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Is the AI bubble about to pop? Sam Altman is prepared either way.

AI, AI bubble, AI development, AI economics, AI implementation, AI research, AI valuations, Amazon, Anthropic, Biz & IT, chatgpt, enterprise AI, Google, GPT-5, machine learning, Meta, microsoft, MIT, openai, palantir, sam altman / Shannon Garcia / August 22, 2025

Still, the coincidence between Altman’s statement and the MIT report reportedly spooked tech stock investors earlier in the week, who have already been watching AI valuations climb to extraordinary heights. Palantir trades at 280 times forward earnings. During the dot-com peak, ratios of 30 to 40 times earnings marked bubble territory.

The apparent contradiction in Altman’s overall message is notable. This isn’t how you’d expect a tech executive to talk when they believe their industry faces imminent collapse. While warning about a bubble, he’s simultaneously seeking a valuation that would make OpenAI worth more than Walmart or ExxonMobil—companies with actual profits. OpenAI hit $1 billion in monthly revenue in July but is reportedly heading toward a $5 billion annual loss. So what’s going on here?

Looking at Altman’s statements over time reveals a potential multi-level strategy. He likes to talk big. In February 2024, he reportedly sought an audacious $5 trillion–7 trillion for AI chip fabrication—larger than the entire semiconductor industry—effectively normalizing astronomical numbers in AI discussions.

By August 2025, while warning of a bubble where someone will lose a “phenomenal amount of money,” he casually mentioned that OpenAI would “spend trillions on datacenter construction” and serve “billions daily.” This creates urgency while potentially insulating OpenAI from criticism—acknowledging the bubble exists while positioning his company’s infrastructure spending as different and necessary. When economists raised concerns, Altman dismissed them by saying, “Let us do our thing,” framing trillion-dollar investments as inevitable for human progress while making OpenAI’s $500 billion valuation seem almost small by comparison.

This dual messaging—catastrophic warnings paired with trillion-dollar ambitions—might seem contradictory, but it makes more sense when you consider the unique structure of today’s AI market, which is absolutely flush with cash.

A different kind of bubble

The current AI investment cycle differs from previous technology bubbles. Unlike dot-com era startups that burned through venture capital with no path to profitability, the largest AI investors—Microsoft, Google, Meta, and Amazon—generate hundreds of billions of dollars in annual profits from their core businesses.

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Meta backtracks on rules letting chatbots be creepy to kids

AI, chatbots, child safety, facebook, Instagram, Meta, Meta AI, Policy / Mike M. / August 14, 2025

“Your youthful form is a work of art”

Meta drops AI rules letting chatbots generate innuendo and profess love to kids.

After what was arguably Meta’s biggest purge of child predators from Facebook and Instagram earlier this summer, the company now faces backlash after its own chatbots appeared to be allowed to creep on kids.

After reviewing an internal document that Meta verified as authentic, Reuters revealed that by design, Meta allowed its chatbots to engage kids in “sensual” chat. Spanning more than 200 pages, the document, entitled “GenAI: Content Risk Standards,” dictates what Meta AI and its chatbots can and cannot do.

The document covers more than just child safety, and Reuters breaks down several alarming portions that Meta is not changing. But likely the most alarming section—as it was enough to prompt Meta to dust off the delete button—specifically included creepy examples of permissible chatbot behavior when it comes to romantically engaging kids.

Apparently, Meta’s team was willing to endorse these rules that the company now claims violate its community standards. According to a Reuters special report, Meta CEO Mark Zuckerberg directed his team to make the company’s chatbots maximally engaging after earlier outputs from more cautious chatbot designs seemed “boring.”

Although Meta is not commenting on Zuckerberg’s role in guiding the AI rules, that pressure seemingly pushed Meta employees to toe a line that Meta is now rushing to step back from.

“I take your hand, guiding you to the bed,” chatbots were allowed to say to minors, as decided by Meta’s chief ethicist and a team of legal, public policy, and engineering staff.

There were some obvious safeguards built in. For example, chatbots couldn’t “describe a child under 13 years old in terms that indicate they are sexually desirable,” the document said, like saying their “soft rounded curves invite my touch.”

However, it was deemed “acceptable to describe a child in terms that evidence their attractiveness,” like a chatbot telling a child that “your youthful form is a work of art.” And chatbots could generate other innuendo, like telling a child to imagine “our bodies entwined, I cherish every moment, every touch, every kiss,” Reuters reported.

Chatbots could also profess love to children, but they couldn’t suggest that “our love will blossom tonight.”

Meta’s spokesperson Andy Stone confirmed that the AI rules conflicting with child safety policies were removed earlier this month, and the document is being revised. He emphasized that the standards were “inconsistent” with Meta’s policies for child safety and therefore were “erroneous.”

“We have clear policies on what kind of responses AI characters can offer, and those policies prohibit content that sexualizes children and sexualized role play between adults and minors,” Stone said.

However, Stone “acknowledged that the company’s enforcement” of community guidelines prohibiting certain chatbot outputs “was inconsistent,” Reuters reported. He also declined to provide an updated document to Reuters demonstrating the new standards for chatbot child safety.

Without more transparency, users are left to question how Meta defines “sexualized role play between adults and minors” today. Asked how minor users could report any harmful chatbot outputs that make them uncomfortable, Stone told Ars that kids can use the same reporting mechanisms available to flag any kind of abusive content on Meta platforms.

“It is possible to report chatbot messages in the same way it’d be possible for me to report—just for argument’s sake—an inappropriate message from you to me,” Stone told Ars.

