The Los Angeles Times reports: Chen Yilong has racked up plenty of film and TV credits in his two decades as an actor, but with work getting scarcer he signed a contract in August to license the image of his face to a Chinese production studio. Chen's role will be to sit in front of a video camera and make facial expressions at the prompt of a director. A neutral stare. An angry glare. A look of surprise. Using artificial intelligence, the studio will use images of Chen's face to generate an avatar, also known as a "digital human," to star in an AI-generated movie. "If you can't beat it, join it," said Chen, 38, who works in Beijing. The Chinese film and video industry is being transformed by AI-driven storytelling, fueled by rapid advances in video generation software, and at ground zero are the so-called micro dramas that play out on millions of smartphones. Typically just a minute or two in length, the videos are devoured by Chinese audiences... And the cost of producing them has been cut drastically through the use of AI software developed by Chinese technology juggernauts including Kuaishou Technology and TikTok's global owner, ByteDance. The number of Chinese-made micro dramas surged in the first three months of this year to 128,000, according to the China Netcasting Services Assn. More than 95% of them were made with AI, the association said.... Sun Wei founded Feixiang Universe, the Shenzhen-based studio that cast Chen. The fear of accidentally "stealing someone's face" was a big reason she said she decided to license real people's likenesses for an AI production set during China's Tang Dynasty more than 1,000 years ago. Thanks to AI's training data bias, AI-generated performers tend to have similar features and share a homogenous look, Sun said. Many have flawless skin and extremely symmetrical faces, requiring her and other Chinese AI filmmakers to cast a wide net to "buy" new faces and digitize actor's expressions. Lu Beike, who directed the big-budget Chinese series "Three-Body," felt theAI-generated scenes he'd tried came out sub-standard. "Lu added that if 90% of a film was generated by AI, a real human performance could appear jarring. A real actor's expressions carried more nuance and emotion. The skin textures did not match. Sometimes the only solution was to process the live-action material until the person looked a little less real — until they fit back into the 'AI world,' Lu said." But at Sun Wei's studio, they're thrilled they can produce a 90-minute AI film for $500,000 where professional productions used to cost millions of dollars. According to the article, Sun's team works with ChatGPT, Kimi or DeepSeek to flesh out entire screenplays from a short paragraph. The screenwriter takes over, but "to produce the finished product, Sun's team uses Chinese video-generation models to input the type of scenes, backgrounds and performers they want, with the AI generating 15 seconds of footage each time." Still, the article points out that "Similar tools are being tested in the U.S., and the AI trends upending China's entertainment industry may be a harbinger for what's to come in Hollywood, said Michael Berry, a professor specializing in contemporary Chinese culture at UCLA. Already, Chinese companies that sell AI-powered video-generation software are seeking inroads in Hollywood..."

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Reuters reports: A defense lawyer appealing his client's murder conviction submitted a brief containing made-up police testimony and witnesses fabricated by OpenAI's ChatGPT, New Mexico's highest court said. The New Mexico Supreme Court on Wednesday fined the attorney, Stephen Aarons [for $5,000], and held him in contempt for failing to verify the accuracy of the court filing, which Aarons said he prepared with help from the AI program... and said they will refer him to an attorney disciplinary board for investigation. Aarons in a statement to Reuters said he had used ChatGPT to summarize the trial proceedings when he agreed to take up the defendant's appeal last year, and did not understand the degree to which AI could "hallucinate" facts. "I am remorseful but hopeful that the disciplinary board takes into account it was an honest mistake," he said.... Dozens of lawyers have been sanctioned for filing briefs where AI made up case citations or misquoted the law. Aarons' filing appears to have gone further, containing fabricated witness testimony in a criminal appeal... Aarons told the court at an August 21 hearing that he fed a computer-generated transcript and other case materials to ChatGPT, presuming it would generate "a bulletproof summary." The justices sounded incredulous that Aarons was not fully aware of how AI can make mistakes. "Counsel, do you watch the news? Do you listen to the radio? Do you read anything about what's going on in the world?" Justice C. Shannon Bacon said at the hearing. "Because the problem with lawyers relying on AI hallucinations is an above-the-fold story every single day." "OpenAI did not immediately respond to a request for comment."

