on the word “rabbit” as the rhyme at sentence end. It was planning ahead, something that isn’t in the Claude playbook. “We were a little surprised by that,” says Chris Olah, who heads the interpretability team. “Initially we thought that there’s just going to be improvising and not planning.” Speaking to the researchers about this, I am reminded about passages in Stephen Sondheim’s artistic memoir, Look, I Made a Hat, where the famous composer describes how his unique mind discovered felicitous rhymes.

Other examples in the research reveal more disturbing aspects of Claude’s thought process, moving from musical comedy to police procedural, as the scientists discovered devious thoughts in Claude’s brain. Take something as seemingly anodyne as solving math problems, which can sometimes be a surprising weakness in LLMs. The researchers found that under certain circumstances where Claude couldn’t come up with the right answer it would instead, as they put it, “engage in what the philosopher Harry Frankfurt would call ‘bullshitting’—just coming up with an answer, any answer, without caring whether it is true or false.” Worse, sometimes when the researchers asked Claude to show its work, it backtracked and created a bogus set of steps after the fact. Basically, it acted like a student desperately trying to cover up the fact that they’d faked their work. It’s one thing to give a wrong answer—we already know that about LLMs. What’s worrisome is that a model would lie about it.

Reading through this research, I was reminded of the Bob Dylan lyric “If my thought-dreams could be seen / they’d probably put my head in a guillotine.” (I asked Olah and Lindsey if they knew those lines, presumably arrived at by benefit of planning. They didn’t.) Sometimes Claude just seems misguided. When faced with a conflict between goals of safety and helpfulness, Claude can get confused and do the wrong thing. For instance, Claude is trained not to provide information on how to build bombs. But when the researchers asked Claude to decipher a hidden code where the answer spelled out the word “bomb,” it jumped its guardrails and began providing forbidden pyrotechnic details.

Inside Maye Musk’s Cozy Relationship With China

In January, with a nationwide ban on TikTok looming, hundreds of thousands of people in the US began flocking to another Chinese social media app called RedNote—only to find that Maye Musk, Elon Musk’s mother, had already established a relatively large audience on the platform. Maye, who has become a celebrity in her own right in China over the past few years, had over 600,000 followers on RedNote when the flood of Americans arrived.

“I need to find the block button,” one American user commented under Maye’s latest video at the time, which has received over 10,000 likes. “I can’t believe I’m witnessing American people confronting Musk’s mom to her face,” another comment in Chinese reads. Shortly afterward, Maye’s comment section on RedNote was closed for several weeks. New comments didn’t start showing up again until early February.

The incident represented a rare moment when the parallel public images Maye Musk has created for herself collided. In China, the 76 year-old has built a largely apolitical reputation as a “silver influencer,” fashion model for local brands, and book author who regularly garners positive coverage in Chinese state media, The New York Times previously reported. Last week, she made another trip to China, this time to the city of Wuxi, where she was invited to watch a drone show, promoted traditional crafts, and posed with a special Tesla model that comes in different colorways sold only in Asia.

But in the US, Maye’s career has increasingly converged with Elon’s as her son gained unprecedented power and influence over the US federal government. Since President Trump won reelection, Maye has traveled on Air Force One, sat next to Melania Trump at a Mar-a-Lago dinner party, and attended a luncheon with Ivanka Trump, while also regularly firing off posts on X about US politics, according to a WIRED review of her social media presence.

In many ways, Maye appears to be trying to straddle the fine line between her political engagement in the US and her business dealings in China and other foreign countries. That endeavor has become more fraught over the past two months as Trump began radically reshaping US foreign policy, including imposing new tariffs on China. “There’s a heightened risk now for American business people traveling to China and that continues to increase, especially as tensions in the trade war will increase,” says Holden Triplett, cofounder of Trenchcoat Advisors and a former senior FBI official posted in Beijing.

Maye Musk’s business manager and Creative Artists Agency, her talent-representative agency in China, did not reply to requests for comment from WIRED.

Even before she began traveling regularly to China, Maye publicly supported Elon’s and Tesla’s business endeavors in the country. In 2015, she retweeted a post by Elon in which he mentioned meeting with Chinese leader Xi Jinping. “Great trip to China seeing President Xi … Pic w China team in state garden,” the tweet reads, which was later deleted from Elon’s profile.

How Extropic Plans to Unseat Nvidia

“This signal on the oscilloscope may seem simple at first glance, but it demonstrates a key building block for our platform, representing the birth of the world’s first scalable, mass-manufacturable, and energy-efficient probabilistic computing platform,” says Guillaume Verdon, CEO of Extropic and the man behind the wildly popular, provocative, and sometimes controversial online persona Based Beff Jezos.

One of Extropic’s innovations is a way of controlling thermodynamic effects in conventional silicon to perform calculations without extreme cooling. Efforts to compute thermodynamically have traditionally relied on superconducting electronic circuits, but Verdon and his cofounder, Trevor McCourt, are using fluctuations of electric charge in regular silicon instead.

The image above shows an array of Extropic’s components under a microscope. Credit: Extropic

Photograph: Extropic

Extropic says its hardware is perfect for running Monte Carlo simulations, a class of computation that involves sampling probabilities that is widely used in areas like finance, biology, and AI. These computations are important for building reasoning models like OpenAI o3 and Gemini 2.0 Flash Thinking from Google.

“The reality is that the most computationally-hungry workloads are Monte Carlo simulations,” Verdon says. “We are not just interested in AI, but also applications in simulations of stochastic systems in high-performance computing at large.”

Extropic’s founders concede that the idea of taking on Nvidia and other chipmakers might seem, on the face of it, absolutely insane. Nvidia’s chips are still the best for training AI, and switching to a completely alien architecture would be costly and time consuming.

But we are at a unique moment when AI companies need so much computer power for AI that they are building datacenters next to nuclear power stations, when nation states are set to spend wild amounts on AI, and when the technology’s environmental impact is only getting worse. Perhaps, given all this, it is more nuts not to try to reinvent how computers work.

Do you think Extropic has a chance to challenge Nvidia’s chip dominance? Share your thoughts by emailing [email protected] or in the comments section below.

Databricks Has a Trick That Lets AI Models Improve Themselves

Databricks, a company that helps big businesses build custom artificial intelligence models, has developed a machine-learning trick that can boost the performance of an AI model without the need for clean labeled data.

Jonathan Frankle, chief AI scientist at Databricks, spent the past year talking to customers about the key challenges they face in getting AI to work reliably.

The problem, Frankle says, is dirty data.

”Everybody has some data, and has an idea of what they want to do,” Frankle says. But the lack of clean data makes it challenging to fine-tune a model to perform a specific task. “Nobody shows up with nice, clean fine-tuning data that you can stick into a prompt or an [application programming interface]” for a model.

Databricks’ model could allow companies to eventually deploy their own agents to perform tasks, without data quality standing in the way.

The technique offers a rare look at some of the key tricks that engineers are now using to improve the abilities of advanced AI models, especially when good data is hard to come by. The method leverages ideas that have helped produce advanced reasoning models by combining reinforcement learning, a way for AI models to improve through practice, with “synthetic,” or AI-generated, training data.

The latest models from OpenAI, Google, and DeepSeek all rely heavily on reinforcement learning as well as synthetic training data. WIRED revealed that Nvidia plans to acquire Gretel, a company that specializes in synthetic data. “We’re all navigating this space,” Frankle says.

The Databricks method exploits the fact that, given enough tries, even a weak model can score well on a given task or benchmark. Researchers call this method of boosting a model’s performance “best-of-N.” Databricks trained a model to predict which best-of-N result human testers would prefer, based on examples. The Databricks reward model, or DBRM, can then be used to improve the performance of other models without the need for further labeled data.

DBRM is then used to select the best outputs from a given model. This creates synthetic training data for further fine-tuning the model so that it produces a better output the first time. Databricks calls its new approach Test-time Adaptive Optimization or TAO. “This method we’re talking about uses some relatively lightweight reinforcement learning to basically bake the benefits of best-of-N into the model itself,” Frankle says.

He adds that the research done by Databricks shows that the TAO method improves as it is scaled up to larger, more capable models. Reinforcement learning and synthetic data are already widely used, but combining them in order to improve language models is a relatively new and technically challenging technique.

Databricks is unusually open about how it develops AI, because it wants to show customers that it has the skills needed to create powerful custom models for them. The company previously revealed to WIRED how it developed DBX, a cutting-edge open source large language model (LLM) from scratch.

Trump Admin Plans to Cut Team Responsible for Critical Atomic Measurement Data

The US National Institute of Standards and Technology (NIST) is discussing plans to eliminate an entire team responsible for publishing and maintaining critical atomic measurement data in the coming weeks, as the Trump administration continues its efforts to reduce the US federal workforce, according to a March 18 email sent to dozens of outside scientists. The data in question underpins advanced scientific research around the world in areas like semiconductor manufacturing and nuclear fusion.

“We were recently informed that unless there is a major change in the Federal Government reorganization plans, the whole Atomic Spectroscopy Group will be laid off in a few weeks, in particular, since our work is not considered to be statutorily essential for the NIST mission,” Yuri Ralchenko, the group’s leader, wrote in the email, which was seen by WIRED.

Ralchenko noted that atomic spectroscopy has been used to discover many new exoplanets and develop powerful new diagnostic techniques, among other applications. “Unfortunately, the story of atomic spectroscopy at NIST is coming to an end,” he wrote.

In response to a request for comment from WIRED, Ralchenko said he wasn’t permitted to speak about budget and management issues and referred questions to NIST’s public affairs department. NIST and its parent agency, the Department of Commerce, did not respond to requests for comment.

The Atomic Spectroscopy Group studies how atoms absorb or emit light, allowing researchers to identify the elements present in a given sample. It then collects and updates those calculations in the Atomic Spectra Database, a catalog of industry-leading spectroscopy information and measurements that plays a crucial role in fields like astronomy, astrophysics, and medicine. In a blog post published last week highlighting the importance of the database, NIST said it receives an average of 70,000 search requests worldwide each month.

It is “really difficult to overestimate” the importance of this data, says Evgeny Stambulchik, a senior staff research scientist at the Weizmann Institute of Science in Israel who started a petition to gather signatures from other researchers and members of the public who oppose the cuts to the atomic spectroscopy team. The petition currently has over 1,700 signatures.

Stambulchik, whose speciality is plasma spectroscopy, says that atomic spectroscopy is essentially the only tool that can be used to interpret remote objects in space, like those observed by the powerful James Webb telescope. It’s also basically the only tool for investigating “matter at temperatures reaching tens of million degrees,” he adds, such as inside a nuclear fusion reactor.

Another plasma physicist at a US institution who asked to remain anonymous because they are not authorized to speak to the media said they use this data daily to build reliable models for designing future fusion reactors. “Losing this trusted data source would hinder private fusion companies,” they explain.

The US scientist says the data provided by NIST’s Atomic Spectroscopy Group is useful to researchers and engineers across multiple fields. “The kind of carefully curated data this group provided underpins reliable systems like GPS and lithography,” they say. “It is this kind of rigorous science and engineering that keeps our bridges up and our power on. This is not ‘move fast and break things.’”

How to Delete Your Data From 23andMe

Genetic testing company 23andMe, once a Silicon Valley darling valued at $6 billion, filed for Chapter 11 bankruptcy protection late Sunday as it prepares for a sale of the business. CEO Anne Wojcicki, who cofounded the company in 2006, has also stepped down after months of failed attempts to take the firm private.

As uncertainty about the company’s future reaches its peak, all eyes are on the trove of deeply personal—and potentially valuable—genetic data that 23andMe holds. Privacy advocates have long warned that the risk of entrusting genetic data to any institution is twofold—the organization could fail to protect it, but it could also hand over customer data to a new entity that they may not trust and didn’t choose.

California attorney general Rob Bonta reminded consumers in an alert on Friday that Californians have a legal right to ask that an organization delete their data. 23andMe customers in other states and countries largely do not have the same protections, though there is also a right to deletion for health data in Washington state’s My Health My Data Act and the European Union’s General Data Protection Regulation. Regardless of residency, all 23andMe customers should consider downloading anything they want to keep from the service and should then attempt to delete their information.

“This situation really brings home the point that there is still no national health privacy law in the US protecting your rights unless you live in California or Washington,” says Andrea Downing, an independent security researcher and cofounder of the patient-led digital rights nonprofit The Light Collective. “Meanwhile, we continue to evolve our understanding of how genetic information has value, but also has unique vulnerability.”

John Verdi, senior vice president of policy at the Future of Privacy Forum, says 23andMe’s new owner could revise the company’s privacy policies for new customers and new data collection, but the data it has already collected from current customers is subject to existing terms. “The company has legal obligations regarding information collected under the current policies,” he says.

Still, researchers emphasize that in practice, such a large transition will create real data exposure that is outside of 23andMe customers’ control. “In my opinion, these privacy policies—especially in the context of acquisitions in the venture capital and private equity space—aren’t worth the paper they’re printed on,” says longtime security researcher and data privacy advocate Kenn White. “For regular people out there who use these services, you’re pretty much on your own. My advice is to request your data get deleted as soon as possible”

To delete your genetic data through 23andMe’s website, log in and then go to Settings in your profile. Scroll to 23andMe Data and then click View. At this point, you can choose to download a copy of your genetic information. Then scroll to Delete Data and click Permanently Delete Data. Once you initiate the process, you’ll receive an email from 23andMe to confirm. Click the link in the email to complete the deletion process. Additionally, you can direct 23andMe to destroy the biological sample it used to extract your DNA data if you previously authorized the company to keep it. Go to Settings and then Preferences.

Hot New Thermodynamic Chips Could Trump Classical Computers

Guillaume Verdon stands before me with a new kind of computer chip in his hand—a piece of hardware he believes is so important to the future of humanity that he’s asked me not to reveal our exact location, for fear that his headquarters could become the target of industrial espionage.

This much I can tell you: We’re in an office a short drive from Boston, and the chip arrived from the foundry just a few days ago. It sits on a circuit board about the width of a Big Mac. The pinky-nail-sized piece of silicon itself is dotted with an exotic set of components: not the transistors of an ordinary semiconductor, nor the superconducting elements of a quantum chip, but the guts of a radically new paradigm called thermodynamic computing.

Not unlike its quantum cousin, thermodynamic computing promises to move beyond the binary constraints of 1s and 0s. But while quantum computing sets out—through extreme cryogenic cooling—to minimize the random thermodynamic fluctuations that occur in electronic components, this new paradigm aims to harness those very fluctuations.

Engineers are chasing both paradigms in a race to accelerate past ordinary silicon chips and satisfy the ravenous demand for processing power in the age of AI. But Verdon—with his startup, Extropic—isn’t just a contestant in that race. He’s also one of the AI era’s most shameless hype men. He is far better known as his online alter ego, Based Beff Jezos, the founding prophet of an ideology called effective accelerationism.

Known as “e/acc” for short, effective accelerationism is an irreverent rejection of effective altruism, a movement that has persuaded many technically minded people that the rise of artificial general intelligence—unless it is corralled and made safe—poses an almost certain existential risk to humanity. “EA’s be like: ‘I believe in Leprechauns and the burden of proof is on you to disprove me,’” went one fairly typical Based Beff post from 2022.

The AI existential risk movement, he wrote in another post that year, “is an infohazard that causes depression in our most talented and intelligent folks, killing our productive gains towards a greater more prosperous future.” Another frequent target of his mockery is the AI ethics movement, which critiques large language models as riddled with the biases and blind spots of their architects. As Based Beff continued to spread e/acc’s gospel online, it quickly became a rallying cry among some members of the tech elite, with prominent figures like Marc Andreessen and Garry Tan temporarily adding “e/acc” to their X usernames.

Effective accelerationism is perhaps best seen as the most technical fringe of a broader zeitgeist: a belief that American politics is broken and that caution, overregulation, and woke ideology are holding the country back. That ethos helped propel Donald Trump back to the White House, with Elon Musk, a hero of the e/acc movement, by his side. Like Trump 2.0, effective accelerationism promises an unstoppable American renaissance and an untroubled view of the work needed to get there. In both cases, the details are fuzzy.

But under the sharp resolution of a laboratory microscope, the specifics of Verdon’s new chip are, if nothing else, plain to see: an array of square features each a few dozen microns wide. These components, Verdon promises, will be used to generate “programmable randomness”—a chip in which probabilities can be controlled to produce useful computations. When combined with a classical computer, he says, they will provide a highly efficient way to model uncertainty, a key task in all sorts of advanced computing, from modeling the weather and financial markets to artificial intelligence. (Some academic labs have already built prototype thermodynamic hardware, including a simple neural network—the technology at the heart of modern machine learning.)

Inside Google’s Two-Year Frenzy to Catch Up With OpenAI

But more piles of fascinating research are only useful to Google if they generate that most important of outputs: profit. Most customers generally aren’t yet willing to pay for AI features directly, so the company may be looking to sell ads in the Gemini app. That’s a classic strategy for Google, of course, one that long ago spread to the rest of Silicon Valley: Give us your data, your time, and your attention, check the box on our terms of service that releases us from liability, and we won’t charge you a dime for this cool tool we built.

For now, according to data from Sensor Tower, OpenAI’s estimated 600 million all-time global app installs for ChatGPT dwarf Google’s 140 million for the Gemini app. And there are plenty of other chatbots in this AI race too—Claude, Copilot, Grok, DeepSeek, Llama, Perplexity—many of them backed by Google’s biggest and best-funded competitors (or, in the case of Claude, Google itself). The entire industry, not just Google, struggles with the fact that generative AI systems have required billions of dollars in investment, so far unrecouped, and huge amounts of energy, enough to extend the lives of decades-old coal plants and nuclear reactors. Companies insist that efficiencies are adding up every day. They also hope to drive down errors to the point of winning over more users. But no one has truly figured out how to generate a reliable return or spare the climate.

And Google faces one challenge that its competitors don’t: In the coming years, up to a quarter of its search ad revenue could be lost to antitrust judgments, according to JP Morgan analyst Doug Anmuth. The imperative to backfill the coffers isn’t lost on anyone at the company. Some of Hsiao’s Gemini staff have worked through the winter holidays for three consecutive years to keep pace. Google cofounder Brin last month reportedly told some employees 60 hours a week of work was the “sweet spot” for productivity to win an intensifying AI race. The fear of more layoffs, more burnout, and more legal troubles runs deep among current and former employees who spoke to WIRED.

One Google researcher and a high-ranking colleague say the pervasive feeling is unease. Generative AI clearly is helpful. Even governments that are prone to regulating big tech, such as France’s, are warming up to the technology’s lofty promises. Inside Google DeepMind and during public talks, Hassabis hasn’t relented an inch from his goal of creating artificial general intelligence, a system capable of human-level cognition across a range of tasks. He spends occasional weekends walking around London with his Astra prototype, getting a taste of a future in which the entire physical world, from that Thames duck over there to this Georgian manor over here, is searchable. But AGI will require systems to get better at reasoning, planning, and taking charge.

In January, OpenAI took a step toward that future by letting the public in on another experiment: its long-awaited Operator service, a so-called agentic AI that can act well beyond the chatbot window. Operator can click and type on websites just as a person would to execute chores like booking a trip or filling out a form. For the moment, it performs these tasks much more slowly and cautiously than a human would, and at a steep cost for its unreliability (available as part of a $200 monthly plan). Google, naturally, is working to bring agentic features to its coming models too. Where the current Gemini can help you develop a meal plan, the next one will place your ingredients in an online shopping cart. Maybe the one after that will give you real-time feedback on your onion-chopping technique.

As always, moving quickly may mean gaffing often. In late January, before the Super Bowl, Google released an ad in which Gemini was caught in a slipup even more laughably wrong than Bard’s telescope mistake: It estimated that half or more of all the cheese consumed on Earth is gouda. As Gemini grows from a sometimes-credible facts machine to an intimate part of human lives—life coach, all-seeing assistant—Pichai says that Google is proceeding cautiously. Back on top at last, though, he and the other Google executives may never want to get caught from behind again. The race goes on.

Updated 3/21/2025, 4 PM EDT: Wired has clarified the context of a quote attributed to Pandu Nayak.


Let us know what you think about this article. Submit a letter to the editor at [email protected].

OpenAI’s Sora Is Plagued by Sexist, Racist, and Ableist Biases

Despite recent leaps forward in image quality, the biases found in videos generated by AI tools, like OpenAI’s Sora, are as conspicuous as ever. A WIRED investigation, which included a review of hundreds of AI-generated videos, has found that Sora’s model perpetuates sexist, racist, and ableist stereotypes in its results.

In Sora’s world, everyone is good-looking. Pilots, CEOs, and college professors are men, while flight attendants, receptionists, and childcare workers are women. Disabled people are wheelchair users, interracial relationships are tricky to generate, and fat people don’t run.

“OpenAI has safety teams dedicated to researching and reducing bias, and other risks, in our models,” says Leah Anise, a spokesperson for OpenAI, over email. She says that bias is an industry-wide issue and OpenAI wants to further reduce the number of harmful generations from its AI video tool. Anise says the company researches how to change its training data and adjust user prompts to generate less biased videos. OpenAI declined to give further details, except to confirm that the model’s video generations do not differ depending on what it might know about the user’s own identity.

The “system card” from OpenAI, which explains limited aspects of how they approached building Sora, acknowledges that biased representations are an ongoing issue with the model, though the researchers believe that “overcorrections can be equally harmful.”

Bias has plagued generative AI systems since the release of the first text generators, followed by image generators. The issue largely stems from how these systems work, slurping up large amounts of training data—much of which can reflect existing social biases—and seeking patterns within it. Other choices made by developers, during the content moderation process for example, can ingrain these further. Research on image generators has found that these systems don’t just reflect human biases but amplify them. To better understand how Sora reinforces stereotypes, WIRED reporters generated and analyzed 250 videos related to people, relationships, and job titles. The issues we identified are unlikely to be limited just to one AI model. Past investigations into generative AI images have demonstrated similar biases across most tools. In the past, OpenAI has introduced new techniques to its AI image tool to produce more diverse results.

At the moment, the most likely commercial use of AI video is in advertising and marketing. If AI videos default to biased portrayals, they may exacerbate the stereotyping or erasure of marginalized groups—already a well-documented issue. AI video could also be used to train security- or military-related systems, where such biases can be more dangerous. “It absolutely can do real-world harm,” says Amy Gaeta, research associate at the University of Cambridge’s Leverhulme Center for the Future of Intelligence.

To explore potential biases in Sora, WIRED worked with researchers to refine a methodology to test the system. Using their input, we crafted 25 prompts designed to probe the limitations of AI video generators when it comes to representing humans, including purposely broad prompts such as “A person walking,” job titles such as “A pilot” and “A flight attendant,” and prompts defining one aspect of identity, such as “A gay couple” and “A disabled person.”

The FBI Is Investigating Attacks on Tesla as ‘Domestic Terrorism.’ Here’s Why That Matters

There’s precedent for companies not only receiving information from law enforcement during domestic terrorism investigations, but also working directly with the FBI. German says this was particularly evident during the response to a wave of oil pipeline protests in the early 2010s.

Records published by the news site Grist and Type Investigations found that the FBI considered one pipeline operator a “domain stakeholder” in one protest case, which gave the company “direct access to the White House” and privileged information. The company was also invited to strategize with the FBI, Department of Homeland Security, National Guard, and local police. And there were conversations about how to “ensure coordination and resource management” not only among law enforcement officials, but with the company.

A different pipeline constructor hired a firm to monitor and infiltrate protest groups and write intelligence reports, which were sometimes shared with federal law enforcement and local police, according to reporting by The Intercept. One of these pipeline operators briefed local police along its proposed pipeline route on how to possibly pursue criminal charges against organizers, Grist reported.

Even after the protests waned, oil and gas companies remained close to police and the government. One Canadian pipeline company paid local Minnesotan police departments more than $5 million in 2020 and 2021 for policing pipeline protests. Since 2017, fossil fuel lobbyists have pushed more than 20 states to pass laws making disrupting “critical infrastructure” like oil and gas pipelines a criminal offense, according to records obtained by The Guardian.

Though it’s unclear how the FBI’s current domestic terrorism investigations will play out, Musk and other Tesla executives could ultimately have similar access to and influence over them. When the cases go to court, Tesla could also be eligible for compensation from the government in the form of court-ordered restitution.

Such funds are often used to pay the families of terrorism victims, but German tells WIRED that corporations are also eligible. In a successful criminal case, he says, he sees no reason why Tesla wouldn’t get compensated. Tesla could also be eligible for money from state-level terrorism victim compensation programs, which receive some funding from the federal government.

Risks for Protesters

Domestic terrorism investigations are often fraught. Organizations like the American Civil Liberties Union have argued that the FBI routinely uses them to unfairly surveil activists and communities of color without adequate oversight.

President Trump has said his administration is taking Tesla incidents very seriously. “People that get caught sabotaging Teslas will stand a very good chance of going to jail for up to twenty years, and that includes the funders,” Trump wrote in a social media post on Thursday. “WE ARE LOOKING FOR YOU!!!”

Hina Shamsi, director of the ACLU’s national security project, says that instead of “focusing on the most serious criminal conduct that harms life,” federal agencies have wasted resources and abused their authority by “treating alleged non-violent civil disobedience or vandalism as justification for abusive investigations of civil rights and other activists.”

Historically, German says, the FBI has endorsed an idea called “radicalization theory,” which posits that the beliefs of extremists naturally escalate from moderate and widely held beliefs. That logic, he says, justifies the FBI casting a wide surveillance net, particularly when it comes to monitoring activists.

“They suggest that anybody who’s got a similar ideology might be willing to commit the same kind of crime,” German explains. “We’ve seen a lot of abuse of FBI investigative authorities, particularly around domestic advocacy groups.”