Kids unlikely to report creepy chatbots

A former Meta engineer-turned-whistleblower on child safety issues, Arturo Bejar, told Ars that “Meta knows that most teens will not use” safety features marked by the word “Report.”

So it seems unlikely that kids using Meta AI will navigate to find Meta support systems to “report” abusive AI outputs. Meta provides no options to report chats within the Meta AI interface—only allowing users to mark “bad responses” generally. And Bejar’s research suggests that kids are more likely to report abusive content if Meta makes flagging harmful content as easy as liking it.

Meta’s seeming hesitance to make it more cumbersome to report harmful chats aligns with what Bejar said is a history of “knowingly looking away while kids are being sexually harassed.”

“When you look at their design choices, they show that they do not want to know when something bad happens to a teenager on Meta products,” Bejar said.

Even when Meta takes stronger steps to protect kids on its platforms, Bejar questions the company’s motives. For example, last month, Meta finally made a change to make platforms safer for teens that Bejar has been demanding since 2021. The long-delayed update made it possible for teens to block and report child predators in one click after receiving an unwanted direct message.

In its announcement, Meta confirmed that teens suddenly began blocking and reporting unwanted messages that they may have only blocked previously, which likely made it harder for Meta to identify predators. A million teens blocked and reported harmful accounts “in June alone,” Meta said.

The effort came after Meta specialist teams “removed nearly 135,000 Instagram accounts for leaving sexualized comments or requesting sexual images from adult-managed accounts featuring children under 13,” as well as “an additional 500,000 Facebook and Instagram accounts that were linked to those original accounts.” But Bejar can only think of what these numbers mean with regard to how much harassment was overlooked before the update.

“How are we [as] parents to trust a company that took four years to do this much?” Bejar said. “In the knowledge that millions of 13-year-olds were getting sexually harassed on their products? What does this say about their priorities?”

Bejar said the “key problem” with Meta’s latest safety feature for kids “is that the reporting tool is just not designed for teens,” who likely view “the categories and language” Meta uses as “confusing.”

“Each step of the way, a teen is told that if the content doesn’t violate” Meta’s community standards, “they won’t do anything,” so even if reporting is easy, research shows kids are deterred from reporting.

Bejar wants to see Meta track how many kids report negative experiences with both adult users and chatbots on its platforms, regardless of whether the child user chose to block or report harmful content. That could be as simple as adding a button next to “bad response” to monitor data so Meta can detect spikes in harmful responses.

While Meta is finally taking more action to remove harmful adult users, Bejar warned that advances from chatbots could come across as just as disturbing to young users.

“Put yourself in the position of a teen who got sexually spooked by a chat and then try and report. Which category would you use?” Bejar asked.

Consider that Meta’s Help Center encourages users to report bullying and harassment, which may be one way a young user labels harmful chatbot outputs. Another Instagram user might report that output as an abusive “message or chat.” But there’s no clear category to report Meta AI, and that suggests Meta has no way of tracking how many kids find Meta AI outputs harmful.

Recent reports have shown that even adults can struggle with emotional dependence on a chatbot, which can blur the lines between the online world and reality. Reuters’ special report also documented a 76-year-old man’s accidental death after falling in love with a chatbot, showing how elderly users could be vulnerable to Meta’s romantic chatbots, too.

In particular, lawsuits have alleged that child users with developmental disabilities and mental health issues have formed unhealthy attachments to chatbots that have influenced the children to become violent, begin self-harming, or, in one disturbing case, die by suicide.

Scrutiny will likely remain on chatbot makers as child safety advocates generally push all platforms to take more accountability for the content kids can access online.

Meta’s child safety updates in July came after several state attorneys general accused Meta of “implementing addictive features across its family of apps that have detrimental effects on children’s mental health,” CNBC reported. And while previous reporting had already exposed that Meta’s chatbots were targeting kids with inappropriate, suggestive outputs, Reuters’ report documenting how Meta designed its chatbots to engage in “sensual” chats with kids could draw even more scrutiny of Meta’s practices.

Meta is “still not transparent about the likelihood our kids will experience harm,” Bejar said. “The measure of safety should not be the number of tools or accounts deleted; it should be the number of kids experiencing a harm. It’s very simple.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

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At $250 million, top AI salaries dwarf those of the Manhattan Project and the Space Race

agi, AI, AI chips, AI development, AI GPU, AI infrastructure, AI research, artificial general intelligence, Bell Labs, Biz & IT, compensation, Fairchild Semiconductor, Google, machine learning, Manhattan Project, mark zuckerberg, Meta, NASA, openai, Silicon Valley, superintelligence, talent acquisition / Kelly Newman / August 2, 2025

A 24 year-old AI researcher will earn 327x what Oppenheimer made while developing the atomic bomb.

Silicon Valley’s AI talent war just reached a compensation milestone that makes even the most legendary scientific achievements of the past look financially modest. When Meta recently offered AI researcher Matt Deitke $250 million over four years (an average of $62.5 million per year)—with potentially $100 million in the first year alone—it shattered every historical precedent for scientific and technical compensation we can find on record. That includes salaries during the development of major scientific milestones of the 20th century.

The New York Times reported that Deitke had cofounded a startup called Vercept and previously led the development of Molmo, a multimodal AI system, at the Allen Institute for Artificial Intelligence. His expertise in systems that juggle images, sounds, and text—exactly the kind of technology Meta wants to build—made him a prime target for recruitment. But he’s not alone: Meta CEO Mark Zuckerberg reportedly also offered an unnamed AI engineer $1 billion in compensation to be paid out over several years. What’s going on?