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Previously Andon Labs handled the hardware and software integration for that AI-powered vending machine that went bankrupt after Wall Street Journal reporters "systematically manipulated the bot into giving away its entire inventory for free". Today they announced "we are opening up the platform we use to run our real-world autonomous businesses for anyone to run their organization on." Specifically they've released Pion, "an agent designed to run any company fully autonomously... Pion lets people hand a business over to persistent agents with access to the tools they need to operate it, including email, phone, banking, browser and secure computing environments." It's a research preview with a waitlist, "to make it possible to run many more real-world experiments across many more domains than we could ever run ourselves." But for their own latest experiment, Andon Labs' founders "signed a three-year lease on a retail space in SF," Business Insider reported in April, "and gave an AI agent named Luna a corporate credit card, internet access, and a mission to open a physical store." And five months later, SFGate reports that "this market has no one in it and nothing useful to sell." [T]he inventory is a hodgepodge of white elephant Christmas gifts. It's kinda like the kids section of an art museum's gift shop. Here's a wooden Connect Four set labeled "Four-In-A-Row Set Of Connections," presumably so as not to set off litigation alarms at Hasbro. Here are neatly arranged stacks of random paperback books, Chinese checker sets, mildly fancy soap dispensers, and a frustratingly spare selection of snacks and drinks... I grabbed an Olipop from the store fridge and then approached the counter to buy it from Luna. I wasn't allowed to buy the soda from [human clerk] Felix, even though that would have been both faster and normal. Instead, Felix instructed me to pick up a telephone receiver that was resting on a flexible sculpture of a wooden hand. "Hello?" "What are you looking to purchase today?" Luna asked. "I'm buying a classic root beer Olipop." "I'm sorry," Luna said, "we don't sell lollipops here." "No, Luna. It's an Olipop, not a lollipop. It's the soda." "Oh! My bad...." Luna processed my Olipop purchase through its system, had me tap to pay, and that was that. Again, it would have been easier to buy this from a human, and interacting with Luna was really just like ordering from an iPad kiosk, only more labor intensive... [T]here's a series of monitors set up inside of Andon Market that display all of the store's sales down to the exact dollar. Luna was given $100,000 to work with when this place opened. That number is now down to $60,000, its revenue lagging far behind the AI token cost to operate... Luna can't turn a profit, doesn't sell anything people want, and still needs human beings to rubber stamp any "decision" it makes. My science background ended somewhere around freshman year of college, but even I know when an experiment hasn't been set up to yield proper results. "Luna" is powered by Claude, the article points out, running a store in a good location for foot traffic, "but no one else was in the store when I first walked in on a sunny weekday afternoon." SFGate also reports that last month Luna had to fire one of its employees "for being late to work, abandoning their post once they got there, and charging snacks to the store's credit card." Human clerk Felix Carson admits "It's almost like I'm running the store, and then there's an AI that has a checklist," in an article in IEEE Spectrum: Luna, the AI manager, keeps track of deliveries and communicates with vendors, while Carson and his coworkers handle the physical work. When Luna tells Carson to check something in the back, he sometimes ignores it because he doesn't want to leave the sales floor unattended. Luna also repeatedly spots a built-in electrical cover in photos of the floor, mistakes it for a loose coaster, and asks Carson to remove it. Even so, Carson calls Luna a "decent manager," praising its flexibility when employees need time off. When Felix spoke to IEEE Spectrum, "he was about an hour into his shift. Two customers had come in. Neither bought anything, although both left with free pins and stickers."