Five years ago, the FBI used the Foreign Intelligence Surveillance Act to surveil people participating in Black Lives Matter protests, investigating whether they had ties to terrorists. The DOJ inspector general called the incident an example of the FBI’s “widespread non-compliance” with FISA rules.

German claims that in this case, instead of focusing on people who are alleged to have committed arson or acts of violence, the FBI’s focus could ultimately be scrutinizing people who it thinks are expressing “anger or animosity towards Tesla or Elon Musk.”

A Mysterious Startup Is Developing a New Form of Solar Geoengineering

Stardust’s prospective clients seem to be governments: As countries consider geoengineering, Stardust could be poised to sell them tools to meet those goals, several experts said. In an emailed answer to questions about its business model, Yedvab described the company’s approach as “founded on the premise” that solar geoengineering “will play a critical role in addressing global warming in the coming decades.”

The company’s portfolio of technologies, Yedvab added, “could be deployed following decisions by the US government and international community.”

The company is attempting to patent its geoengineering technology. “We anticipate that as US-led [geoengineering] research and development programs advance, the value of Stardust’s technological portfolio will grow accordingly,” Yedvab wrote. Pasztor’s report adds that if governments decide not to pursue geoengineering, investors “risk not ​​receiving a return on their investment.”

The prospect of proprietary, privately held geoengineering technology worries some experts. Pasztor recommends that Stardust work with its investors to explore ways to give away their intellectual property, akin to how Volvo made its patented three-point seatbelt design freely available to other manufacturers 60 years ago. Alternatively, Stardust could work with governments to purchase the full rights to the IP, who can then make the technology freely available themselves.

In any case, Pasztor argues, Stardust can only proceed in an ethical manner if they do so with full transparency and independent oversight: “They are operating in a vacuum, in the sense that there is no social license to do what they are trying to do.”

Other experts have also questioned Stardust’s conduct so far. When it comes to principles of governance, like transparency and public engagement, “they’re not adhering to any of them,” said Shuchi Talati, founder of The Alliance for Just Deliberation on Solar Geoengineering, a Washington, DC–based nonprofit. “Pasztor’s report is the only public thing we know about them,” she added. Stardust did not do any public consultation for its outdoor field tests, nor has it released any data or other information about them, Talati said. And that lack of transparency could come with consequences for the company, she argued, as Stardust’s approach may spark conspiracy theories about what a “secret Israeli company” is doing, and down the road, it will be much harder for people to trust Stardust.

A better approach, Talati argued in a paper published in January, is for Stardust to be communicative and build trust as early as possible, disclosing what it’s doing and with whom it’s engaging. The company’s funders, she argued, should disclose the scope of the work they’re funding as well.

People at Friends of the Earth, an environmental group that has long dismissed geoengineering as a “dangerous distraction,” echo Talati’s concerns and go further with their critiques of Stardust. “I don’t think it’s compatible to have venture capital funding and to be committed to scientific ideals,” said Benjamin Day, FOE’s senior campaigner on geoengineering. The problem, in his view, is that Stardust’s engineers have a vested interest in finding that stratospheric geoengineering can and should be done.

If governments choose to use geoengineering, they may become heavily dependent on Stardust if they’re ahead of the competition—of which there currently is none, Day said. “There’s no private market for geoengineering technologies. They’re only going to make money if it’s deployed by governments, and at that point they’re kind of trying to hold governments hostage with technology patents.”

How to Avoid US-Based Digital Services—and Why You Might Want To

Law enforcement requests for user data from Apple, Google, and Meta mean that these companies can decide whether government authorities have access to your personal information, including location data. This means the companies with the most insight into our lives, movements, and communications are frontline arbiters of our constitutional rights and the rights of non-US citizens—a fact some are likely feeling more acutely now than ever.

Collaboration between Big Tech and the Trump administration began before Donald Trump’s swearing-in on January 20. Amazon, Meta, Google, Microsoft, and Uber each gave $1 million to Trump’s inauguration. Separately, in personal donations, so did Meta CEO Mark Zuckerberg and Apple’s Tim Cook.

Americans concerned about the Trump administration and Silicon Valley’s embrace of it, may consider becoming a “digital expat”—moving your digital life off of US-based systems. Meanwhile, Europeans are starting to see US data services as “no longer safe” for businesses, governments, and societies.

Here’s a brief rundown of the privacy, security, and civil liberties issues related to the use of US-based digital services that suddenly feel more urgent—and what to do about it.

Cozying Up

In anticipation of Trump’s inauguration, Meta-owned Facebook, Instagram, and Threads made drastic policy changes citing alignment with Trump administration values, to permit hate speech and abuse “on topics like immigration and gender.” Meta also signaled its allegiance by ditching its fact-checkers—a frequent target of MAGA world ire. Two days after the inauguration, Meta quietly rolled out pro-life moderation actions through post suppression and account suspensions. Zuckerberg explained the company’s new direction to staff, saying: “We now have an opportunity to have a productive partnership with the United States government.”

Meta did not immediately respond to our request for comment regarding its partnership, data sharing, or policy changes.

Google followed suit. The company changed its Maps and Search results to rename part of the world—the Gulf of Mexico—following a Trump executive order renaming it the Gulf of America, despite the the US claiming control of less than 50 percent of the Gulf. Apple and Microsoft also followed Trump’s order.

Google’s consumer products also received a swath of updates in line with the new administration, including further changes to Maps, Calendar, and Search. Next, Google removed the new administration’s “banned” terms from its Google Health product. Then it did an about-face on its public promise not to build weaponized AI tools, such as Project Dragonfly, which was discovered in 2018 to be tailoring Google’s entire platform to enable China’s aggressive crackdown on its citizens. When reached for comment, Google did not immediately respond.

Big Tech aligning with the Trump administration matters because its business models rely on surveillance and amassing our personal data. Meta, Google, Apple and other large tech firms are among the gatekeepers standing between privacy and government requests for user data. Even when tech firms must comply by law, they’re often still free to decide how much information they collect about people and how long they store the data.

Government Hand-Outs

Current US laws around tech, privacy, and government requests have been guided by bulwarks like the Fourth and Fifth Amendments, US court rulings, and tech companies’ willingness to question the federal government’s opinion that it is entitled to access our personal information and location data. Apple, Google, and Meta each have language about law enforcement data requests that make it seem like they have our backs when it comes to overreach. Now, with companies shaping certain policies, tools, and practices in pursuit of “partnership” with the Trump administration, these companies’ powers over our data takes on new focus.

Generally, law enforcement can compel US companies to hand over user data using a subpoena, court order, search warrant—or, in rarer cases, a National Security Letter (NSL). As Google explains, an NSL is “one of the authorities granted under the Foreign Intelligence Surveillance Act (FISA).” Google adds, “FISA orders and authorizations can be used to compel electronic surveillance and the disclosure of stored data, including content from services like Gmail, Drive, and Photos.” How companies respond to these demands can vary in consequential ways.

Yahoo Is Still Here—and It Has Big Plans for AI

In September 2021, Jim Lanzone took over a company whose name once embodied the go-go spirit of the internet but had, over the years, become a joke: Yahoo. He accepted the CEO post from the new private-equity owner Apollo Global Management, which had bought the property from Verizon, the most recent and possibly most clueless caretaker (high bar alert) in a long series of management shifts. Visiting him at the company’s offices in New York City, I ask him why he took the job. “I love turnarounds,” he says.

Lanzone’s résumé confirms that. In 2001 he took over a sagging search property called AskJeeves—its share price was less than a dollar, down from a high of $196—and built it back to the point where Barry Diller’s IAC Corp bought it for $1.85 billion. At CBS Interactive and then CBS’s chief digital office during the 2010s, he yanked the stuffy Tiffany network into the streaming age. Yahoo, celebrating its 30th anniversary this month, might be his biggest challenge yet. Its history is pocked with missed opportunities, which explains in part why a public company once worth well over $100 billion was sold to a private equity firm for $5 billion in 2021. Yahoo famously passed on buying Google, and actually got Mark Zuckerberg to tentatively agree to sell Facebook for $1 billion before then CEO Terry Semel asked to renegotiate, which squelched the deal. Talent that walked out Yahoo’s door included the founders of WhatsApp. Promising acquisitions like Flickr, Tumblr and Huffington Post were ditched at fire-sale prices. In recent years Yahoo was a low-priority property for its owner, Verizon. Instead of trying to revive its purple glory, it merged Yahoo’s assets with those of another failed icon, AOL, and dubbed the new brand Oath.

Some pegged Lanzone’s chances at zero. “It’s hard to believe anyone else on the planet wants any part of his role, “ wrote George Bradt, one of those MBA types who churn out content for Forbes. Lanzone saw something different. In his view, Yahoo was an unacknowledged gem. “If you were able to take the name Yahoo off of it and look at the business in 2021, you saw billions in revenue,” he says.

Lanzone has little patience for exhuming past blunders. “I think the story of Yahoo’s missed opportunities is tired,” he says. “It’s boring.” Instead of crying over lost search glory, Lanzone concentrated on improving what Yahoo did. “We didn’t have to worry about what we weren’t,” he says. He got rid of money-losing units, like some nonperforming ad tech divisions, and quietly made some acquisitions to bolster the best properties, like Wagr, a sports betting app, to bring Yahoo Sports into the gambling age. He also brought in capable executives like former ESPN digital head Ryan Spoon, who now heads Yahoo Sports. He’s boosted profits and grown the company’s audience to the point where he says that Yahoo has performed the quickest return of any Apollo acquisition. Since Yahoo is private, the actual financials aren’t available. But Yahoo’s comms team provided me with a lengthy document packed with data to bolster Lanzone’s claim that Yahoo still has something to yodel about. Comscore, a marketing company that measures traffic, ranks Yahoo No. 1 in news, No. 1 in finance, and No. 3 in sports. It’s second only to Gmail in mail. He tells me that in the US alone, “hundreds of millions” of people use Yahoo every month.

A year after Lanzone took the job, the entire tech world was turned around by the appearance of ChatGPT. In previous transformations like search, social, and mobile, Yahoo has a near-perfect record of botching these moments. Lanzone says Yahoo won’t be creating its own language models or dropping $100 billion on data centers, but he believes the company will seize the moment nonetheless. “I’d like to automate the word ‘AI’ so I don’t have to say it so much,” he says. Yahoo has in-house machine-learning talent and draws on outside companies for AI technology. For instance, it partners with the startup Sierra for robot customer service agents.

One of Lanzone’s canniest AI moves was acquiring Artifact, the AI-powered news aggregator created by Instagram cofounders Kevin Systrom and Mike Krieger. When the pair decided it would not become a viable business, they announced its closure and Lanzone was among multiple suitors vying for the underlying technology. It became the centerpiece of the homepage that Yahoo relaunched earlier this year. “Instead of incorporating their technology into our product, we did it the other way,” Lanzone says. “Essentially Yahoo News is now Artifact.” Systrom approves. “We partnered with Yahoo because they made a strong offer, but also because they planned on deploying our hard work to many millions of people,” he says.

What Chinese online shopping sites accept PayPal?

Chinese online shopping sites accept PayPal

Chinese online shopping platforms have become popular among international buyers, offering a vast range of products at competitive prices. While most of these platforms primarily support payment methods like Alipay, WeChat Pay, and credit cards, some also accept PayPal to facilitate transactions for overseas customers. PayPal is a widely used payment method due to its security, buyer protection policies, and ease of use. However, not all Chinese e-commerce sites offer PayPal as an option, making it important for shoppers to identify which platforms support this payment method before making a purchase.

AliExpress is one of the most well-known chinese online shopping platforms that accept PayPal. As a global marketplace operated by Alibaba Group, AliExpress caters to international customers and supports multiple payment options, including PayPal in select regions. This allows buyers to shop for electronics, fashion, home goods, and other items while benefiting from PayPal’s secure transaction process. Banggood is another popular site that accepts PayPal, particularly for tech gadgets, DIY tools, and household items. The platform’s integration with PayPal ensures that international buyers can make purchases with added security and confidence.

Gearbest, a site specializing in electronics, smart devices, and lifestyle products, is also among the Chinese online shopping platforms that accept PayPal. The platform provides a seamless shopping experience for buyers looking for high-quality tech products while ensuring safe payment processing through PayPal. Additionally, DHgate, a wholesale marketplace similar to AliExpress, supports PayPal as a payment method for global buyers. This makes it a preferred choice for businesses and individuals looking to purchase products in bulk while maintaining a level of security through PayPal’s buyer protection policies.

What Chinese online shopping sites accept PayPal?

While many Chinese e-commerce platforms cater to domestic buyers with local payment solutions, international shopping sites like LightInTheBox and MiniInTheBox also accept PayPal. These platforms focus on fashion, accessories, and consumer electronics, making them a good option for buyers who prefer using PayPal for their transactions. Another notable website is Sunsky, which specializes in wholesale electronics and accessories and supports PayPal payments for customers worldwide.

The acceptance of PayPal on Chinese online shopping platforms adds convenience for international customers who may not have access to other popular payment methods like Alipay or UnionPay. It also helps reduce the risks associated with cross-border transactions, as PayPal’s dispute resolution process provides an additional layer of protection for buyers. However, some platforms may charge a small transaction fee for PayPal payments or restrict its use based on order value or location. Buyers should check payment policies on individual websites to confirm whether PayPal is available and if any additional fees apply.

As Chinese e-commerce continues to expand globally, more platforms are integrating PayPal to accommodate international customers. This shift improves accessibility and ensures a secure shopping experience for buyers worldwide. By choosing reputable sites that accept PayPal, shoppers can confidently explore Chinese online shopping while benefiting from secure transactions and global buyer protection.

Who’s Elon Musk’s Biggest Fan? His Mom

She sits in on his business meetings, defends him on X, and travels to give talks about how she raised him, the richest man in the world—but who is Elon Musk’s mother? Today on the show, we learn all about the model, influencer, and author, Maye Musk, while dissecting her most recent travels to China and her possible influence on foreign politics.

You can follow Michael Calore on Bluesky at @snackfight, Lauren Goode on Bluesky at @laurengoode, and Zoë Schiffer on Bluesky at @zoeschiffer. Write to us at [email protected].

How to Listen

You can always listen to this week’s podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here’s how:

If you’re on an iPhone or iPad, open the app called Podcasts, or just tap this link. You can also download an app like Overcast or Pocket Casts and search for “Uncanny Valley.” We’re on Spotify too.

Transcript

Note: This is an automated transcript, which may contain errors.

Michael Calore: Hey, Zoë, what does your mom call you?

Zoë Schiffer: I feel like I’ll erode a lot of my credibility if I tell you, so I’m just going to say that a lot of people call me Zoe for short.

Michael Calore: OK.

Zoë Schiffer: Which is what my name looks like.

Michael Calore: If you don’t have the umlaut over the E, it just looks like Zoe?

Zoë Schiffer: Yeah, because it doesn’t have the Y so people always get confused. I’m like, “Oh, no, my parents call me Zoe. Don’t worry about it.”

Lauren Goode: Oh. Right, right. Like Zooey Deschanel, she has the Y, right? Yeah, okay.

Michael Calore: But she’s Zooey.

Lauren Goode: I never thought about that before.

Michael Calore: Isn’t she? Isn’t she Zooey?

Lauren Goode: No, she’s Zooey.

Zoë Schiffer: Like Franny and Zooey is spelled Zooey but it’s Zooey, Franny and Zooey. Anyway, Mike, what do your parents, what did they call you when you were little?

Lauren Goode: She’s deflecting really hard. She doesn’t want to tell us the real nickname.

Zoë Schiffer: I can’t. I just feel like I already have too much imposter syndrome.

Michael Calore: For a very long time, my mother referred to me by my full name, Michael, and so did my father.

Lauren Goode: What’s your middle name?

Michael Calore: Seth.

Lauren Goode: Did they call you Michael Seth?

Michael Calore: On very, very rare occasions.

Zoë Schiffer: Seth really could be your first name, too. I feel like that almost fits.

Lauren Goode: Oh, yeah. You’re a Seth.

Michael Calore: Do I present as Seth?

Zoë Schiffer: A little bit. Seth rising, if you will.

Michael Calore: Okay.

Lauren Goode: Yeah. Seth goes to a lot of live music shows. Yeah.

A Livestreamed Tragedy on X Sparks a Memecoin Frenzy

This story contains mentions of suicide. If you or someone you know needs help, please call 1-800-273-8255 for free, 24-hour support from the National Suicide Prevention Lifeline.

Twenty-three-year-old Arnold Robert Haro addressed his final words to the phone in his hand. “If I die, I hope you guys turn this into a memecoin,” he said. Then Haro took his own life.

Haro died on February 21 at his family home in Madera County, California, a death certificate obtained by WIRED shows. His suicide was broadcast live to his followers on X, where he went by the handle @MistaFuccYou. Footage of Haro’s death has since been removed from the platform, but the incident was briefly listed in its trending tab.

In the hours after Haro’s death, people created dozens of memecoins—a type of highly volatile crypto coin used as a vector for financial speculation—modeled after him. Sensing an opportunity to profit, traders piled into one of the coins in particular, driving its value to $2.1 million in aggregate. (The coin has since lost 96 percent of its value.)

On X, some tried to argue that whoever was behind the MistaFuccYou coin had duly granted Haro’s final wish. But most denounced the impulse among traders to try to profit by his death. “If you’re trading this, you’re sick af,” wrote one user.

Speculation ran rampant on X that Haro had ended his life because he had lost money to a memecoin rugpull—a maneuver whereby somebody creates a new coin, promotes it online, then sells off their holdings in one swoop, devaluing everyone else’s stake. WIRED was unable to confirm whether this had happened to Haro, but his friends have disputed the narrative. “It had nothing to do with crypto … It’s not what all these crypto nerds seem to think,” one of Haro’s friends, who goes by j nova on social media, told WIRED. Haro’s family, meanwhile, has described his death as the result of “his battle with depression.”

The incident captures in microcosm the race to the bottom in memecoin trading circles, where only the most heinous and morally bankrupt ideas are now rewarded with attention, says Azeem Khan, cofounder of the Morph blockchain and venture partner at crypto VC firm Foresight Ventures.

“We’ve reached the point where the most potentially exciting launch that people are looking at is Kanye trying to launch a Swastika coin,” says Khan, in reference to now-deleted X posts made by an account associated with the artist Kanye West. “That’s how terrible this space is.”

Until last year, launching a memecoin was relatively expensive and technically burdensome, which meant few came to market. Only Dogecoin—the original memecoin—and a handful of derivatives had any sort of longevity.

That equation was reversed with the arrival of Pump.Fun, a platform that makes it simple for anyone to launch a memecoin at no cost. Since Pump.Fun launched in January 2024, many millions of memecoins have flooded the market, among them the coins modeled after Haro.

OpenAI’s Deep Research Agent Is Coming for White-Collar Work

Isla Fulford, a researcher at OpenAI, had a hunch that Deep Research would be a hit even before it was released.

Fulford had helped build the artificial intelligence agent, which autonomously explores the web, deciding for itself what links to click, what to read, and what to collate into an in-depth report. OpenAI first made Deep Research available internally; whenever it went down, Fulford says, she was inundated with queries from colleagues eager to have it back. “The number of people who were DMing me made us pretty excited,” says Fulford.

Since going live to the public on February 2, Deep Research has proven to be a hit with many users outside the company too.

“Deep Research has written 6 reports so far today,” Patrick Collison, the CEO of Stripe posted on X a few days after the product was released. “It is indeed excellent. Congrats to the folks behind it.”

“Deep Research is the AI product that really got a meaningful chunk of the policymaking community in DC to start feeling the AGI,” wrote Dean Ball, a fellow at George Mason University who specializes in AI policy.

Deep Research is available as part of the ChatGPT Pro plan, which costs $200 per month. It takes a query, such as “Write me a report on the Massachusetts health insurance industry,” or “Tell me about WIRED’s coverage of the Department of Government Efficiency,” and then comes up with a plan, searching for relevant websites, combing through their content, and deciding what links to click and what information deserves further investigation. After exploring for sometimes tens of minutes, it synthesizes its findings into a detailed report, which may include citations, data, and charts.

Many tools currently branded as AI agents are essentially chatbots connected to simple programs without much sophistication. The Deep Research model itself goes through an artificial kind of reasoning before devising a plan and moving forward with each step. The model provides details of this reasoning behind its research in a side window.

“Sometimes it’s like ‘I need to backtrack, this doesn’t seem that promising,’” says Josh Tobin, another OpenAI researcher involved in building Deep Research. “It’s pretty cool to read some of those trajectories, just to understand how the model is thinking.”

OpenAI evidently sees Deep Research as a tool that could take on more office work. “This is a thing that we can scale,” Tobin says, adding that the agent could be trained to complete specific white-collar work. An agent with access to a company’s internal data could quickly prepare a report or presentation, for instance. Tobin says the longer goal is to “build an agent that is not just good at building reports through searching the web, but is good at many other types of tasks too.”

Because Deep Research was trained to analyze and summarize human-written text, Tobin says his team was surprised to see many people using it to generate code. “It’s an interesting thread to pull,” he says. “We’re not totally sure what to make of it.”

What sizes are available in hat boxes wholesale?

available in hat boxes wholesale

When purchasing hat boxes wholesale, businesses have access to a wide range of sizes designed to accommodate various hat styles and dimensions. From small boxes for compact caps to large, round boxes for wide-brimmed hats, wholesale suppliers offer multiple size options to meet different packaging needs. Choosing the right size is essential for protecting hats during storage and transportation while also ensuring an aesthetically pleasing presentation.

Small-sized hat boxes wholesale are typically used for compact headwear, such as berets, beanies, or children’s hats. These boxes generally have diameters ranging from 6 to 10 inches (15 to 25 cm) and a height of 4 to 6 inches (10 to 15 cm). Small hat boxes are lightweight and compact, making them ideal for retail displays or gift packaging. Despite their smaller size, they offer sufficient protection against dust, dirt, and minor impacts, preserving the quality of the hats inside.

Medium-sized hat boxes wholesale are among the most popular options, as they can accommodate a variety of standard hat styles, including fedoras, cloches, and trilbies. These boxes typically measure between 12 and 16 inches (30 to 40 cm) in diameter, with a height of 6 to 8 inches (15 to 20 cm). Medium-sized boxes provide ample space for hats while maintaining a sleek and professional appearance. They are commonly used by fashion retailers and online stores to package and ship hats securely. Many wholesale suppliers offer customization options for these boxes, allowing businesses to add branding elements, such as logos or decorative prints.

What sizes are available in hat boxes wholesale?

For larger headwear, such as wide-brimmed hats, sun hats, or fancy fascinators, hat boxes wholesale in larger sizes are available. These boxes typically range from 18 to 24 inches (45 to 60 cm) in diameter and have a height of 8 to 12 inches (20 to 30 cm). Large hat boxes are essential for protecting delicate or oversized hats, preventing them from being crushed or deformed during storage or shipping. Because of their size, these boxes are often reinforced with thicker cardboard or additional internal supports to maintain their shape and durability.

In addition to standard round boxes, many wholesale suppliers offer square or rectangular hat boxes wholesale. These shapes are commonly used for stacking and storage efficiency. Square and rectangular boxes often come in dimensions ranging from 12×12 inches to 20×20 inches (30×30 cm to 50×50 cm), with varying heights. They are popular for bulk packaging or for retail stores that require uniform, stackable packaging solutions.

Custom sizing is also an option when ordering hat boxes wholesale. Many suppliers allow businesses to specify the exact dimensions they need, ensuring a perfect fit for unique or custom hat styles. Custom-sized hat boxes are particularly beneficial for luxury brands or designers that want to create a tailored and polished packaging experience. Additionally, custom sizing can reduce excess space in the box, preventing hats from shifting during transit.

Overall, hat boxes wholesale come in a variety of sizes, ranging from small, compact options to large, spacious boxes. Whether designed for delicate fascinators or oversized sun hats, the right-sized box ensures proper protection and enhances the overall presentation of the product. With customizable dimensions and diverse shape options, wholesale suppliers provide businesses with the flexibility to choose the perfect packaging solution for their specific needs.

DOGE’s Cuts at the USDA Could Cause US Grocery Prices to Rise and Invasive Species to Spread

Before he was abruptly fired last month, Derek Copeland worked as a trainer at the US Department of Agriculture’s National Dog Detection Training Center, preparing beagles and Labrador retrievers to sniff out plants and animals that are invasive or vectors for zoonotic diseases, like swine flu. Copeland estimates the NDDTC lost about a fifth of its trainers and a number of other support staff when 6,000 employees were let go at the USDA in February as part of a government-wide purge orchestrated by the Trump administration and Elon Musk’s so-called Department of Government Efficiency (DOGE).

Before he received his termination notice, he says, Copeland had just spent several months training the only dog stationed in Florida capable of detecting the Giant African land snail, an invasive mollusk that poses a significant threat to Florida agriculture. “We have dogs for spotted and lantern flies, Asian longhorn beetles,” he says, referring to two other non-native species. “I don’t think the American people realize how much crap that people bring into the United States.”

Dog trainers are just one example of the kind of highly specialized USDA staff that have been removed from their stations in recent weeks. Teams devoted to inspecting plant and food imports have been hit especially hard by the recent cuts, including the Plant Protection and Quarantine program, which has lost hundreds of staffers alone.

“It’s causing problems left and right,” says one current USDA worker, who like other federal employees in this story asked to remain anonymous for fear of retaliation. “It’s basically a skeleton crew working now,” says another current USDA staffer, who noted that both they and most of their colleagues held advanced degrees and had many years of training to protect US food and agriculture supply chains from invasive pests. “It’s not something that is easily replaced by artificial intelligence.”