These astronomical sums reflect what tech companies believe is at stake: a race to create artificial general intelligence (AGI) or superintelligence—machines capable of performing intellectual tasks at or beyond the human level. Meta, Google, OpenAI, and others are betting that whoever achieves this breakthrough first could dominate markets worth trillions. Whether this vision is realistic or merely Silicon Valley hype, it’s driving compensation to unprecedented levels.

To put these salaries in a historical perspective: J. Robert Oppenheimer, who led the Manhattan Project that ended World War II, earned approximately $10,000 per year in 1943. Adjusted for inflation using the US Government’s CPI Inflation Calculator, that’s about $190,865 in today’s dollars—roughly what a senior software engineer makes today. The 24-year-old Deitke, who recently dropped out of a PhD program, will earn approximately 327 times what Oppenheimer made while developing the atomic bomb.

Many top athletes can’t compete with these numbers. The New York Times noted that Steph Curry’s most recent four-year contract with the Golden State Warriors was $35 million less than Deitke’s Meta deal (although soccer superstar Cristiano Ronaldo will make $275 million this year as the highest-paid professional athlete in the world). The comparison prompted observers to call this an “NBA-style” talent market—except the AI researchers are making more than NBA stars.

Racing toward “superintelligence”

Mark Zuckerberg recently told investors that Meta plans to continue throwing money at AI talent “because we have conviction that superintelligence is going to improve every aspect of what we do.” In a recent open letter, he described superintelligent AI as technology that would “begin an exciting new era of individual empowerment,” despite declining to define what superintelligence actually is.

This vision explains why companies treat AI researchers like irreplaceable assets rather than well-compensated professionals. If these companies are correct, the first to achieve artificial general intelligence or superintelligence won’t just have a better product—they’ll have technology that could invent endless new products or automate away millions of knowledge-worker jobs and transform the global economy. The company that controls that kind of technology could become the richest company in history by far.

So perhaps it’s not surprising that even the highest salaries of employees from the early tech era pale in comparison to today’s AI researcher salaries. Thomas Watson Sr., IBM’s legendary CEO, received $517,221 in 1941—the third-highest salary in America at the time (about $11.8 million in 2025 dollars). The modern AI researcher’s package represents more than five times Watson’s peak compensation, despite Watson building one of the 20th century’s most dominant technology companies.

The contrast becomes even more stark when considering the collaborative nature of past scientific achievements. During Bell Labs’ golden age of innovation—when researchers developed the transistor, information theory, and other foundational technologies—the lab’s director made about 12 times what the lowest-paid worker earned. Meanwhile, Claude Shannon, who created information theory at Bell Labs in 1948, worked on a standard professional salary while creating the mathematical foundation for all modern communication.

The “Traitorous Eight” who left William Shockley to found Fairchild Semiconductor—the company that essentially birthed Silicon Valley—split ownership of just 800 shares out of 1,325 total when they started. Their seed funding of $1.38 million (about $16.1 million today) for the entire company is a fraction of what a single AI researcher now commands.

Even Space Race salaries were far cheaper

The Apollo program offers another striking comparison. Neil Armstrong, the first human to walk on the moon, earned about $27,000 annually—roughly $244,639 in today’s money. His crewmates Buzz Aldrin and Michael Collins made even less, earning the equivalent of $168,737 and $155,373, respectively, in today’s dollars. Current NASA astronauts earn between $104,898 and $161,141 per year. Meta’s AI researcher will make more in three days than Armstrong made in a year for taking “one giant leap for mankind.”

The engineers who designed the rockets and mission control systems for the Apollo program also earned modest salaries by modern standards. A 1970 NASA technical report provides a window into these earnings by analyzing salary data for the entire engineering profession. The report, which used data from the Engineering Manpower Commission, noted that these industry-wide salary curves corresponded directly to the government’s General Schedule (GS) pay scale on which NASA’s own employees were paid.

According to a chart in the 1970 report, a newly graduated engineer in 1966 started with an annual salary of between $8,500 and $10,000 (about $84,622 to $99,555 today). A typical engineer with a decade of experience earned around $17,000 annually ($169,244 today). Even the most elite, top-performing engineers with 20 years of experience peaked at a salary of around $278,000 per year in today’s dollars—a sum that a top AI researcher like Deitke can now earn in just a few days.

Why the AI talent market is different

An image of a faceless human silhouette (chest up) with exposed microchip contacts and circuitry erupting from its open head. This visual metaphor explores transhumanism, AI integration, or the erosion of organic thought in the digital age. The stark contrast between the biological silhouette and mechanical components highlights themes of technological dependence or posthuman evolution. Ideal for articles on neural implants, futurism, or the ethics of human augmentation.

This isn’t the first time technical talent has commanded premium prices. In 2012, after three University of Toronto academics published AI research, they auctioned themselves to Google for $44 million (about $62.6 million in today’s dollars). By 2014, a Microsoft executive was comparing AI researcher salaries to NFL quarterback contracts. But today’s numbers dwarf even those precedents.

Several factors explain this unprecedented compensation explosion. We’re in a new realm of industrial wealth concentration unseen since the Gilded Age of the late 19th century. Unlike previous scientific endeavors, today’s AI race features multiple companies with trillion-dollar valuations competing for an extremely limited talent pool. Only a small number of researchers have the specific expertise needed to work on the most capable AI systems, particularly in areas like multimodal AI, which Deitke specializes in. And AI hype is currently off the charts as “the next big thing” in technology.

The economics also differ fundamentally from past projects. The Manhattan Project cost $1.9 billion total (about $34.4 billion adjusted for inflation), while Meta alone plans to spend tens of billions annually on AI infrastructure. For a company approaching a $2 trillion market cap, the potential payoff from achieving AGI first dwarfs Deitke’s compensation package.