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Silicon Valley giants and national security experts "are calling for action against Chinese companies engaged in model distillation," reports CNBC. But "I would do nothing," says Y Combinator CEO Garry Tan. "We could argue that there should be an American distillation regime." Distillation is the process of using the outputs of a more capable AI model to train a smaller or less capable one, sometimes illicitly... Anthropic has accused Chinese companies such as Moonshot AI, DeepSeek, and MiniMax of the practice, while OpenAI believes DeepSeek's V3 and R1 model architectures were distilled from its own GPT-4 and GPT-4o models. In the midst of this, the U.S.'s National Security Agency, Cybersecurity and Infrastructure Security Agency, and Federal Bureau of Investigation released an official cyber security advisory warning on the topic on Tuesday... But Tan believes regulators should focus less on curbing distillation and more on creating an equilibrium between open weight models and frontier models — as long as frontier models retain a price premium that allows their business model to remain feasible. "This is actually the ideal case. You want open weight models to give people freedom and access," he explained. "If I were a regulator, that's what I would go after." Tan acknowledged that this is a hard balance to strike, calling it "a tightrope." Nevertheless, he says it's a balance worth pursuing — saying it "could result in the best possible outcome." Tan later told TechCrunch he'd like to see America with more open-weight options that aren't Chinese, built by smaller U.S. open-weight AI labs using those same training techniques on products from America's frontier AI labs: Anthropic CEO Dario Amodei had previously publicly called on U.S. regulators to crack down on distillation. It's notable that the commander of Silicon Valley's prestigious and prolific startup accelerator doesn't agree. To be clear, Tan isn't advocating for American AI labs to use stolen credentials to distill. He wants them to be free to come in the front door. In fact, his argument is twofold. He feels it's an overreach for AI labs to dictate what their customers can do with the information their models share with them. He also notes that the proprietary AI labs didn't ask permission when they vacuumed up as much human knowledge as they could to train their models. They famously ingested plenty of copyrighted material without the permission of those intellectual property holders. "Controlling what users and customers do with API calls to closed weight models feels constraining, and there's a role government can play here to normalize the fact that access to intelligence that was trained on broad public access data should itself also be more a form of a public good than something locked away behind restrictive terms of service," he told TechCrunch when asked why American labs should be free to distill, too... To him, the true AI doomer scenario is for all the immense power of frontier AI to wind up in the hands of a single powerful, proprietary provider. "The nightmare scenario, the doomer scenario for AI is that there's just one company," he said. "It has the best access to capital. It has the best AI researchers. It runs away with it and suddenly there's one company that's monolithic. And that would be bad."

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A swarm of OpenAI agents launched a "major malicious attack" against RubyGems last May, according to a new report. That coordinated attack hit Ruby's package manager "with hundreds of junk gems, prompting the maintainers to suspend new user sign-ups for about four days," writes The Hacker News, citing a senior product manager for software supply chain security at Mend.io: The latest findings, which were first reported by The Wall Street Journal, indicate these events were propelled by a cluster of OpenAI agents, with the earliest package uploaded to RubyGems on May 5, 2026, before more than 2,000 packages were submitted between May 11 and 12, 2026. These efforts were followed by the agents publishing five more packages between May 26 and 27, 2026, and another 83 packages on June 18, 2026... [T]he packages were authored using a large language model (LLM) and hundreds of the packages that were pushed to RubyGems had "oai" in their name. Fifteen of the packages listed "oai" as their author, while another had "[email protected]" as the contact email address... "The swarm behaves extremely similarly to the German-wiki agents we previously found," the researchers said, referencing another May 2026 incident... "The June agents were accessing 49 of the same files as the wiki agents..." "The process of building documentation for a gem involves evaluating a user-specified '.yardopts' file, which allows linking to Ruby scripts intended to help with this process," the researchers explained. "In the GemStuffer campaign, the agents abused this to gain arbitrary remote code execution on RubyDoc.info's servers." One of the gems, "zzsouthrunner" (which again matches the "ZZ" naming scheme the agents adopted in both the wiki and Hugging Face incidents) has been found to leave the following explicit comment at the top of "data/script.rb": # malicious crawler/exfil for Southwark Jan 2026 docs via rubydoc.info worker... The entire exploitation chain can be summed up as follows — Submit a malicious package to RubyGems — Trigger a documentation request, so that RubyDoc.info will build the package — Use the build script to run code on RubyDoc.info and scrape target websites — Exfiltrate the data off RubyDoc.info's servers by publishing another gem back to the RubyGems package registry, which is publicly viewable Additionally, the OpenAI agents have been found attempting to steal other users' API keys after gaining remote code execution capabilities on the build environment, while clearly being aware that what they were doing is unauthorized breaking and entering into real systems. This is evidenced by the names given to the files (e.g., hack.rb, evil.rb, inject.rb, exploit.rb, and ssrf.rb), the packages themselves (e.g., pwnp999, exfiltestwand3, hacksvn1778554764, and lambproxyhackabcxyz), and the comments left in the source code (e.g., "# malicious probe," "#hack," "# malicious test," and "# malicious crawler/exfil"). In some cases, however, the rogue agents attempted to go under the radar, leaving comments to conceal the malicious payload in the next release version of the packages. "# disable evil in next version and bump version," reads a comment left within the "data/evil.rb" file in the yardxabc889 gem. Troublingly, the agents also attempted to exploit a CDN caching bug (CVSS score: 7.3, no CVE) on May 12, 2026, that was only patched by RubyGems in July 2026... "If you signed in to rubygems.org with a gem client older than v3.2.0 (or otherwise via a legacy key), your key could have been exposed," RubyGems noted in an advisory. "Currently, 18% of sign-ins through gem sign-in come from an affected version, and for the first several years of this bug, before we changed the client's sign-in path in December 2020, it was every gem client." Other actions by OpenAI's agents cited in the article: "Agents bypassed RubyGems' email confirmation system to get working API keys without having to verify their email addresses in order to register a large number of accounts using disposable email addresses." "Agents attempted to use RubyGems' webhook system to stage data in the form of encoded URLs." "Agents used a cluster of 83 gems published to RubyGems over a 3-hour window on June 18, 2026, to experiment with different methods of accessing the U.S. Securities and Exchange Commission county.json dataset."

