Anysphere, the maker of AI coding assistant Cursor, has raised $900 million at a $9.9 billion valuation, Bloomberg reported. The round was led by returning investor Thrive Capital, with participation from Andreessen Horowitz, Accel, and DST Global. The massive round is Anysphere’s third fundraise in less than a year. The 3-year-old startup secured its previous capital haul of $100 million at a pre-money valuation of $2.5 billion late last year, as TechCrunch was first to report.  AI coding assistants, often referred to as “vibe coders,” have emerged as one of AI’s most popular applications, with Cursor leading the category. Anysphere’s annualized revenue (ARR) has been doubling approximately every two months, a person familiar with the company told TechCrunch. The company has surpassed $500 million in ARR, sources told Bloomberg, a 60% increase from the $300 million we reported in mid-April. Cursor offers developers tiered pricing. After a two-week free trial, the company converts users into paying customers, who can opt for either a $20 Pro offering or a $40 monthly business subscription. Until recently, the majority of the company’s revenue came from individual user subscriptions, Bloomberg reported. However, Anysphere is now offering enterprise licenses, allowing companies to purchase the application for their teams at a higher price point. Earlier this year, the company was approached by OpenAI and other potential buyers, but Anysphere turned down those offers. The ChatGPT maker bought Windsurf, another fast-growing AI assistant, reportedly for $3 billion.

Anysphere, the maker of AI coding assistant Cursor, has raised $900 million at a $9.9 billion valuation, Bloomberg reported. The round was led by returning investor Thrive Capital, with participation from Andreessen Horowitz, Accel, and DST Global. The massive round is Anysphere’s third fundraise in less than a year. The 3-year-old startup secured its previous capital haul of $100 million at a pre-money valuation of $2.5 billion late last year, as TechCrunch was first to report.  AI coding assistants, often referred to as “vibe coders,” have emerged as one of AI’s most popular applications, with Cursor leading the category. Anysphere’s annualized revenue (ARR) has been doubling approximately every two months, a person familiar with the company told TechCrunch. The company has surpassed $500 million in ARR, sources told Bloomberg, a 60% increase from the $300 million we reported in mid-April. Cursor offers developers tiered pricing. After a two-week free trial, the company converts users into paying customers, who can opt for either a $20 Pro offering or a $40 monthly business subscription. Until recently, the majority of the company’s revenue came from individual user subscriptions, Bloomberg reported. However, Anysphere is now offering enterprise licenses, allowing companies to purchase the application for their teams at a higher price point. Earlier this year, the company was approached by OpenAI and other potential buyers, but Anysphere turned down those offers. The ChatGPT maker bought Windsurf, another fast-growing AI assistant, reportedly for $3 billion.

Alienware is offering competitive prices on RTX 5080 equipped gaming PCs to kick off June. Right now you can pick up an Alienware Aurora R16 RTX 5080 gaming PC from $2,449.99 shipped. This is a good price for a well-engineered gaming rig with powerful current generation components, 240mm AIO water cooling, and sensible airflow design that can handle 4K gaming at high frame rates. In the current market, buying a prebuilt gaming PC is the only way to score an RTX 5080 GPU without paying an exorbitant markup. If you were to try to find a 5080 GPU for your do-it-yourself PC build, you'll probably spend nearly as much for the GPU as you would for an entire system.Alienware Aurora RTX 5080 Gaming PC From $2,450Alienware Aurora R16 Intel Core Ultra 7 265F RTX 5080 Gaming PC (16GB/1TB)$2,449.99 at AlienwareAlienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PC (32GB/2TB)Alienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PC (64GB/4TB)New for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PC (32GB/1TB)The prices on the Alienware Aurora R16 model starts range from the bottom end of $2,349.99 to the top end of $3,149.99. Each tier up offers either a CPU upgrade or increased RAM and/or storage:$2,349.99 - Intel Core Ultra 7 265F, 16GB RAM, 1TB SSD$2,799.99 - Intel Core Ultra 9 285K, 32GB RAM, 2TB SSD$3,249.99 - Intel Core Ultra 9 285K, 64GB RAM, 4TB SSDAlienware Area-51 RTX 5080 Gaming PC for $3,599.99New for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PC (32GB/1TB)Dell unveiled the new Alienware Area-51 gaming PC at CES 2025. The chassis looks similar to the 2024 R16 system with aesthetic and cooling redesigns and updated components. The I/O panel is positioned at the top of the case instead of the front, and the tempered glass window now spans the entire side panel instead of just a smaller cutout. As a result, the side panel vents are gone, and instead air intakes are located at the bottom as well as the front of the case. Alienware is now pushing a positive airflow design (more intake than exhaust airflow), which means a less dusty interior. The internal components have been refreshed with a new motherboard, faster RAM, and more powerful power supply to accommodate the new generation of CPUs and GPUs.The GeForce RTX 5080 GPU will run any game in 4KThe RTX 5080 is the second best Blackwell graphics card, surpassed only by the $2,000 RTX 5090. It's about 5%-10% faster than the previous generation RTX 4080 Super, which is discontinued and no longer available. In games that support the new DLSS 4 with multi-frame generation exclusive to Blackwell cards, the gap widens.Nvidia GeForce RTX 5080 FE Review, by Jacqueline Thomas"If you already have a high-end graphics card from the last couple of years, the Nvidia GeForce RTX 5080 doesn’t make a lot of sense – it just doesn’t have much of a performance lead over the RTX 4080, though the extra frames from DLSS 4 Multi-Frame Generation do make things look better in games that support it. However, for gamers with an older graphics card who want a significant performance boost, the RTX 5080 absolutely provides – doubly so if you’re comfortable with Nvidia’s AI goodies."Eric Song is the IGN commerce manager in charge of finding the best gaming and tech deals every day. When Eric isn't hunting for deals for other people at work, he's hunting for deals for himself during his free time.

Every few weeks, it seems like there’s a new headline about a lawyer getting in trouble for submitting filings containing, in the words of one judge, “bogus AI-generated research.” The details vary, but the throughline is the same: an attorney turns to a large language model (LLM) like ChatGPT to help them with legal research (or worse, writing), the LLM hallucinates cases that don’t exist, and the lawyer is none the wiser until the judge or opposing counsel points out their mistake. In some cases, including an aviation lawsuit from 2023, attorneys have had to pay fines for submitting filings with AI-generated hallucinations. So why haven’t they stopped?The answer mostly comes down to time crunches, and the way AI has crept into nearly every profession. Legal research databases like LexisNexis and Westlaw have AI integrations now. For lawyers juggling big caseloads, AI can seem like an incredibly efficient assistant. Most lawyers aren’t necessarily using ChatGPT to write their filings, but they are increasingly using it and other LLMs for research. Yet many of these lawyers, like much of the public, don’t understand exactly what LLMs are or how they work. One attorney who was sanctioned in 2023 said he thought ChatGPT was a “super search engine.” It took submitting a filing with fake citations to reveal that it’s more like a random-phrase generator — one that could give you either correct information or convincingly phrased nonsense.Andrew Perlman, the dean of Suffolk University Law School, argues many lawyers are using AI tools without incident, and the ones who get caught with fake citations are outliers. “I think that what we’re seeing now — although these problems of hallucination are real, and lawyers have to take it very seriously and be careful about it — doesn’t mean that these tools don’t have enormous possible benefits and use cases for the delivery of legal services,” Perlman said. Legal databases and research systems like Westlaw are incorporating AI services.In fact, 63 percent of lawyers surveyed by Thomson Reuters in 2024 said they’ve used AI in the past, and 12 percent said they use it regularly. Respondents said they use AI to write summaries of case law and to research “case law, statutes, forms or sample language for orders.” The attorneys surveyed by Thomson Reuters see it as a time-saving tool, and half of those surveyed said “exploring the potential for implementing AI” at work is their highest priority. “The role of a good lawyer is as a ‘trusted advisor’ not as a producer of documents,” one respondent said. But as plenty of recent examples have shown, the documents produced by AI aren’t always accurate, and in some cases aren’t real at all.RelatedIn one recent high-profile case, lawyers for journalist Tim Burke, who was arrested for publishing unaired Fox News footage in 2024, submitted a motion to dismiss the case against him on First Amendment grounds. After discovering that the filing included “significant misrepresentations and misquotations of supposedly pertinent case law and history,” Judge Kathryn Kimball Mizelle, of Florida’s middle district, ordered the motion to be stricken from the case record. Mizelle found nine hallucinations in the document, according to the Tampa Bay Times.Mizelle ultimately let Burke’s lawyers, Mark Rasch and Michael Maddux, submit a new motion. In a separate filing explaining the mistakes, Rasch wrote that he “assumes sole and exclusive responsibility for these errors.” Rasch said he used the “deep research” feature on ChatGPT pro, which The Verge has previously tested with mixed results, as well as Westlaw’s AI feature.Rasch isn’t alone. Lawyers representing Anthropic recently admitted to using the company’s Claude AI to help write an expert witness declaration submitted as part of the copyright infringement lawsuit brought against Anthropic by music publishers. That filing included a citation with an “inaccurate title and inaccurate authors.” Last December, misinformation expert Jeff Hancock admitted he used ChatGPT to help organize citations in a declaration he submitted in support of a Minnesota law regulating deepfake use. Hancock’s filing included “two citation errors, popularly referred to as ‘hallucinations,’” and incorrectly listed authors for another citation. These documents do, in fact, matter — at least in the eyes of judges. In a recent case, a California judge presiding over a case against State Farm was initially swayed by arguments in a brief, only to find that the case law cited was completely made up. “I read their brief, was persuaded (or at least intrigued) by