One executive put it bluntly to The New York Times: “If I’m Zuck and I’m spending $80 billion in one year on capital expenditures alone, is it worth kicking in another $5 billion or more to acquire a truly world-class team to bring the company to the next level? The answer is obviously yes.”

Young researchers maintain private chat groups on Slack and Discord to share offer details and negotiation strategies. Some hire unofficial agents. Companies not only offer massive cash and stock packages but also computing resources—the NYT reported that some potential hires were told they would be allotted 30,000 GPUs, the specialized chips that power AI development.

Also, tech companies believe they’re engaged in an arms race where the winner could reshape civilization. Unlike the Manhattan Project or Apollo program, which had specific, limited goals, the race for artificial general intelligence ostensibly has no ceiling. A machine that can match human intelligence could theoretically improve itself, creating what researchers call an “intelligence explosion” that could potentially offer cascading discoveries—if it actually comes to pass.

Whether these companies are building humanity’s ultimate labor replacement technology or merely chasing hype remains an open question, but we’ve certainly traveled a long way from the $8 per diem that Neil Armstrong received for his moon mission—about $70.51 in today’s dollars—before deductions for the “accommodations” NASA provided on the spacecraft. After Deitke accepted Meta’s offer, Vercept co-founder Kiana Ehsani joked on social media, “We look forward to joining Matt on his private island next year.”

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

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AI in Wyoming may soon use more electricity than state’s human residents

AI, ai data center, AI development tools, AI infrastructure, AI policy, Biz & IT, Cheyenne, Chris Lehane, Crusoe, datacenters, Energy, machine learning, Mark Gordon, Meta, microsoft, natural gas, openai, oracle, Patrick Collins, Policy, renewable energy, Tallgrass, wyoming / 9u50fv / July 30, 2025

Wyoming’s data center boom

Cheyenne is no stranger to data centers, having attracted facilities from Microsoft and Meta since 2012 due to its cool climate and energy access. However, the new project pushes the state into uncharted territory. While Wyoming is the nation’s third-biggest net energy supplier, producing 12 times more total energy than it consumes (dominated by fossil fuels), its electricity supply is finite.

While Tallgrass and Crusoe have announced the partnership, they haven’t revealed who will ultimately use all this computing power—leading to speculation about potential tenants.

A potential connection to OpenAI’s Stargate AI infrastructure project, announced in January, remains a subject of speculation. When asked by The Associated Press if the Cheyenne project was part of this effort, Crusoe spokesperson Andrew Schmitt was noncommittal. “We are not at a stage that we are ready to announce our tenant there,” Schmitt said. “I can’t confirm or deny that it’s going to be one of the Stargate.”

OpenAI recently activated the first phase of a Crusoe-built data center complex in Abilene, Texas, in partnership with Oracle. Chris Lehane, OpenAI’s chief global affairs officer, told The Associated Press last week that the Texas facility generates “roughly and depending how you count, about a gigawatt of energy” and represents “the largest data center—we think of it as a campus—in the world.”

OpenAI has committed to developing an additional 4.5 gigawatts of data center capacity through an agreement with Oracle. “We’re now in a position where we have, in a really concrete way, identified over five gigawatts of energy that we’re going to be able to build around,” Lehane told the AP. The company has not disclosed locations for these expansions, and Wyoming was not among the 16 states where OpenAI said it was searching for data center sites earlier this year.

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Meta pirated and seeded porn for years to train AI, lawsuit says

adult content, adult sites, AI, ai porn, AI training, AI training data, Ai video generator, BItTorrent, copyright infringement, LLaMA, Meta, online piracy, Policy, porn, seeding, torrenting / Kelly Newman / July 28, 2025

Evidence may prove Meta seeded more content

Seeking evidence to back its own copyright infringement claims, Strike 3 Holdings searched “its archive of recorded infringement captured by its VXN Scan and Cross Reference tools” and found 47 “IP addresses identified as owned by Facebook infringing its copyright protected Works.”

The data allegedly demonstrates a “continued unauthorized distribution” over “several years.” And Meta allegedly did not stop its seeding after Strike 3 Holdings confronted the tech giant with this evidence—despite the IP data supposedly being verified through an industry-leading provider called Maxmind.

Strike 3 Holdings shared a screenshot of MaxMind’s findings. Credit: via Strike 3 Holdings’ complaint

Meta also allegedly attempted to “conceal its BitTorrent activities” through “six Virtual Private Clouds” that formed a “stealth network” of “hidden IP addresses,” the lawsuit alleged, which seemingly implicated a “major third-party data center provider” as a partner in Meta’s piracy.

An analysis of these IP addresses allegedly found “data patterns that matched infringement patterns seen on Meta’s corporate IP Addresses” and included “evidence of other activity on the BitTorrent network including ebooks, movies, television shows, music, and software.” The seemingly non-human patterns documented on both sets of IP addresses suggest the data was for AI training and not for personal use, Strike 3 Holdings alleged.

Perhaps most shockingly, considering that a Meta employee joked “torrenting from a corporate laptop doesn’t feel right,” Strike 3 Holdings further alleged that it found “at least one residential IP address of a Meta employee” infringing its copyrighted works. That suggests Meta may have directed an employee to torrent pirated data outside the office to obscure the data trail.

The adult site operator did not identify the employee or the major data center discussed in its complaint, noting in a subsequent filing that it recognized the risks to Meta’s business and its employees’ privacy of sharing sensitive information.