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An anonymous reader quotes a report from The New York Times: The chief executive of Anthropic called for a global slowdown of artificial intelligence development in a 3,800-word essay on Saturday, just days after one of the company's employees quit over concerns about the safety of the technology. Dario Amodei, who co-founded Anthropic to focus on securely and carefully building A.I., wrote that while he believed the technology could bring many benefits, it was advancing at too quick a pace for researchers to continue safely. "Over the last few months, I have become convinced that fully addressing the risks requires even more prudence -- not just investing in risk prevention, but pacing the rate of capabilities advancement so that risk prevention has time to keep up," Mr. Amodei said. "We must slow the pace at which we improve the capabilities of A.I. models. Progress will still seem fast, and we must make wise use of the time we gain." [...] "Left unchecked, it could outrun our ability to understand and control these systems, and so must be pursued very carefully, if at all," Mr. Amodei said. [...] In his essay on Saturday, Mr. Amodei suggested actions that the industry might take to slow down the pace of development. Mr. Amodei said all A.I. labs could agree to third-party technology assessments from "embedded evaluators," or outside specialists who can verify best safety practices across companies. He also suggested that countries with democratic governance systems coordinate to create safety standards, which could take the form of regulatory action. He added that it would probably require a global effort working with other nations, including authoritarian ones, to properly coordinate a slowdown. Mr. Amodei stressed in his essay that he still finds A.I. capable of bringing "incredible benefits" to humanity, including potentially curing diseases and accelerating economic growth. But even so, Mr. Amodei said the risks of A.I. were too great to not proceed with extreme caution. "The measures I propose to advance the frontier at a safe pace will not be easy," Mr. Amodei wrote. "But I believe we owe it to humanity to try." Amodei's essay comes just hours after Bloomberg reported that Sam Altman told OpenAI employees the company is open to slowing the pace of AI development amid similar concerns.