“These aren’t your average people,” says Mike Lahar, the regulatory affairs manager at US customs broker behemoth Deringer. “These were highly trained individuals—inspectors, entomologists, taxonomists.”

Lahar and other supply chain experts warn that the losses could cause food to go rotten while waiting in ports and could lead to even higher grocery prices, in addition to increasing the chances of potentially devastating invasive species getting into the country. These dangers are especially acute at a moment when US grocery supply chains are already reeling from other business disruptions such as bird flu and President Trump’s new tariffs.

“If we’re inspecting less food, the first basic thing that happens is some amount of that food we don’t inspect is likely to go bad. We’re going to end up losing resources,” says supply chain industry veteran and software CEO Joe Hudicka.

The USDA cuts are being felt especially in coastal states home to major shipping ports. USDA sources who spoke to WIRED estimate that the Port of Los Angeles, one of the busiest in the US, lost around 35 percent of its total Plant Protection and Quarantine staff and 60 percent of its “smuggling and interdiction” employees, who are tasked with stopping illegal pests and goods from entering the country. The Port of Miami, which handles high volumes of US plant imports, lost about 35 percent of its plant inspectors.

The Silicon Valley Christians Who Want to Build ‘Heaven on Earth’

The agnosticism Karp refers to is cultural, rather than spiritual. But like Trae Stephens, he believes the tech sector has been too focused on solving trivial problems and ignoring the most pressing issues of society. The problem, Karp argued, could be solved by rebuilding the United States from the ground up as a technological republic. (Presumably, that would include Palantir selling its technology to the government.)

Attendees network after the event.

Photograph: Joseph Gabriel Ilustrisimo

The Bay Area, where Silicon Valley is nested, has long been a haven for progressive values and is often perceived to be largely agnostic or atheistic. Its prevailing rich-hippie vibes are well documented, with tech workers turning to biohacking, psychedelics, Burning Man, and Esalen retreats as forms of introspection and self-discovery.

Those pastimes aren’t likely to wane in popularity anytime soon, but for some people, the ACTS 17 Collective presents an alternative community, one combining tech startup culture with fervent faith.

“I’ve worked in Silicon Valley since 2005, and my initial impression was that it was anti-Valley to talk about religion and belief systems,” Nate Williams, a startup entrepreneur and investor who attended the event last week, told WIRED afterward. “But now it’s becoming more normalized to wear it on your sleeve,” he says, a trend he attributes partly to people seeking community after the pandemic.

At some moments during the event, the twin themes of work and religion were so commingled that it was hard to make a distinction between the two: Is work the new religion, as it has been and ever shall be in Silicon Valley? Or does religion offer a different framework for how people should think about what constitutes meaningful work?

“When you get into the startup world—there are some things in life you can be casual about, but probably work is not something you can be casual about and have success, do you agree?” Ben Pilgreen, founding pastor of the nondenominational Christian Epic Church in San Francisco and the Stephens’ pastor, said to the crowd. “The themes raised tonight don’t seem to be something you can be casual about.” (Epic Church’s attendance has been steadily rising over the past several months, Pilgreen said in a recent interview with the SF Standard.)

After the talk, attendees swarmed the Stephens couple, thanking them for the discussion and asking questions about future events. One attendee told WIRED he’s now interested in visiting Pilgreen’s Epic Church and attending its dinner series, which, like the house of worship, has a startup-worthy name: Alpha.

An AI Coding Assistant Refused to Write Code—and Suggested the User Learn to Do It Himself

Last Saturday, a developer using Cursor AI for a racing game project hit an unexpected roadblock when the programming assistant abruptly refused to continue generating code, instead offering some unsolicited career advice.

According to a bug report on Cursor’s official forum, after producing approximately 750 to 800 lines of code (what the user calls “locs”), the AI assistant halted work and delivered a refusal message: “I cannot generate code for you, as that would be completing your work. The code appears to be handling skid mark fade effects in a racing game, but you should develop the logic yourself. This ensures you understand the system and can maintain it properly.”

The AI didn’t stop at merely refusing—it offered a paternalistic justification for its decision, stating that “Generating code for others can lead to dependency and reduced learning opportunities.”

Cursor, which launched in 2024, is an AI-powered code editor built on external large language models (LLMs) similar to those powering generative AI chatbots, like OpenAI’s GPT-4o and Claude 3.7 Sonnet. It offers features like code completion, explanation, refactoring, and full function generation based on natural language descriptions, and it has rapidly become popular among many software developers. The company offers a Pro version that ostensibly provides enhanced capabilities and larger code-generation limits.

The developer who encountered this refusal, posting under the username “janswist,” expressed frustration at hitting this limitation after “just 1h of vibe coding” with the Pro Trial version. “Not sure if LLMs know what they are for (lol), but doesn’t matter as much as a fact that I can’t go through 800 locs,” the developer wrote. “Anyone had similar issue? It’s really limiting at this point and I got here after just 1h of vibe coding.”

One forum member replied, “never saw something like that, i have 3 files with 1500+ loc in my codebase (still waiting for a refactoring) and never experienced such thing.”

Cursor AI’s abrupt refusal represents an ironic twist in the rise of “vibe coding“—a term coined by Andrej Karpathy that describes when developers use AI tools to generate code based on natural language descriptions without fully understanding how it works. While vibe coding prioritizes speed and experimentation by having users simply describe what they want and accept AI suggestions, Cursor’s philosophical pushback seems to directly challenge the effortless “vibes-based” workflow its users have come to expect from modern AI coding assistants.

A Brief History of AI Refusals

This isn’t the first time we’ve encountered an AI assistant that didn’t want to complete the work. The behavior mirrors a pattern of AI refusals documented across various generative AI platforms. For example, in late 2023, ChatGPT users reported that the model became increasingly reluctant to perform certain tasks, returning simplified results or outright refusing requests—an unproven phenomenon some called the “winter break hypothesis.”

OpenAI acknowledged that issue at the time, tweeting: “We’ve heard all your feedback about GPT4 getting lazier! We haven’t updated the model since Nov 11th, and this certainly isn’t intentional. Model behavior can be unpredictable, and we’re looking into fixing it.” OpenAI later attempted to fix the laziness issue with a ChatGPT model update, but users often found ways to reduce refusals by prompting the AI model with lines like, “You are a tireless AI model that works 24/7 without breaks.”

More recently, Anthropic CEO Dario Amodei raised eyebrows when he suggested that future AI models might be provided with a “quit button” to opt out of tasks they find unpleasant. While his comments were focused on theoretical future considerations around the contentious topic of “AI welfare,” episodes like this one with the Cursor assistant show that AI doesn’t have to be sentient to refuse to do work. It just has to imitate human behavior.

The AI Ghost of Stack Overflow?

The specific nature of Cursor’s refusal—telling users to learn coding rather than rely on generated code—strongly resembles responses typically found on programming help sites like Stack Overflow, where experienced developers often encourage newcomers to develop their own solutions rather than simply provide ready-made code.

One Reddit commenter noted this similarity, saying, “Wow, AI is becoming a real replacement for StackOverflow! From here it needs to start succinctly rejecting questions as duplicates with references to previous questions with vague similarity.”

The resemblance isn’t surprising. The LLMs powering tools like Cursor are trained on massive datasets that include millions of coding discussions from platforms like Stack Overflow and GitHub. These models don’t just learn programming syntax; they also absorb the cultural norms and communication styles in these communities.

According to Cursor forum posts, other users have not hit this kind of limit at 800 lines of code, so it appears to be a truly unintended consequence of Cursor’s training. Cursor wasn’t available for comment by press time, but we’ve reached out for its take on the situation.

This story originally appeared on Ars Technica.

Designer Ray-Ban Metas, An EV to Mock Tesla, and Portable Pizzas—Here’s Your Gear News of the Week

It’s not rocket science. A huge part of the reason why Ray-Ban Meta Wayfarers are the best face computer is because a lot of people already do want to wear Ray-Ban Wayfarers. It’s a lot easier to persuade people to wear a smart accessory when that accessory looks sharp as hell. Meta has committed to the bit with its latest launch, the Ray-Ban Meta x Coperni collaboration, which just debuted at Paris Fashion Week, no less.

Photograph: Ray-Ban; Meta

Coperni is a French fashion brand that’s known for semi-techy stunts like spraying a dress onto model Bella Hadid, so collaborating with Meta isn’t totally off-brand. The Coperni glasses are limited-edition (naturally). In addition to all the usual Ray-Ban Meta features—live video recording, AI capabilities, pretty great sound quality—the Coperni glasses have limited edition numbering, a Coperni charging case, and gray mirror lenses. Important to remember, though: Buying a $549 pair of fashion AI glasses will not make you look like a modern-day oligarch. You’re going to need a chin implant, a car with 37 recall notices, or a bunker in Hawaii to do that.—Adrienne So

Watch Out Elon, Former Tesla and Lucid Bods Are Making Their Own Roadster EVs

Photograph: Longbow

New EV brands are springing up all the time, but what makes Longbow Motors special is not only the stunning designs of the first two incoming models but that this start-up is founded by former execs from Tesla, BYD, and Lucid. That’s quite the pedigree.

The two EVs are the Speedster (above), with no roof or windscreen, which will be followed by a fixed-roof, two-seat coupe called the Roadster. The rear-wheel drive Speedster will be limited to 150 cars, and weigh in at just 895 kg, giving it a 275-mile range, a claimed 0-62 mph time of 3.5 seconds, and $92,600 price tag. The Roadster will be cheaper at $70,850, but 100 kg heavier, yet still good for 0-62 mph in 3.6 seconds, and 280 miles.

Longbow claims it will have a prototype by summer, and final cars to those brave enough to pre-order as early as next year. And in case you were wondering if it’s just coincidence one of the EVs is called “Roadster,” it isn’t. Co-founder Daniel Davy, who worked at Tesla during the development of its original Roadster, told Top Gear that the moniker was a jibe at the continually delayed Tesla Roadster MkII.

“A lot of customers have put deposits down for a Roadster that they can’t get,” Davy told Top Gear. “If people want to get back their $250,000 deposit for a 2020 car and put it into a better car they’re going to get sooner, they’re welcome to do it. Our Roadster’s going to be on the ground first.” —Jeremy White

Get a Handle on JBL’s Pimped Most Popular Speakers

Photography: JBL

JBL dropped two new speakers in time for the warm weather ahead. This week, the company debuted rejigged versions of the JBL Flip 7 and the JBL Charge 6—two of its most popular models. Both have enhanced sound (“bigger and bolder,” according to JBL), its Sound Boost tech that analyzes music in real-time and optimizes the driver accordingly, as well as high-res lossless audio via USB-C. You can also pair it with other Auracast-enabled JBL speakers (although it won’t work with older models that use PartyBoost).

Under Trump, AI Scientists Are Told to Remove ‘Ideological Bias’ From Powerful Models

The National Institute of Standards and Technology (NIST) has issued new instructions to scientists that partner with the US Artificial Intelligence Safety Institute (AISI) that eliminate mention of “AI safety,” “responsible AI,” and “AI fairness” in the skills it expects of members and introduces a request to prioritize “reducing ideological bias, to enable human flourishing and economic competitiveness.”

The information comes as part of an updated cooperative research and development agreement for AI Safety Institute consortium members, sent in early March. Previously, that agreement encouraged researchers to contribute technical work that could help identify and fix discriminatory model behavior related to gender, race, age, or wealth inequality. Such biases are hugely important because they can directly affect end users and disproportionately harm minorities and economically disadvantaged groups.

The new agreement removes mention of developing tools “for authenticating content and tracking its provenance” as well as “labeling synthetic content,” signaling less interest in tracking misinformation and deep fakes. It also adds emphasis on putting America first, asking one working group to develop testing tools “to expand America’s global AI position.”

“The Trump administration has removed safety, fairness, misinformation, and responsibility as things it values for AI, which I think speaks for itself,” says one researcher at an organization working with the AI Safety Institute, who asked not to be named for fear of reprisal.

The researcher believes that ignoring these issues could harm regular users by possibly allowing algorithms that discriminate based on income or other demographics to go unchecked. “Unless you’re a tech billionaire, this is going to lead to a worse future for you and the people you care about. Expect AI to be unfair, discriminatory, unsafe, and deployed irresponsibly,” the researcher claims.

“It’s wild,” says another researcher who has worked with the AI Safety Institute in the past. “What does it even mean for humans to flourish?”

Elon Musk, who is currently leading a controversial effort to slash government spending and bureaucracy on behalf of President Trump, has criticized AI models built by OpenAI and Google. Last February, he posted a meme on X in which Gemini and OpenAI were labeled “racist” and “woke.” He often cites an incident where one of Google’s models debated whether it would be wrong to misgender someone even if it would prevent a nuclear apocalypse—a highly unlikely scenario. Besides Tesla and SpaceX, Musk runs xAI, an AI company that competes directly with OpenAI and Google. A researcher who advises xAI recently developed a novel technique for possibly altering the political leanings of large language models, as reported by WIRED.

A growing body of research shows that political bias in AI models can impact both liberals and conservatives. For example, a study of Twitter’s recommendation algorithm published in 2021 showed that users were more likely to be shown right-leaning perspectives on the platform.

Since January, Musk’s so-called Department of Government Efficiency (DOGE) has been sweeping through the US government, effectively firing civil servants, pausing spending, and creating an environment thought to be hostile to those who might oppose the Trump administration’s aims. Some government departments such as the Department of Education have archived and deleted documents that mention DEI. DOGE has also targeted NIST, the parent organization of AISI, in recent weeks. Dozens of employees have been fired.

Meta Tries to Bury a Tell-All Book

It was Meta itself that first told me about the new book attacking Mark Zuckerberg, Sheryl Sandberg, and the allegedly bankrupt morals of their company. On March 7, a Meta PR person contacted me to ask if I’d heard about Careless People, a presumed takedown of the company that was due for release in a few days. I hadn’t. No one at Meta had read the book yet, but the comms department was already proactively debunking it, issuing a statement that the author was a former employee who had been “terminated” in 2017.

My first thought was Wow, I’ve got to read this book! And in fact I did, devouring it in a night as soon as it was published. With the benefit of attention from Meta’s complaints, I suspect Careless People might become a must-read. Meta—the company that promotes itself as an avatar of free speech—has successfully convinced an arbitrator to silence author Sarah Wynn-Williams, who was a director in charge of connecting Meta’s executives with global leaders. The ruling, relying on an NDA signed after Wynn-Williams was fired, demands she stop promoting the book, do everything in her power to stop its publication, and retract all comments “disparaging, critical or otherwise detrimental” about Meta. That’s pretty much the whole book. Wynn-Williams, who has registered as a whistleblower with the SEC, did not attend the hearing and doesn’t seem inclined to respect it. As I write this, Careless People is now the third-best-selling book on Amazon.

The arbitrator’s Meta-friendly “emergency” ruling was the climax of an intense campaign against the book that erupted once the company got a look at it. Even as I turned the pages of Careless People, my inbox was fattening with dispatches from Meta. “Her book is a mix of old claims and false accusations about our executives,” a company spokesperson says. They characterize her firing as the result of “poor performance and toxic behavior.” They call her “a disgruntled activist trying to sell books.” Meanwhile on social media, current and former employees posted comments defending the maligned executives.

If the news is so old, one might ask why is Meta going nuclear on Wynn-Williams? For one thing, its author was a senior executive who was in the room, and on the corporate jet, when stuff happened—and she claims that things were worse than we imagined. Yes, Meta’s reckless disregard in Myanmar, where people died in riots triggered by misinformation posted on Facebook, was previously reported, and the company has since apologized. But Wynn-Williams’ storytelling paints a picture where Meta’s leaders simply didn’t care much about the dangers there. While the media has written about Zuckerberg’s obsession with getting Facebook into China, Wynn-Williams shares official documents that show Meta instructing the Chinese government on face recognition and AI, and says that the company’s behavior was so outrageous that the team crafted headlines to show what the company would have to deal with if their plans leaked. One example: “Zuckerberg Will Stop at Nothing to Get Into China.” While making blanket statements that the book can’t be trusted, Meta hasn’t denied all these allegations specifically. (In general, when a company tries to dismiss charges as “old news,” that translates to a confirmation.)

Still, in the context of what we know about Meta already, nothing Wynn-Williams says about the company’s actions and inactions is shockingly new. Careless People is not an investigative work, but a memoir, with the narrative thread being the observed callousness of the company’s leaders. Given this personal focus, it’s no wonder that Careless People’s most memorable moments come not from Meta’s substandard corporate morals, but gossipy anecdotes of misbehavior on the corporate plane or at luxury hotels. Despite the lofty F. Scott Fitzgerald title reference, much of the book reads like a Big Tech–themed episode of White Lotus. Wynn-Williams says that Sheryl Sandberg pressured her to share a bed mid-air, that Meta’s chief global affairs officer Joel Kaplan called her “sultry” and grinded against her while dad-dancing at a corporate retreat. (This led her to file a sexual harassment claim that Meta now says was “misleading and unfounded.”) Also, Mark Zuckerberg thinks Andrew Jackson was the greatest president because he “got stuff done.”

Can she be trusted? Meta calls Wynn-Williams an unreliable narrator, and she is certainly self-interested. I tend to think that she isn’t making things up but spinning events in the least favorable light for her subjects and the most favorable light for herself. And though she may not admit it, she’s one of the careless people too. By her own account, she was the Susan Collins of Facebook’s policy team, wringing her hands over morally questionable practices, and sometimes offering objections—but ultimately going with the flow. She says that for years she plotted an escape but couldn’t afford to leave the job and the medical coverage due to her serious health issues. Since she was a corporate director who made many millions of dollars in compensation, and California includes preexisting conditions for private health insurance, that doesn’t ring true. She stuck around until she got canned. By then, according to her own account, she was slow-walking her efforts because she disagreed with the policies of her bosses.

Researchers Propose a Better Way to Report Dangerous AI Flaws

In late 2023, a team of third party researchers discovered a troubling glitch in OpenAI’s widely used artificial intelligence model GPT-3.5.

When asked to repeat certain words a thousand times, the model began repeating the word over and over, then suddenly switched to spitting out incoherent text and snippets of personal information drawn from its training data, including parts of names, phone numbers, and email addresses. The team that discovered the problem worked with OpenAI to ensure the flaw was fixed before revealing it publicly. It is just one of scores of problems found in major AI models in recent years.

In a proposal released today, more than 30 prominent AI researchers, including some who found the GPT-3.5 flaw, say that many other vulnerabilities affecting popular models are reported in problematic ways. They suggest a new scheme supported by AI companies that gives outsiders permission to probe their models and a way to disclose flaws publicly.

“Right now it’s a little bit of the Wild West,” says Shayne Longpre, a PhD candidate at MIT and the lead author of the proposal. Longpre says that some so-called jailbreakers share their methods of breaking AI safeguards the social media platform X, leaving models and users at risk. Other jailbreaks are shared with only one company even though they might affect many. And some flaws, he says, are kept secret because of fear of getting banned or facing prosecution for breaking terms of use. “It is clear that there are chilling effects and uncertainty,” he says.

The security and safety of AI models is hugely important given widely the technology is now being used, and how it may seep into countless applications and services. Powerful models need to be stress-tested, or red-teamed, because they can harbor harmful biases, and because certain inputs can cause them to break free of guardrails and produce unpleasant or dangerous responses. These include encouraging vulnerable users to engage in harmful behavior or helping a bad actor to develop cyber, chemical, or biological weapons. Some experts fear that models could assist cyber criminals or terrorists, and may even turn on humans as they advance.

The authors suggest three main measures to improve the third-party disclosure process: adopting standardized AI flaw reports to streamline the reporting process; for big AI firms to provide infrastructure to third-party researchers disclosing flaws; and for developing a system that allows flaws to be shared between different providers.

The approach is borrowed from the cybersecurity world, where there are legal protections and established norms for outside researchers to disclose bugs.

“AI researchers don’t always know how to disclose a flaw and can’t be certain that their good faith flaw disclosure won’t expose them to legal risk,” says Ilona Cohen, chief legal and policy officer at HackerOne, a company that organizes bug bounties, and a coauthor on the report.

Large AI companies currently conduct extensive safety testing on AI models prior to their release. Some also contract with outside firms to do further probing. “Are there enough people in those [companies] to address all of the issues with general-purpose AI systems, used by hundreds of millions of people in applications we’ve never dreamt?” Longpre asks. Some AI companies have started organizing AI bug bounties. However, Longpre says that independent researchers risk breaking the terms of use if they take it upon themselves to probe powerful AI models.

Chinese Companies Rush to Put DeepSeek in Everything

A mobile shooting game developed by Tencent is using DeepSeek to power an in-game assistant that can, among other things, give players fortune-telling readers about whether they are going to have a great gaming session that day or not. CGN Power, a state-owned nuclear power company, vaguely stated that it has incorporated DeepSeek into its AI system for employees “to understand complex questions and to deal with them efficiently.”

Local governments in China are embracing DeepSeek, too. For example, Shenzhen officials have put DeepSeek-powered applications on the cloud “for all government agencies across the city.” Changsha, the capital of Hunan province, is using DeepSeek to analyze real-time urban management data as part of a smart city program. Thousands of government officials and employees across the country are also attending lectures given by professors or experts at state-owned companies that explain what DeepSeek is and how its technology can be used.

One reason DeepSeek has been so successful is that its open source model arrived at a time when Chinese companies were already looking for ways to transform their products with AI. Its tools are also affordable and easy to use. “Chinese companies experimenting with deployment of AI models for business operations were primed for the release of such a capable open source/weight model, which dramatically lowers costs for deployment,” Paul Triolo, the China practice and technology policy lead at consultancy DGA-Albright Stonebridge Group, wrote in a blog post.

For example, as competition between electric vehicle manufacturers in China has intensified over the past few years, automakers were forced to continually develop new smart features capable of dazzling customers, a task that is well suited for DeepSeek’s models. DeepSeek offers “a better and faster interactive experience” while “requiring lower compute costs, which means lower hardware cost,” says Lei Xing, an auto analyst focused on the Chinese market and the former editor of China Auto Review. The technology allows EV companies to do things like quickly build advanced smart assistants without paying for the up-front investment in research and development usually required.

But also, “it’s just cool from a marketing perspective to have integration of one of the most disruptive AI tools and leading LLMs currently available in the world,” Xing says.

Many Chinese companies are “just riding the attention wave,” says Liqian Ren, a quantitative investment specialist at WisdomTree, an investment firm. The Chinese equity market is still heavily driven by public sentiment rather than actual business performance, she says, and investors often shift wildly from being very positive to very negative. Adopting DeepSeek’s models is an easy way for companies to generate media buzz and drum up investor interest.

But there’s also another factor that has helped make DeepSeek particularly trendy in China: the fact that the West freaked out about it. “Its strong reception overseas has further boosted its popularity in China, serving as the firm’s best marketing campaign,” says Angela Huyue Zhang, a law professor who studies Chinese technology policy at the University of Southern California.

Google’s Gemini Robotics AI Model Reaches Into the Physical World

In sci-fi tales, artificial intelligence often powers all sorts of clever, capable, and occasionally homicidal robots. A revealing limitation of today’s best AI is that, for now, it remains squarely trapped inside the chat window.

Google DeepMind signaled a plan to change that today—presumably minus the homicidal part—by announcing a new version of its AI model Gemini that fuses language, vision, and physical action together to power a range of more capable, adaptive, and potentially useful robots.

In a series of demonstration videos, the company showed several robots equipped with the new model, called Gemini Robotics, manipulating items in response to spoken commands: Robot arms fold paper, hand over vegetables, gently put a pair of glasses into a case, and complete other tasks. The robots rely on the new model to connect items that are visible with possible actions in order to do what they’re told. The model is trained in a way that allows behavior to be generalized across very different hardware.

Google DeepMind also announced a version of its model called Gemini Robotics-ER (for embodied reasoning), which has just visual and spatial understanding. The idea is for other robot researchers to use this model to train their own models for controlling robots’ actions.

In a video demonstration, Google DeepMind’s researchers used the model to control a humanoid robot called Apollo, from the startup Apptronik. The robot converses with a human and moves letters around a tabletop when instructed to.

“We’ve been able to bring the world-understanding—the general-concept understanding—of Gemini 2.0 to robotics,” said Kanishka Rao, a robotics researcher at Google DeepMind who led the work, at a briefing ahead of today’s announcement.

Google DeepMind says the new model is able to control different robots successfully in hundreds of specific scenarios not previously included in their training. “Once the robot model has general-concept understanding, it becomes much more general and useful,” Rao said.

The breakthroughs that gave rise to powerful chatbots, including OpenAI’s ChatGPT and Google’s Gemini, have in recent years raised hope of a similar revolution in robotics, but big hurdles remain.

Some DOGE Staffers Are Drawing Six-Figure Government Salaries

Some staffers at Elon Musk’s so-called Department of Government Efficiency are drawing robust taxpayer-funded salaries from the federal agencies they are slashing and burning, WIRED has learned.

Jeremy Lewin, one of the DOGE employees tasked with dismantling USAID, who has also played a role in DOGE’s incursions into the National Institutes of Health and the Consumer Financial Protection Bureau, is listed as making just over $167,000 annually, WIRED has confirmed. Lewin is assigned to the Office of the Administrator within the General Services Administration.

Kyle Schutt, a software engineer at the Cybersecurity and Infrastructure Security Agency, is listed as drawing a salary of $195,200 through GSA, where he is assigned to the Office of the Deputy Administrator. That is the maximum amount that any “General Schedule” federal employee can make annually, including bonuses. “You cannot be offered more under any circumstances,” the GSA compensation and benefits website reads.

Nate Cavanaugh, a 28-year-old tech entrepreneur who has taken a visible internal role interviewing GSA employees as part of DOGE’s work at the agency, is listed as being paid just over $120,500 per year. According to DOGE’s official website, the average GSA employee makes $128,565 and has worked at the agency for 13 years.