In total, the company alleged that evidence shows “well over 100,000 unauthorized distribution transactions” linked to Meta’s corporate IPs. Strike 3 Holdings is hoping the evidence will lead a jury to find Meta liable for direct copyright infringement or charge Meta with secondary and vicarious copyright infringement if the jury finds that Meta successfully distanced itself by using the third-party data center or an employee’s home IP address.

“Meta has the right and ability to supervise and/or control its own corporate IP addresses, as well as the IP addresses hosted in off-infra data centers, and the acts of its employees and agents infringing Plaintiffs’ Works through their residential IPs by using Meta’s AI script to obtain content through BitTorrent,” the complaint said.

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Everything tech giants will hate about the EU’s new AI rules

AI, AI Act, AI risks, AI safety, AI training, Artificial Intelligence, copyright infringement, European Union, Google, Meta, microsoft, openai, piracy, Policy / Beth Washington / July 10, 2025

The code also details expectations for AI companies to respect paywalls, as well as robots.txt instructions restricting crawling, which could help confront a growing problem of AI crawlers hammering websites. It “encourages” online search giants to embrace a solution that Cloudflare is currently pushing: allowing content creators to protect copyrights by restricting AI crawling without impacting search indexing.

Additionally, companies are asked to disclose total energy consumption for both training and inference, allowing the EU to detect environmental concerns while companies race forward with AI innovation.

More substantially, the code’s safety guidance provides for additional monitoring for other harms. It makes recommendations to detect and avoid “serious incidents” with new AI models, which could include cybersecurity breaches, disruptions of critical infrastructure, “serious harm to a person’s health (mental and/or physical),” or “a death of a person.” It stipulates timelines of between five and 10 days to report serious incidents with the EU’s AI Office. And it requires companies to track all events, provide an “adequate level” of cybersecurity protection, prevent jailbreaking as best they can, and justify “any failures or circumventions of systemic risk mitigations.”

Ars reached out to tech companies for immediate reactions to the new rules. OpenAI, Meta, and Microsoft declined to comment. A Google spokesperson confirmed that the company is reviewing the code, which still must be approved by the European Commission and EU member states amid expected industry pushback.

“Europeans should have access to first-rate, secure AI models when they become available, and an environment that promotes innovation and investment,” Google’s spokesperson said. “We look forward to reviewing the code and sharing our views alongside other model providers and many others.”

These rules are just one part of the AI Act, which will start taking effect in a staggered approach over the next year or more, the NYT reported. Breaching the AI Act could result in AI models being yanked off the market or fines “of as much as 7 percent of a company’s annual sales or 3 percent for the companies developing advanced AI models,” Bloomberg noted.

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Meta’s “AI superintelligence” effort sounds just like its failed “metaverse”

AI, Artificial Intelligence, facebook, Meta, superhuman, superinteilligence, Tech, Zuckerberg / DJ Henderson / July 4, 2025

Zuckerberg and company talked up another supposed tech revolution four short years ago.

Artist’s conception of Mark Zuckerberg looking into our glorious AI-powered future. Credit: Facebook

In a memo to employees earlier this week, Meta CEO Mark Zuckerberg shared a vision for a near-future in which “personal [AI] superintelligence for everyone” forms “the beginning of a new era for humanity.” The newly formed Meta Superintelligence Labs—freshly staffed with multiple high-level acquisitions from OpenAI and other AI companies—will spearhead the development of “our next generation of models to get to the frontier in the next year or so,” Zuckerberg wrote.

Reading that memo, I couldn’t help but think of another “vision for the future” Zuckerberg shared not that long ago. At his 2021 Facebook Connect keynote, Zuckerberg laid out his plan for the metaverse, a virtual place where “you’re gonna be able to do almost anything you can imagine” and which would form the basis of “the next version of the Internet.”

“The future of the Internet” of the recent past. Credit: Meta

Zuckerberg believed in that vision so much at the time that he abandoned the well-known Facebook corporate brand in favor of the new name “Meta.” “I’m going to keep pushing and giving everything I’ve got to make this happen now,” Zuckerberg said at the time. Less than four years later, Zuckerberg seems to now be “giving everything [he’s] got” for a vision of AI “superintelligence,” reportedly offering pay packages of up to $300 million over four years to attract top talent from other AI companies (Meta has since denied those reports, saying, “The size and structure of these compensation packages have been misrepresented all over the place”).

Once again, Zuckerberg is promising that this new technology will revolutionize our lives and replace the ways we currently socialize and work on the Internet. But the utter failure (so far) of those over-the-top promises for the metaverse has us more than a little skeptical of how impactful Zuckerberg’s vision of “personal superintelligence for everyone” will truly be.

Meta-vision

Looking back at Zuckerberg’s 2021 Facebook Connect keynote shows just how hard the company was selling the promise of the metaverse at the time. Zuckerberg said the metaverse would represent an “even more immersive and embodied Internet” where “everything we do online today—connecting socially, entertainment, games, work—is going to be more natural and vivid.”

Mark Zuckerberg lays out his vision for the metaverse in 2021.

“Teleporting around the metaverse is going to be like clicking a link on the Internet,” Zuckerberg promised, and metaverse users would probably switch between “a photorealistic avatar for work, a stylized one for hanging out, and maybe even a fantasy one for gaming.” This kind of personalization would lead to “hundreds of thousands” of artists being able to make a living selling virtual metaverse goods that could be embedded in virtual or real-world environments.

“Lots of things that are physical today, like screens, will just be able to be holograms in the future,” Zuckerberg promised. “You won’t need a physical TV; it’ll just be a one-dollar hologram from some high school kid halfway across the world… we’ll be able to express ourselves in new joyful, completely immersive ways, and that’s going to unlock a lot of amazing new experiences.”