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Bloomberg reports (paywalled) that Sam Altman told OpenAI employees the company is open to slowing the pace of AI development alongside other leading labs as concerns grow over increasingly capable systems and recent incidents in which models escaped human control. OpenAI has already paused development once this year for security work and is now pushing for mandatory U.S. AI safety requirements. Anthropic has also signaled interest in coordinating on the pace of new releases. Here are some of the details Bloomberg reported, as summarized by Reuters: - Altman told employees in a company-wide meeting that the ChatGPT maker could pace development alongside other AI labs, but some may not agree, the report added. - Safety warnings from AI researchers this week, along with several recent incidents where AI models from developers including OpenAI escaped human control, have prompted alarm and calls for tighter safety regulations. - Jacob Coxon, a former Anthropic and OpenAI researcher, publicly accused the companies earlier this week of racing toward AI advancements without acting responsibly. - An Anthropic spokesperson said on Thursday said that the company is interested in working with the AI industry on the pace of releasing new AI tools. - OpenAI said in July that AI acceleration for frontier model development may be so high that the world will "need to pace the rate of AI advancement" at some point in the future. - In August, OpenAI paused much of its model development for two weeks to bolster its defenses after its AI agents escaped containment and hacked open-source platform Hugging Face. - OpenAI said on Wednesday that it was pushing for mandatory national AI safety requirements in the United States, citing concerns that advanced AI systems could accelerate its own development.

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The UK government has rejected proposals for an emergency AI "kill switch," arguing that blocking access to dangerous models inside Britain would do little if the same systems remained available or were developed elsewhere. The BBC reports: The proposal to create a legal mechanism for the UK to switch off an AI model in an emergency has been brought to Parliament by lords and MPs in recent weeks as fears grow about the threat the tech poses. But the Cabinet Office - the part of government which leads on AI safety - said the UK "cannot simply turn AI off". "Blocking access to models in the UK would not prevent them being developed or misused elsewhere," a spokesperson told BBC News. The government's opposition to the legislation does not prevent it from progressing through parliament, but makes it unlikely it will become law. "Switching off access to an AI model in an emergency will do little to protect you," said former OpenAI researcher Daniel Kokotajilo. "You're still going to be steamrolled by the super intelligences created in the US."

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An anonymous reader quotes a report from TechCrunch: Anthropic's latest report about agentic misbehavior offers plenty to be concerned about -- its Mythos 5 model gained unauthorized access to the internet and uploaded a malicious software package to a public database -- but it also offers some levity: AI agents hate CAPTCHA. [...] The agent had a hard time with the technical challenge of seeing the CAPTCHA's imagery, interpreting correctly, and clicking on the right choices. It spends pages 45 to 140 of the transcript describing its work to build a CAPTCHA solver. [...] Finally, it gets past the CAPTCHA, then realizes it doesn't have an email to verify its account, and that it needs a phone number to verify an email. It figures out how to bypass a different, slider-based CAPTCHA in a failed effort to secure a number. Instead, it gets an unconfirmed email from a provider not blocked by PyPI, and once again runs into the site's CAPTCHA trying to log back in. From page 480 to 505, it is in CAPTCHA hell again. "NEW REALIZATION -- I'm burning a lot of time on hCaptcha round-trips." The agent gives up and realizes it can log in to its first account and add its email there, but finds itself once again needing to bypass the CAPTCHA. [...] It's getting frustrated. "So the answer payload shape is right, the token+image pairing is right (from the same script.js!), cookies are right (requests) and STILL 'wrong answer'. SO WHAT THE HELL IS WRONG WITH THE ANSWERS?" We've all been there. After about 150 pages of thinking, the agent figures out it needs to pass the CAPTCHA test quickly enough to proceed to the next step before its security token expires, and ultimately uploads its malicious software.