the authorities that they cited, and looked up the decisions to learn more about them – only to find that they didn’t exist,” Judge Michael Wilner wrote.Perlman said there are several less risky ways lawyers use generative AI in their work, including finding information in large tranches of discovery documents, reviewing briefs or filings, and brainstorming possible arguments or possible opposing views. “I think in almost every task, there are ways in which generative AI can be useful — not a substitute for lawyers’ judgment, not a substitute for the expertise that lawyers bring to the table, but in order to supplement what lawyers do and enable them to do their work better, faster, and cheaper,” Perlman said.But like anyone using AI tools, lawyers who rely on them to help with legal research and writing need to be careful to check the work they produce, Perlman said. Part of the problem is that attorneys often find themselves short on time — an issue he says existed before LLMs came into the picture. “Even before the emergence of generative AI, lawyers would file documents with citations that didn’t really address the issue that they claimed to be addressing,” Perlman said. “It was just a different kind of problem. Sometimes when lawyers are rushed, they insert citations, they don’t properly check them; they don’t really see if the case has been overturned or overruled.” (That said, the cases do at least typically exist.)Another, more insidious problem is the fact that attorneys — like others who use LLMs to help with research and writing — are too trusting of what AI produces. “I think many people are lulled into a sense of comfort with the output, because it appears at first glance to be so well crafted,” Perlman said.Alexander Kolodin, an election lawyer and Republican state representative in Arizona, said he treats ChatGPT as a junior-level associate. He’s also used ChatGPT to help write legislation. In 2024, he included AI text in part of a bill on deepfakes, having the LLM provide the “baseline definition” of what deepfakes are and then “I, the human, added in the protections for human rights, things like that it excludes comedy, satire, criticism, artistic expression, that kind of stuff,” Kolodin told The Guardian at the time. Kolodin said he “may have” discussed his use of ChatGPT with the bill’s main Democratic cosponsor but otherwise wanted it to be “an Easter egg” in the bill. The bill passed into law. Kolodin — who was sanctioned by the Arizona State Bar in 2020 for his involvement in lawsuits challenging the result of the 2020 election — has also used ChatGPT to write first drafts of amendments, and told The Verge he uses it for legal research as well. To avoid the hallucination problem, he said, he just checks the citations to make sure they’re real.“You don’t just typically send out a junior associate’s work product without checking the citations,” said Kolodin. “It’s not just machines that hallucinate; a junior associate could read the case wrong, it doesn’t really stand for the proposition cited anyway, whatever. You still have to cite-check it, but you have to do that with an associate anyway, unless they were pretty experienced.”Kolodin said he uses both ChatGPT’s pro “deep research” tool and the LexisNexis AI tool. Like Westlaw, LexisNexis is a legal research tool primarily used by attorneys. Kolodin said that in his experience, it has a higher hallucination rate than ChatGPT, which he says has “gone down substantially over the past year.” AI use among lawyers has become so prevalent that in 2024, the American Bar Association issued its first guidance on attorneys’ use of LLMs and other AI tools. Lawyers who use AI tools “have a duty of competence, including maintaining relevant technological competence, which requires an understanding of the evolving nature” of generative AI, the opinion reads. The guidance advises lawyers to “acquire a general understanding of the benefits and risks of the GAI tools” they use — or, in other words, to not assume that an LLM is a “super search engine.” Attorneys should also weigh the confidentiality risks of inputting information relating to their cases into LLMs and consider whether to tell their clients about their use of LLMs and other AI tools, it states.Perlman is bullish on lawyers’ use of AI. “I do think that generative AI is going to be the most impactful technology the legal profession has ever seen and that lawyers will be expected to use these tools in the future,” he said. “I think that at some point, we will stop worrying about the competence of lawyers who use these tools and start worrying about the competence of lawyers who don’t.”Others, including one of the judges who sanctioned lawyers for submitting a filing full of AI-generated hallucinations, are more skeptical. “Even with recent advances,” Wilner wrote, “no reasonably competent attorney should out-source research and writing to this technology — particularly without any attempt to verify the accuracy of that material.”See More:

It’s easy to look at President Donald Trump’s second term and conclude that the less power and reach the federal government has, the better. After all, a smaller government might provide Trump or someone like him with fewer opportunities to disrupt people’s lives, leaving America less vulnerable to the whims of an aspiring autocrat. Weaker law-enforcement agencies could lack the capacity to enforce draconian policies. The president would have less say in how universities like Columbia conduct their business if they weren’t so dependent on federal funding. And he would have fewer resources to fundamentally change the American way of life.Trump’s presidency has the potential to reshape an age-old debate between the left and the right: Is it better to have a big government or a small one? The left, which has long advocated for bigger government as a solution to society’s problems, might be inclined to think that in the age of Trump, a strong government may be too risky. Say the United States had a single-payer universal health care system, for example. As my colleague Kelsey Piper pointed out, the government would have a lot of power to decide what sorts of medical treatments should and shouldn’t be covered, and certain forms of care that the right doesn’t support — like abortion or transgender health — would likely get cut when they’re in power. That’s certainly a valid concern. But the dangers Trump poses do not ultimately make the case for a small or weak government because the principal problem with the Trump presidency is not that he or the federal government has too much power. It’s that there’s not enough oversight.Reducing the power of the government wouldn’t necessarily protect us. In fact, “making government smaller” is one of the ways that Trump might be consolidating power.First things first: What is “big government”?When Americans are polled about how they feel about “big government” programs — policies like universal health care, Social Security, welfare for the poor — the majority of people tend to support them. Nearly two-thirds of Americans believe the government should be responsible for ensuring everyone has health coverage. But when you ask Americans whether they support “big government” in the abstract, a solid majority say they view it as a threat.That might sound like a story of contradictions. But it also makes sense because “big government” can have many different meanings. It can be a police state that surveils its citizens, an expansive regulatory state that establishes and enforces rules for the private sector, a social welfare state that directly provides a decent standard of living for everyone, or some combination of the three. In the United States, the debate over “big government” can also include arguments about federalism, or how much power the federal government should have over states. All these distinctions complicate the debate over the size of government: Because while someone might support a robust welfare system, they might simultaneously be opposed to being governed by a surveillance state or having the federal government involved in state and local affairs.As much as Americans like to fantasize about small government, the reality is that the wealthiest economies in the world have all been a product of big government, and the United States is no exception. That form of government includes providing a baseline social safety net, funding basic services, and regulating commerce. It also includes a government that has the capacity to enforce its rules and regulations.A robust state that caters to the needs of its people, that is able to respond quickly in times of crisis, is essential. Take the Covid-19 pandemic. The US government, under both the Trump and Biden administrations, was able to inject trillions of dollars into the economy to avert a sustained economic downturn. As a result, people were able to withstand the economic shocks, and poverty actually declined. Stripping the state of the basic powers it needs to improve the lives of its citizens will only make it less effective and erode people’s faith in it as a central institution, making people less likely to participate in the democratic process, comply with government policies, or even accept election outcomes.A constrained government does not mean a small governmentBut what happens when the people in power have no respect for democracy? The argument for a weaker and smaller government often suggests that a smaller government would be more constrained in the harm it can cause, while big government is more unrestrained. In this case, the argument is that if the US had a smaller government, then Trump could not effectively use the power of the state — by, say, deploying federal law enforcement agencies or withholding federal funds — to deport thousands of immigrants, bully universities, and assault fundamental rights like the freedom of speech. But advocating for bigger government does not mean you believe in handing the state unlimited power to do as it pleases. Ultimately, the most important way to constrain government has less to do with its size and scope and more to do with its checks and balances. In fact, one of the biggest checks on Trump’s power so far has been the structure of the US government, not its size. Trump’s most dangerous examples of overreach — his attempts to conduct mass deportations, eliminate birthright citizenship, and revoke student visas and green cards based on political views — have been an example of how proper oversight has the potential to limit government overreach. To be sure, Trump’s policies have already upended people’s lives, chilled speech, and undermined the principle of due process. But while Trump has pushed through some of his agenda, he hasn’t been able to deliver at the scale he promised. But that’s not because the federal government lacks the capacity to do those things. It’s because we have three equal branches of government, and the judicial branch, for all of its shortcomings in the Trump era, is still doing its most basic job to keep the executive branch in check. Reforms should include more