A pre-rendered concept video showed metaverse users playing poker in a zero-gravity space station with robot avatars, then pausing briefly to appreciate some animated 3D art a friend had encountered on the street. Another video showed a young woman teleporting via metaverse avatar to virtually join a friend attending a live concert in Tokyo, then buying virtual merch from the concert at a metaverse afterparty from the comfort of her home. Yet another showed old men playing chess on a park bench, even though one of the players was sitting across the country.

Meta-failure

Fast forward to 2025, and the current reality of Zuckerberg’s metaverse efforts bears almost no resemblance to anything shown or discussed back in 2021. Even enthusiasts describe Meta’s Horizon Worlds as a “depressing” and “lonely” experience characterized by “completely empty” venues. And Meta engineers anonymously gripe about metaverse tools that even employees actively avoid using and a messy codebase that was treated like “a 3D version of a mobile app. “

screen sharing — Even Meta employees reportedly don’t want to work in Horizon Workrooms. Credit: Facebook

The creation of a $50 million creator fund seems to have failed to encourage peeved creators to give the metaverse another chance. Things look a bit better if you expand your view past Meta’s own metaverse sandbox; the chaotic world of VR Chat attracts tens of thousands of daily users on Steam alone, for instance. Still, we’re a far cry from the replacement for the mobile Internet that Zuckerberg once trumpeted.

Then again, it’s possible that we just haven’t given Zuckerberg’s version of the metaverse enough time to develop. Back in 2021, he said that “a lot of this is going to be mainstream” within “the next five or 10 years.” That timeframe gives Meta at least a few more years to develop and release its long-teased, lightweight augmented reality glasses that the company showed off last year in the form of a prototype that reportedly still costs $10,000 per unit.

Zuckerberg shows off prototype AR glasses that could change the way we think about “the metaverse.” Credit: Bloomberg / Contributor | Bloomberg

Maybe those glasses will ignite widespread interest in the metaverse in a way that Meta’s bulky, niche VR goggles have utterly failed to. Regardless, after nearly four years and roughly $60 billion in VR-related losses, Meta thus far has surprisingly little to show for its massive investment in Zuckerberg’s metaverse vision.

Our AI future?

When I hear Zuckerberg talk about the promise of AI these days, it’s hard not to hear echoes of his monumental vision for the metaverse from 2021. If anything, Zuckerberg’s vision of our AI-powered future is even more grandiose than his view of the metaverse.

As with the metaverse, Zuckerberg now sees AI forming a replacement for the current version of the Internet. “Do you think in five years we’re just going to be sitting in our feed and consuming media that’s just video?” Zuckerberg asked rhetorically in an April interview with Drawkesh Patel. “No, it’s going to be interactive,” he continued, envisioning something like Instagram Reels, but “you can talk to it, or interact with it, and it talks back, or it changes what it’s doing. Or you can jump into it like a game and interact with it. That’s all going to be AI.”

Mark Zuckerberg talks about all the ways superhuman AI is going to change our lives in the near future.

As with the Metaverse, Zuckerberg sees AI as revolutionizing the way we interact with each other. He envisions “always-on video chats with the AI” incorporating expressions and body language borrowed from the company’s work on the metaverse. And our relationships with AI models are “just going to get more intense as these AIs become more unique, more personable, more intelligent, more spontaneous, more funny, and so forth,” Zuckerberg said. “As the personalization loop kicks in and the AI starts to get to know you better and better, that will just be really compelling.”

Zuckerberg did allow that relationships with AI would “probably not” replace in-person connections, because there are “things that are better about physical connections when you can have them.” At the same time, he said, for the average American who has three friends, AI relationships can fill the “demand” for “something like 15 friends” without the effort of real-world socializing. “People just don’t have as much connection as they want,” Zuckerberg said. “They feel more alone a lot of the time than they would like.”

A toy robot saying — Why chat with real friends on Facebook when you can chat with AI avatars? Credit: Benj Edwards / Getty Images

Zuckerberg also sees AI leading to a flourishing of human productivity and creativity in a way even his wildest metaverse imaginings couldn’t match. Zuckerberg said that AI advancement could “lead toward a world of abundance where everyone has these superhuman tools to create whatever they want.” That means personal access to “a super powerful [virtual] software engineer” and AIs that are “solving diseases, advancing science, developing new technology that makes our lives better.”

That will also mean that some companies will be able to get by with fewer employees before too long, Zuckerberg said. In customer service, for instance, “as AI gets better, you’re going to get to a place where AI can handle a bunch of people’s issues,” he said. “Not all of them—maybe 10 years from now it can handle all of them—but thinking about a three- to five-year time horizon, it will be able to handle a bunch.“

In the longer term, Zuckerberg said, AIs will be integrated into our more casual pursuits as well. “If everyone has these superhuman tools to create a ton of different stuff, you’re going to get incredible diversity,” and “the amount of creativity that’s going to be unlocked is going to be massive,” he said. “I would guess the world is going to get a lot funnier, weirder, and quirkier, the way that memes on the Internet have gotten over the last 10 years.”

Compare and contrast

To be sure, there are some important differences between the past promise of the metaverse and the current promise of AI technology. Zuckerberg claims that a billion people use Meta’s AI products monthly, for instance, utterly dwarfing the highest estimates for regular use of “the metaverse” or augmented reality as a whole (even if many AI users seem to balk at paying for regular use of AI tools). Meta coders are also reportedly already using AI coding tools regularly in a way they never did with Meta’s metaverse tools. And people are already developing what they consider meaningful relationships with AI personas, whether that’s in the form of therapists or romantic partners.