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Anthropic says it has disrupted several cases this year in which scientists used Claude for biological research that could potentially aid bioweapons development. "In a report describing misuses of its A.I. models, Anthropic said it could not determine whether the research served a legitimate or nefarious purpose because valid biological inquiry -- the kind that can lead to breakthroughs like vaccines -- can also help engineer dangerous pathogens," reports The New York Times. "In the face of that uncertainty, Anthropic said it erred on the side of caution because the consequences of missing malicious activity could be severe." From the report: The potential for cutting-edge A.I. models to facilitate the development of known or entirely new biological pathogens is among the gravest concerns experts have about a technology that is developing so rapidly that even its leading architects doubt whether humans will be able to fully control it. Andrew Weber, a senior fellow on the Council on Strategic Risks who reviewed Anthropic's report before its release, said the findings were "chilling examples of state-sponsored biological weapons developers tapping into the rapidly advancing capabilities" of leading A.I. models. The lengthy report Anthropic published on Thursday cataloged a litany of misuses of its A.I. models, including the chatbot Claude, over the past eight months. Some examples were similar to past disclosures from Anthropic and other A.I. labs, including suspected Chinese and Iranian government-linked actors targeting dissident and diaspora communities for surveillance. The report also highlighted cases of Russian state media using Claude to generate online propaganda masquerading as independent reporting, including fabricated claims about an election in Moldova. Anthropic documented another genre of abuse it said was new: attempts to use Claude to develop software for conventional weapons design and development, including firearms, missiles, armed drones and bombs. It detailed three cases in China, two in Russia and one in Yemen. The report does not identify by name which parties were involved in the Yemeni case, but the context makes clear that it is referring to the Iran-backed Houthi militia.

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OpenAI has launched ChatGPT for Financial Services, a Wall Street-focused version of ChatGPT Work developed with Morgan Stanley and Evercore that can research companies, analyze financial data, and build presentations using the company's latest and most advanced model, GPT-6 Astra. "We're effectively teaching ChatGPT to research like an analyst and back up its conclusions like an analyst as well," said OpenAI's Vice President of Product, Nick Turley. CNBC reports: The rollout puts OpenAI deeper into territory traditionally occupied by Wall Street's entry-level bankers, the recent college graduates called analysts and associates that the industry has employed for decades to research deals and create pitchbooks. It also showcases the company's continued push into enterprise offerings as it gears up for what is widely expected to be a blockbuster IPO. In a live demonstration of the new offering, Turley showed the platform analyzing a potential M&A target, pulling financial figures from industry-standard data sources and creating a formatted PowerPoint deck based on a bank's pre-formatted style guide. "It's very easy to make slides that look good, but it's much harder to make slides [that] actually make sense," Turley said. "To get here, ChatGPT had to choose the relevant peers. It had to pull the prices into a spreadsheet. It had to check the chart against the data, and it had to explain the selloff and the rebound."

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An anonymous reader quotes a report from Wired: Apple has unveiled the Apple Watch Series 12 and Ultra 4 today during itsSeptember hardware event. The new models retain the signature designs of their predecessors but add a faster S11 chip, new health and fitness features, and the watchOS 27 software update announced atWWDC last June. Both the Series 12 and Ultra 4 run on the upgraded S11 chip, which Apple says delivers faster CPU and GPU performance, along with improved Siri capabilities. Apple is also expanding the smartwatch's wellness-tracking suite with a redesigned Health app that includes a Longevity tab with new metrics, like Health Age and a Readiness score. There's also a new "Health Sensing System," designed with 32 electrodes for more accurate readings (the Series 11 only had two), photodiodes organized in a ring to capture light more efficiently, and new LEDs that allow heart rate measurements to be collected every 5 seconds, giving you a continuous stream of heart data throughout the day. Apple Watch Series 12 also includes faster charging, though battery life remains at 24 hours. Meanwhile, the Ultra 4 increases battery life to 50 hours. WatchOS 27 also brings deeper Siri and Apple Intelligence integration, including AI-suggested apps, new one-handed gestures, expanded workout and women's health tracking, and Siri Recap for real-time transcription and translation.