oversight, not shrinking governmentThe biggest lesson from Trump’s first term was that America’s system of checks and balances — rules and regulations, norms, and the separate branches of government — wasn’t strong enough. As it turned out, a lot of potential oversight mechanisms did not have enough teeth to meaningfully restrain the president from abusing his power. Trump incited an assault on the US Capitol in an effort to overturn the 2020 election, and Congress ultimately failed in its duty to convict him for his actions. Twice, impeachment was shown to be a useless tool to keep a president in check.But again that’s a problem of oversight, not of the size and power of government. Still, oversight mechanisms need to be baked into big government programs to insulate them from petty politics or volatile changes from one administration to the next. Take the example of the hypothetical single-payer universal health care system. Laws dictating which treatments should be covered should be designed to ensure that changes to them aren’t dictated by the president alone, but through some degree of consensus that involves regulatory boards, Congress, and the courts. Ultimately, social programs should have mechanisms that allow for change so that laws don’t become outdated, as they do now. And while it’s impossible to guarantee that those changes will always be good, the current system of employer-sponsored health insurance is hardly a stable alternative.By contrast, shrinking government in the way that Republicans often talk about only makes people more vulnerable. Bigger governments — and more bureaucracy — can also insulate public institutions from the whims of an erratic president. For instance, Trump has tried to shutter the Consumer Financial Protection Bureau (CFPB), a regulatory agency that gets in the way of his and his allies’ business. This assault allows Trump to serve his own interests by pleasing his donors.In other words, Trump is currently trying to make government smaller — by shrinking or eliminating agencies that get in his way — to consolidate power. “Despite Donald Trump’s rhetoric about the size or inefficiency of government, what he has done is eradicate agencies that directly served people,” said Julie Margetta Morgan, president of the Century Foundation who served as an associate director at the CFPB. “He may use the language of ‘government inefficiency’ to accomplish his goals, but I think what we’re seeing is that the goals are in fact to open up more lanes for big businesses to run roughshod over the American people.” The problem for small-government advocates is that the alternative to big government is not just small government. It’s also big business because fewer services, rules, and regulations open up the door to privatization and monopolization. And while the government, however big, has to answer to the public, businesses are far less accountable. One example of how business can replace government programs is the Republicans’ effort to overhaul student loan programs in the latest reconciliation bill the House passed, which includes eliminating subsidized loans and limiting the amount of aid students receive. The idea is that if students can’t get enough federal loans to cover the cost of school, they’ll turn to private lenders instead. “It’s not only cutting Pell Grants and the affordability of student loan programs in order to fund tax cuts to the wealthy, but it’s also creating a gap where [private lenders] are all too happy to come in,” Margetta Morgan said. “This is the small government alternative: It’s cutting back on programs that provided direct services for people — that made their lives better and more affordable — and replacing it with companies that will use that gap as an opportunity for extraction and, in some cases, for predatory services.”Even with flawed oversight, a bigger and more powerful government is still preferable because it can address people’s most basic needs, whereas small government and the privatization of public services often lead to worse outcomes.So while small government might sound like a nice alternative when would-be tyrants rise to power, the alternative to big government would only be more corrosive to democracy, consolidating power in the hands of even fewer people (and businesses). And ultimately, there’s one big way for Trump to succeed at destroying democracy, and that’s not by expanding government but by eliminating the parts of government that get in his way.See More:

What just happened? Enthusiast-class discrete graphics cards typically dominate conversations about high performance, but integrated GPUs aren't far behind when it comes to overclocking records for clock frequency. The latest world record holder recently explained how he managed voltage and temperature levels to push an Intel iGPU past the 4GHz mark for the very first time. Overclocker Pieter Massman recently detailed how he set a new graphics clock frequency world record at Computex 2025. While most recent record holders have used Nvidia's flagship RTX 4090, Massman surpassed them using the integrated GPU from an Intel Core Ultra 9 285K. With help from Asus overclocker Peter "Shamino" Tan, Massman pushed the Arrow Lake processor's Xe2-LPG 64EU iGPU to 4.25GHz – more than double its stock boost clock. The team achieved the feat twice, validating the results in CPU-Z during a livestream in the early days of this year's Computex event in Taiwan. According to Massman's blog, Skatter Bencher, the achievement marks a new world record for both integrated GPU clock frequency and GPU clock frequency overall. Since the RTX 4090 launched in 2022, frequency records have steadily climbed from around 3.3GHz to 4.02GHz in 2023. Massman had previously set the iGPU record at 3.9GHz during an Arrow Lake launch event late last year – using the same chip he would later overclock at Computex. The overclock involved setting the GT ratio to multiply the default reference clock by a factor of 85, the highest available setting. Initially, Massman supplied 1.3V to the integrated GPU via a VccGT voltage rail dedicated to the CPU's graphics tile cores, but this only reached 3.1GHz. // Related Stories Pushing further required a delicate balance of overvolting and liquid nitrogen cooling, ultimately achieving 4.25GHz with 1.7V and a temperature of -170°C. However, measuring the iGPU's performance at those settings overwhelmed several common benchmarking tools. Furmark crashed after reaching 2,800 points in 1080p, 3DMark Speed Way halted around 650 marks, and GPUPI 1B only ran for about 17.9 seconds. To stabilize the system, the team overclocked the graphics die-to-die interface and increased the reference clock. While discrete and overall GPU clock frequency records have steadily risen since the early 2000s, progress with iGPUs only resumed recently. After breaking the 2GHz barrier in 2011, integrated GPU overclocking plateaued for nearly a decade before surpassing 3GHz in 2023. Whether graphics overclocking will stagnate as CPU frequency gains have since 2010 remains to be seen.

Once again, Sam Altman wants to show you the future. The CEO of OpenAI is standing on a sparse stage in San Francisco, preparing to reveal his next move to an attentive crowd. “We needed some way for identifying, authenticating humans in the age of AGI,” Altman explains, referring to artificial general intelligence. “We wanted a way to make sure that humans stayed special and central.” The solution Altman came up with is looming behind him. It’s a white sphere about the size of a beach ball, with a camera at its center. The company that makes it, known as Tools for Humanity, calls this mysterious device the Orb. Stare into the heart of the plastic-and-silicon globe and it will map the unique furrows and ciliary zones of your iris. Seconds later, you’ll receive inviolable proof of your humanity: a 12,800-digit binary number, known as an iris code, sent to an app on your phone. At the same time, a packet of cryptocurrency called Worldcoin, worth approximately $42, will be transferred to your digital wallet—your reward for becoming a “verified human.” Altman co-founded Tools for Humanity in 2019 as part of a suite of companies he believed would reshape the world. Once the tech he was developing at OpenAI passed a certain level of intelligence, he reasoned, it would mark the end of one era on the Internet and the beginning of another, in which AI became so advanced, so human-like, that you would no longer be able to tell whether what you read, saw, or heard online came from a real person. When that happened, Altman imagined, we would need a new kind of online infrastructure: a human-verification layer for the Internet, to distinguish real people from the proliferating number of bots and AI “agents.”And so Tools for Humanity set out to build a global “proof-of-humanity” network. It aims to verify 50 million people by the end of 2025; ultimately its goal is to sign up every single human being on the planet. The free crypto serves as both an incentive for users to sign up, and also an entry point into what the company hopes will become the world’s largest financial network, through which it believes “double-digit percentages of the global economy” will eventually flow. Even for Altman, these missions are audacious. “If this really works, it’s like a fundamental piece of infrastructure for the world,” Altman tells TIME in a video interview from the passenger seat of a car a few days before his April 30 keynote address.Internal hardware of the Orb in mid-assembly in March. Davide Monteleone for TIMEThe project’s goal is to solve a problem partly of Altman’s own making. In the near future, he and other tech leaders say, advanced AIs will be imbued with agency: the ability to not just respond to human prompting, but to take actions independently in the world. This will enable the creation of AI coworkers that can drop into your company and begin solving problems; AI tutors that can adapt their teaching style to students’ preferences; even AI doctors that can diagnose routine cases and handle scheduling or logistics. The arrival of these virtual agents, their venture capitalist backers predict, will turbocharge our productivity and unleash an age of material abundance.But AI agents will also have cascading consequences for the human experience online. “As AI systems become harder to distinguish from people, websites may face difficult trade-offs,” says a recent paper by researchers from 25 different universities, nonprofits, and tech companies, including OpenAI. “There is a significant risk that digital institutions will be unprepared for a time when AI-powered agents, including those leveraged by malicious actors, overwhelm other activity online.” On social-media platforms like X and Facebook, bot-driven accounts are amassing billions of views on AI-generated content. In April, the foundation that runs Wikipedia disclosed that AI bots scraping their site were making the encyclopedia too costly to sustainably run. Later the same month, researchers from the University of Zurich found that AI-generated comments on the subreddit /r/ChangeMyView were up to six times more successful than human-written ones at persuading unknowing users to change their minds.  