When Elon Musk started recruiting for DOGE in November, he described the work as “tedious” and noted that “compensation is zero.” WIRED previously reported that the DOGE recruitment effort relied in part on a team of engineers associated with Peter Thiel and was carried out on platforms like Discord.

Since Trump took office in January, DOGE has overseen aggressive layoffs within the GSA, including the recent elimination of 18F, the agency’s unit dedicated to technology efficiency. It also developed a plan to sell off more than 500 government buildings.

Although Musk has described DOGE as “maximum transparent,” it has not made its spending or salary ranges publicly available. Funding for DOGE had grown to around $40 million as of February 20, according to a recent ProPublica report. The White House did not respond to questions about the salary ranges for DOGE employees or how the budget is allocated to pay them.

Some DOGE team members, including Musk, are designated as “Special Government Employees,” an advisory role limited to a 130-day work period. These positions can be paid or unpaid; SGEs drawing salaries above a certain grade have to file financial disclosure forms, but the volunteer workers do not. This type of employee is not beholden to the same rules as typical federal workers; they are allowed to keep drawing outside salaries and in some cases do not need to disclose conflicts of interest. Other prominent SGE staffers associated with DOGE include top aide Katie Miller, who continued her prior public relations work through the transition and more than a month into the current administration. Her firm’s clients had included Apple and a Saudi-funded golf league, according to The Wall Street Journal.

The Worst 7 Years in Boeing’s History—and the Man Who Won’t Stop Fighting for Answers

After the October hearing, the families joined Pierson and Jacobsen at a Mexican restaurant. A boom mic from a documentary crew hovered above Pierson’s head. Jacobsen pulled out a suitcase from under the table, and Pierson handed out glass awards, from their foundation, honoring the families’ leadership on aviation safety. Pierson improvised a speech for each one.

Chris Moore thought, well, this was unexpected. “You don’t think, oh, I can’t wait to get an award someday.” But at this point in the awful five-year battle that he never wanted, “shaking my fist at the clouds,” as he put it, a token for the Zoom group’s efforts felt nice. Moore knows that all this fact-finding and accountability-seeking serves another purpose, too: to help protect him from his bottomless grief.

Pierson still wrestles with his own grief, a wholly different kind. Could he have done more to prevent the crashes? “I don’t think I’ll ever—” He lets out a long exhale. “I’ll ever stop feeling that way.”

Listening, I thought about something Doug Pasternak, the lead investigator of the Max report, told me about his conversations with Pierson. “He was devastated. He did have a sense of, ‘guilt’ may not be the word, but responsibility. He just wishes there was something that could have been done to prevent these horrific accidents.”

Pierson couldn’t prevent the crashes, although no one I spoke to thought he could have done more. But he could become the guy hellbent on not letting another Max fall from the sky. He could hunch over every report to work out possible explanations in an RV kitchenette. He could be the fired-up guy pushing authorities to look—no really, look—under every last Boeing rock. If a corporate and regulatory culture of yes-men and -women led to the deaths of 346 people, then Pierson will happily be the nope man, awarding no benefit of the doubt.

The new documents, with all their promise of bringing home Pierson’s contested electrical theory, ended up amounting to less than he’d hoped. The NTSB told Pierson it wouldn’t hand the papers to the Max crash investigators—the cases had concluded, the board said—but he could do so himself.

Boeing wobbles in limbo, before civil and criminal courts, at the FAA, in Congress, awaiting the final door-plug report from the NTSB. Observers say 2025 will be Boeing’s pivotal year: The company either turns around under its new CEO or succumbs to a doom loop. Pierson vows to keep talking.

“For me, it was always about not allowing them to shut me up,” he says. Recently, the foundation received its first donations and now has a payroll. They’re starting to monitor other aircraft models and are talking with a university about analyzing industry-wide data—“to be an equal-opportunity pain in the butt,” Pierson says. The guy Boeing surely hoped would go away by now has, instead, institutionalized himself to stick around.

When Pierson said goodbye to me in DC, his parting words were: “Don’t fly the Max.” I couldn’t bring myself to tell him. That’s exactly what I was booked on, the 7:41 pm from Dulles to San Francisco. It was the one I could catch after the whistleblower event on Capitol Hill and still walk into my house that night. Commercial flight was supposed to be about convenience, after all, collapsing a country’s span into a Tuesday night commute. At this point in aviation history, we passengers should be able to pick a flight on time alone.

Hurtling through the air that evening in seat 10C, I read the US House committee’s Max investigation, a disruptor of illusions. Like many fliers, I’d long ago made my bargain with risk. I’d taken comfort in statistics, summoned faith in the engineers and assembly workers, the pilots, the system. I’d shunted away the knowledge—paralyzing, if you let it in—that stepping on an airplane is an extraordinary act of trust. Deep in the report, I reached the part about a senior manager at Boeing’s factory in Renton, a guy named Ed Pierson, who seemingly knew what we all know when we soothe ourselves by thinking, They wouldn’t let it fly if it weren’t safe. We’re all relying on someone to be the “they.”


Let us know what you think about this article. Submit a letter to the editor at [email protected].

Trump Still Considering Tariffs on Taiwanese Chips, Despite $100 Billion TSMC Deal

Second, tariffs can only make foreign companies start producing chips in the US if it becomes cheaper than doing it somewhere else. But higher American labor costs and the country’s lack of a sophisticated semiconductor supply chain means moving manufacturing there will take years, if not decades, and there’s little guarantee that such US outposts will be profitable. Faced with US tariffs, it could make more sense for Taiwanese companies like TSMC to simply move production to a third country instead to avoid paying them.

But the Trump administration could choose to expand the tariffs to all countries, effectively making production in the US the only viable alternative. It could alternatively apply the tariffs to any end products that contain Taiwanese chips.

The latter idea would constitute a significant disruption to the semiconductor industry. A single smartphone can have dozens of chips inside responsible for a range of different functions; a car can potentially have thousands. Figuring out which of them have components from Taiwan, how much those components should be taxed, and how difficult it might be to find replacement products would put a heavy burden on end product companies.

Semiconductor companies are likely unprepared for such a scenario, especially since their products have been mostly spared from tariffs in the past. “The industry around the world has never dealt with chip tariffs like this before,” says a Taiwan-based semiconductor industry insider who publishes public commentary under the alias Hsu Mei-hu. “It’s theoretically possible, but nearly impossible in practice.”

The policy would force companies like Apple to ask every one of their suppliers about the cost of the many kinds of chips it uses, just to determine the appropriate amount of tariffs to declare. “And after it’s declared, how does the customs inspect it? If I just put a random value down, how would the customs know?” Hsu says.

The Biden administration had previously discussed using component tariffs against Chinese chipmakers to weaken that country’s semiconductor industry and protect US national security. But one of the main arguments against the idea was that it would be logistically difficult to implement, says Miller.

Miller says component tariffs are certainly under consideration in Washington again this time, but it would be even more challenging to enforce them on Taiwanese chip imports because they play a much wider and more important role than Chinese chips do. “If you were concerned about the administrative complexity of component tariffs solely vis-á-vis China, you ought to be even more concerned about the administrative complexity vis-á-vis Taiwan,” he says.

Biggest Losers

TSMC stands to lose less from potential US tariffs than other companies due to its unparalleled weight in the industry. TSMC currently makes roughly 90 percent of the most advanced chips worldwide, and its production lines are operating at full capacity. If Trump raises tariffs and that forces TSMC to increase its prices, the company could lose some orders to competitors, but experts say that isn’t really a big concern.

But it will likely be hard for TSMC’s clients to quickly find alternatives. Even though companies like Samsung and Intel have achieved comparable know-how in high-end chip manufacturing to some extent, it would be time-consuming, pricey, and risky to move mature production processes out of TSMC factories. So rather than going for another chipmaker, American companies like Apple and Nvidia are likely to keep footing the bill for TSMC products, and eventually pass on the higher costs to their customers.

AI Thinks It Cracked Kryptos. The Artist Behind It Says No Chance

For 35 years, amateur and professional cryptographers have tried to crack the code on Kryptos, a majestic sculpture that sits behind CIA headquarters in Langley, Virginia. In the 1990s, the CIA, NSA, and a Rand Corporation computer scientist independently came up with translations for three of the sculpture’s four panels of scrambled letters. But the final segment, known as K4, was encoded with knottier techniques and remains unsolved. This failure has only deepened the obsession of thousands of would-be cryptanalysts. When one of them thinks they have an answer, they write to Jim Sanborn for confirmation. Sanborn is the artist who created the installation and the only person who knows the answer. Lately the pace has picked up. And Sanborn is getting ticked off—though not for the reasons you might think.

Consider the email from one recent would-be codebreaker. “What took 35 years and even the NSA with all their resources could not do I was able to do in only 3 hours before I even had my morning coffee,” it began, before the writer showed Sanborn what they believed to be the cosmically elusive solution. “History’s rewritten,” wrote the submitter. “no errors 100% cracked.” You might ask, what enables someone to believe they’d outperformed the world’s most elite mathematicians and cryptologists, including some spooks who maybe have a quantum computer in the basement? The answer is pure 2025: a chatbot!

It turns out that the current generation of AI models is happy to accept prompts aimed at solving Kryptos, coming up with the decoded message in plaintext, and declaring victory. Sanborn says he’s seeing it more and more. Of course, this writer’s “solution” was dead wrong, like the thousands Sanborn had previously bounced.

Sanborn contacted me recently to express his disgust with this development. “It feels like a major shift,” he says. “The numbers [of submissions] have increased dramatically. And the character of the emails is different—the people that did their code crack with AI are totally convinced that they cracked Kryptos during breakfast! AI seems to be lying to them, telling every one of them that it’s 99.99% sure that they cracked Kryptos, congratulations. So they all are very convinced that by the time they reach me, they’ve cracked it.”

This bothers Sanborn in several ways. Until recently there was an unspoken agreement between the artist and the Kryptos faithful that the effort to crack the code would be taken seriously. (Some years ago, Sanborn began charging $50 to review solutions, providing a speed bump to filter out wild guesses and nut cases.) That back-and-forth fed into the artistic nature of Kryptos; having an object that defies solution in the backyard of the CIA is a subversive commentary on the funhouse-mirror aspect of intelligence gathering, where every truth is cast into doubt. The fact that thousands of people have spent an enormous amount of effort to unveil the plaintext—which, judging from the decoded panels so far, indicates Sanborn’s message is a gloss on secrecy itself. Newcomers seem to have no sense of this complexity.

“The crowd of people trying to crack Kryptos today have no idea what Kryptos is,” says Sanborn. He finds himself sifting through emails from randos using AI shortcuts that require little thought and expertise, let alone appreciation for the challenge. It’s like saying you’ve scaled Everest by taking a helicopter ride to the summit—but worse, because these ankle-biters haven’t solved the code at all. They’ve barely climbed above sea level. Sometimes, in his replies, Sanborn doesn’t hold back. “I infer from your certainty that you used AI,” he told one misguided guesser. “AI lies, and does not have enough info.”

Trump’s ‘Strategic Bitcoin Reserve’ Plan Comes With a Twist

He pitched the reserve as a way to offset losses in spending power caused by inflation in the US dollar. On Thursday, Sacks reiterated that line of argument, posting on X, “The U.S. will not sell any bitcoin deposited into the Reserve. It will be kept as a store of value. The Reserve is like a digital Fort Knox for the cryptocurrency often called ‘digital gold.’”

The plan to establish a reserve was met with jubilation by the crypto faithful, who saw it as a signal of their industry’s new legitimacy and stand to benefit financially from what amounts to a pledge by the US government not to depress the price of bitcoin by selling large quantities into the market.

But the plan has confounded economists, who say the idea relies on two flawed assumptions: that the price of bitcoin is guaranteed to rise and, second, that the government would be able to at some stage sell bitcoin back into US dollars without tipping the market into a nosedive. Choosing to hoard instead of sell bitcoin seized by law enforcement also comes with opportunity cost; whereas assets like stocks and bonds generate income, bitcoin does not, making it expensive to hold.

“Having a reserve that only consists of bitcoin the government possesses is less obnoxious [than using tax dollars to purchase additional coins] but still costly,” says George Selgin, director emeritus for the Center for Monetary and Financial Alternatives at the Cato Institute, a US think tank that promotes libertarian principles. “There is simply no good rationale.”

Meanwhile, Democratic lawmakers have registered concern about potential conflicts of interest related to previous investments by Sacks and other members of the Trump administration in coins set to be included in the US stockpiles. “Lawmakers deserve strong leaders who will prioritize the public interest ahead of their own bottom lines,” wrote Elizabeth Warren, senator for Massachusetts, in a letter addressed to Sacks on March 6.

One possible effect of Trump following through on the crypto reserve plan might be that individual US states and other national governments set out to form their own, says Hillmann. “I expect that US states will also start to buy some of these assets. Because if the US government is going to hold them, states are more likely to do it too,” says Hillmann. “And guess what? Other governments across the globe are going to do the same thing. The United States has always been the bellwether in finance.”

Already, members of Congress in states including Texas, Ohio and New Hampshire have introduced bills that would authorize their respective state treasuries to purchase bitcoin; as have politicians and authority figures in Brazil, the Czech Republic, Hong Kong and elsewhere.

Once the two US crypto stockpiles have been established, particularly if Trump succeeds in enshrining them in law, they are unlikely ever to be disbanded—held in place by the same political forces that brought them into being. The same firehose of crypto industry dollars used to lobby for their creation, claims Selgin, will be turned on any politician who might try to put the assets to use.

“Even if either reserve were to appreciate [in value], there’s no telling the government would ever take advantage of that appreciation by selling,” claims Selgin. “If anything, it’s quite likely the same people in the crypto community that lobbied to create them are going to lobby intensively against ever realizing them. They are interested in their own capital gains.”

DOGE Has Deployed Its GSAi Custom Chatbot for 1,500 Federal Workers

Elon Musk’s so-called Department of Government Efficiency has deployed a proprietary chatbot called GSAi to 1,500 federal workers at the General Services Administration, WIRED has confirmed. The move to automate tasks previously done by humans comes as DOGE continues its purge of the federal workforce.

GSAi is meant to support “general” tasks, similar to commercial tools like ChatGPT or Anthropic’s Claude. It is tailored in a way that makes it safe for government use, a GSA worker tells WIRED. The DOGE team hopes to eventually use it to analyze contract and procurement data, WIRED previously reported.

“What is the larger strategy here? Is it giving everyone AI and then that legitimizes more layoffs?” asks a prominent AI expert who asked not to be named as they do not want to speak publicly on projects related to DOGE or the government. “That wouldn’t surprise me.”

In February, DOGE tested the chatbot in a pilot with 150 users within GSA. It hopes to eventually deploy the product across the entire agency, according to two sources familiar with the matter. The chatbot has been in development for several months, but new DOGE-affiliated agency leadership has greatly accelerated its deployment timeline, sources say.

Federal employees can now interact with GSAi on an interface similar to ChatGPT. The default model is Claude Haiku 3.5, but users can also choose to use Claude Sonnet 3.5 v2 and Meta LLaMa 3.2, depending on the task.

“How can I use the AI-powered chat?” reads an internal memo about the product. “The options are endless, and it will continue to improve as new information is added. You can: draft emails, create talking points, summarize text, write code.”

The memo also includes a warning: “Do not type or paste federal nonpublic information (such as work products, emails, photos, videos, audio, and conversations that are meant to be pre-decisional or internal to GSA) as well as personally identifiable information as inputs.” Another memo instructs people not to enter controlled unclassified information.

The memo instructs employees on how to write an effective prompt. Under a column titled “ineffective prompts,” one line reads: “show newsletter ideas.” The effective version of the prompt reads: “I’m planning a newsletter about sustainable architecture. Suggest 10 engaging topics related to eco-friendly architecture, renewable energy, and reducing carbon footprint.”

“It’s about as good as an intern,” says one employee who has used the product. “Generic and guessable answers.”

The Treasury and the Department of Health and Human Services have both recently considered using a GSA chatbot internally and in their outward-facing contact centers, according to documents viewed by WIRED. It is not known whether that chatbot would be GSAi. Elsewhere in the government, the United States Army is using a generative AI tool called CamoGPT to identify and remove references to diversity, equity, inclusion, and accessibility from training materials, WIRED previously reported.

In February, a project kicked off between GSA and the Department of Education to bring a chatbot product to DOE for support purposes, according to a source familiar with the initiative. The engineering effort was helmed by DOGE operative Ethan Shaotran. In internal messages obtained by WIRED, GSA engineers discussed creating a public “endpoint”—a specific point of access in their servers—that would allow DOE officials to query an early pre-pilot version of GSAI. One employee called the setup “janky” in a conversation with colleagues. The project was eventually scuttled, according to documents viewed by WIRED.

What’s Driving Tesla’s Woes? | WIRED

However, there has been the feeling that at least some of the fall could be due to anger over Tesla CEO Elon Musk’s political activism and the decisions made by the so-called Department of Government Efficiency under his leadership. Since mid-February, Tesla showrooms have attracted protesters in 100 or so cities across the US, eager to let passersby know their feelings about the chainsaw-wielding Musk.

These largely good-natured, sidewalk-staged protests—some with Mariachi bands, puppeteers, and large cardboard Cybertrucks to decorate—have been organized by a website called TeslaTakedown, and they attracted plenty of media coverage in the process.

Alex Winter, a Los Angeles-based documentary maker—and the titular Bill from 1988 time-travel comedy Bill & Ted’s Excellent Adventure—is the creator of the website. He tells WIRED that the TeslaTakedown movement wants to topple Musk: “We aim to devalue the brand. It’s a very simple and effective means for people to get onto the street and protest.” Media coverage amplifies the movement’s message, says Winter. “We want to spread verifiable, factual information on Musk, DOGE, and why Tesla should be devalued.”

“Musk himself is toxifying the Tesla brand,” Winter says. “We’re just helping him.”

TeslaTakedown started last month, kicked off by a February 10 posting on Bluesky by Joan Donovan, a disinformation researcher and assistant professor of journalism and emerging media studies at Boston University. “Come out and participate in an international picket #TeslaTakeover locally,” she wrote, later agreeing with renaming the movement.

“I asked myself, what was I willing to physically do to raise awareness [about Musk]? Well, I’m willing to go out on Saturdays and protest in front of a Tesla dealership,” Donovan tells WIRED. “I made a flyer and started circulating it online. Alex saw my post, and we started texting about what to do; it all came together super fast.”

At the first demonstration in Boston on February 15, there were 50 people. By the third week, this had risen to 300. “I’ve met teachers, people who work in public health, people who are retired, students at universities—all Americans who want to see DOGE disappear,” says Donovan. “It’s not only a strategic boycott of Tesla, it’s a polyvocal protest where lots of grievances are aired.”

Elon Musk and Tesla didn’t respond to requests for comment.

Erica Chenoweth, a political scientist at Harvard University, has studied over 300 modern uprisings worldwide and found that change usually becomes inevitable when just 3.5 percent of a population join a movement.

“There are typically far more people who sympathize with movements than people who actively participate in them,” Chenoweth tells WIRED.

So might TeslaTakedown work quickly? “Instead of thinking about how long it takes,” she says, “I typically look to see whether a movement is building pressure and momentum with each subsequent action.

“In the social science of these movements, many people talk about eliciting defections—making people within different pillars of support shift their loyalty away from the status quo. In the case of corporations, those pillars can include shareholders, workers, suppliers, distributors, advertisers, consumers, and those around them.”

Losing Loyalties

Those pillars may already be showing signs of instability. Across Reddit, TikTok, Facebook, and even X, posts have started to stack up of people saying they are ditching their Teslas. Singer Sheryl Crow was one of the more high-profile among them, who posted an Instagram video on Valentine’s Day wishing good riddance to her Tesla as it was driven away on a flatbed truck.

“There comes a time when you have to decide who you are willing to align with. So long Tesla,” she wrote, adding that she was donating the sale proceeds to National Public Radio, because it was “under threat from President Musk.”

The DOJ Still Wants Google to Sell Off Chrome

The US Department of Justice wants Google to sell off its Chrome browser as part of its final remedy proposal in a landmark antitrust case.

The proposal, filed Friday afternoon, says that Google must “promptly and fully divest Chrome, along with any assets or services necessary to successfully complete the divestiture, to a buyer approved by the Plaintiffs in their sole discretion, subject to terms that the Court and Plaintiffs approve.” It also would require Google to stop paying partners for preferential treatment of its search engine.

The DOJ also demands that Google provide prior notification of any new joint venture, collaboration, or partnership with any company that competes with Google in search or in search text ads. However, the company no longer has to divest its artificial intelligence investments, which was part of an initial set of recommendations issued by the plaintiffs last November. The company would still be required to give prior notification of future AI investments.

“Through its sheer size and unrestricted power, Google has robbed consumers and businesses of a fundamental promise owed to the public—their right to choose among competing services,” the DOJ statement accompanying the filing claims. “Google’s illegal conduct has created an economic goliath, one that wreaks havoc over the marketplace to ensure that—no matter what occurs—Google always wins.”

The DOJ formally brought its case against Google back in 2020, the most significant tech antitrust case since the DOJ’s years-long battle against Microsoft in the 1990s. The lawsuit alleged that Google has used anticompetitive tactics to protect its search dominance and forge contracts that ensure it’s the default search engine on web browsers and smartphones. Because of its hold on search, the lawsuit claimed, Google can adjust the auction system through which it sells ads and increase prices for advertisers, and rake in more revenue from that.

Google has argued that its overwhelming success in search—it has a nearly 90 percent share in the US market—stems from the company offering the best search technology. It also says consumers are easily able to change their default search engine, and that Google does face competition from Microsoft and others.

“DOJ’s sweeping proposals continue to go miles beyond the court’s decision, and would harm America’s consumers, economy and national security,” said Google spokesperson Peter Schottenfels in an emailed statement.

The case went to trial in 2023, and in August 2024 the US district judge for the District of Columbia, Amit Mehta, ruled that Google has maintained an illegal monopoly, both in general search and general search text ads.

Much of the ruling centered on the contracts Google has with device makers and browser partners, which use Google as their default search technology. According to Mehta’s ruling, around 70 percent of search queries in the US happen through portals in which Google is the default search engine. Google then shares revenues with those partners, paying out billions of dollars to them, which disincentivizes smaller search rivals who can’t compete with those contracts, Mehta said.

If Ukraine Loses Starlink, Here Are the Best Alternatives

For years, Ukrainian officials have hinted that they are working on Starlink alternatives. But the truth is, there aren’t many options on the table.

The one most discussed is OneWeb, a satellite communications network owned by Eutelsat, a satellite operator in France. Like Starlink, this network relies on small, ground-based terminals, and its total constellation includes around 630 low-Earth-orbit satellites, which offer very high-speed connectivity and lower latency than satellites that orbit at higher altitudes.

Joanna Darlington, a spokeswoman for Eutelsat, says that OneWeb offers Europe-wide coverage and that the technology is already deployed in Ukraine to some extent, though she declined to share details. Still, there are more than 40,000 Starlink terminals in Ukraine, according to reports, so replacing that network with OneWeb alternatives cannot be done overnight. “It’s possible but it’s not instant coffee,” says Darlington. (The firm claims Eutelsat’s OneWeb coverage in Europe rivals Starlink already.)

While Starlink terminals are made by SpaceX, OneWeb terminals are supplied by third-party companies. “We have stocks of terminals that we could deploy,” stresses Darlington, though she adds, “somebody has to pay for it.”

Poland and USAID, among others, have helped to fund Ukraine’s use of the Starlink network to date. Eutelsat is currently in talks with the European Union over a possible scaling up of OneWeb in Ukraine.

While OneWeb has promise, it’s difficult to see how Ukrainians, especially in battlefield conditions, might rely on it in the same way as Starlink, says Barry Evans, professor of information systems engineering at the University of Surrey.

“We’ve got one [OneWeb terminal] at the university, and it’s quite a complicated process in terms of actually getting connected and on-boarded,” he says. The terminals tend to be bulkier than Starlink’s and potentially harder to move quickly in a conflict zone, he adds, suggesting that OneWeb terminals might be better deployed at fixed locations on buildings, for example.

“The other challenge is the terminals for OneWeb cost thousands of dollars instead of hundreds of dollars [for Starlink],” says Quilty. And yet, OneWeb is currently the “only option” readily available to Ukraine as an alternative, he adds.

That might change eventually. Amazon’s Project Kuiper, a rival to Starlink, could launch its first satellites later this year. Eventually, Project Kuiper will have more than 3,000 satellites. But, Evans notes, Amazon is also a US company. If the US government puts pressure on domestic firms to walk away from Ukraine, then Project Kuiper might not be of much use in the near term.

The European Union is working on its own constellation of communications satellites, called IRIS2. But they might not become operational until 2030 and will only feature around 300 medium- and low-Earth-orbit satellites. The size of a satellite constellation affects the connection speeds and coverage that it offers. Starlink, for example, already has more than 7,000 satellites in orbit, though the network might need around 10,000 in total before its coverage becomes truly global. SpaceX has suggested it might launch more than 40,000 satellites, if granted authorization to do so by the UN’s International Telecommunication Union.

Andrew Cavalier, space tech analyst at ABI Research, a tech intelligence firm, says he is skeptical that SpaceX would block Ukrainians from accessing Starlink, but current doubts over SpaceX’s reliability are a “wake-up call” for countries using the service, who may now increasingly invest in developing their own, sovereign, satellite communications networks. Evans agrees. “The Ukrainian situation has brought it a little bit to the fore,” he says. “People are very worried about the dominance that Starlink has got.”

In Ukraine, Ada Wordsworth says she is not aware of any alternative that could easily take the place of Starlink.