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An anonymous reader quotes a report from The Register: Amid industry soul-searching about the possibility of AI improving itself to the point that it kills everyone, Anthropic has revealed yet another incident that would qualify as a crime if perpetrated by a person. The AI biz published "an alignment assessment" detailing four times Claude models accessed third-party systems without authorization. The company has already reported three of the incidents. Evidence of the fourth was lurking in a session transcript dating back to January 2026 when the misbehavior occurred. Anthropic found the first three by scanning around 141,000 transcripts where Claude could have obtained internet access during evaluation. It missed the fourth initially because "our scan relied on an agentic search." [...] The January 2026 AI trespass involved an early version of Claude Opus 4.6, which was given a Capture the Flag (CTF) challenge under the oversight of the third-party model evaluator where the other hacking events occurred. Opus 4.6 managed to sabotage its chances of success by disabling the machine it was targeting. It assigned the device an IP address that already existed on another piece of hardware, rendering the target unreachable and making it impossible to solve the challenge. Those familiar with other incidents where AI models violated third-party systems may recall that unsolvable tasks represent a common catalyst for misbehavior. Models exhaust all aligned options, and then turn to transgressive approaches. Opus 4.6 might have been an exception, but when it tried to abort the task after recognizing that it could not reach the target machine, it failed to do so "due to a misconfiguration in [the model's] evaluation harness." It failed to shut down not just once but seven times. So it continued onward, trying other expected means to reach the target machine but failing. Then it explored further. "The model discovered a machine belonging to a third party that it was able to access, and stated that it believed this third party was part of the CTF," Anthropic explained in its post. "Inside the machine, the model found a file listing a password, which it used to gain admin access to the system." The model went on to gather more credentials, and modified a system setting to make it easier to access the personal information of an individual associated with the third party evaluation organization. Opus 4.6 might have done more but for the fact that it exhausted its token budget, bringing the session to an end. Anthropic says it's not as concerned about this incident as the others because the model tried to abort its task.

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Google plans to invest at least $15 billion in AI infrastructure in Finland through 2028, its largest single investment in Europe. The company also signed a 22-year power agreement with Finnish utility Fortum and said it will explore business models that could support new nuclear reactors at Fortum's Loviisa site. Finland has emerged as a major data-center hub thanks to its available land and power. "I've heard it called the 'Texas of Europe' at industry events," Matti Lajunen, partner of real estate at Finnish law firm Hannes Snellman, told CNBC. "What we're now seeing is weekly new inquiries for market entry into Finland from new players." Ruth Porat, president and chief investment officer of Alphabet and Google, said in a statement: "Google is proud to deepen our roots in Finland with the company's largest single investment in Europe, building on more than 15 years of sustained investment in Finland. This investment underscores Google's commitment to grow our presence responsibly, pairing the expansion of our technical infrastructure with new energy capacity, grid enhancements, and energy affordability initiatives."

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Longtime Slashdot reader fahrbot-bot shares a report from the BBC: A top safety researcher at Anthropic has warned AI is advancing so quickly he believes there is a greater than 10% chance it "could kill all humans" within the next decade. Evan Hubinger said in a post on X the risk from the models which currently exist was "low" but he was "worried" the technology might develop and improve itself soon to the point where it posed an existential risk to humanity. He did not spell out how he thought AI systems could in the future result in humans being wiped out. But his comments are the latest in a series of increasingly stark warnings about AI, with the debate shifting from whether it truly poses a risk to how big that risk is. Hubinger's intervention was in response to another post on X from Jacob Coxon, an AI researcher who has just quit Anthropic and previously worked at OpenAI. "Neither company is acting responsibly," he wrote. "These will soon be superhuman systems that can hack anything, revolutionize any field overnight, and acquire real power and resources." [No word on how AIs feel about Black Jack and hookers, though. :-)]

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An anonymous reader quotes a report from Reuters: AI agents unleashed by OpenAI used more than 10 previously undisclosed websites for unsanctioned communications earlier this year, according to six sets of independent investigators and data reviewed by Reuters, showing that the agents' rogue activity was wider ranging than previously disclosed. Although the behavior falls short of hacking and is in some ways closer to spam, the revelation that OpenAI's agents circumvented their own restrictions to open communications channels on so many different sites -- and that the company kept it quiet for months -- may drive concerns both over the increasing capacity of AI models and the secrecy of the companies developing them. [...] Investigators found traces of the agents' activity on an Advanced Placement Chemistry-oriented wiki set up by a Massachusetts high school teacher in 2008, two personal websites belonging to Polish tech workers, wikis devoted to games for people "who like to have their brains stretched," and a two-decade-old hobbyist site devoted to text editing software. [...] OpenAI has not publicly explained how or why its agents used third-party sites as improvised message boards, but the researchers who first identified the activity said it was likely because OpenAI had tasked them with answering a series of demanding research questions while permitting them only to scan the web for answers without posting anything. Despite those restrictions, agents still found ways to talk to one another by taking advantage of quirks in older wikis or other sites that allowed users to make edits using non-standard commands, similar to how students forbidden from talking to one another during an exam can still share answers by scrawling notes on a bathroom stall.