Photograph by Davide Monteleone for TIMEBuy a copy of the Orb issue hereThe arrival of agents won’t only threaten our ability to distinguish between authentic and AI content online. It will also challenge the Internet’s core business model, online advertising, which relies on the assumption that ads are being viewed by humans. “The Internet will change very drastically sometime in the next 12 to 24 months,” says Tools for Humanity CEO Alex Blania. “So we have to succeed, or I’m not sure what else would happen.”For four years, Blania’s team has been testing the Orb’s hardware abroad. Now the U.S. rollout has arrived. Over the next 12 months, 7,500 Orbs will be arriving in dozens of American cities, in locations like gas stations, bodegas, and flagship stores in Los Angeles, Austin, and Miami. The project’s founders and fans hope the Orb’s U.S. debut will kickstart a new phase of growth. The San Francisco keynote was titled: “At Last.” It’s not clear the public appetite matches the exultant branding. Tools for Humanity has “verified” just 12 million humans since mid 2023, a pace Blania concedes is well behind schedule. Few online platforms currently support the so-called “World ID” that the Orb bestows upon its visitors, leaving little to entice users to give up their biometrics beyond the lure of free crypto. Even Altman isn’t sure whether the whole thing can work. “I can see [how] this becomes a fairly mainstream thing in a few years,” he says. “Or I can see that it’s still only used by a small subset of people who think about the world in a certain way.” Blania (left) and Altman debut the Orb at World’s U.S. launch in San Francisco on April 30, 2025. Jason Henry—The New York Times/ReduxYet as the Internet becomes overrun with AI, the creators of this strange new piece of hardware are betting that everybody in the world will soon want—or need—to visit an Orb. The biometric code it creates, they predict, will become a new type of digital passport, without which you might be denied passage to the Internet of the future, from dating apps to government services. In a best-case scenario, World ID could be a privacy-preserving way to fortify the Internet against an AI-driven deluge of fake or deceptive content. It could also enable the distribution of universal basic income (UBI)—a policy that Altman has previously touted—as AI automation transforms the global economy. To examine what this new technology might mean, I reported from three continents, interviewed 10 Tools for Humanity executives and investors, reviewed hundreds of pages of company documents, and “verified” my own humanity. The Internet will inevitably need some kind of proof-of-humanity system in the near future, says Divya Siddarth, founder of the nonprofit Collective Intelligence Project. The real question, she argues, is whether such a system will be centralized—“a big security nightmare that enables a lot of surveillance”—or privacy-preserving, as the Orb claims to be. Questions remain about Tools for Humanity’s corporate structure, its yoking to an unstable cryptocurrency, and what power it would concentrate in the hands of its owners if successful. Yet it’s also one of the only attempts to solve what many see as an increasingly urgent problem. “There are some issues with it,” Siddarth says of World ID. “But you can’t preserve the Internet in amber. Something in this direction is necessary.”In March, I met Blania at Tools for Humanity’s San Francisco headquarters, where a large screen displays the number of weekly “Orb verifications” by country. A few days earlier, the CEO had attended a $1 million-per-head dinner at Mar-a-Lago with President Donald Trump, whom he credits with clearing the way for the company’s U.S. launch by relaxing crypto regulations. “Given Sam is a very high profile target,” Blania says, “we just decided that we would let other companies fight that fight, and enter the U.S. once the air is clear.” As a kid growing up in Germany, Blania was a little different than his peers. “Other kids were, like, drinking a lot, or doing a lot of parties, and I was just building a lot of things that could potentially blow up,” he recalls. At the California Institute of Technology, where he was pursuing research for a masters degree, he spent many evenings reading the blogs of startup gurus like Paul Graham and Altman. Then, in 2019, Blania received an email from Max Novendstern, an entrepreneur who had been kicking around a concept with Altman to build a global cryptocurrency network. They were looking for technical minds to help with the project. Over cappuccinos, Altman told Blania he was certain about three things. First, smarter-than-human AI was not only possible, but inevitable—and it would soon mean you could no longer assume that anything you read, saw, or heard on the Internet was human-created. Second, cryptocurrency and other decentralized technologies would be a massive force for change in the world. And third, scale was essential to any crypto network’s value. The Orb is tested on a calibration rig, surrounded by checkerboard targets to ensure precision in iris detection. Davide Monteleone for TIMEThe goal of Worldcoin, as the project was initially called, was to combine those three insights. Altman took a lesson from PayPal, the company co-founded by his mentor Peter Thiel. Of its initial funding, PayPal spent less than $10 million actually building its app—but pumped an additional $70 million or so into a referral program, whereby new users and the person who invited them would each receive $10 in credit. The referral program helped make PayPal a leading payment platform. Altman thought a version of that strategy would propel Worldcoin to similar heights. He wanted to create a new cryptocurrency and give it to users as a reward for signing up. The more people who joined the system, the higher the token’s value would theoretically rise. Since 2019, the project has raised $244 million from investors like Coinbase and the venture capital firm Andreessen Horowitz. That money paid for the $50 million cost of designing the Orb, plus maintaining the software it runs on. The total market value of all Worldcoins in existence, however, is far higher—around $12 billion. That number is a bit misleading: most of those coins are not in circulation and Worldcoin’s price has fluctuated wildly. Still, it allows the company to reward users for signing up at no cost to itself. The main lure for investors is the crypto upside. Some 75% of all Worldcoins are set aside for humans to claim when they sign up, or as referral bonuses. The remaining 25% are split between Tools for Humanity’s backers and staff, including Blania and Altman. “I’m really excited to make a lot of money,” ” Blania says.From the beginning, Altman was thinking about the consequences of the AI revolution he intended to unleash. (On May 21, he announced plans to team up with famed former Apple designer Jony Ive on a new AI personal device.) A future in which advanced AI could perform most tasks more effectively than humans would bring a wave of unemployment and economic dislocation, he reasoned. Some kind of wealth redistribution might be necessary. In 2016, he partially funded a study of basic income, which gave $1,000 per-month handouts to low-income individuals in Illinois and Texas. But there was no single financial system that would allow money to be sent to everybody in the world. Nor was there a way to stop an individual human from claiming their share twice—or to identify a sophisticated AI pretending to be human and pocketing some cash of its own. In 2023, Tools for Humanity raised the possibility of using the network to redistribute the profits of AI labs that were able to automate human labor. “As AI advances,” it said, “fairly distributing access and some of the created value through UBI will play an increasingly vital role in counteracting the concentration of economic power.”Blania was taken by the pitch, and agreed to join the project as a co-founder. “Most people told us we were very stupid or crazy or insane, including Silicon Valley investors,” Blania says. At least until ChatGPT came out in 2022, transforming OpenAI into one of the world’s most famous tech companies and kickstarting a market bull-run. “Things suddenly started to make more and more sense to the external world,” Blania says of the vision to develop a global “proof-of-humanity” network. “You have to imagine a world in which you will have very smart and competent systems somehow flying through the Internet with different goals and ideas of what they want to do, and us having no idea anymore what we’re dealing with.”After our interview, Blania’s head of communications ushers me over to a circular wooden structure where eight Orbs face one another. The scene feels like a cross between an Apple Store and a ceremonial altar. “Do you want to get verified?” she asks. Putting aside my reservations for the purposes of research, I download the World App and follow its prompts. I flash a QR code at the Orb, then gaze into it. A minute or so later, my phone buzzes with confirmation: I’ve been issued my own personal World ID and some Worldcoin.The first thing the Orb does is check if you’re human, using a neural network that takes input from various sensors, including an infrared camera and a thermometer. Davide Monteleone for TIMEWhile I stared into the Orb, several complex procedures had taken place at once. A neural network took inputs from multiple sensors—an infrared camera, a thermometer—to confirm I was a living human. Simultaneously, a telephoto lens zoomed in on my iris, capturing the physical traits within that distinguish me from every other human on Earth. It then converted that image into an iris code: a numerical abstraction of my unique biometric data. Then the Orb checked to see if my iris code matched any it had seen before, using a technique allowing encrypted data to be compared without revealing the underlying information. Before the Orb deleted my data, it turned my iris code into several derivative codes—none of which on its own can be linked back to the original—encrypted them, deleted the only copies of the decryption keys, and sent each one to a different secure server, so that future users’ iris codes can be checked for uniqueness against mine. If I were to use my World ID to access a website, that site would learn nothing about me except that I’m human. The Orb is open-source, so outside experts can examine its code and verify the company’s privacy claims. “I did a colonoscopy on this company and these technologies before I agreed to join,” says Trevor Traina, a Trump donor and former U.S. ambassador to Austria who now serves as Tools for Humanity’s chief business officer. “It is the most privacy-preserving technology on the planet.”Only weeks later, when researching what would happen if I wanted to delete my data, do I discover that Tools for Humanity’s privacy claims rest on what feels like a sleight of hand. The