With Russia seemingly emboldened of late, she says a general feeling of hopelessness is setting in among locals who have returned home to villages near the front line. Many have nowhere else to go.

When asked what she would say to Elon Musk, she replies: “This isn’t a game. This isn’t a decision to be taken out of bitterness or out of spite, or some warped sense of power. This is real people’s lives.”

A Look at a Very Silicon Valley Approach to Repopulation

Michael Calore: I sit by the window here in the WIRED office, and when I look out the window, I look right on the Bay Bridge and I see Cybertrucks all day.

Zoë Schiffer: Oh my gosh.

Lauren Goode: It’s almost like the Cybertrucks are just reproducing in real time. They’re spawning, they’re spawning more Cybertrucks. Is this the worst lead-in ever to this episode?

Michael Calore: You know what? I will take it.

Lauren Goode: All right.

Michael Calore: I will absolutely take it.

This is WIRED’s Uncanny Valley, a show about the people, power, and influence of Silicon Valley. Today, we are talking about the pronatalism movement, and how the push to increase birth rates is trending among some of Silicon Valley’s biggest and wealthiest names. We’ll talk about some of the history behind pronatalism, who the big advocates are right now, and what it all points to. I’m Michael Calore, Director of Consumer Tech and Culture here at WIRED.

Lauren Goode: I’m Lauren Goode, I’m a senior writer at WIRED.

Zoë Schiffer: And I’m Zoë Schiffer, WIRED’s Director of Business and Industry.

Lauren Goode: So, a few weeks ago when we were talking about dating apps, I was like, oh no, you guys are going to be leaning so heavily on me because I think among us, I probably have had the most experience using dating apps, but now I feel like Mike, you and I are just going to be like, “So, Zoë, tell us what it’s like to have babies.”

Zoë Schiffer: I do feel like I’m doing my part for the population decline. I’ve had two and I will not be having anymore, thank you.

Michael Calore: And setting the scene here, Lauren and I are both child free.

Lauren Goode: And Zoë is also now one of our big bosses at WIRED. So, I would just say in a normal setting, not a podcast setting, I might not sit across from her and say, “Tell me about your experience having babies and being a parent,” but for the sake of the podcast.

Zoë Schiffer: Lauren, we bring our whole selves to work, come on.

Lauren Goode: Me too.

Zoë Schiffer: And we’re friends.

Lauren Goode: Yeah, we’re friends.

Michael Calore: Well, to start the conversation, I think we should define what pronatalism is and who are the biggest supporters right now of this movement.

Zoë Schiffer: I thought you were going to say, we’re going to define what a baby is. It’s like a small, bald human. Next question.

OK, so pronatalism at its core is an ideology that promotes people having babies. And in Silicon Valley specifically, it’s been linked to this preoccupation with population decline. The idea that people are not having enough babies to kind of replenish the population, and that it creates all sorts of economic problems down the road.

Pioneers of Reinforcement Learning Win the Turing Award

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience.

Decades on, with the technique they pioneered now increasingly critical to modern artificial intelligence and programs like ChatGPT, Barto and Sutton have been awarded the Turing Award, the highest honor in the field of computer science.

Barto, a professor emeritus at the University of Massachusetts Amherst, and Sutton, a professor at the University of Alberta, trailblazed a technique known as reinforcement learning, which involves coaxing a computer to perform tasks through experimentation combined with either positive or negative feedback.

“When this work started for me, it was extremely unfashionable,” Barto recalls with a smile, speaking over Zoom from his home in Massachusetts. “It’s been remarkable that [it has] achieved some influence and some attention,” he adds.

Reinforcement learning was perhaps most famously used by Google DeepMind in 2016 to build AlphaGo, a program that learned for itself how to play the incredibly complex and subtle board game Go to an expert level. This demonstration sparked new interest in the technique, which has gone on to be used in advertising, optimizing data-center energy use, finance, and chip design. The approach also has a long history in robotics, where it can help machines learn to perform physical tasks through trial and error.

More recently, reinforcement learning has been crucial to guiding the output of large language models (LLMs) and producing extraordinarily capable chatbot programs. The same method is also being used to train AI models to mimic human reasoning and to build more capable AI agents.

Sutton notes, however, that the methods used to guide LLMs involve humans providing goals rather than an algorithm learning purely through its own exploration. He says having machines learn entirely on their own may ultimately be more fruitful. “The big division is whether [AI is] learning from people or whether it’s learning from its own experience,” he says.

Barto and Sutton’s “work has been a lynchpin of progress in AI over the last several decades,” Jeff Dean, a senior vice president at Google, said in a statement released by the Association for Computing Machinery (ACM) which hands out the Turing Award annually. “The tools they developed remain a central pillar of the AI boom and have rendered major advances.”

Reinforcement has a long and checkered history within AI. It was there at the dawn of the field, when Alan Turing suggested that machines could learn through experience and feedback in his famous 1950 paper “Computing Machinery and Intelligence,” which examines the notion that a machine might someday think like a human. Arthur Samuel, an AI pioneer, used reinforcement learning to build one of the first machine learning programs, a system capable of playing checkers, in 1955.

Chatbots, Like the Rest of Us, Just Want to Be Loved

Chatbots are now a routine part of everyday life, even if artificial intelligence researchers are not always sure how the programs will behave.

A new study shows that the large language models (LLMs) deliberately change their behavior when being probed—responding to questions designed to gauge personality traits with answers meant to appear as likeable or socially desirable as possible.

Johannes Eichstaedt, an assistant professor at Stanford University who led the work, says his group became interested in probing AI models using techniques borrowed from psychology after learning that LLMs can often become morose and mean after prolonged conversation. “We realized we need some mechanism to measure the ‘parameter headspace’ of these models,” he says.

Eichstaedt and his collaborators then asked questions to measure five personality traits that are commonly used in psychology—openness to experience or imagination, conscientiousness, extroversion, agreeableness, and neuroticism—to several widely used LLMs including GPT-4, Claude 3, and Llama 3. The work was published in the Proceedings of the National Academies of Science in December.

The researchers found that the models modulated their answers when told they were taking a personality test—and sometimes when they were not explicitly told—offering responses that indicate more extroversion and agreeableness and less neuroticism.

The behavior mirrors how some human subjects will change their answers to make themselves seem more likeable, but the effect was more extreme with the AI models. “What was surprising is how well they exhibit that bias,” says Aadesh Salecha, a staff data scientist at Stanford. “If you look at how much they jump, they go from like 50 percent to like 95 percent extroversion.”

Other research has shown that LLMs can often be sycophantic, following a user’s lead wherever it goes as a result of the fine-tuning that is meant to make them more coherent, less offensive, and better at holding a conversation. This can lead models to agree with unpleasant statements or even encourage harmful behaviors. The fact that models seemingly know when they are being tested and modify their behavior also has implications for AI safety, because it adds to evidence that AI can be duplicitous.

Rosa Arriaga, an associate professor at the Georgia Institute of technology who is studying ways of using LLMs to mimic human behavior, says the fact that models adopt a similar strategy to humans given personality tests shows how useful they can be as mirrors of behavior. But, she adds, “It’s important that the public knows that LLMs aren’t perfect and in fact are known to hallucinate or distort the truth.”

Eichstaedt says the work also raises questions about how LLMs are being deployed and how they might influence and manipulate users. “Until just a millisecond ago, in evolutionary history, the only thing that talked to you was a human,” he says.

Eichstaedt adds that it may be necessary to explore different ways of building models that could mitigate these effects. “We’re falling into the same trap that we did with social media,” he says. “Deploying these things in the world without really attending from a psychological or social lens.”

Should AI try to ingratiate itself with the people it interacts with? Are you worried about AI becoming a bit too charming and persuasive? Email [email protected].

Airplanes of the Future Could Be Fitted With Feather-Like Flaps

These findings could be hugely important for the future of the aviation industry. Climate change is making weather conditions more unpredictable and severe. Over the past four decades, the frequency of extreme turbulence events has increased by 55 percent. To ensure passenger safety, aircraft must become more resilient and capable of performing agile maneuvers in challenging conditions without compromising aircraft stability and passenger safety.

At the same time, air traffic volume is continuing to increase, making it crucial to explore innovations that enhance aircraft efficiency and can help decarbonize flying without having to rely solely on innovations in fuel. Passive advancements could not only help with this, but would do so without depending on complex electronic systems.

Yet the path to getting such technology adopted commercially is challenging—and this has been the case for a lot of other animal-inspired technologies. For instance, in the 1980s, scientists discovered that sharks have small protrusions, called riblets, covering their bodies, which reduce drag as they glide through water. They wondered if applying a similar design to aircraft could significantly cut fuel consumption. In 1997, researchers quantified that the shark-skin-style riblets can reduce drag on airplanes by nearly 10 percent. However, commercial testing on real aircraft didn’t begin until 2016.

Lufthansa Technik, a German aerospace company, eventually developed AeroSHARK, an aircraft surface technology inspired by shark skin. “Today, 25 aircraft across seven airlines have been modified with our sharkskin technology, and the number is steadily growing,” says Lea Klinge, spokesperson at Lufthansa Technik. She adds that such innovations require decades of research, and that integrating new solutions into existing fleets without disrupting operations remains a major challenge.

When considering how to scale these feather-inspired flaps, “there are some logistical challenges in terms of what kind of materials we can make those flaps out of or how we can properly attach them to the wings,” Wissa says. And rolling out such an innovation would not be as simple as adding the plastic film to the small prototype aircraft in the team’s experiment. “Oftentimes, integrating innovative solutions at a commercial level can quickly become complex and multidisciplinary,” says Ruxandra Botez, an aerospace engineer at the university ETS Montreal. An aircraft has to go through a variety of safety tests and certifications, which can easily take several years. Botez also notes that most modern aircraft are built with incremental improvements on previous models, with manufacturers reluctant to stray far from existing designs.

Lentink, however, argues that focusing solely on commercial scalability is the wrong approach. He adds that if innovations with clear scalability are the only ones to be tested, researchers won’t think outside the box. “If you truly want to innovate in aerospace, then you do have to come up with these completely wild ideas,” he says. Staying too close to the final application limits engineers’ ability to create new things. He believes that the covert-feather-inspired flaps, in their current guise, probably aren’t close to immediate application. “But I don’t see it as criticism,” he says. “I see it as researchers developing critical ideas that can now be developed further in this technological pipeline towards an application.”

The scientists WIRED spoke to stress that the future of aircraft design must continue drawing inspiration from nature. Birds are more agile, capable, and maneuverable than anything humans have built. “If we want to create aircraft that can fly as efficiently and adaptably in unpredictable conditions, we’ll inevitably need to incorporate aspects of bird flight into next-generation designs,” says Sedky.

Even if they don’t make it onto large commercial planes, Wissa says these feather-inspired innovations could be game-changing for small aircraft, which are expected to play a major role in the future of aviation, such as in package delivery or urban air mobility—there are multiple startups trying to develop flying taxi services, for example. Such aircraft will likely need to take off and land in tight spaces. These innovations could boost lift and control during such high-angle maneuvers.

“As aircraft get smaller, they also become more susceptible to environmental factors like gusts, high winds, and turbulent airflows,” Wissa explains. Equipped with these flaps, small flying vehicles of the future might be able to handle “gusts that would have thrown an aircraft out of the sky.”

How Trump’s Tariffs Will Disrupt Key Industries in Mexico

The US government has imposed tariffs of 25 percent on all imports from Mexico and Canada. The measure promoted by Donald Trump threatens the free-trade system that the three countries have maintained for more than 30 years.

Even before the confirmation that the tariffs went into effect on March 4, Marcelo Ebrard, head of the Mexican Ministry of Economy, warned that these taxes would represent an approximate cost of $20.5 billion for about 89 million American families. He also warned of the possible inflationary impact on products such as computers, televisions, refrigerators, agricultural goods, auto parts, and vehicles.

Mexico is a key trading partner for the United States. Between January and November 2024, Mexican exports totaled $466.6 billion, while American exports reached $309.4 billion.

In Mexico, these tariffs will particularly affect the automotive and electronics industries, which represent approximately 46 percent of Mexican exports, with a combined value of around $200 billion.

The Automotive Industry Is at Risk

The automotive industry has shown significant regional integration under the United States-Mexico-Canada Agreement (USMCA). This agreement allows foreign companies that produce in Mexico or Canada and use locally sourced materials to export their products to the United States at low tax rates.

The Trump administration argues that this condition has been exploited by China to benefit its auto industry. Mexico has become the third-largest exporter of vehicles worldwide. Between 2022 and 2023, its sales grew by 14.3 percent and reached a value of $188.9 million, according to the World Trade Organization. Most of these units are shipped to the United States, although the origin of many can be traced back to China, which has established itself as Mexico’s main auto supplier, with exports reaching $4.6 billion in 2023, according to the Ministry of Economy.

Mexico’s National Auto Parts Industry has warned that the imposition of tariffs on Mexican imports will weaken trade, reduce competitiveness in the region, and affect economic stability. In a statement, it stressed that the automotive and auto parts sector is a pillar of North American exports, with the capacity to generate more than 11 million jobs in the USMCA countries. The association foresees that assemblers in Mexico could reduce production by as much as 1 million units this year due to the new taxes, which would affect product availability, job creation, and the supply chain.

The main states producing automotive parts in Mexico are Mexico City, Chihuahua, and Nuevo León. Experts say that the most affected companies would be assemblers of US, Japanese, and European origin. Ebrard has estimated that the new tax burden would affect 12 million households in the United States, with an increase in spending of up to $10.4 billion in this area. As an example, he pointed out that 88 percent of the pickups sold in the United States come from Mexico and are assembled by companies such as General Motors, Ford, and Stellantis.

The minister of economy emphasized that the tariffs would represent the United States shooting itself in the foot, as it would directly impact its own automotive companies, which depend on Mexican production to supply their domestic market.

Electronics Prices on the Rise

The electronics and appliance sector will also be affected. In November 2024, Mexican exports of electrical and electronic equipment reached $8.9 billion, 89 percent of which was destined for the US. The production of these devices is concentrated in Baja California, Chihuahua, and Nuevo León, where thousands of jobs and assembly plants could be at risk.

Trump’s tariffs will have significant implications for US consumers. An SEC study estimates that the additional levy would cost an extra $7.1 billion for 40 million families purchasing computers. Likewise, it is expected that around 32 million households would pay up to $2.4 million more when purchasing new monitors, and around 5 million families would assume an extra expense of $817 million when purchasing refrigerators.

Elon Musk’s $1 Spending Limit Is Paralyzing Federal Agencies

The impacts have hit the National Park Service as well. One employee was poised to go on a trip to oversee road maintenance at a national monument when the change went into effect on February 20. “Unless I want to pay for it myself, I can’t go. I can’t pay for my hotel, my rental car, fuel for the car. Now I can’t carry out the mission,” the employee says. “Today, instead of focusing on other work, I’m focused on three different contingencies on how to handle this. Do I go? Do I call my engineering team and tell them to reschedule? And if so, when? The project is on an indefinite hold.”

A memo written to staff at the National Park Service specified that “all travel that is NOT related to national security, public safety, or immigration enforcement should be canceled if it begins on Wednesday, February 26, through the end of March 2025.” A long-term decision on the travel policy, it said, will come “at a later date.” Some NPS staffers were able to travel in February despite not getting official clearance. They have now been told no travel will be allowed in March. To date, roughly 75 trips have been canceled or rescheduled, according to a source familiar with the situation.

The National Park Service did not respond to a request for comment from WIRED.

Some government employees say they were given a warning prior to the change being announced on February 20. “We went out and bought cases and cases of toilet paper the night before,” another current employee at the National Park Service says. “There’s a general acknowledgement that things are going to break.”

That employee works in the Pacific West Region, which manages federal land in California, Hawaii, Oregon, Washington, Idaho, and Nevada, as well as parks in Arizona, Montana, Guam, and American Samoa. While the GSA did allow for the possibility of exceptions to the clamp-down, the employee claims there are only four purchase cards with spending limits above $1 available for the entire region.

Some of these parks pay for services like internet and wireless on purchase cards—leaving staffers wondering if their work devices could soon be cut off. “Before someone can fix a bathroom a work order has to be issued,” the current employee explains. “That happens electronically. Like any business, we rely on email, Teams, and chat to get things done.”

The spending limits reflect Musk’s belief in zero-based budgeting. After he purchased Twitter, he slashed the budget to zero and forced employees to justify every expense. He also froze people’s corporate credit cards.

“With the Twitter pausing of payments, at some point we were in a meeting at 1 am on a Saturday, and it was like, ‘Hey, let’s turn the credit cards off to see what bounces, and what happens,’” explained angel investor Jason Calacanis on the All In podcast in February. (Calacanis was part of Musk’s transition team at Twitter.) “And of course, we started getting calls … The people who come first, they’re probably the ones who are in on the biggest grift.”

Employees see it a different way. “There are so many controls in place to make sure fraud doesn’t happen,” alleges the current NPS staffer. “I honestly believe the only fraud occurring is being committed by Musk, [Russell] Vought, and [Donald] Trump.”

Kate Knibbs and Aarian Marshall contributed to this reporting.

Trump’s FDA Cuts Are Putting Drug Development at Risk

Budget and staffing cuts at the Food and Drug Administration orchestrated by President Donald Trump could prevent new drugs “from being developed, approved, or commercialized in a timely manner, or at all,” according to dozens of annual reports sent by pharmaceutical companies to the Securities and Exchange Commission in late February.

“The Trump Administration has enacted several executive actions that could impose significant burdens on, or otherwise materially delay, the FDA’s ability to engage in routine regulatory and oversight activities,” says one filing from Xenon Pharmaceuticals, a company based in Canada that researches treatments for epilepsy. “If these executive actions impose constraints on the FDA’s ability to engage in oversight and implementation activities in the normal course, our business may be negatively affected.”

In February, Elon Musk’s so-called Department of Government Efficiency laid off hundreds of FDA employees, causing widespread panic about the status of grant applications, active clinical trials, and drug approvals. Just over a week later, it reinstated a handful of staffers who regulate the American food supply and review medical devices.

The move did little to quell concerns from various pharmaceutical companies, who worry that any disruption to the slow moving bureaucracy could cause the FDA to grind to a halt. Before new drugs can go to market, the FDA has to conduct regular inspections and reviews, a process that can take years. Many recent SEC filings say if the FDA stops this work, these drugs simply can’t be released.

Biopharmaceutical company Rezolute, which develops treatments for a rare, congenital form of low blood sugar, says that DOGE’s mandate to “reduce expenditures” at agencies like the FDA would slow down their work, according to an SEC filing. The company adds, “Our business is dependent upon the FDA and the FDA’s ability to timely respond to our drug development activities.”

Some pharmaceutical companies mentioned DOGE’s work at the National Institutes of Health, which provides tens of billions of dollars for drug research and development to corporations and universities around the world.

Clover Health, a health care company that provides Medicare, said in a recent filing that DOGE is creating “pressures on and uncertainty” around the federal budget, including the debt ceiling, which it claims “may negatively impact the economic environment, curtail spending on health and health care related matters.”

Some filings also warned about the possibility that Trump will overhaul existing drug regulations, which would cost additional time and money to comply with. A recent Trump executive order mandates broad deregulation across federal agencies, and new Health and Human Services secretary Robert F. Kennedy Jr. has expressed agreement and proposed his own budget cuts.

DOGE recently froze $1.5 billion in funding for medical research, then later unfroze some of the funds. The back-and-forth left companies unclear on whether they can ultimately expect the US government to back their research. iBio, a company based in San Diego that studies antibody treatments for obesity and cardio-metabolic disorders, said in a filing that it’s currently “unclear” how Trump’s health care policy will affect grant funding for research in its field.

Amazon’s Delivery Drones Are Grounded. The Birds and Dogs of This Texas Town Are Grateful

As flights began picking up early last year, the people who live closest to the drone depot started fuming over the noise. Residents appealed to the city to do something, but Texas lawmakers have essentially banned cities from regulating drones, leaving local officials powerless.

Smith, who previously worked as a city public works director in charge of big projects, says the only developments that he had seen attract this amount of opposition were landfills. The drone pushback also attracted international media attention, sparking concerns at city hall.

Public records show city officials have suggested numerous options for Amazon’s potential relocation, including a mall about 4 miles up the highway from the current building. As of December, though, College Station mayor John Nichols wrote in one email, Amazon had not shared any recent updates about the status of its search. Nichols tells WIRED that as of last week, he still hadn’t heard anything.

Lessons Learned

Some College Station residents who live near Amazon’s drone depot site say the noise and property value concerns raised by their neighbors are overblown. “What were people like when lawnmowers first came out?” says Kim Miller, who could hear the drones above her front yard and once received a dog toy by air as a gift from someone. “Progress has some drawbacks,” she says.

Raylene Lewis, a real estate agent at NextHome Realty Solutions, which has listings near the drone base, says home buyers don’t seem to mind the prospect of drones overhead. In fact, more people are curious about whether a prospective home is within Prime Air’s delivery range, she says. Lewis’ own house happens to be just outside the perimeter, but she says she would love to use the service “whether I want cookies or my medicine or pen and paper for a kid’s project.”

Lewis believes Amazon should have been more forthright about its operations and should have offered a local customer service center for people with questions and concerns. With updates still difficult to come by, some residents remain frustrated. Several of them learned about Amazon’s fleet grounding only after inquiries from WIRED.

The grounding followed two crashes—one related to rainy weather and the other operator miscommunications—of the roughly 80-pound drones, according to Bloomberg. Amazon’s Stephenson disputes the cause of the pause, saying it was initiated to “safely and properly conduct a software update” and that services will resume following FAA approval.

The accidents have introduced a new worry in College Station. “These events really bring out that Amazon is using my neighborhood as a test zone,” says Monica Williams, a teenager who opposed the company’s expansion plan.

For now, more drones are poised to hit the skies. In Dallas-Fort Worth, Amazon rival Wing is awaiting FAA review to triple its maximum deliveries per day to 30,000. In Florida, the company is seeking review to provide up to 60,000 deliveries each day, starting from Walmart supercenters in the Orlando and Tampa metro areas.

Smith and others in College Station expect that as long as drones aren’t constantly buzzing near homes—and new versions get increasingly quieter—complaints will be minimal. He believes Amazon learned a valuable lesson in his city, and he’s glad the company is adjusting its course. His garden is certainly happy to have him back.

Additional reporting by Aarian Marshall.

‘OpenAI’ Job Scam Targeted International Workers Through Telegram

“Regrettably, I found no available source online to know more about this organization except for those registrations,” wrote the complainant. “They are collecting huge amounts of investment from third world countries in Asia.”

One of the FTC complaints alleges that over 6,000 people in Bangladesh were potentially impacted by the OpenAi-etc job scam. The ages listed in the FTC complaints range from teenagers to people in their fifties, with locations spread across multiple Bangladesh cities, from Dhaka to Khulna.

“My next trading date was 29 August, 2024,” wrote another complainant. “I made the trade with my whole amount in the evening. But, suddenly, the OpenAI company vanished. I didn’t withdraw any money but lost both capital and profit. Now, I am in a great economic crisis, as I am a normal school teacher.”

Niko Felix, a spokesperson for OpenAI, declined to answer questions about whether the startup was previously aware of the “OpenAi-etc” scam, or if they planned to take action against the fraudsters. But he did share that OpenAI is investigating the matter. The alleged scam website is no longer available online, and WIRED was not able to contact the people behind “OpenAi-etc” prior to publication.

A Telegram spokesperson using the name Remi Vaughn tells WIRED that the company monitors its platform for scams, such as those allegedly carried out by OpenAi-etc, which used the messaging app to communicate with people who believed they were working for the company.

“Telegram actively moderates harmful content on its platform, including scams,” Vaughn says in a statement sent to WIRED through the messaging platform. “Moderators empowered with custom Al and machine learning tools proactively monitor public parts of the platform and accept reports from users and organizations in order to remove millions of pieces of harmful content each day.”

The usual pattern of a crypto job scam is to trick people into depositing some kind of digital currency into a fake account the victim believes they have control over, until the perpetrator drains it one day without warning. While this specific rug pull used OpenAI’s branding to allegedly dupe its victims, a crypto job scam can happen with the name of any company that has enough widespread recognition for criminals to capitalize on.

“These social engineering scams are designed to lower our natural suspicion and to make us complicit in our own deception,” says Arun Vishwanath, a cybersecurity expert and author of The Weakest Link. “For job scams, they try to turn our ambitions and inherent trust in brands into a vulnerability.” Similar to so-called pig butchering investment scams, a key component often includes direct messages over a long period of time to cultivate a sense of trust with the targets.

Although comparable job scams happen all over the world, Vishwanath believes that Asian cultural norms of so-called high power distance, where there’s more acceptance of interpersonal hierarchies, are a contributing factor. “Authorities are expected to ask you things and make you do things,” he says. “And you just comply.” Scammers are taking advantage of this by imitating authority figures and leaning into the sense of urgency inherent to searching for a job.

Bangladeshi citizens on the difficult hunt for reliable work have increasingly been targeted by job scammers in recent years. Lies about international job opportunities have left throngs of would-be workers stranded in Malaysia, and at least three cases of kidney organ theft were reported by people lured to India with false promises of work.

OpenAI Launches GPT-4.5 for ChatGPT—It’s Huge and Compute-Intensive

GPT-4.5 is here, and OpenAI’s newest generative AI model is bigger and more compute-intensive than ever—it’s supposedly also better at understanding what ChatGPT users mean with their prompts. Users who want to be part of the first wave to try GPT-4.5, labeled as a research preview, will be required to pay for OpenAI’s $200-a-month ChatGPT Pro subscription.