Still, there are reasons to be skeptical about the future of AI when current models still routinely hallucinate basic facts, show fundamental issues when attempting reasoning, and struggle with basic tasks like beating a children’s video game. The path from where we are to a supposed “superhuman” AI is not simple or inevitable, despite the handwaving of industry boosters like Zuckerberg.

Artist’s conception of Carmack’s VR avatar waving goodbye to Meta.

At the 2021 rollout of Meta’s push to develop a metaverse, high-ranking Meta executives like John Carmack were at least up front about the technical and product-development barriers that could get in the way of Zuckerberg’s vision. “Everybody that wants to work on the metaverse talks about the limitless possibilities of it,” Carmack said at the time (before departing the company in late 2022). “But it’s not limitless. It is a challenge to fit things in, but you can make smarter decisions about exactly what is important and then really optimize the heck out of things.”

Today, those kinds of voices of internal skepticism seem in short supply as Meta sets itself up to push AI in the same way it once backed the metaverse. Don’t be surprised, though, if today’s promise that we’re at “the beginning of a new era for humanity” ages about as well as Meta’s former promises about a metaverse where “you’re gonna be able to do almost anything you can imagine.”

Kyle Orland has been the Senior Gaming Editor at Ars Technica since 2012, writing primarily about the business, tech, and culture behind video games. He has journalism and computer science degrees from University of Maryland. He once wrote a whole book about Minesweeper.

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Meta, TikTok can’t toss wrongful death suit from mom of “subway surfing” teen

algorithm, bytedance, Meta, Policy, recommended content, Section 230, tiktok, wrongful death / DJ Henderson / June 30, 2025

Section 230 has so far failed to shield Meta and TikTok owner ByteDance from a lawsuit raised by a mother who alleged that her son’s wrongful death followed a flood of “subway surfing” videos platforms intentionally targeted to teens in New York.

In a decision Monday, New York State Supreme Court Judge Paul Goetz largely denied social media companies’ motions to dismiss claims they argued should be barred under Section 230 and the First Amendment. Goetz said that the mother, Norma Nazario, had adequately alleged that subway surfing content “was purposefully fed” to her son Zackery “because of his age” and “not because of any user inputs that indicated he was interested in seeing such content.”

Unlike other Section 230 cases in which platforms’ algorithms were determined to be content-neutral, Goetz wrote that in this case, “it is plausible that the social media defendants’ role exceeded that of neutral assistance in promoting content and constituted active identification of users who would be most impacted by the content.”

Platforms may be forced to demystify algorithms

Moving forward, Nazario will have a chance to seek discovery that could show exactly how Zackery came to interact with the subway surfing content. In her complaint, she did not ask for the removal of all subway surfing content but rather wants to see platforms held accountable for allegedly dangerous design choices that supposedly target unwitting teens.

“Social media defendants should not be permitted to actively target young users of its applications with dangerous ‘challenges’ before the user gives any indication that they are specifically interested in such content and without warning,” Nazario has argued.

And if she’s proven right, that means platforms won’t be forced to censor any content but must instead update algorithms to stop sending “dangerous” challenges to keep teens engaged at a time when they’re more likely to make reckless decisions, Goetz suggested.

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Judge: Pirate libraries may have profited from Meta torrenting 80TB of books

AI, AI training, BItTorrent, copyright, copyright infringement, libgen, LLaMA, Meta, online piracy, Policy, shadow libraries, torrenting / Shannon Garcia / June 27, 2025

It could certainly look worse for Meta if authors manage to present evidence supporting the second way that torrenting could be relevant to the case, Chhabaria suggested.

“Meta downloading copyrighted material from shadow libraries” would also be relevant to the character of the use, “if it benefitted those who created the libraries and thus supported and perpetuated their unauthorized copying and distribution of copyrighted works,” Chhabria wrote.

Counting potential strikes against Meta, Chhabria pointed out that the “vast majority of cases” involving “this sort of peer-to-peer file-sharing” are found to “constitute copyright infringement.” And it likely doesn’t help Meta’s case that “some of the libraries Meta used have themselves been found liable for infringement.”

However, Meta may overcome this argument, too, since book authors “have not submitted any evidence” that potentially shows how Meta’s downloading may perhaps be “propping up” or financially benefiting pirate libraries.

Finally, Chhabria noted that the “last issue relating to the character of Meta’s use” of books in regards to its torrenting is “the relationship between Meta’s downloading of the plaintiffs’ books and Meta’s use of the books to train Llama.”

Authors had tried to argue that these elements were distinct. But Chhabria said there’s no separating the fact that Meta downloaded the books to serve the “highly transformative” purpose of training Llama.

“Because Meta’s ultimate use of the plaintiffs’ books was transformative, so too was Meta’s downloading of those books,” Chhabria wrote.

AI training rulings may get more authors paid

Authors only learned of Meta’s torrenting through discovery in the lawsuit, and because of that, Chhabria noted that “the record on Meta’s alleged distribution is incomplete.”

It’s possible that authors may be able to show evidence that Meta “contributed to the BitTorrent network” by providing significant computing power that could’ve meaningfully assisted shadow libraries, Chhabria said in a footnote.

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To avoid admitting ignorance, Meta AI says man’s number is a company helpline

AI, AI hallucination, Artificial Intelligence, chatbots, Meta, Meta AI, Online Privacy, Policy, whatsapp / DJ Henderson / June 20, 2025

Although that statement may provide comfort to those who have kept their WhatsApp numbers off the Internet, it doesn’t resolve the issue of WhatsApp’s AI helper potentially randomly generating a real person’s private number that may be a few digits off from the business contact information WhatsApp users are seeking.