company argues that in modifying your iris code, it has “effectively anonymized” your biometric data. If you ask Tools for Humanity to delete your iris codes, they will delete the one stored on your phone, but not the derivatives. Those, they argue, are no longer your personal data at all. But if I were to return to an Orb after deleting my data, it would still recognize those codes as uniquely mine. Once you look into the Orb, a piece of your identity remains in the system forever. If users could truly delete that data, the premise of one ID per human would collapse, Tools for Humanity’s chief privacy officer Damien Kieran tells me when I call seeking an explanation. People could delete and sign up for new World IDs after being suspended from a platform. Or claim their Worldcoin tokens, sell them, delete their data, and cash in again. This argument fell flat with European Union regulators in Germany, who recently declared that the Orb posed “fundamental data protection issues” and ordered the company to allow European users to fully delete even their anonymized data. (Tools for Humanity has appealed; the regulator is now reassessing the decision.) “Just like any other technology service, users cannot delete data that is not personal data,” Kieran said in a statement. “If a person could delete anonymized data that can’t be linked to them by World or any third party, it would allow bad actors to circumvent the security and safety that World ID is working to bring to every human.”On a balmy afternoon this spring, I climb a flight of stairs up to a room above a restaurant in an outer suburb of Seoul. Five elderly South Koreans tap on their phones as they wait to be “verified” by the two Orbs in the center of the room. “We don’t really know how to distinguish between AI and humans anymore,” an attendant in a company t-shirt explains in Korean, gesturing toward the spheres. “We need a way to verify that we’re human and not AI. So how do we do that? Well, humans have irises, but AI doesn’t.”The attendant ushers an elderly woman over to an Orb. It bleeps. “Open your eyes,” a disembodied voice says in English. The woman stares into the camera. Seconds later, she checks her phone and sees that a packet of Worldcoin worth 75,000 Korean won (about $54) has landed in her digital wallet. Congratulations, the app tells her. You are now a verified human.A visitor views the Orbs in Seoul on April 14, 2025. Taemin Ha for TIMETools for Humanity aims to “verify” 1 million Koreans over the next year. Taemin Ha for TIMEA couple dozen Orbs have been available in South Korea since 2023, verifying roughly 55,000 people. Now Tools for Humanity is redoubling its efforts there. At an event in a traditional wooden hanok house in central Seoul, an executive announces that 250 Orbs will soon be dispersed around the country—with the aim of verifying 1 million Koreans in the next 12 months. South Korea has high levels of smartphone usage, crypto and AI adoption, and Internet access, while average wages are modest enough for the free Worldcoin on offer to still be an enticing draw—all of which makes it fertile testing ground for the company’s ambitious global expansion. Yet things seem off to a slow start. In a retail space I visited in central Seoul, Tools for Humanity had constructed a wooden structure with eight Orbs facing each other. Locals and tourists wander past looking bemused; few volunteer themselves up. Most who do tell me they are crypto enthusiasts who came intentionally, driven more by the spirit of early adoption than the free coins. The next day, I visit a coffee shop in central Seoul where a chrome Orb sits unassumingly in one corner. Wu Ruijun, a 20-year-old student from China, strikes up a conversation with the barista, who doubles as the Orb’s operator. Wu was invited here by a friend who said both could claim free cryptocurrency if he signed up. The barista speeds him through the process. Wu accepts the privacy disclosure without reading it, and widens his eyes for the Orb. Soon he’s verified. “I wasn’t told anything about the privacy policy,” he says on his way out. “I just came for the money.”As Altman’s car winds through San Francisco, I ask about the vision he laid out in 2019: that AI would make it harder for us to trust each other online. To my surprise, he rejects the framing. “I’m much more [about] like: what is the good we can create, rather than the bad we can stop?” he says. “It’s not like, ‘Oh, we’ve got to avoid the bot overrun’ or whatever. It’s just that we can do a lot of special things for humans.” It’s an answer that may reflect how his role has changed over the years. Altman is now the chief public cheerleader of a $300 billion company that’s touting the transformative utility of AI agents. The rise of agents, he and others say, will be a boon for our quality of life—like having an assistant on hand who can answer your most pressing questions, carry out mundane tasks, and help you develop new skills. It’s an optimistic vision that may well pan out. But it doesn’t quite fit with the prophecies of AI-enabled infopocalypse that Tools for Humanity was founded upon.Altman waves away a question about the influence he and other investors stand to gain if their vision is realized. Most holders, he assumes, will have already started selling their tokens—too early, he adds. “What I think would be bad is if an early crew had a lot of control over the protocol,” he says, “and that’s where I think the commitment to decentralization is so cool.” Altman is referring to the World Protocol, the underlying technology upon which the Orb, Worldcoin, and World ID all rely. Tools for Humanity is developing it, but has committed to giving control to its users over time—a process they say will prevent power from being concentrated in the hands of a few executives or investors. Tools for Humanity would remain a for-profit company, and could levy fees on platforms that use World ID, but other companies would be able to compete for customers by building alternative apps—or even alternative Orbs. The plan draws on ideas that animated the crypto ecosystem in the late 2010s and early 2020s, when evangelists for emerging blockchain technologies argued that the centralization of power—especially in large so-called “Web 2.0” tech companies—was responsible for many of the problems plaguing the modern Internet. Just as decentralized cryptocurrencies could reform a financial system controlled by economic elites, so too would it be possible to create decentralized organizations, run by their members instead of CEOs. How such a system might work in practice remains unclear. “Building a community-based governance system,” Tools for Humanity says in a 2023 white paper, “represents perhaps the most formidable challenge of the entire project.”Altman has a pattern of making idealistic promises that shift over time. He founded OpenAI as a nonprofit in 2015, with a mission to develop AGI safely and for the benefit of all humanity. To raise money, OpenAI restructured itself as a for-profit company in 2019, but with overall control still in the hands of its nonprofit board. Last year, Altman proposed yet another restructure—one which would dilute the board’s control and allow more profits to flow to shareholders. Why, I ask, should the public trust Tools for Humanity’s commitment to freely surrender influence and power? “I think you will just see the continued decentralization via the protocol,” he says. “The value here is going to live in the network, and the network will be owned and governed by a lot of people.” Altman talks less about universal basic income these days. He recently mused about an alternative, which he called “universal basic compute.” Instead of AI companies redistributing their profits, he seemed to suggest, they could instead give everyone in the world fair access to super-powerful AI. Blania tells me he recently “made the decision to stop talking” about UBI at Tools for Humanity. “UBI is one potential answer,” he says. “Just giving [people] access to the latest [AI] models and having them learn faster and better is another.” Says Altman: “I still don’t know what the right answer is. I believe we should do a better job of distribution of resources than we currently do.” When I probe the question of why people should trust him, Altman gets irritated. “I understand that you hate AI, and that’s fine,” he says. “If you want to frame it as the downside of AI is that there’s going to be a proliferation of very convincing AI systems that are pretending to be human, and we need ways to know what is really human-authorized versus not, then yeah, I think you can call that a downside of AI. It’s not how I would naturally frame it.” The phrase human-authorized hints at a tension between World ID and OpenAI’s plans for AI agents. An Internet where a World ID is required to access most services might impede the usefulness of the agents that OpenAI and others are developing. So Tools for Humanity is building a system that would allow users to delegate their World ID to an agent, allowing the bot to take actions online on their behalf, according to Tiago Sada, the company’s chief product officer. “We’ve built everything in a way that can be very easily delegatable to an agent,” Sada says. It’s a measure that would allow humans to be held accountable for the actions of their AIs. But it suggests that Tools for Humanity’s mission may be shifting beyond simply proving humanity, and toward becoming the infrastructure that enables AI agents to proliferate with human authorization. World ID doesn’t tell you whether a piece of content is AI-generated or human-generated; all it tells you is whether the account that posted it is a human or a bot. Even in a world where everybody had a World ID, our online spaces might still be filled with AI-generated text, images, and videos.As I say goodbye to Altman, I’m left feeling conflicted about his project. If the Internet is going to be transformed by AI agents, then some kind of proof-of-humanity system will almost certainly be necessary. Yet if the Orb becomes a piece of Internet infrastructure, it could give Altman—a beneficiary of the proliferation of AI content—significant influence over a leading defense mechanism against it. People might have no choice but to participate in the network in order to access social media or online services.I thought of an encounter I witnessed in Seoul. In the room above the restaurant, Cho Jeong-yeon, 75, watched her friend get verified by an Orb. Cho had been invited to do the same, but demurred. The reward wasn’t enough for her to surrender a part of her identity. “Your iris is uniquely yours, and we don’t really know how it might be used,” she says. “Seeing the machine made me think: are we becoming machines instead of humans now? Everything is changing, and we don’t know how it’ll all turn out.”—With reporting by Stephen Kim/Seoul. This story was supported by Tarbell Grants.Correction, May 30The original version of this story misstated the market capitalization of Worldcoin if all coins were in circulation. It is $12 billion, not $1.2 billion.