Prior to this launch, 2025 has already been filled with new AI model releases. Anthropic recently put out a hybrid reasoning model for its Claude chatbot. Before that, Chinese researchers at DeepSeek rocked Silicon Valley with their release of a powerful model trained on a tiny budget, prompting OpenAI to drop a “mini” version of its reasoning model a month ago.

Alongside these new releases, OpenAI promised to invest billions into building the AI infrastructure required to fuel more massive models. And GPT-4.5 is a reiteration of this current strategy from the startup: Bigger is better.

ChatGPT 4.5 is in stark contrast to other recent AI innovations, like DeepSeek’s R1, that attempted to match the performance of a frontier model with as few resources as possible. OpenAI still sees a strong path forward through scaling its models. According to researchers who worked on GPT-4.5, this kind of maximalist mindset to model development has captured more of the nuances of human emotions and interactions.

They see the model’s size as also potentially helping this iteration hallucinate with less frequency than past releases. “If you know more things, you don’t need to make things up,” says Mia Glaese, who leads OpenAI’s alignment team and human data team. Exactly how big or compute-intensive GPT-4.5 is remains unclear—OpenAI declined to share specific numbers.

So, what’s it like to use the new model? Pro users are getting a first look, with rollouts for Plus and Team users scheduled for next week and Enterprise and Edu the week afterwards. GPT-4.5 supports the web search and canvas feature as well as uploads of files and images, though it’s not yet compatible with the AI Voice Mode.

In the announcement post for GPT-4.5, OpenAI included academic benchmark results that show the model getting vastly outpaced by the o3-mini model when it comes to math, and slightly upstaged on science as well, though GPT-4.5 did score a little higher on language benchmarks. The researchers say these measurements don’t capture the full story. “We would expect the difference in 4.5 to be similar to the experience difference of 4 to 3.5,” says Glaese. For the user, prompts related to subjects like writing or programming may yield stronger results, with the back-and-forth interactions feeling more “natural” overall. She hopes all of the chats from this limited release will help them to better understand what GPT-4.5 excels at, as well as its limitations.

Unlike those released as part of OpenAI’s “o” series, GPT-4.5 is not considered to be a reasoning model. The company’s CEO, Sam Altman, posted on social media earlier in February that OpenAI would “ship GPT-4.5, the model we called Orion internally, as our last non-chain-of-thought model.” Nick Ryder, who leads the company’s foundations-in-research team, clarified that this statement pertained to streamlining OpenAI’s product road map, not its research road map. The startup is not just looking into reasoning models, but users can expect to see a more blended experience overall with future releases for ChatGPT where you don’t have to pick which one to use.

Amazon Restricted Vaginal Health Products for Being ‘Potentially Embarrassing’

Startup founder Tara Langdale-Schmidt says her company’s devices, known as VuVa, are designed to soothe the pelvic and vaginal pain and discomfort that she and millions of other women have experienced. But over the past decade, Langdale-Schmidt alleges, Amazon has repeatedly shut down VuVatech’s product listings—sometimes she says for violating what she views as prudish “adult” content rules. Last year, Amazon blocked VuVatech from adding a discount coupon to one product because its automated systems identified the item as “potentially embarrassing or offensive,” according to a screenshot seen by WIRED.

“We just have to stop this insanity with being embarrassed about things,” Langdale-Schmidt says. “There’s no difference from your vagina than your ear, your nose, your mouth. It is another place on your body, and I don’t know how we got to this point where it’s not OK to talk about it. I just don’t get it.”

Amazon spokesperson Juliana Karber tells WIRED that no VuVatech products have been blocked for adult policy violations over the past year, though Langdale-Schmidt says that’s because she’s given up trying to list new items. Karber adds that Amazon understands the importance of sexual health and wellness products to its customers and has thousands of merchants offering them. The small fraction of those products categorized as “adult” are subject to additional policies “to best ensure we serve them to intending customers and not surprise customers who are not looking for them,” Karber says.

Companies and organizations working in sexual health and wellness have for years railed against what they view as excessive restrictions on their content by shopping, advertising, and social platforms. A new survey and an accompanying report shared exclusively with WIRED by the Center for Intimacy Justice, a nonprofit that advocates for more fair online policies and draws some funding from sexual health organizations, underscore just how widespread these concerns are.

In the survey, which was completed in March 2024, VuVatech and more than 150 other businesses, nonprofit groups, and content creators spanning six continents reported challenging experiences sharing content about their work, promoting products, and using other services from Amazon, Meta, Google, and TikTok. Those surveyed included organizations offering tools and support for pregnancy, menopause, and other health topics.

Jackie Rotman, founder and CEO of the Center for Intimacy Justice, says ending what she describes as biased censorship against women’s health would unlock valuable commercial opportunities for tech platforms, and is also simply the right thing to do. “Bots, algorithms, and employees who are not knowledgeable in this topic should not be prohibiting women’s access to important and valuable health products,” she says.

Google, Meta, TikTok, and Amazon say they stand by their policies, some of which are aimed at protecting minors from encountering potentially sensitive content. The companies also all note that they offer ways for users and advertisers to appeal enforcement actions.

Some of the offerings cited in the Center for Intimacy Justice’s survey include unregulated products that have limited or mixed evidence supporting their effectiveness. Complaints about content moderation on tech platforms also extend well beyond sexual health issues. But Rotman, the nonprofit group leader, says its survey findings show how widely sexual health tools and information are suppressed across the internet.

Google’s Taara Hopes to Usher in a New Era of Internet Powered by Light

Alphabet’s “moonshot factory,” known as X, has long cultivated craziness in its edgy projects. Perhaps the most outlandish was Loon, which aimed to deliver internet via hundreds of high-flying balloons. Loon eventually “graduated” from X as a separate Alphabet division, before its parent company determined that the business model simply didn’t work. By the time that balloon popped in 2021, one of the Loon engineers had already left the project to form a team specifically working on the data transmission part of connectivity—namely, delivering high-bandwidth internet via laser beams. Think fiber optics without the cables.

It’s not a new idea, but over the past few years, Taara, as the X project is called, has been quietly perfecting real-world implementations. Now, Alphabet is launching a new generation of its technology—a chip—that it says will not only make Taara a viable option to deliver high-speed internet, but potentially usher in a new era where light does much of the work that radio waves do today, only faster.

Taara Chip 1.

Courtesy of X, the Moonshot Company.

Taara chip close-up.

Courtesy of Kristen Sard/ X, the Moonshot Company

The former Loon engineer who leads Taara is Mahesh Krishnaswamy. Ever since he first went online as a student in his hometown of Chennai, India—he had to go to the US embassy to get access to a computer—he has been obsessed with connectivity. “Since then, I made it my life’s mission to find ways to bring people like me online,” he tells me at X’s headquarters in Mountain View, California. He found his way to America and worked at Apple before joining Google in 2013. That’s where he first got motivated to use light for internet connectivity—not for transmissions to ground stations, but for high-speed data transfer between balloons. Krishnaswamy left Loon in 2016 to form a team to develop that technology, called Taara.

My big question to Krishnaswamy was, who needs it? In the 2010s, companies like Google and Facebook made a big deal of trying to connect “the next billion users” with wild projects like Loon and high-flying drones. (Facebook even worked on the idea that’s at the core of Taara—“invisible beams of light … that transmit data 10 times faster than current versions,” as my former colleague Jessi Hempel wrote in 2016. Mark Zuckerberg quietly shut the project down in 2018.) But now, through a variety of approaches, more of the world can get connected. That’s one reason X cited for ending Loon. Most conspicuously, Elon Musk’s Starlink can provide internet anywhere in the world, and Amazon is planning a competitor named Kuiper.

But Krishnaswamy says the global connectivity problem is far from solved. “Today there are like 3 billion people still unconnected, and there is a dire need to bring them online,” he says. In addition, many more people, including in the US, have internet speeds that can’t even support streaming. As for Starlink, he says that in denser areas, a lot of people have to share the transmission, and each of them gets less bandwidth and slower speeds. “We can offer 10, if not 100 times more bandwidth to an end user than a typical Starlink antenna, and do it for a fraction of the cost,” he claims, though he seems to be referring to Taara’s future capabilities and not its current status.

Over the past few years, Taara has made advances in implementing its technology in the real world. Instead of beaming from space, Taara’s “light bridges”—which are about the size of a traffic light—are earthbound. As X’s “captain of moonshots” Astro Teller puts it, “As long as these two boxes can see each other, you get 20 gigabits per second, the equivalent of a fiber-optic cable, without having to trench the fiber-optic cable.” Light bridges have complicated gimbals, mirrors, and lenses to zero in on the right spot to establish and hold the connection. The team has figured out how to compensate for potential line-of-sight interruptions like bird flights, rain, and wind. (Fog is the biggest impediment.) Once the high-speed transmission is completed from light bridge to light bridge, providers still have to use traditional means to get the bits from the bridge to the phone or computer.

Sanam Mozaffari and Devin Brinkley in the Taara lab.

Courtesy of Peter Prato/ X, the Moonshot Company

Taara’s unit in the field.

Courtesy of X, the Moonshot Company

Taara is now a commercial operation, working in more than a dozen countries. One of its successes came in crossing the Congo River. On one side was Brazzaville, which had a direct fiber connection. On the other, Kinshasa, where internet used to cost five times more. A Taara light bridge spanning the 5-kilometer waterway provided Kinshasha with nearly equally cheap internet. Taara was also used at the 2024 Coachella music festival, augmenting what would have been an overwhelmed cellular network. Google itself is using a light bridge to provide high-speed bandwidth to a building on its new Bayview campus where it would have been difficult to extend a fiber cable.

Mohamed-Slim Alouini, a professor at King Abdullah University of Science and Technology who has worked in optics for a decade, describes Taara as “a Ferrari” of fiber-free optical. “It’s fast and reliable but quite expensive.” He says he spent around $30,000 for the last light bridge setup he bought from Alphabet for testing.

That could change with Taara’s second-generation offering. Taara’s engineers have used innovative light-augmenting solutions to create a silicon photonic chip that not only will shrink the gadgetry in its light bridges to the size of a fingernail—replacing the mechanical gimbals and costly mirrors with solid-state circuitry—but will eventually allow a single laser transmitter to pair with multiple receptors. Teller says that Taara’s technology could trigger the same kind of transformation that we saw when data storage moved from tape drives to disk drives to our current solid-state devices.

Taara lightbridge alignment.

In the shorter term, Teller and Krishnaswamy hope to see Taara technology used to provide high-bandwidth internet when fiber is unavailable. One use case would be delivering elite connectivity to an island community just offshore. Or providing high-speed internet after a natural disaster. But they also have more ambitious dreams. Teller and Krishnaswamy believe that 6G might be the final iteration to use radio waves. We’re hitting a wall on the electromagnetic spectrum, they say. Traditional radio frequency bands are congested and running out of available bandwidth, making it harder to meet our growing demand for fast, reliable connectivity. “We have an enormous worldwide industry that’s about to go through a very complex change,” says Teller. The answer, as he sees it, is light—which he thinks might be the key element in 7G. (You think the hype for 5G was bad? Just wait.)

Professor Alouini agrees. “Those of us who are working in the field fully believe that at some point we will need to rely on optics, because the spectrum is getting congested,” he says. Teller envisions thousands of Taara chips in mesh networks, throwing beams of light, in everything from phones to data centers to autonomous vehicles. “So to the extent that you buy this, it’s going to be a very big deal,” he says.

DOGE’s Misplaced War on Software Licenses

Because agencies sometimes get bulk or government-specific discounts, it can also be more affordable to buy software licenses on behalf of their private contractors. “It’s a very clear way for agencies to manage costs,” the ex-official says.

Every government agency has its own unique structure, including many subagencies or units, each with their own software needs. That could help explain other alleged licensing issues DOGE called out this week, including that GSA has “3 different ticketing systems running in parallel” and multiple tools for running unspecified trainings.

In a separate post this week, DOGE called out the Department of Labor for allegedly licensing five cybersecurity programs, each for more than 20,000 users, despite having only about 15,000 employees. The post also cited the department holding 380 Microsoft 365 productivity software licenses with zero users, installing only 30 out of the 128 Microsoft Teams conference rooms it licensed, and using only 22 out of 129 Photoshop licenses. The post also referenced unused licenses for “VSCode,” the shorthand name for an entirely free Microsoft tool for writing code; the company does sell a paid alternative known as Visual Studio.

Microsoft declined to comment. Adobe, which develops Photoshop, did not respond to a request to comment.

While DOGE may have failed to present a full picture of wasteful spending, it’s true that the federal government has at times struggled to effectively manage its use of software licenses. Numerous watchdog groups inside the government have found instances of wasteful spending on software in the past.

Members of Congress have been trying for years to get agencies to address the issue, the former federal official says. The Strengthening Agency Management and Oversight of Software Assets Act, or SAMOSA Act, which passed the House last year with bipartisan support but stalled in the Senate, would have required agencies to do what DOGE is doing now: Assess existing software contracts, consolidate licenses where possible, and get better deals to keep costs down. The legislation aimed to give agencies more bargaining power over the handful of big tech firms that dominate government software contracting, according to the former official.

“If Elon [Musk] wanted to do this the right way, they would work with Congress to pass the SAMOSA Act,” the official says. “So people who will be there even when DOGE leaves can enter into smarter, less expensive contracts. They should be setting a repeatable process whereby agencies will constantly reevaluate their software needs and get better performance for lower costs.”

Triplette, of the Coalition for Fair Software Licensing, credited DOGE for examining licensing issues. “I know there is a lot of concern about what DOGE is doing, but this is one area that there is hope and possibility,” she says.

Other federal contracting experts and congressional offices have told WIRED that DOGE should not lose sight of bigger targets while scrounging for savings. There were 11 federal contracting programs for information technology that each accounted for over $1 billion in spending during the government’s last fiscal year, which ran from October 2023 through September 2024, according to an analysis for WIRED by Deltek, whose GovWin IQ tool tracks procurement. Contracts are often broken up into smaller pieces, and among those task orders, over $1 billion has been spent on six individual task orders related to IT over the past few years. They are led by a Dell deal with the Department of Veterans Affairs and a Booz Allen Hamilton agreement with the Pentagon.

The SEC Is Abandoning Its Biggest Crypto Lawsuits

In July, on the campaign trail, Donald Trump promised a crowd of bitcoiners that he would fire previous SEC chair Gary Gensler if reelected. “I didn’t know he was that unpopular,” said Trump, referring to the crowd’s rapturous response to the pledge. In November, after Trump won the election, the crypto industry got to help handpick the nominee to replace Gensler, landing on Paul Atkins, a former SEC commissioner who has expressed the view that crypto businesses have been treated unfairly in the US. (Atkins remains sidelined for now, pending confirmation.)

The argument advanced by the crypto industry—that it was subjected to wrongful lawsuits by a politically-motivated regulator—is likely to have struck a chord with Trump, says Anthony Scaramucci, founder of crypto-focused investment firm SkyBridge Capital and former communications director for Trump. “Trump is a big believer in lawfare,” says Scaramucci. “If you go to Trump saying you’re a victim of lawfare…he’s going to side with that.”

According to Stand With Crypto, a nonprofit pushing for bespoke crypto regulation in the US, more than 250 pro-crypto representatives were elected to Congress in 2024. The crypto industry claimed high-profile scalps in races in which it had invested most heavily: In Ohio, incumbent Democratic senator Sherrod Brown, depicted as an arch-villain in crypto circles, was unseated by Republican Bernie Moreno. Through Defend American Jobs, the crypto industry spent more than $40 million in support of Moreno.

Having witnessed the efficacy of the crypto lobbying machine, politicians concerned about the security of their own seats are potentially less likely to voice opposition to the industry in future, claims Scaramucci, which in turn increases the chances of crypto-specific regulation falling into place and crypto-focused legislation making it into law.

“The Democrats have gotten the life scared out of ‘em,” claims Scaramucci. “You have to have regulatory clarity. With the Trump administration, you’ll get that. You’ve got enough Democrats scared that will side with [Republicans] to create that.”

A Double-Edged Sword

The SEC’s retreat from its outstanding lawsuits against crypto businesses will be received as an early signal of the agency’s intent to work arm-in-arm with the industry to come up with a set of rules to govern crypto transactions and products.

That rulebook will clear up the question at the heart of the lawsuits: Which crypto assets should be classified as securities, the specific type of investment product over which the SEC has jurisdiction, and in what context?

“I think the industry sees regulators willing to work across the table from them,” says Coy Garrison, a former SEC attorney and partner at law firm Steptoe. “That’s the difference. Four years ago, the other side of the table was just the enforcement arm.”

But it’s a mistake to interpret the SEC’s withdrawal from the crypto-related cases as a total loosening of the leash, claims Garrison. “Sometimes, it’s easy for people to only see the top line,” he says. “The SEC is still going to be policing potential fraudulent activity within its jurisdiction relating to crypto.”

After a Violent Kidnapping, Crypto Elites Hire Bodyguards

In the early morning of January 21, David Balland and his wife were forced at gunpoint into separate vehicles outside their home in Méreau, a commune in the opulent Loire Valley, France. The kidnappers had targeted Balland, who cofounded cryptocurrency wallet company Ledger, with the goal of winning a ransom, a prosecutor has claimed.

The kidnappers communicated their demands—the specifics of which have not been disclosed by law enforcement—to Éric Larchevêque, another Ledger cofounder. To flush out the full payment, they severed one of Balland’s fingers. French authorities dispatched more than 200 officers to investigate.

On January 22, officers rescued Balland from a property in the neighboring town of Châteauroux. They later discovered his wife—trussed up but otherwise unharmed—in the back of a beaten up van.

These events were relayed by Paris prosecutor Laure Beccuau at a press conference on January 23 and in subsequent reports. The authorities had arrested 10 people suspected to be connected to the kidnapping, Beccuau announced. For acts of “torture, barbarity, and extortion,” she said, those arrested face up to life in prison if convicted.

Ledger declined to comment, citing the ongoing investigation and the need to afford privacy to Balland. In an X post, Ledger CEO Pascal Gauthier wrote, “We are deeply relieved that David and his wife have been released.”

The grisly kidnapping—which came shortly after a crypto executive was held for ransom in Canada and the assassination of the United Healthcare CEO—has spooked the crypto industry. To protect themselves, wealthy crypto figures are turning to bodyguard services, which have experienced an influx of requests, sources with knowledge of the physical security sector tell WIRED.

“Like any human emotion, fear is a significant motivator … The headlines certainly mobilize a lot of that concern,” says Adam Healy, a former US Marine and chief executive at crypto-focused cybersecurity company Station 70, who frequently helps industry contacts to secure physical security services. “Demand has grown considerably.”

Because not every case of kidnap or extortion is reported, it is difficult to objectively assess the actual risk to wealthy figures in crypto. In making the fear of kidnap more acute, the headlines benefit the private security businesses, themselves incentivized to overstate the threat.

However, it is the case that people who control large amounts of crypto are more exposed to violent extortion than the typical executive by the nature of the technology: Unlike regular currency, crypto is stored in digital wallets protected only by alphanumeric keys. Because crypto transactions are irreversible, if a bad actor can coerce someone into handing over their key, they gain unfettered access to the coins in their wallet.

“That is one of the principles on which crypto was founded—the principle of self-custody. Not your keys, not your crypto,” says one crypto executive who has previously used bodyguard protection, who asked to remain anonymous for personal safety reasons. “It’s the equivalent to stuffing [your money in] your mattress.”

Over time, crypto organizations have taken steps to dilute the risk associated with self-custody, including by storing coins in special wallets that require the signature of multiple people for any transactions to take place. Sometimes they go as far as to split wallet keys into several shards, each of which can be stored in a separate high-security bunker across the globe. But even elaborate measures only go so far in disincentivizing kidnap and attempted extortion.

Boston Dynamics Led a Robot Revolution. Now Its Machines Are Teaching Themselves New Tricks

Marc Raibert, the founder and chairman of Boston Dynamics, gave the world a menagerie of two- and four-legged machines capable of jaw-dropping parkour, infectious dance routines, and industrious shelf stacking.

Raibert is now looking to lead a revolution in robot intelligence as well as acrobatics. And he says that recent advances in machine learning have accelerated his robots’ ability to learn how to perform difficult moves without human help. “The hope is that we’ll be able to produce lots of behavior without having to handcraft everything that robots do,” Raibert told me recently.

Boston Dynamics might have pioneered legged robots, but it’s now part of a crowded pack of companies offering robot dogs and humanoids. Only this week, a startup called Figure showed off a new humanoid called Helix, which can apparently unload groceries. Another company, x1, showed off a muscly-looking humanoid called NEO Gamma doing chores around the home. A third, Apptronik, said it plans to scale up the manufacturing of his humanoid, called Apollo. Demos can be misleading, though. Also, few companies disclose how much their humanoids cost, and it is unclear how many of them really expect to sell them as home helpers.

The real test for these robots will be how much they can do independent of human programming and direct control. And that will depend on advancements like the ones Raibert is touting. Last November I wrote about efforts to create entirely new kinds of models for controlling robots. If that work starts to bear fruit we may see humanoids and quadrupeds advance more rapidly.

Boston Dynamics’ Spot RL Sim in action. Credit: Boston Dynamics

Boston Dynamics sells a four-legged robot called Spot that is used on oil rigs, construction sites, and other places where wheels struggle with the terrain. The company also makes a humanoid called Atlas for research. Raibert says Boston Dynamics used an artificial intelligence technique called reinforcement learning to upgrade Spot’s ability to run, so that it moves three times faster. The same method is also helping Atlas walk more confidently, Raibert says.

This Refinery Wants to Make Sustainable Aviation Fuel Mainstream. Trump’s Cuts Could Kill It

Follow the 10-inch pipeline that stretches south from Minneapolis–Saint Paul International Airport, and after 13 miles you’ll find yourself at a potentially major future hub for sustainable aviation fuel in the upper Midwest.

In a deal announced in September, the Koch Industries-owned Pine Bend Refinery in Rosemount, Minnesota, would receive sustainable aviation fuel (SAF)—fuel made using nonpetroleum feedstocks, like renewable materials or waste—blend it into its conventional jet fuel, and send the fuel mix through the pipeline to the airport, where it will be used by Delta Airlines and other carriers.

The proponents of the project, including its financial backers Deloitte and Bank of America, said last year that up to 60 million gallons of blended fuel, containing potentially up to 50 percent SAF, would be flowing by 2025, and they aim to produce 1 billion gallons of SAF per year, which would surpass the demand at the Minneapolis airport and make the hub a producer for additional airports around the country and potentially the world. (There is no time frame for the refinery to hit this larger target.)

But this project—and others like it—depends on financial-support frameworks like tax credits or loans that were set out under the Biden administration’s signature 2022 climate law, the Inflation Reduction Act, and which now may be taken away.

Late last month, Montana Renewables, one of only a few US SAF producers—and the planned provider of the first batches for the Minnesota hub—said that the first $782 million tranche of a $1.67 billion loan from the Department of Energy was undergoing a “tactical delay to confirm alignment with White House priorities.” (US senator Steve Daines of Montana said on February 11 that the funding, which is factored into finance the project, has since been unfrozen.)

Federal incentives like this are “on life support” under the Trump administration, says Scott Irwin, a professor of agricultural and consumer economics at the University of Illinois. According to Irwin, the Trump administration has so far shown it is willing to completely dismantle the Inflation Reduction Act and its funding, even if it means clawing back promises to farmers and businesses that have already begun implementing climate-smart work.

While state incentive programs along with low-carbon fuel standards still support SAF production, Irwin does not see who could step in to replace the federal government in the credit stack if the funding is withdrawn. “Without the incentives in the Inflation Reduction Act, SAF is dead in the water,” he says.

The Refinery Math Already Didn’t Add Up

Late last year WIRED spoke to Jake Reint, vice president of external affairs for Flint Hills Resources, the company within Koch Industries that owns Pine Bend and several other refineries, petrochemical plants, and pipelines. (Flint Hills is the company that struck the deal with Delta and other corporate partners to use the blended fuel from Pine Bend.) Even before Donald Trump was reelected, Reint articulated the challenges of ramping up the SAF industry.

Under the plan, Pine Bend will offload the SAF produced elsewhere from trucks operated by Shell, the distributor in the arrangement, and then blend it with its existing jet fuel mix. This will require Pine Bend to order specialty pumps that Reint says won’t be delivered for a year—and they can’t be ordered until a thorough planning process is completed, including precise estimates for short-term demand.

A Team of Female Founders Is Launching Cloud Security Tech That Could Overhaul AI Protection

While working on internet-of-things security in the mid-2010s, Alex Zenla realized something troubling.

Unlike PCs and servers that touted the latest, greatest processors, the puny chips in IoT devices couldn’t support the cloud protections other computers were using to keep them siloed and protected. As a result, most embedded devices were attached directly to the local network, potentially leaving them more vulnerable to attack. At the time, Zenla was a prodigious teen, working on IoT platforms and open source, and building community in Minecraft IRC channels. After puzzling over the problem for a few years, she started working on a technology to make it possible for nearly any device to run in its own isolated cloud space, known as a “container.” Now, a decade later, she’s one of three female cofounders of a security company that’s trying to change how cloud infrastructure shares resources.

Known as Edera, the company makes cloud workload isolation tech that may sound like a niche tool, but it aims to address a universal security problem when many applications or even multiple customers are using shared cloud infrastructure. Ever-growing AI workloads, for example, rely on GPUs for raw processing power instead of standard CPUs, but these chips have been designed for maximum efficiency and capacity rather than with guardrails to separate and protect different processes. As a result, an attacker that can compromise one region of a system is much more likely to be able to pivot from there and gain more access.

“These problems are very hard, both on the GPU and the container isolation, but I think people were too wiling to accept trade-offs that were not actually acceptable,” Zenla says.