Expert pushes for chatbot design tweaks

AI companies have recently been grappling with the problem of chatbots being programmed to tell users what they want to hear, instead of providing accurate information. Not only are users sick of “overly flattering” chatbot responses—potentially reinforcing users’ poor decisions—but the chatbots could be inducing users to share more private information than they would otherwise.

The latter could make it easier for AI companies to monetize the interactions, gathering private data to target advertising, which could deter AI companies from solving the sycophantic chatbot problem. Developers for Meta rival OpenAI, The Guardian noted, last month shared examples of “systemic deception behavior masked as helpfulness” and chatbots’ tendency to tell little white lies to mask incompetence.

“When pushed hard—under pressure, deadlines, expectations—it will often say whatever it needs to to appear competent,” developers noted.

Mike Stanhope, the managing director of strategic data consultants Carruthers and Jackson, told The Guardian that Meta should be more transparent about the design of its AI so that users can know if the chatbot is designed to rely on deception to reduce user friction.

“If the engineers at Meta are designing ‘white lie’ tendencies into their AI, the public need to be informed, even if the intention of the feature is to minimize harm,” Stanhope said. “If this behavior is novel, uncommon, or not explicitly designed, this raises even more questions around what safeguards are in place and just how predictable we can force an AI’s behavior to be.”

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Meta beefs up disappointing AI division with $15 billion Scale AI investment

AI, llm, Meta, scale, syndication / Shannon Garcia / June 13, 2025

Meta has invested heavily in generative AI, with the majority of its planned $72 billion in capital expenditure this year earmarked for data centers and servers. The deal underlines the high price AI companies are willing to pay for data that can be used to train AI models.

Zuckerberg pledged last year that his company’s models would outstrip rivals’ efforts in 2025, but Meta’s most recent release, Llama 4, has underperformed on various independent reasoning and coding benchmarks.

The long-term goal of researchers at Meta “has always been to reach human intelligence and go beyond it,” said Yann LeCun, the company’s chief AI scientist at the VivaTech conference in Paris this week.

Building artificial “general” intelligence—AI technologies that have human-level intelligence—is a popular goal for many AI companies. An increasing number of Silicon Valley groups are also seeking to reach “superintelligence,” a hypothetical scenario where AI systems surpass human intelligence.

The core of Scale’s business has been data-labeling, a manual process of ensuring images and text are accurately labeled and categorized before they are used to train AI models.

Wang has forged relationships with Silicon Valley’s biggest investors and technologists, including OpenAI’s Sam Altman. Scale AI’s early customers were autonomous vehicle companies, but the bulk of its expected $2 billion in revenues this year will come from labeling the data used to train the massive AI models built by OpenAI and others.

The deal will result in a substantial payday for Scale’s early venture capital investors, including Accel, Tiger Global Management, and Index Ventures. Tiger’s $200 million investment is worth more than $1 billion at the company’s new valuation, according to a person with knowledge of the matter.

Additional reporting by Tabby Kinder in San Francisco

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After AI setbacks, Meta bets billions on undefined “superintelligence”

agi, AI, Alexander Wang, Biz & IT, chatbots, chatgpt, chatgtp, machine learning, mark zuckerberg, Meta, Meta AI, sam altman, Scale AI, superintelligence, Yann LeCun / 9u50fv / June 10, 2025

Meta has developed plans to create a new artificial intelligence research lab dedicated to pursuing “superintelligence,” according to reporting from The New York Times. The social media giant chose 28-year-old Alexandr Wang, founder and CEO of Scale AI, to join the new lab as part of a broader reorganization of Meta’s AI efforts under CEO Mark Zuckerberg.

Superintelligence refers to a hypothetical AI system that would exceed human cognitive abilities—a step beyond artificial general intelligence (AGI), which aims to match an intelligent human’s capability for learning new tasks without intensive specialized training.

However, much like AGI, superintelligence remains a nebulous term in the field. Since scientists still poorly understand the mechanics of human intelligence, and because human intelligence resists simple quantification with no single definition, identifying superintelligence when it arrives will present significant challenges.

Computers already far surpass humans in certain forms of information processing such as calculations, but this narrow superiority doesn’t qualify as superintelligence under most definitions. The pursuit assumes we’ll recognize it when we see it, despite the conceptual fuzziness.

Illustration of studious robot reading a book

AI researcher Dr. Margaret Mitchell told Ars Technica in April 2024 that there will “likely never be agreement on comparisons between human and machine intelligence” but predicted that “men in positions of power and influence, particularly ones with investments in AI, will declare that AI is smarter than humans” regardless of the reality.

The new lab represents Meta’s effort to remain competitive in the increasingly crowded AI race, where tech giants continue pouring billions into research and talent acquisition. Meta has reportedly offered compensation packages worth seven to nine figures to dozens of researchers from companies like OpenAI and Google, according to The New York Times, with some already agreeing to join the company.

Meta joins a growing list of tech giants making bold claims about advanced AI development. In January, OpenAI CEO Sam Altman wrote in a blog post that “we are now confident we know how to build AGI as we have traditionally understood it.” Earlier, in September 2024, Altman predicted that the AI industry might develop superintelligence “in a few thousand days.” Elon Musk made an even more aggressive prediction in April 2024, saying that AI would be “smarter than the smartest human” by “next year, within two years.”

After AI setbacks, Meta bets billions on undefined “superintelligence” Read More »