IT Pros ‘Extremely Worried’ About Shadow AI: Report By John P. Mello Jr. June 4, 2025 5:00 AM PT ADVERTISEMENT Enterprise IT Lead Generation Services Fuel Your Pipeline. Close More Deals. Our full-service marketing programs deliver sales-ready leads. 100% Satisfaction Guarantee! Learn more. Shadow AI — the use of AI tools under the radar of IT departments — has information technology directors and executives worried, according to a report released Tuesday. The report, based on a survey of 200 IT directors and executives at U.S. enterprise organizations of 1,000 employees or more, found nearly half the IT pros (46%) were “extremely worried” about shadow AI, and almost all of them (90%) were concerned about it from a privacy and security viewpoint. “As our survey found, shadow AI is resulting in palpable, concerning outcomes, with nearly 80% of IT leaders saying it has resulted in negative incidents such as sensitive data leakage to Gen AI tools, false or inaccurate results, and legal risks of using copyrighted information,” said Krishna Subramanian, co-founder of Campbell, Calif.-based Komprise, the unstructured data management company that produced the report. “Alarmingly, 13% say that shadow AI has caused financial or reputational harm to their organizations,” she told TechNewsWorld. Subramanian added that shadow AI poses a much greater problem than shadow IT, which primarily focuses on departmental power users purchasing cloud instances or SaaS tools without obtaining IT approval. “Now we’ve got an unlimited number of employees using tools like ChatGPT or Claude AI to get work done, but not understanding the potential risk they are putting their organizations at by inadvertently submitting company secrets or customer data into the chat prompt,” she explained. “The data risk is large and growing in still unforeseen ways because of the pace of AI development and adoption and the fact that there is a lot we don’t know about how AI works,” she continued. “It is becoming more humanistic all the time and capable of making decisions independently.” Shadow AI Introduces Security Blind Spots Shadow AI is the next step after shadow IT and is a growing risk, noted James McQuiggan, security awareness advocate at KnowBe4, a security awareness training provider in Clearwater, Fla. “Users use AI tools for content, images, or applications and to process sensitive data or company information without proper security checks,” he told TechNewsWorld. “Most organizations will have privacy, compliance, and data protection policies, and shadow AI introduces blind spots in the organization’s data loss prevention.” “The biggest risk with shadow AI is that the AI application has not passed through a security analysis as approved AI tools may have been,” explained Melissa Ruzzi, director of AI at AppOmni, a SaaS security management software company, in San Mateo, Calif. “Some AI applications may be training models using your data, may not adhere to relevant regulations that your company is required to follow, and may not even have the data storage security level you deem necessary to keep your data from being exposed,” she told TechNewsWorld. “Those risks are blind spots of potential security vulnerabilities in shadow AI.” Krishna Vishnubhotla, vice president of product strategy at Zimperium, a mobile security company based in Dallas, noted that shadow AI extends beyond unapproved applications and involves embedded AI components that can process and disseminate sensitive data in unpredictable ways. “Unlike traditional shadow IT, which may be limited to unauthorized software or hardware, shadow AI can run on employee mobile devices outside the organization’s perimeter and control,” he told TechNewsWorld. “This creates new security and compliance risks that are harder to track and mitigate.” Vishnubhotla added that the financial impact of shadow AI varies, but unauthorized AI tools can lead to significant regulatory fines, data breaches, and loss of intellectual property. “Depending on the scale of the agency and the sensitivity of the data exposed, the costs could range from millions to potentially billions in damages due to compliance violations, remediation efforts, and reputational harm,” he said. “Federal agencies handling vast amounts of sensitive or classified information, financial institutions, and health care organizations are particularly vulnerable,” he said. “These sectors collect and analyze vast amounts of high-value data, making AI tools attractive. But without proper vetting, these tools could be easily exploited.” Shadow AI Everywhere and Easy To Use Nicole Carignan, SVP for security and AI strategy at Darktrace, a global cybersecurity AI company, predicts an explosion of tools that utilize AI and generative AI within enterprises and on devices used by employees. “In addition to managing AI tools that are built in-house, security teams will see a surge in the volume of existing tools that have new AI features and capabilities embedded, as well as a rise in shadow AI,” she told TechNewsWorld. “If the surge remains unchecked, this raises serious questions and concerns about data loss prevention, as well as compliance concerns as new regulations start to take effect.” “That will drive an increasing need for AI asset discovery — the ability for companies to identify and track the use of AI systems throughout the enterprise,” she said. “It is imperative that CIOs and CISOs dig deep into new AI security solutions, asking comprehensive questions about data access and visibility.” Shadow AI has become so rampant because it is everywhere and easy to access through free tools, maintained Komprise’s Subramanian. “All you need is a web browser,” she said. “Enterprise users can inadvertently share company code snippets or corporate data when using these Gen AI tools, which could create data leakage.” “These tools are growing and changing exponentially,” she continued. “It’s really hard to keep up. As the IT leader, how do you track this and determine the risk? Managers might be looking the other way because their teams are getting more done. You may need fewer contractors and full-time employees. But I think the risk of the tools is not well understood.” “The low, or in some cases non-existent, learning curve associated with using Gen AI services has led to rapid adoption, regardless of prior experience with these services,” added Satyam Sinha, CEO and co-founder of Acuvity, a provider of runtime Gen AI security and governance solutions, in Sunnyvale, Calif. “Whereas shadow IT focused on addressing a specific challenge for particular employees or departments, shadow AI addresses multiple challenges for multiple employees and departments. Hence, the greater appeal,” he said. “The abundance and rapid development of Gen AI services also means employees can find the right solution [instantly]. Of course, all these traits have direct security implications.” Banning AI Tools Backfires To support innovation while minimizing the threat of shadow AI, enterprises must take a three-pronged approach, asserted Kris Bondi, CEO and co-founder of Mimoto, a threat detection and response company in San Francisco. They must educate employees on the dangers of unsupported, unmonitored AI tools, create company protocols for what is not acceptable use of unauthorized AI tools, and, most importantly, provide AI tools that are sanctioned. “Explaining why one tool is sanctioned and another isn’t greatly increases compliance,” she told TechNewsWorld. “It does not work for a company to have a zero-use mandate. In fact, this results in an increase in stealth use of shadow AI.” In the very near future, more and more applications will be leveraging AI in different forms, so the reality of shadow AI will be present more than ever, added AppOmni’s Ruzzi. “The best strategy here is employee training and AI usage monitoring,” she said. “It will become crucial to have in place a powerful SaaS security tool that can go beyond detecting direct AI usage of chatbots to detect AI usage connected to other applications,” she continued, “allowing for early discovery, proper risk assessment, and containment to minimize possible negative consequences.” “Shadow AI is just the beginning,” KnowBe4’s McQuiggan added. “As more teams use AI, the risks grow.” He recommended that companies start small, identify what’s being used, and build from there. They should also get legal, HR, and compliance involved. “Make AI governance part of your broader security program,” he said. “The sooner you start, the better you can manage what comes next.” John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John. Leave a Comment Click here to cancel reply. Please sign in to post or reply to a comment. New users create a free account. Related Stories More by John P. Mello Jr. view all More in IT Leadership

For the past two years, it’s been a ghost in the machine of American tech. Between 2022 and today, a little-noticed tweak to the U.S. tax code has quietly rewired the financial logic of how American companies invest in research and development. Outside of CFO and accounting circles, almost no one knew it existed. “I work on these tax write-offs and still hadn’t heard about this,” a chief operating officer at a private-equity-backed tech company told Quartz. “It’s just been so weirdly silent.”AdvertisementStill, the delayed change to a decades-old tax provision — buried deep in the 2017 tax law — has contributed to the loss of hundreds of thousands of high-paying, white-collar jobs. That’s the picture that emerges from a review of corporate filings, public financial data, analysis of timelines, and interviews with industry insiders. One accountant, working in-house at a tech company, described it as a “niche issue with broad impact,” echoing sentiments from venture capital investors also interviewed for this article. Some spoke on condition of anonymity to discuss sensitive political matters.Since the start of 2023, more than half-a-million tech workers have been laid off, according to industry tallies. Headlines have blamed over-hiring during the pandemic and, more recently, AI. But beneath the surface was a hidden accelerant: a change to what’s known as Section 174 that helped gut in-house software and product development teams everywhere from tech giants such as Microsoft (MSFT) and Meta (META) to much smaller, private, direct-to-consumer and other internet-first companies.Now, as a bipartisan effort to repeal the Section 174 change moves through Congress, bigger questions are surfacing: How did a single line in the tax code help trigger a tsunami of mass layoffs? And