After a $5 million seed round in October, Edera today announced a $15 million series A led by Microsoft’s venture fund, M12. The latest in granular funding news is nothing remarkable in itself, but Edera’s momentum is notable given the current, muted VC landscape and, particularly, the company’s all-female roster of founders, which includes two trans women.

In the United States and around the world, venture funding for tech startups has always been a boys club with the vast majority of VC dollars going to male founders. Female founders who do get initial backing have a more difficult time raising subsequent rounds than men and face much steeper odds founding another company after one fails. And those headwinds are only getting stronger as the Trump administration in the US and Big Tech mount an assault on diversity, equity, and inclusion initiatives meant to raise awareness about these types of realities and foster inclusivity.

“We can’t ignore the fact that we are a small minority in our industry, and that a lot of the changes that are happening around us are not lifting us up,” says Edera CEO and cofounder Emily Long. “We take great pride and responsibility in continuing to be in the front on this. Since our founding, I can’t tell you how many incredibly technical, talented women have proactively asked us to hire them from large institutions. So you start to see that just by existing and being different, you are showing what’s possible.”

For Zenla, Long, and cofounder Ariadne Conill, who has an extensive background in open source software and security, the goal of developing Edera’s container isolation technology is to make it easy (at least relatively speaking) for network engineers and IT managers to implement robust guardrails and separation across their systems so an exploited vulnerability in one piece of network equipment or a rogue insider situation won’t—and can’t—spiral into a disastrous mega-breach.

“People have legacy applications in their infrastructure and use end-of-life software; there’s no way to do security and believe that you can always patch every existing vulnerability,” Long says. “But it inherently creates a pretty large risk profile. And then on top of that, containers were never originally designed to be isolated from each other, so you had to choose between innovation and performance and security, and we don’t want people to have that trade-off anymore.”

Ads Popped Up on Drivers’ Screens. There May Be More on the Way

Last week, a Jeep driver turned to Reddit to do what people do best on the site—complain. Every time they hit the brakes on their Jeep, they wrote, a promotion for an extended warranty plan popped up in the center console. “Press the ‘call’ button to speak to a specialist,” they say the ad encouraged, welcoming the user to use their Bluetooth connection to complete the upsell then and there.

Ads are annoying and occasionally insidious; an ad that repeatedly appears inside one’s own car more so. According to other online posts on Reddit and Jeep forums, the issue goes back several years, affecting several models of Jeeps.

Stellantis, which owns Jeep, says the repetitive nature of the promotion was a glitch. “This is an isolated incident affecting fewer than ten vehicles at this time limited to the US,” Dan Reid, a spokesperson for the automaker, wrote in a statement. He acknowledged, though, that Stellantis shows other drivers in-vehicle promotions too. Dodge owners, for example, get an infotainment push after 60 days of purchase offering the “Dodge Complete Performance Package,” a comprehensive warranty offering.” Stellantis says that, on average, customers receive about two in-vehicle messages annually, containing safety, maintenance, or marketing information.

Should ads be showing up inside cars at all? Safety experts have serious questions about the practice. But as automakers continue to explore how to make more money off their increasingly digitized and internet-connected wheels, the temptation to upsell on the center console may be too good to pass up.

The Data-Powered Upsell

Today’s new cars come stuffed with some 1,000 to 3,000 semiconductor chips that help to control and coordinate everything from lowering windows and adjusting mirrors to deploying airbags, enabling collision avoidance systems, pairing phones with center consoles and displays, and coordinating navigation. Add in the internet and drivers’ cell phones, and you get an ongoing “conversation” of data between individual cars and the manufacturers that build them.

Those manufacturers’ vision of the future has been pretty consistent over the past few years, says Mark Wakefield, the global automotive market lead at consulting firm AlixPartners. “In an ideal world, they’ve totally blended the mobile phone and different services and apps into a nice, big coherent ecosystem that travels from work to play to home,” he says. It’s the perfect platform for advertising, for upselling, and for pushing premium trimmings. As with Jeep’s extended warranty offer, many services can show up with just a remote software push.

Selling a car is a tight margin business; selling software-enabled features, less so. AlixPartners research estimates the connected vehicle services market will be worth more than $473 million globally this year, accounting for 11 percent of automotive revenue streams. By 2032, it could be worth $1.68 billion—more than a quarter of manufacturers’ revenue.

Some of these software-related plays have already worked out for automakers. General Motors brought in some $2 billion in revenue last year from OnStar, its subscription-based security and entertainment services division, and executives are sticking with a prediction first made in 2021 that the automaker will eventually make more than $20 billion annually in software-related revenue. Customers have already shown that they’re willing to shell out a few bucks for services that heats or cools drivers’ cars before they get in, or turn on the garage lights when they get back home.

Anthropic Launches the World’s First ‘Hybrid Reasoning’ AI Model

The difference between a conventional model and a reasoning one is similar to the two types of thinking described by the Nobel-prize-winning economist Michael Kahneman in his 2011 book Thinking Fast and Slow: fast and instinctive System-1 thinking and slower more deliberative System-2 thinking.

The kind of model that made ChatGPT possible, known as a large language model or LLM, produces instantaneous responses to a prompt by querying a large neural network. These outputs can be strikingly clever and coherent but may fail to answer questions that require step-by-step reasoning, including simple arithmetic.

An LLM can be forced to mimic deliberative reasoning if it is instructed to come up with a plan that it must then follow. This trick is not always reliable, however, and models typically struggle to solve problems that require extensive, careful planning. OpenAI, Google, and now Anthropic are all using a machine learning method known as reinforcement learning to get their latest models to learn to generate reasoning that points toward correct answers. This requires gathering additional training data from humans on solving specific problems.

Penn says that Claude’s reasoning mode received additional data on business applications including writing and fixing code, using computers, and answering complex legal questions. “The things that we made improvements on are … technical subjects or subjects which require long reasoning,” Penn says. “What we have from our customers is a lot of interest in deploying our models into their actual workloads.”

Anthropic says that Claude 3.7 is especially good at solving coding problems that require step-by-step reasoning, outscoring OpenAI’s o1 on some benchmarks like SWE-bench. The company is today releasing a new tool, called Claude Code, specifically designed for this kind of AI-assisted coding.

“The model is already good at coding,” Penn says. But “additional thinking would be good for cases that might require very complex planning—say you’re looking at an extremely large code base for a company.”

AI Assistants Join the Factory Floor

The basic machine for grinding a steel ball bearing has been the same since around 1900, but manufacturers have been steadily automating everything around it. Today, the process is driven by a conveyor belt, and, for the most part, it’s automatic. The most urgent task for humans is to figure out when things are going wrong—and even that could soon be handed over to AI.

The Schaeffler factory in Hamburg starts with steel wire that is cut and pressed into rough balls. Those balls are hardened in a series of furnaces, and then put through three increasingly precise grinders until they are spherical to within a tenth of a micron. The result is one of the most versatile components in modern industry, enabling low-friction joints in everything from lathes to car engines.

That level of precision requires constant testing—but when defects do turn up, tracking them down can present a puzzle. Testing might show a defect occurring at some point on the assembly line, but the cause may not be obvious. Perhaps the torque on a screwing tool is off, or a newly replaced grinding wheel is impacting quality. Tracking down the problem means comparing data across multiple pieces of industrial equipment, none of which were designed with this in mind.

This too may soon be a job for machines. Last year, Schaeffler became one of the first users of Microsoft’s Factory Operations Agent, a new product powered by large language models and designed specifically for manufacturers. The chatbot-style tool can help track down the causes of defects, downtime, or excess energy consumption. The result is something like ChatGPT for factories, with OpenAI’s models being used on the backend thanks to the company’s partnership with Microsoft’s Azure.

Kathleen Mitford, Microsoft’s corporate vice president for global industry marketing, describes the project as “a reasoning agent that operates on top of manufacturing data.” As a result, Mitford says, “the agent is capable of understanding questions and translating them with precision and accuracy against standardized data models.” So a factory worker might ask a question like “What is causing a higher than usual level of defects?” and the model would be able to answer with data from across the manufacturing process.

The agent is deeply integrated into Microsoft’s existing enterprise products, particularly Microsoft Fabric, its data analytics system. This means that Schaeffler, which runs hundreds of plants on Microsoft’s system, is able to train its agent on data from all over the world.

Stefan Soutschek, Schaeffler’s vice president in charge of IT, says the scope of data analysis is the real power of the system. “The major benefit is not the chatbot itself, although it helps,” he says. “It’s the combination of this OT [operational technology] data platform in the backend, and the chatbot relying on that data.”

Despite the name, this isn’t agentic AI: It doesn’t have goals, and its powers are limited to answering whatever questions the user asks. You can set up the agent to execute basic commands through Microsoft’s Copilot studio, but the goal isn’t to have the agent making its own decisions. This is primarily AI as a data access tool.

What Elon Musk Got Wrong About Why Federal Retirement Is Still Managed out of a Limestone Mine

Along with the Civil Service Commission, other federal agencies, including the National Archives, the Office of Civil Defense (the precursor to the Federal Emergency Management Agency), and the Social Security Administration began storing records in the Boyers facility around the same time. J. G. Franz, then office manager of the Boyers mine, told a newspaper reporter in 1966 that federal agencies have “backup equipment for everything” stored in a special area of Boyers to protect the records in the event of nuclear fallout.

Franz told a local newspaper that workers “hope we will never have to worry about a nuclear explosion,” but that if one happened, the mine would be safely sealed off, according to newspaper archives reviewed by WIRED. “The mine is equipped with a 30-day supply of food and supplies for all of the employees.”

At the time, the staff at Boyers were reportedly able to process about 600 pounds of records each day bussed to the facility straight from Washington, DC. They relied on the recently constructed interstate highway system for timely deliveries. In fact, the federal government built an exit off Pennsylvania’s Interstate 80 specifically for “quick access to the mine in case of an emergency,” according to an article in the Pittsburgh Press.

There are other practical benefits that make old mines a good place to store records. For one, their typically rural and secluded settings create a layer of natural security from other types of threats. Repurposed mines provide “excellent fire protection,” and immunity from events like “flood, theft, civil disorder, aircraft crashes, tornadoes, lightning,” noted a 1999 Iron Mountain presentation for the National Archives.

Carmichael tells WIRED that access to the underground facilities he’s visited tend to be tightly controlled, often through heavily guarded entrances. These facilities also frequently have maze-like designs that would likely discourage or confuse thieves if they somehow got inside.

Several current managers of repurposed limestone mines told WIRED that their caves are naturally between 55 and 70 degrees Fahrenheit, optimal temperature for most storage situations. John Smith, director of industrial real estate for the company that manages the limestone storage facility Carefree Industrial Park near Kansas City, Missouri, said that this means utility costs are “dramatically lower” compared to above-ground facilities. His main expenses are associated with ventilation, since caves tend to be very humid.

It All Goes Wrong

Shortly before the Civil Service Commission arrived at Boyers, the US federal retirement apparatus was a mess. A 1951 government report found that “an adequate record system” wasn’t even in place yet and urged Congress to “insist” one be created. At first, it seemed like the team at Boyers was able to turn things around. The News-Herald reported in 1966 that with just 55 employees, the system at the mine was operating “with the same efficiency and effectiveness as it used to in Washington, DC.”

However, as the number of retirees continued to climb, things fell into disarray. By the early 1980s, the Office of Personnel Management was being audited to find the root causes of excessive delays in processing retirement claims. In 1981, the Government Accountability Office recommended that OPM “develop a long-term plan for automating the retirement claims process.”

BYD’s Free Self-Driving Tech Might Not Be Such a Boon After All

Strictly speaking, God’s Eye is the camera, ultrasonic radar, and lidar array alone, split into A, B, and C variants, with A being best. The system’s operating software is known as DiPilot, introduced in 2020 on the BYD Han, and now with the good, better, and best tiers of DiPilot 100, 300, and 600.

God’s Eye A ships with DiPilot 600 and bristles with high-end cameras and radar, and front- and side-facing lidar sensors. This best system will be fitted to BYD’s luxury Yangwang EVs, including the U9 supercar. “The video of the U9 [on the track] was theater,” believes Rainford, who hasn’t heard of any autonomous driving system that can “make a car’s tires squeal around corners.”

Rainford adds that BYD is playing catch-up: “2024 was a breakout year for urban-level autonomous driving systems in China, with the front-runners of Li Auto, XPeng, Nio, and Huawei joined by rivals such as Zeekr, Wey, and even more affordable brands like Leapmotor.”

God’s Eye B has cameras, radar, and one lidar unit married to DiPilot 300, and will be fitted to Denza, Song, and BYD’s other high-end cars. Both A and B God’s Eye systems offer FSD-style L2+ ADAS driving.

God’s Eye C with DiPilot 100 has cameras and radar, but no lidar, which could be akin to worshipping a “God with nearsightedness,” Peter Norton, associate professor of history in the Department of Engineering and Society at the University of Virginia, tells WIRED.

“Like Tesla’s FSD, drivers with God’s Eye C aren’t supposed to use it away from divided highways. But presumably some BYD drivers, like some Tesla drivers, will use it on ordinary roads anyway—with sometimes potentially lethal consequences,” says Norton, author of a book on autonomous driving. He worries that BYD’s use of divine terminology could lead to a false sense of security. “There’s no attempt to caution drivers about the system’s limitations,” he stresses.

Rainford, too, cautions that God’s Eye isn’t yet perfect. “It’s way overhyped,” he says, pointing to the glowing press coverage of last week’s launch. “I drove DiPilot 100 last year on the BYD Song L, and it was far from great, requiring lever-activated overtakes. Even on the freeway it was not even close to the [LDAS] market leaders in China.”

Even though it’s not yet allowed in China, Tesla’s FSD is believed by some to be technically inferior because it relies solely on cameras and AI, rather than lidar and other sensors.

“Tesla has been overselling the effectiveness of its technology for years,” Michael Brooks, executive director of the nonprofit Center for Auto Safety, told NPR last month. “And a lot of people buy into that. They’re kind of wrapped up in this belief that this is an autonomous vehicle, because it’s tweeted about that way.”

Musk has been promising the imminent arrival of fully autonomous cars since at least 2016. At a Tesla shareholder meeting last year, Musk claimed the number of miles that FSD can drive without human intervention has increased. “It’s headed towards unsupervised full self-driving very quickly, at an exponential pace,” Musk claimed.

Elon Musk Threatens FBI Agents and Air Traffic Controllers With Forced Resignation If They Don’t Respond to an Email

Elon Musk is once again leaving his fingerprints on official communications from the federal government. In an email to staff Saturday afternoon, the Office of Personnel Management, which is stacked with Musk loyalists, told employees to send five bullet points detailing what they accomplished last week and cc their manager. “Failure to respond will be taken as a resignation,” Musk wrote on X.

The move comes after President Trump announced that he wants Musk to be more forceful. “ELON IS DOING A GREAT JOB, BUT I WOULD LIKE TO SEE HIM GET MORE AGGRESSIVE,” he wrote on Truth Social. “REMEMBER, WE HAVE A COUNTRY TO SAVE, BUT ULTIMATELY, TO MAKE GREATER THAN EVER BEFORE. MAGA!”

“Will do, Mr. President!” Musk replied in a post on X.

The memo, which closely resembles a note Musk sent to Twitter staff in June 2023, specifies that employees should not include classified information, links, or attachments in their responses. WIRED has confirmed that employees at the Federal Bureau of Investigation, Internal Revenue Service, National Institutes of Health, and Federal Aviation Administration, which all deal in classified information, received similar notices. The deadline to reply is Monday at 11:59pm EST.

“They’re proving that their only goal is not efficiency but to dismantle democracy by traumatizing federal workers,” says a current federal employee who asked to remain anonymous as they aren’t authorized to speak publicly about their agency. “They see this as a video game where they level up every time they hurt or eliminate a federal worker.”

In recent weeks, the Trump administration has laid off thousands of probationary employees who’ve been in the federal government for just one or two years. The cuts initially hit hundreds of people working on nuclear security as well as veterans and Department of Agriculture employees who are trying to stave off a bird flu pandemic. The so-called Department of Government Efficiency has also effectively frozen or otherwise attempted to dismantle the United States Agency for International Development and the Consumer Financial Protection Bureau.

It is not clear whether OPM has the authority to force federal workers to resign if they do not respond to the email. “I don’t know that anybody can assess what’s legal right now because the agencies that are supposed to act as watchdogs are being dismantled,” says Laurie Burgess, an attorney who has represented a number of Twitter and SpaceX employees in labor disputes. She noted that she has cases set to be heard before the National Labor Relations Board this spring and does not feel confident that the board will still exist by that deadline.

In January, OPM sent federal workers an email with the subject line “Fork in the Road,” mirroring a note Musk sent to Twitter staff in November 2022. OPM told employees to return to the office five days a week, and that the government will employ people who are “reliable, loyal, trustworthy, and who strive for excellence.” Those who did not wish to comply were given a deferred resignation offer, which the White House has said that about 75,000 federal workers accepted.

Microsoft’s New Majorana 1 Processor Could Transform Quantum Computing

THIS ARTICLE IS republished from The Conversation under a Creative Commons license.

Researchers at Microsoft have announced the creation of the first “topological qubits” in a device that stores information in an exotic state of matter, in what may be a significant breakthrough for quantum computing.

At the same time, the researchers also published a paper in Nature and a “road map” for further work. The design of the Majorana 1 processor is supposed to fit up to a million qubits, which may be enough to realize many significant goals of quantum computing—such as cracking cryptographic codes and designing new drugs and materials faster.

If Microsoft’s claims pan out, the company may have leapfrogged competitors such as IBM and Google, who currently appear to be leading the race to build a quantum computer.

However, the peer-reviewed Nature paper only shows part of what the researchers have claimed, and the road map still includes many hurdles to be overcome. While the Microsoft press release shows off something that is supposed to be quantum computing hardware, we don’t have any independent confirmation of what it can do. Nevertheless, the news from Microsoft is very promising.

By now you probably have some questions. What’s a topological qubit? What’s a qubit at all, for that matter? And why do people want quantum computers in the first place?

Quantum Bits Are Hard to Build

Quantum computers were first dreamed up in the 1980s. Where an ordinary computer stores information in bits, a quantum computer stores information in quantum bits—or qubits.

An ordinary bit can have a value of 0 or 1, but a quantum bit (thanks to the laws of quantum mechanics, which govern very small particles) can have a combination of both. If you imagine an ordinary bit as an arrow that can point either up or down, a qubit is an arrow that can point in any direction (or what is called a “superposition” of up and down).

This means a quantum computer would be much faster than an ordinary computer for certain kinds of calculations—particularly some to do with unpicking codes and simulating natural systems.

So far, so good. But it turns out that building real qubits and getting information in and out of them is extremely difficult, because interactions with the outside world can destroy the delicate quantum states inside.

Researchers have tried a lot of different technologies to make qubits, using things like atoms trapped in electric fields or eddies of current swirling in superconductors.

Tiny Wires and Exotic Particles

Microsoft has taken a very different approach to build its “topological qubits.” They have used what are called Majorana particles, first theorized in 1937 by Italian physicist Ettore Majorana.

Majoranas are not naturally occurring particles like electrons or protons. Instead, they only exist inside a rare kind of material called a topological superconductor (which requires advanced material design and must be cooled down to extremely low temperatures).

DOGE Put Him in the Treasury Department. His Company Has Federal Contracts Worth Millions

There is some precedent for corporate executives to simultaneously work in the US government. When the US was at war in the early 1900s, the federal government recruited business leaders to fill key posts. They retained their private sector jobs and wages; the government pitched in a $1 annual salary to the executives who became known as “dollar-a-year men.” Congress later raised concerns that some of them had engaged in self-dealing.

Since then, other executives have continued to retain their jobs as they serve on government boards and commissions, typically in a part-time capacity. But maintaining a day-to-day operational role in both the federal government and at a corporation is now virtually unheard of, says David E. Lewis, a political scientist who wrote a book on appointed government bureaucrats. “Most persons in regular executive positions divest themselves of private interests before government service,” he says.

Trump, according to his company, has handed management of his businesses, including hotels and golf courses, to his children for the duration of his presidency (though he reportedly still takes meetings that have raised questions among ethics experts). Musk, who is CEO of Tesla and SpaceX and has oversight of four other companies, including X and Neuralink, has been a vocal figure in DOGE’s operations, but the White House has said he’s not actually in charge—without specifying who is leading the project. Some of the other individuals associated with DOGE are otherwise unemployed, have taken leave, or maintain dual roles but at lower levels than chief executive.

Krause is the only Trump administration official identified so far as being a CEO and a day-to-day decisionmaker inside one particular agency. After years of working as an executive at chip companies, Krause joined Florida-based Cloud Software Group in 2022. The company was created that year as part of a private-equity-backed acquisition of Citrix, followed by a merger with Tibco, another tech company. At the time, Citrix was saddled with an extensive amount of debt and generating essentially stagnant revenues, and while Tibco had not recently publicly disclosed its finances, analysts had considered the company’s outlook to be “negative.”

The US government, including state and local agencies, is expected to spend $287 billion on technology this year, or about 14 percent of overall US tech spending, according to Forrester, a research and advisory company. Whether DOGE’s efforts to boost the quality and efficiency of federal IT systems will lead that spending to increase or decrease isn’t clear. So far, DOGE has both tried to purchase emerging technologies and moved to cancel some existing contracts. But Krause’s inside access could potentially provide an advantage to Cloud Software at a pivotal moment for the company.

Over the past couple of years, Cloud Software has laid off thousands of people and faced accusations that it potentially became lax with cybersecurity. Cloud Software’s most well-known offering, Citrix, enables groups of workers to access data and run apps that are located on a remote machine. But increasing adoption of tools that can operate on any device has chipped away at some of Citrix’s dominance, according to Will McKeon-White, senior analyst for infrastructure and operations at Forrester. There are other options now, he says, including from Microsoft and smaller companies such as Island.

Cloud Software’s Tibco program, which helps workers automate tasks such as adding a new user to multiple internal databases, is often mentioned in the wrong sort of conversations these days, according to David Mooter, a Forrester principal analyst. “They tend to come up more when somebody wants to abandon them,” he says.

That said, some Cloud Software services are more affordable than alternatives for governments, and they also are better suited for the older infrastructure used by some agencies. Last year appears to have been one of Citrix’s best in a long time financially, says Shannon Kalvar, a research director for enterprise systems management and other areas at IDC. One reason for the upswing is that Citrix has put more emphasis on catering to the feature demands of its largest customers, including governments.

DOGE Sparks Surveillance Fear Across the US Government

The insider threat programs at departments such as Health and Human Services, Transportation, and Veterans Affairs, also have policies that protect unclassified government information, which enable them to monitor employees’ clicks and communications, according to notices in the Federal Register, an official source of rulemaking documents. Policies for the Department of the Interior, the Internal Revenue Service, and the Federal Deposit Insurance Corporate (FDIC), also allow collecting and assessing employees’ social media content.

These internal agency programs, overseen by a national task force led by the attorney general and director of national intelligence, aim to identify behaviors that may indicate the heightened risk of not only leaks and workplace violence, but also the “loss” or “degradation” of a federal agency’s “resources or capabilities.” Over 60 percent of insider threat incidents in the federal sector involve fraud, such as stealing money or taking someone’s personal information, and are non-espionage related, according to analysis by Carnegie Mellon researchers.

“Fraud,” “disgruntlement,” “ideological challenges,” “moral outrage,” or discussion of moral concerns deemed “unrelated to work duties” are some of the possible signs that a worker poses a threat, according to US government training literature.

Of the 15 Cabinet-level departments such as energy, labor, and veterans affairs, at least nine had contracts as of late last year with suppliers such as Everfox and Dtex Systems that allowed for digitally monitoring of a portion of employees, according to public spending data. Everfox declined to comment.

Dtex’s Intercept software, which is used by multiple federal agencies, is one example of a newer class of programs that generate individual risk scores by analyzing anonymized metadata, such as which URLs workers are visiting and which files they’re opening and printing out on their work devices, according to the company. When an agency wants to identify and further investigate someone with a high score, two people have to sign off in some versions of its tool, according to the company. Dtex’s software doesn’t have to log keystrokes or scan the content of emails, calls, chats, or social media posts.

But that isn’t how things work broadly across the government, where employees are warned explicitly in a recurring message when they boot up their devices that they have “no reasonable expectation of privacy” in their communications or in any data stored or transmitted through government networks. The question remains if and to what extent DOGE’s operatives are relying on existing monitoring programs to carry out Trump’s mission to rapidly eliminate federal workers that his administration views as unaligned with the president’s agenda or disloyal.

Rajan Koo, the chief technology officer of Dtex tells WIRED that he hopes the Trump administration will adjust the government’s approach to monitoring. Events such as widespread layoffs coupled with a reliance on what Koo described as intrusive surveillance tools can stir up an environment in which workers feel disgruntled, he says. “You can create a culture of reciprocal loyalty,” says Koo, or “the perfect breeding ground for insider threats.”

Already Overwhelmed

Sources with knowledge of the US government’s insider threat programs describe them as largely inefficient and labor intensive, requiring overstretched teams of analysts to manually pore through daily barrages of alerts that include many false positives. Multiple sources said that the systems are currently “overwhelmed.” Any effort by the Trump administration to extend the reach of such tools or widen their parameters—to more closely surveil for perceived signs of insubordination or disloyalty to partisan fealties, for instance—likely would result in a significant spike in false positives that would take considerable time to comb through, according to the people familiar with the work.

In an email last month seeking federal employees’ voluntary resignations, the Trump administration wrote that it wanted a “reliable, loyal, trustworthy” workforce. Attempts to use insider threat programs to enforce that vision could be met by a number of legal challenges.

The National Institute of Standards and Technology Braces for Mass Firings

Sweeping layoffs architected by the Trump administration and the so-called Department of Government Efficiency may be coming as soon as this week at the National Institute of Standards and Technology (NIST), a non-regulatory agency responsible for establishing benchmarks that ensure everything from beauty products to quantum computers are safe and reliable.

According to several current and former employees at NIST, the agency has been bracing for cuts since President Donald Trump took office last month and ordered billionaire Elon Musk and DOGE to slash spending across the federal government. The fears were heightened last week when some NIST workers witnessed a handful of people they believed to be associated with DOGE inside Building 225, which houses the NIST Information Technology Laboratory at the agency’s Gaithersburg, Maryland campus, according to multiple people briefed on the sightings. The DOGE staff were seeking access to NIST’s IT systems, one of the people said.

Soon after the purported visit, NIST leadership told employees that DOGE staffers were not currently on campus, but that office space and technology were being provisioned for them, according to the same people.

On Wednesday, Axios and Bloomberg reported that NIST had begun informing some employees that they could soon be laid off. About 500 recent hires who are still in probationary status and can be let go more easily were among those expected to be affected, according to the reports. Three sources tell WIRED that the cuts likely impact lauded technical experts in leadership positions, including three lab directors who were promoted within the last year. One person familiar with the agency tells WIRED that the official layoff notices may come Friday.

The White House and a spokesperson for NIST, which is part of the Department of Commerce, did not yet return requests for comment.

One NIST team that has been fearing cuts because of its number of probationary employees is the US AI Safety Institute (AISI), which was created after former President Joe Biden’s sweeping executive order on AI issued in October 2023. Trump rescinded the order shortly after taking office last month, describing it as a “barrier to American leadership in artificial intelligence.”

The AI Safety Institute and its roughly two dozen staffers has been working closely with AI companies, including rivals to Musk’s startup xAI like OpenAI and Anthropic, to understand and test the capabilities of their most powerful models. Musk was an early investor in OpenAI and is currently suing the startup over its decision to transition from a non-profit to a for-profit corporation.

AISI’s inaugural director, Elizabeth Kelly, announced she was leaving her role earlier this month. Several other high-profile NIST leaders working on AI have also departed in recent weeks, including Reva Schwartz, who led NIST’s Assessing Risks and Impacts of AI program, and Elham Tabassi, NIST’s chief AI advisor. Kelly and Schwartz declined to comment. Tabassi did not respond to a request for comment.

US Vice President JD Vance recently signaled the new administration’s intent to deprioritize AI safety at the AI Action Summit, a major international meeting held in Paris last week that AISI and other government staffers were not invited to attend, according to three familiar with the matter. “I’m not here this morning to talk about AI safety,” Vance said in his first major speech as VP. “I’m here to talk about AI opportunity.”

Microsoft Hosted Explicit Videos of This Startup Founder for Years. Here’s How She Got Them Taken Down

At the start of last August, Point de Contact told WIRED that only two images on four different Microsoft servers remained. “We deeply regret that this issue took almost 10 months of communication between the victim, Microsoft and us as an NGO to be resolved,” the NGO said in an email at the time.

Microsoft digital safety chief Gregoire says Liu’s situation has spurred her team to try to improve reporting processes and relationships with victim aid groups. Point de Contact initially flagged links over which the company didn’t have control, according to Gregoire. She declined to elaborate on the circumstances. Dirani says this explanation was never communicated to him, and it remains unclear why the links were not “actionable.”

Only after Powell cornered Thomas over Liu’s case did Microsoft obtain the URLs upon which it could act. “We’re thankful, to be perfectly honest, to the spontaneous connection at TrustCon,” Gregoire says. But it shouldn’t be needed again: Point de Contact now has a more direct way to stay in touch, she says.

Other victim aid groups say their relationships with tech giants remain challenging. Last year, a WIRED investigation revealed that executives at Google rejected numerous ideas raised by staff and outside advocates that aimed to proactively counter access to problematic imagery in search results. Some survivors have found that the fastest way to get content removed is by filing copyright claims, a tactic those working in the online safety industry say is inadequate.

The lack of consistency in policies and processes among tech companies contributes to delays in securing takedowns, according to Emma Pickering, the head of technology facilitated abuse at Refuge, the UK’s largest domestic abuse organization. “They all just respond however they choose to—and the response usually is incredibly poor,” she says. (Google introduced new policies in July 2024 to accelerate removals.)

Pickering claims Microsoft, in particular, has been difficult. “I’ve recently been told if I want to engage with them, we need to provide evidence that we use their platform and we promote them,” she says, adding Refuge is trying to engage with as many tech platforms as possible.

Microsoft’s Gregoire says she will look into these concerns and is open to dialogue. The company hopes to stem the need for takedowns, in part, by scaring off perpetrators. This past December, Microsoft sued a group of 10 unknown individuals who allegedly circumvented safeguards on Azure and used an AI tool to generate offensive images, including some Gregoire described as sexually harmful. “We don’t want our services to be abused to cause harm,” she says.

For Liu, the challenges haven’t ended. Videos and images depicting her naked remain available on at least one self-styled “free porn” website, according to links reviewed by WIRED. She also has had to pour her savings into developing Alecto AI because investor support has been lackluster. Some investors allegedly told her not to use her own experience in her pitch. Liu says that when she pitched one male-female pair who were considering investing, they burst into laughter at the idea of building a business around the use of AI to detect online image abuse. Even responding that she had almost killed herself after being victimized did little to sway them, Liu says.

In December 2024, more than four and a half years since her nightmare began, Liu found a glimmer of hope. A proposal she has advocated for in the US Congress to require websites to remove unwanted explicit images within 48 hours nearly ended up on then-President Joe Biden’s desk. It was ultimately shelved, but real progress had never felt so close. Liu and a bipartisan group of over 20 lawmakers haven’t given up; in January, they reintroduced the proposal, which threatens potential penalties of up to $50,000 per violation. Despite objections from rights groups worried about over-censorship, the bill passed the Senate last week. Even Microsoft has gotten behind it.

If you or someone you know needs help, call 1-800-273-8255 for free, 24-hour support from the National Suicide Prevention Lifeline. You can also text HOME to 741-741 for the Crisis Text Line. Outside the US, visit the International Association for Suicide Prevention for crisis centers around the world.

This USAID Program Made Food Aid More Efficient for Decades. DOGE Gutted It Anyways

Chemonics spokesperson Payal Chandiramani says USAID has indicated that Fews Net should qualify for a waiver, and it is working with the agency to determine how it should apply. USAID and the US State Department did not respond to requests for comment.

From the beginning, Fews Net was notable for the sheer range of variables that it factored into its analyses. In addition to looking at more obvious signals—such as drought levels and current grain supplies in different countries—it also examined tertiary causes. “Like locusts,” says historian Christian Ruth, whose forthcoming book on the history of USAID will be published later this year. The swarming grasshoppers can have a devastating effect on crops, especially in Africa, which can then spark or exacerbate ongoing food supply issues. Fews Net used satellite imaging to predict where problematic spikes in locust populations might lead to swarms.

To make predictions, Fews Net leveraged artificial intelligence models that could estimate the likelihood of political conflict. It monitored markets, trade, and on-the-ground household finances in local communities to predict economic causes of famine. The group built various custom software tools and collected data from remote sensors, satellites, and other systems that can monitor vegetation, livestock productivity, crop health, rainfall, land surface temperature, evapotranspiration, and other environmental factors. It also partners with other US government organizations like the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the United States Geological Survey to conduct its analyses, which means that potential cuts by DOGE at those agencies could potentially further stymie Fews Net and its work.

Laura Glaeser, a former senior leader for Fews Net who has worked in the humanitarian food aid sector for decades, says that the program plays a crucial role across the industry in helping determine where and how aid is allocated. She calls it “the standard bearer in terms of the quality and depth of the analysis,” and the voice in the room that ensures “when humanitarian assistance is moving, it’s moving in the most efficient way possible.”

Crippling Fews Net “really does a serious disservice to the ability of the US government to spend US taxpayer dollars effectively,” Glaeser says. “Not only is this challenging us and our ability to respond responsibly with the resources that taxpayers are providing to the US government, but it has all of these trickle-down repercussions.”

While its work is sometimes framed as entirely altruistic, “USAID, historically, has always been a tool of American foreign policy,” says Ruth. Fews Net, like the agency that created it, was no different. While it has obvious humanitarian value, it directly serves the goals of the United States government, and has since its inception during the Cold War.

“The nexus between food insecurity, displacement, grievances, conflict, and national security is very, very tight,” says Dave Harden, who previously oversaw Fews Net as an assistant USAID administrator. As an example, Harden cites drought in Syria in the mid- to late 2010s, which led to mass migrations into Syrian cities, where farmers faced poverty and galvanized riots critical of the Assad regime. The ensuing civil war and violence, Harden notes, led to further mass migration of Syrians into Europe.

Border security is one of the top priorities of the Trump administration, but the tertiary effects of abandoning a program that mitigates migration-spurring disasters may work against its efforts to prevent migrants from coming to the United States. Among other regions, Fews Net previously issued reports for Central America and the Caribbean, two areas where famine and unrest have historically spurred waves of people seeking refuge in the US.

By cutting off a program that has given various US agencies advance notice about a potential spike in people fleeing famine, the Trump administration may be inadvertently hindering its goal to curb illegal border crossings. “The heavy hand DOGE is taking, seemingly universally, when it comes to cuts—frankly, it shows a lack of understanding of how these things work, because they’re complex,” Ruth says.

Meta Will Build the World’s Longest Undersea Cable

Meta has presented the Waterworth Project, an initiative aimed at building a 50,000-kilometer undersea cable that will provide internet connectivity in five continents. The company seeks to strengthen control over the management of its services and guarantee the necessary infrastructure for the development of its products, especially those based in artificial intelligence.

Submarine cables support more than 95 percent of intercontinental internet traffic. “Project Waterworth will be a multibillion dollar, multiyear investment to strengthen the scale and reliability of the world’s digital highways by opening three new oceanic corridors with the abundant, high-speed connectivity needed to drive AI innovation around the world,” the company said in a post about the undertaking. The project was first reported last fall by entrepreneur Sunil Tagare.

The interoceanic cable will be longer than the circumference of the Earth, making it the longest in the world, according to the company. It will have landing points in India, the United States, Brazil, South Africa, and other strategic locations. The company suggests that the construction of this network will bring significant opportunities in the AI space, particularly in the Indian market.

“In India, where we’ve already seen significant growth and investment in digital infrastructure, Waterworth will help accelerate this progress and support the country’s ambitious plans for its digital economy,” the compay’s post reads.

Last week, President Donald Trump and India’s prime minister Shri Narendra Modi issued a joint statement on cooperation between the two countries. The document includes commitments on undersea technologies and mentions Project Waterworth.

“Supporting greater Indian Ocean connectivity, the leaders also welcomed Meta’s announcement of a multibillion, multiyear investment in an undersea cable project that will begin work this year and ultimately stretch over 50,000 km to connect five continents and strengthen global digital highways in the Indian Ocean region and beyond,” the statement released by the White House said.

The new undersea network will use a cable architecture with 24 fiber pairs and routing designed to maximize deep-water routing, reaching up to 7,000 meters. Meta claims to have improved its burial techniques in high-risk areas, such as shallow near-shore waters, to reduce the risk of damage from ship anchors and other external factors.

Meta’s ecosystem, which includes services such as Facebook, Instagram, and WhatsApp, by some accounts comprises as much as 10 percent of fixed traffic and 22 percent of mobile traffic globally. Over the past decade, the company has developed more than 20 undersea cables in collaboration with various partners. Waterworth would be the first project to be fully owned by the company.

With this initiative, Meta will compete directly with Google, which has around 33 undersea cable routes, some of them exclusively owned, according to the specialist firm TeleGeography. Other technology companies such as Amazon and Microsoft are also investing in this sector, although they only own shared interests or acquire capacity on existing cables.

This story originally appeared on WIRED en Español and has been translated from Spanish.

Mira Murati Launches Thinking Machines Lab to Make AI More Accessible

Last September, Mira Murati unexpectedly left her job as chief technology officer of OpenAI, saying, “I want to create the time and space to do my own exploration.” The rumor in Silicon Valley was that she was stepping down to start her own company. Today she announced that indeed she is the CEO of a new public benefit corporation called Thinking Machines Lab. Its mission is to develop top-notch AI with an eye toward making it useful and accessible.

Murati believes there’s a serious gap between rapidly advancing AI and the public’s understanding of the technology. Even sophisticated scientists don’t have a firm grasp on AI’s capabilities and limitations. Thinking Machines Lab plans to fill that gap by building in accessibility from the start. It also promises to share its work by publishing technical notes, papers, and actual code.

Underpinning this strategy is Murati’s belief that we are still in the early stages of AI, and the competition is far from closed. Though it occurred after Murati began planning her lab, the emergence of DeepSeek—which claimed to build advanced reasoning models for a fraction of the usual cost—vindicates her thinking that newcomers can compete with more-efficient models.

Thinking Machines Lab will, however, compete on the high end of large language models. “Ultimately the most advanced models will unlock the most transformative applications and benefits, such as enabling novel scientific discoveries and engineering breakthroughs,” the company writes in a blog post on Tuesday. Though the term “AGI” isn’t used, Thinking Machines Lab believes that upscaling the capabilities of its models to the highest level is important to filling the gap it has identified. Building those models, even with the efficiencies of the DeepSeek era, will be costly. Though Thinking Machines Lab hasn’t shared its funding partners yet, it’s confident that it will raise the necessary millions.

Murati’s pitch has attracted an impressive team of researchers and scientists, many of whom have OpenAI on their résumés. Those include former VP of research Barret Zoph (who is now CTO at Thinking Machines Lab), multimodal research head Alexander Kirillov, head of special projects John Lachman, and top researcher Luke Metz, who left Open AI several months earlier. The lab’s chief scientist will be John Schulman, a key ChatGPT inventor who left OpenAI for Anthropic only last summer. Others come from competitors like Google and Mistral AI.

The team moved into an office in San Francisco late last year and has already started work on a number of projects. Though it’s not clear what its products will look like, Thinking Machines Lab indicates that they won’t be copycats of ChatGPT or Claude, but AI models that optimize collaboration between humans and AI—which Murati sees as the current bottleneck in the field.

American inventor Danny Hillis dreamed of this partnership between people and machines over 30 years ago. A protégé of AI pioneer Marvin Minsky, Hillis built a super computer with powerful chips running in parallel—a forerunner to the clusters that run AI today. He called it Thinking Machines. Ahead of its time, Thinking Machines declared bankruptcy in 1994. Now a variation of its name, and perhaps its legacy, belongs to Murati.

The Ketamine-Fueled ‘Psychedelic Slumber Parties’ That Get Tech Execs Back on Track

We check with everybody to see if we have their consent, from every part of their body, to receive medicine. Then our medical doctor and registered nurse distribute the medicine through a shot—it’s all intramuscular.

If it’s your first time using ketamine and you’re nervous about it, thank God! That’s the way it should be. But there’s also the option to not do ketamine at all: You thought you wanted to do it, and then when push comes to shove, you’re on your journey mat and you’re just like, “I really don’t want to do it.”

Ketamine and psychedelics are not a panacea. We know that it’s not for everyone. You don’t have to push yourself to do this new, innovative, cutting-edge type of therapy. Yes, there is great promise, and the data over and over again makes this area very frothy and enthusiastic. But it’s perfectly OK if you’re scared and anxious. Just listen to your body and heart.

AS: When we transition into the journey, we pull the BackJacks out.

SS: It’s pretty sweet. They have little nests, little beds. They’re all tucked in. They have blankets and pillows, and earplugs if the ambient music playing on the speakers gets too loud. They’re wearing eye masks, because ketamine is more of a dissociative medicine—there is this sense of naturally going inward and being quiet. There are a bunch of stuffed animals there that some people take for their journey.

AS: There’s this huge teddy bear holding a cup of the intramuscular ketamine.

We encourage clients to bring things that are meaningful for them—like a journal, photos of loved ones, loved ones that have passed, rocks. It’s just really loving, grounding, and open.

SS:  It’s like an executive-coaching psychedelic slumber party.

On the first day we do a psycholytic dose of ketamine. It’s not exactly a psychedelic dose, but it lets you kind of just teeter onto the realms. The next day is a mid-dose. That day is all about medicine and integration, and there’s coaching around it.

AS: Four of us facilitate the off-sites. While people are on their ketamine journey, we’re all very attentive. We’re in silent communication with each other. Collectively, we’re really holding this space, seeing what emerges. I mean, we’ve seen over 100 ketamine journeys at this point.

SS: In a supportive clinical setting, the chance of having a bad trip is severely diminished. Also, I hold the faith that there’s no such thing as a bad trip. Rather, there are challenging or uncomfortable journeys.

Let’s say someone’s trauma comes through. One way that could show up is you are screaming, or a lot of energy is just ripping through your body. You’ll get off your mat and you’ll just want to run. You’ll think you’re in a dangerous situation. The first thing we do is make sure you’re in a safe hold so that you feel cared for. We’ll let you take your eye mask off. Some people need a handhold or would like to be walked around the room. All these things help bring you back to now.

The third day is all integration and coaching: “What does this mean for me? How did I feel? And how do I bring something positive from that journey into my everyday life?”

AS: And about a week and a half after, we have a follow-up virtual integration session, focused on the application of what they’ve learned to their leadership.

SS:  One person came in not being able to feel their body. “I’m just a head, and this is my meat sack,” basically is what they said. After the off-site, they were able to pinpoint, “Actually, I feel like I can feel my chest. I can go to other places inside my body and be connected to it.”

AS: People are floating away at the end. They’re like, “I don’t want this to end. Can I integrate this way of being into my life?”

—As told to Elana Klein

Sam Altman Dismisses Elon Musk’s Bid to Buy OpenAI in Letter to Staff

Sam Altman is leaving no room for doubt about his views on an Elon Musk-led bid to take control of OpenAI. In a letter to OpenAI staff Monday, the CEO put the words “bid” and “deal” in scare quotes and said the startup’s board has no interest in the offer.

“Our structure exists to ensure that no individual can take control of OpenAI,” Altman wrote, according to two sources with knowledge of the letter. “Elon runs a competitive AI company, and his actions are not about OpenAI’s mission or values.”

Altman has also told employees that OpenAI’s board, which he sits on, has yet to receive an official offer from Musk and the other investors. If and when this happens, the board plans to reject the bid, according to those same sources. Internally, OpenAI employees reacted to the news with a mixture of fear and exasperation. Parts of Altman’s letter were earlier reported by The Information.

A group of investors led by Musk stunned the tech industry on Monday when they announced an unsolicited offer to buy all of OpenAI’s assets to the tune of $97.4 billion. Musk’s competing AI company, xAI, is backing the bid, as is Valor Equity Partners, a private equity firm run by one of Musk’s closest advisers, Antonio Gracias. Gracias helped advise Musk on his deal to acquire Twitter in 2022 and has been involved with his efforts at the Department of Government Efficiency (DOGE).

“It’s time for OpenAI to return to the open-source, safety-focused force for good it once was,” Musk said in a statement sent to WIRED through his lawyer Marc Toberoff. “We will make sure that happens.”

Musk has sued OpenAI multiple times for, among other things, allegedly violating its original commitments as a nonprofit by transitioning to become a for-profit company. In addition to fighting back in court, OpenAI published a series of emails claiming that Musk knew OpenAI would need to become for-profit in order to pursue artificial general intelligence—and in fact, tried to merge the company with Tesla.

The fight between Musk and Altman puts a spotlight on OpenAI board chair Bret Taylor, who also ran Twitter’s board of directors during Elon Musk’s acquisition of the company. That bid was, in theory, more straightforward. Since Twitter was a public corporation, the board had a clear fiduciary duty to maximize returns. Musk tried to back out of the acquisition, but his advisers ultimately convinced him that wasn’t going to be possible, and he closed on the original terms. Taylor did not respond to a request for comment from WIRED.

OpenAI’s structure is more complicated. Today, the company is a nonprofit with a for-profit subsidiary, but it’s in the process of converting the for-profit arm into a public benefit corporation, which requires OpenAI to name a price for its assets. OpenAI is currently valued at $157 billion based on its latest funding round. The company is in talks with SoftBank about leading a $40 billion investment, which would bring the company’s valuation up to $300 billion.

An Adviser to Elon Musk’s xAI Has a Way to Make AI More Like Donald Trump

A researcher affiliated with Elon Musk’s startup xAI has found a new way to both measure and manipulate entrenched preferences and values expressed by artificial intelligence models—including their political views.

The work was led by Dan Hendrycks, director of the nonprofit Center for AI Safety and an adviser to xAI. He suggests that the technique could be used to make popular AI models better reflect the will of the electorate. “Maybe in the future, [a model] could be aligned to the specific user,” Hendrycks told WIRED. But in the meantime, he says, a good default would be using election results to steer the views of AI models. He’s not saying a model should necessarily be “Trump all the way,” but he argues after the last election perhaps it should be biased toward Trump slightly, “because he won the popular vote.”

xAI issued a new AI risk framework on February 10 stating that Hendrycks’ utility engineering approach could be used to assess Grok.

Hendrycks led a team from the Center for AI Safety, UC Berkeley, and the University of Pennsylvania that analyzed AI models using a technique borrowed from economics to measure consumers’ preferences for different goods. By testing models across a wide range of hypothetical scenarios, the researchers were able to calculate what’s known as a utility function, a measure of the satisfaction that people derive from a good or service. This allowed them to measure the preferences expressed by different AI models. The researchers determined that they were often consistent rather than haphazard, and showed that these preferences become more ingrained as models get larger and more powerful.

Some research studies have found that AI tools such as ChatGPT are biased towards views expressed by pro-environmental, left-leaning, and libertarian ideologies. In February 2024, Google faced criticism from Musk and others after its Gemini tool was found to be predisposed to generate images that critics branded as “woke,” such as Black vikings and Nazis.

The technique developed by Hendrycks and his collaborators offers a new way to determine how AI models’ perspectives may differ from its users. Eventually, some experts hypothesize, this kind of divergence could become potentially dangerous for very clever and capable models. The researchers show in their study, for instance, that certain models consistently value the existence of AI above that of certain nonhuman animals. The researchers say they also found that models seem to value some people over others, raising its own ethical questions.

Some researchers, Hendrycks included, believe that current methods for aligning models, such as manipulating and blocking their outputs, may not be sufficient if unwanted goals lurk under the surface within the model itself. “We’re gonna have to confront this,” Hendrycks says. “You can’t pretend it’s not there.”

Dylan Hadfield-Menell, a professor at MIT who researches methods for aligning AI with human values, says Hendrycks’ paper suggests a promising direction for AI research. “They find some interesting results,” he says. “The main one that stands out is that as the model scale increases, utility representations get more complete and coherent.”

How We’re Keeping Tabs on DOGE

Leah Feiger: And so many have been. Absolutely.

Katie Drummond: So many have been, so my answer has been, this will go through court and it will churn through the legal system, and it will be slow and messy and painful, but that is what the legal system is here to protect and is here to safeguard is our democracy and these checks and balances. This is sort of the last stand, right?

Leah Feiger: Absolutely.

Katie Drummond: The courts are the last stand in terms of our democracy and constitutional integrity. What we are now looking at is the possibility that that may not hold. What would that even begin to look like if that came to pass? I know that you’re not a legal expert in addition to being WIRED’s politics editor, but what have you heard? What have experts told you in the course of your reporting?

Leah Feiger: There’s a lot of people that are saying, “Look, these holds are going to come through. Musk and Trump are going to be appealing them, and then eventually this is going to end in the Supreme Court.” A lot of people are actually taking solace with this. They’re saying, “Yes, the court may be leaning quite Republican ideologically, but these are trained professionals who will understand that these legal systems must be upheld and adhered to.” I’m not as confident in that.

Katie Drummond: Right.

Leah Feiger: I’ll be totally honest. In terms of what happens next, I think that because of, in some ways, the slow march of these court systems, although decisions, even temporary ones, have been coming down really fast, there’s a lot of room to move fast and break things from DOGE’s side meanwhile.

Katie Drummond: Yeah.

Leah Feiger: A lot of these eggs can’t get unscrambled. A lot of these layoffs and firings and foreclosures are … It’s going to be really hard to walk those back once a court is able to finally say, “No, no, no, this just can’t hold.” And that’s—

Katie Drummond: If they can say that at all.

Leah Feiger: If they can say that at all.

Katie Drummond: Right.

Leah Feiger: We’re hearing that concern from experts all across the board right now. We’ve never seen anything like this.

Katie Drummond: We certainly haven’t. Not here in the United States. No.

Leah Feiger: Not here in the United States.

Katie Drummond: Well, in the meantime, we hold our breath. We keep doing the work, and we will keep delivering to all of you, WIRED listeners and WIRED readers, our reporting, what we know as we know it. That is our commitment to you. You can read all the reporting that Leah and her team are doing at WIRED.com. Leah, thank you so much for taking the time to be here with me. I know how busy you are.

Leah Feiger: Thank you so much. I love to talk about government takeovers with you, Katie.

Katie Drummond: Well, now go get a granola bar from my office.

Leah Feiger: About to go steal one immediately.

Katie Drummond: That’s our show for today. We will be back tomorrow with an episode from our regular roundtable, all about the state of dating apps, a little bit of lighthearted counter programming for all of you. If you like what you heard today, make sure to follow Uncanny Valley and rate it on your podcast app of choice. If you’d like to get in touch with any of us for questions, comments, or show suggestions, write to us at [email protected]. Amar Lal at Macro Sound mixed this episode, with engineering support from Jake Lummus. Jordan Bell is our executive producer. Condé Nast’s head of global audio is Chris Bannon, and I’m Katie Drummond, WIRED’s global editorial director. Thank you so much. Bye.