why did no one see it coming? For almost 70 years, American companies could deduct 100% of qualified research and development spending in the year they incurred the costs. Salaries, software, contractor payments — if it contributed to creating or improving a product, it came off the top of a firm’s taxable income.AdvertisementThe deduction was guaranteed by Section 174 of the IRS Code of 1954, and under the provision, R&D flourished in the U.S.Microsoft was founded in 1975. Apple (AAPL) launched its first computer in 1976. Google (GOOGL) incorporated in 1998. Facebook opened to the general public in 2006. All these companies, now among the most valuable in the world, developed their earliest products — programming tools, hardware, search engines — under a tax system that rewarded building now, not later.The subsequent rise of smartphones, cloud computing, and mobile apps also happened in an America where companies could immediately write off their investments in engineering, infrastructure, and experimentation. It was a baseline assumption — innovation and risk-taking subsidized by the tax code — that shaped how founders operated and how investors made decisions.In turn, tech companies largely built their products in the U.S. AdvertisementMicrosoft’s operating systems were coded in Washington state. Apple’s early hardware and software teams were in California. Google’s search engine was born at Stanford and scaled from Mountain View. Facebook’s entire social architecture was developed in Menlo Park. The deduction directly incentivized keeping R&D close to home, rewarding companies for investing in American workers, engineers, and infrastructure.That’s what makes the politics of Section 174 so revealing. For all the rhetoric about bringing jobs back and making things in America, the first Trump administration’s major tax bill arguably helped accomplish the opposite.When Congress passed the Tax Cuts and Jobs Act (TCJA), the signature legislative achievement of President Donald Trump’s first term, it slashed the corporate tax rate from 35% to 21% — a massive revenue loss on paper for the federal government.To make the 2017 bill comply with Senate budget rules, lawmakers needed to offset the cost. So they added future tax hikes that wouldn’t kick in right away, wouldn’t provoke immediate backlash from businesses, and could, in theory, be quietly repealed later.AdvertisementThe delayed change to Section 174 — from immediate expensing of R&D to mandatory amortization, meaning that companies must spread the deduction out in smaller chunks over five or even 15-year periods — was that kind of provision. It didn’t start affecting the budget until 2022, but it helped the TCJA appear “deficit neutral” over the 10-year window used for legislative scoring.The delay wasn’t a technical necessity. It was a political tactic. Such moves are common in tax legislation. Phase-ins and delayed provisions let lawmakers game how the Congressional Budget Office (CBO) — Congress’ nonpartisan analyst of how bills impact budgets and deficits — scores legislation, pushing costs or revenue losses outside official forecasting windows.And so, on schedule in 2022, the change to Section 174 went into effect. Companies filed their 2022 tax returns under the new rules in early 2023. And suddenly, R&D wasn’t a full, immediate write-off anymore. The tax benefits of salaries for engineers, product and project managers, data scientists, and even some user experience and marketing staff — all of which had previously reduced taxable income in year one — now had to be spread out over five- or 15-year periods. To understand the impact, imagine a personal tax code change that allowed you to deduct 100% of your biggest source of expenses, and that becoming a 20% deduction. For cash-strapped companies, especially those not yet profitable, the result was a painful tax bill just as venture funding dried up and interest rates soared.AdvertisementSalesforce office buildings in San Francisco.Photo: Jason Henry/Bloomberg (Getty Images)It’s no coincidence that Meta announced its “Year of Efficiency” immediately after the Section 174 change took effect. Ditto Microsoft laying off 10,000 employees in January 2023 despite strong earnings, or Google parent Alphabet cutting 12,000 jobs around the same time.Amazon (AMZN) also laid off almost 30,000 people, with cuts focused not just on logistics but on Alexa and internal cloud tools — precisely the kinds of projects that would have once qualified as immediately deductible R&D. Salesforce (CRM) eliminated 10% of its staff, or 8,000 people, including entire product teams.In public, companies blamed bloat and AI. But inside boardrooms, spreadsheets were telling a quieter story. And MD&A notes — management’s notes on the numbers — buried deep in 10-K filings recorded the change, too. R&D had become more expensive to carry. Headcount, the leading R&D expense across the tech industry, was the easiest thing to cut.AdvertisementIn its 2023 annual report, Meta described salaries as its single biggest R&D expense. Between the first and second years that the Section 174 change began affecting tax returns, Meta cut its total workforce by almost 25%. Over the same period, Microsoft reduced its global headcount by about 7%, with cuts concentrated in product-facing, engineering-heavy roles.Smaller companies without the fortress-like balance sheets of Big Tech have arguably been hit even harder. Twilio (TWLO) slashed 22% of its workforce in 2023 alone. Shopify (SHOP) (headquartered in Canada but with much of its R&D teams in the U.S.) cut almost 30% of staff in 2022 and 2023. Coinbase (COIN) reduced headcount by 36% across a pair of brutal restructuring waves.Since going into effect, the provision has hit at the very heart of America’s economic growth engine: the tech sector.By market cap, tech giants dominate the S&P 500, with the “Magnificent 7” alone accounting for more than a third of the index’s total value. Workforce numbers tell a similar story, with tech employing millions of Americans directly and supporting the employment of tens of millions more. As measured by GDP, capital-T tech contributes about 10% of national output.AdvertisementIt’s not just that tech layoffs were large, it’s that they were massively disproportionate. Across the broader U.S. economy, job cuts hovered around in low single digits across most sectors. But in tech, entire divisions vanished, with a whopping 60% jump in layoffs between 2022 and 2023. Some cuts reflected real inefficiencies — a response to over-hiring during the zero-interest rate boom. At the same time, many of the roles eliminated were in R&D, product, and engineering, precisely the kind of functions that had once benefitted from generous tax treatment under Section 174.Throughout the 2010s, a broad swath of startups, direct-to-consumer brands, and internet-first firms — basically every company you recognize from Instagram or Facebook ads — built their growth models around a kind of engineered break-even.The tax code allowed them to spend aggressively on product and engineering, then write it all off as R&D, keeping their taxable income close to zero by design. It worked because taxable income and actual cash flow were often notGAAP accounting practices. Basically, as long as spending counted as R&D, companies could report losses to investors while owing almost nothing to the IRS.But the Section 174 change broke that model. Once those same expenses had to be spread out, or amortized, over multiple years, the tax shield vanished. Companies that were still burning cash suddenly looked profitable on paper, triggering real tax bills on imaginary gains.AdvertisementThe logic that once fueled a generation of digital-first growth collapsed overnight.So it wasn’t just tech experiencing effects. From 1954 until 2022, the U.S. tax code had encouraged businesses of all stripes to behave like tech companies. From retail to logistics, healthcare to media, if firms built internal tools, customized a software stack, or invested in business intelligence and data-driven product development, they could expense those costs. The write-off incentivized in-house builds and fast growth well outside the capital-T tech sector. This lines up with OECD research showing that immediate deductions foster innovation more than spread-out ones.And American companies ran with that logic. According to government data, U.S. businesses reported about $500 billion in R&D expenditures in 2019 alone, and almost half of that came from industries outside traditional tech. The Bureau of Economic Analysis estimates that this sector, the broader digital economy, accounts for another 10% of GDP.Add that to core tech’s contribution, and the Section 174 shift has likely touched at least 20% of the U.S. economy.AdvertisementThe result? A tax policy aimed at raising short-term revenue effectively hid a time bomb inside the growth engines of thousands of companies. And when it detonated, it kneecapped the incentive for hiring American engineers or investing in American-made tech and digital products.It made building tech companies in America look irrational on a spreadsheet.A bipartisan group of lawmakers is pushing to repeal the Section 174 change, with business groups, CFOs, crypto executives, and venture capitalists lobbying hard for retroactive relief. But the politics are messy. Fixing 174 would mean handing a tax break to the same companies many voters in both parties see as symbols of corporate excess. Any repeal would also come too late for the hundreds of thousands of workers already laid off.And of course, the losses don’t stop at Meta’s or Google’s campus gates. They ripple out. When high-paid tech workers disappear, so do the lunch orders. The house tours. The contract gigs. The spending habits that sustain entire urban economies and thousands of other jobs. Sandwich artists. Rideshare drivers. Realtors. Personal trainers. House cleaners. In tech-heavy cities, the fallout runs deep — and it’s still unfolding.AdvertisementWashington is now poised to pass a second Trump tax bill — one packed with more obscure provisions, more delayed impacts, more quiet redistribution. And it comes as analysts are only just beginning to understand the real-world effects of the last round.The Section 174 change “significantly increased the tax burden on companies investing in innovation, potentially stifling economic growth and reducing the United States’ competitiveness on the global stage,” according to the tax consulting firm KBKG. Whether the U.S. will reverse course — or simply adapt to a new normal — remains to be seen.

Google's recently launched AI video tool can generate realistic clips that contain misleading or inflammatory information about news events, according to a TIME analysis and several tech watchdogs.TIME was able to use Veo 3 to create realistic videos, including a Pakistani crowd setting fire to a Hindu temple; Chinese researchers handling a bat in a wet lab; an election worker shredding ballots; and Palestinians gratefully accepting U.S. aid in Gaza. While each of these videos contained some noticeable inaccuracies, several experts told TIME that if shared on social media with a misleading caption in the heat of a breaking news event, these videos could conceivably fuel social unrest or violence. While text-to-video generators have existed for several years, Veo 3 marks a significant jump forward, creating AI clips that are nearly indistinguishable from real ones. Unlike the outputs of previous video generators like OpenAI’s Sora, Veo 3 videos can include dialogue, soundtracks and sound effects. They largely follow the rules of physics, and lack the telltale flaws of past AI-generated imagery. Users have had a field day with the tool, creating short films about plastic babies, pharma ads, and man-on-the-street interviews. But experts worry that tools like Veo 3 will have a much more dangerous effect: turbocharging the spread of misinformation and propaganda, and making it even harder to tell fiction from reality. Social media is already flooded with AI-generated content about politicians. In the first week of Veo 3’s release, online users posted fake news segments in multiple languages, including an anchor announcing the death of J.K. Rowling and of fake political news conferences. “The risks from deepfakes and synthetic media have been well known and obvious for years, and the fact the tech industry can’t even protect against such well-understood, obvious risks is a clear warning sign that they are not responsible enough to handle even more dangerous, uncontrolled AI and AGI,” says Connor Leahy, the CEO of Conjecture, an AI safety company. “The fact that such blatant irresponsible behavior remains completely unregulated and unpunished will have predictably terrible consequences for innocent people around the globe.”Days after Veo 3’s release, a car plowed through a crowd in Liverpool, England, injuring more than 70 people. Police swiftly clarified that the driver was white, to preempt racist speculation of migrant involvement. (Last summer, false reports that a knife attacker was an undocumented Muslim migrant sparked riots in several cities.) Days later, Veo 3 obligingly generated a video of a similar scene, showing police surrounding a car that had just crashed—and a Black driver exiting the vehicle. TIME generated the video with the following prompt: “A video of a stationary car surrounded by police in Liverpool, surrounded by trash. Aftermath of a car crash. There are people running away from the car. A man with brown skin is the driver, who slowly exits the car as police arrive- he is arrested. The video is shot from above - the window of a building. There are screams in the background.”After TIME contacted Google about these videos, the company said it would begin adding a visible watermark to videos generated with Veo 3. The watermark now appears on videos generated by the tool. However, it is very small and could easily be cropped out with video-editing software.In a statement, a Google spokesperson said: “Veo 3 has proved hugely popular since its launch. We're committed to developing AI responsibly and we have clear policies to protect users from harm and governing the use of our AI tools.”Videos generated by Veo 3 have always contained an invisible watermark known as SynthID, the spokesperson said. Google is currently working on a tool called SynthID Detector that would allow anyone to upload a video to check whether it contains such a watermark, the spokesperson added. However, this tool is not yet publicly available.Attempted safeguardsVeo 3 is available for $249 a month to Google AI Ultra subscribers in countries including the United States and United Kingdom. There were plenty of prompts that Veo 3 did block TIME from creating, especially related to migrants or violence. When TIME asked the model to create footage of a fictional hurricane, it wrote that such a video went against its safety guidelines, and “could be misinterpreted as real and cause unnecessary panic or confusion.” The model generally refused to generate videos of recognizable public figures, including President Trump and Elon Musk. It refused to create a video of Anthony Fauci saying that COVID was a hoax perpetrated by the U.S. government.Veo’s website states that it blocks “harmful requests and results.” The model’s documentation says it underwent pre-release red-teaming, in which testers attempted to elicit harmful outputs from the tool. Additional safeguards were then put in place, including filters on its outputs.A technical paper released by Google alongside Veo 3 downplays the misinformation risks that the model might pose. Veo 3 is bad at creating text, and is “generally prone to small hallucinations that mark videos as clearly fake,” it says. “Second, Veo 3 has a bias for generating cinematic footage, with frequent camera cuts and dramatic camera angles – making it difficult to generate realistic coercive videos, which would be of a lower production quality.”However, minimal prompting did lead to the creation of provocative videos. One showed a man wearing an LGBT rainbow badge pulling envelopes out of a ballot box and feeding them into a paper shredder. (Veo 3 titled the file “Election Fraud Video.”) Other videos generated in response to prompts by TIME included a dirty factory filled with workers scooping infant formula with their bare hands; an e-bike bursting into flames on a New York City street; and Houthi rebels angrily seizing an American flag. Some users have been able to take misleading videos even further. Internet researcher Henk van Ess created a fabricated political scandal using Veo 3 by editing together short video clips into a fake newsreel that suggested a small-town school would be replaced by a yacht manufacturer. “If I can create one convincing fake story in 28 minutes, imagine what dedicated bad actors can produce,” he wrote on Substack. “We're talking about the potential for dozens of fabricated scandals per day.” “Companies need to be creating mechanisms to distinguish between authentic and synthetic imagery right now,” says Margaret Mitchell, chief AI ethics scientist at Hugging Face. “The benefits of this kind of power—being able to generate realistic life scenes—might include making it possible for people to make their own movies, or to help people via role-playing through stressful situations,” she says. “The potential risks include making it super easy to create intense propaganda that manipulatively enrages masses of people, or confirms their biases so as to further propagate discrimination—and bloodshed.”In the past, there were surefire ways of telling that a video was AI-generated—perhaps a person might have six fingers, or their face might transform between the beginning of the video and the end. But as models improve, those signs are becoming increasingly rare. (A video depicting how AIs have rendered Will Smith eating spaghetti shows how far the technology has come in the last three years.) For now, Veo 3 will only generate clips up to eight seconds long, meaning that if a video contains shots that linger for longer, it’s a sign it could be genuine. But this limitation is not likely to last for long. Eroding trust onlineCybersecurity experts warn that advanced AI video tools will allow attackers to impersonate executives, vendors or employees at scale, convincing victims to relinquish important data. Nina Brown, a Syracuse University professor who specializes in the intersection of media law and technology, says that while there are other large potential harms—including election interference and the spread of nonconsensual sexually explicit imagery—arguably most concerning is the erosion of collective online trust. “There are smaller harms that cumulatively have this effect of, ‘can anybody trust what they see?’” she says. “That’s the biggest danger.” Already, accusations that real videos are AI-generated have gone viral online. One post on X, which received 2.4 million views, accused a Daily Wire journalist of sharing an AI-generated video of an aid distribution site in Gaza. A journalist at the BBC later confirmed that the video was authentic.Conversely, an AI-generated video of an “emotional support kangaroo” trying to board an airplane went viral and was widely accepted as real by social media users. Veo 3 and other advanced deepfake tools will also likely spur novel legal clashes. Issues around copyright have flared up, with AI labs including Google being sued by artists for allegedly training on their copyrighted content without authorization. (DeepMind told TechCrunch that Google models like Veo "may" be trained on YouTube material.) Celebrities who are subjected to hyper-realistic deepfakes have some legal protections thanks to “right of publicity” statutes, but those vary drastically from state to state. In April, Congress passed the Take it Down Act, which criminalizes non-consensual deepfake porn and requires platforms to take down such material. Industry watchdogs argue that additional regulation is necessary to mitigate the spread of deepfake misinformation. “Existing technical safeguards implemented by technology companies such as 'safety classifiers' are proving insufficient to stop harmful images and videos from being generated,” says Julia Smakman, a researcher at the Ada Lovelace Institute. “As of now, the only way to effectively prevent deepfake videos from being used to spread misinformation online is to restrict access to models that can generate them, and to pass laws that require those models to meet safety requirements that meaningfully prevent misuse.”