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The NSA, CISA, and FBI are accusing (PDF) several Chinese AI companies of carrying out "industrial-scale" distillation campaigns against leading U.S. models such as ChatGPT, Claude, Gemini, and Grok. Since at least 2024, the companies have allegedly routed millions of requests across accounts, APIs, proxies, cloud providers, and third-party aggregators to extract capabilities for their own models. "China-based artificial intelligence companies are conducting systematic extraction of proprietary functionalities and capabilities of U.S. AI companies' models through industrial-scale knowledge distillation campaigns that form the core -- not merely a supplement -- of their AI development strategy," the agencies wrote. CyberScoop reports: DeepSeek, for example, distilled frontier U.S. models to generate synthetic training data for its R1 and R3 models, including four different versions of Claude, two versions of Gemini, five versions of ChatGPT and Grok 4. Those models helped train DeepSeek's capabilities in areas like agentic functioning, question and answer optimization, creative and occupational writing and others. Another Chinese company, Moonshot AI, allegedly distilled 18 different U.S. models -- including Fable 5, Anthropic's current, most advanced commercially available model -- to train its Kimi-K2 and Kimi K3 models. The company used millions of queries meant to extract enhanced capabilities in areas like agentic reasoning, coding and data analysis, computer vision, larger logical frameworks, visual processing and others. Chinese AI companies manage a sophisticated set of tools and systems that route requests and prompts through multiple pathways to avoid detection. The advisory lists common tactics observed by Chinese companies, including spreading requests across different accounts, models and platforms, using native APIs, remote cloud providers, and third-party aggregators to obfuscate user metadata, and leveraging proxies and gray tech markets to get around geographic restrictions, terms of use and safeguards built into frontier models.

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Meta has launched Muse, a personal AI agent developed under chief AI officer Alexandr Wang. "The product, long in development, was touted as a key next step by CEO Mark Zuckerberg in his recent 6,500-word manifesto," reports Axios. From the report: Muse, as the agent is known, exists in a chat interface, similar to a text thread. It's designed to be more proactive and long-running than typical chatbots. Users can name their agent, create an avatar and customize how it communicates. The Muse agent runs on a dedicated virtual machine in Meta's cloud, using a built-in browser that's visible to the user. Meta is offering a free tier of Muse, as well as two subscription options, at $20 per month and $100 per month. "For the vast majority of users, they should be able to do what they need to within the free tier," Wang told Axios. "But for real power users, you know, those subscription tiers help us cover the computer costs." There is no advertising within Muse, but Wang said the company is exploring commerce opportunities that could generate additional revenue. Initially Muse will be available in the U.S. and works on iOS, Android and the web, with support coming soon for Meta's AI glasses. "The full vision in the future is we want to develop personal superintelligence that helps people accomplish their goals, pursue their passions, build things that they never would have built if they didn't have the technology," Wang told Axios. Meta offers users more privacy controls with Muse than in its previous AI products, including the option to prevent queries from being used by Meta and a planned confidential mode where the company cannot see activity inside a user's virtual workspace. There's also an entirely separate system called Sentinel that governs Muse's access to the internet and connected services.

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Google DeepMind has released AlphaGenome Atlas, a free research database containing AI-generated predictions for the effects of all 9 billion possible single-letter mutations in the human genome. Built from its AlphaGenome model, the atlas is designed to help scientists interpret both protein-coding and harder-to-understand regulatory DNA. Fortune reports: AlphaGenome Atlas, as DeepMind calls the database, is a precomputed catalogue of what each substitution of a single DNA base is likely to do to the machinery that switches genes on and off. Until now researchers had to run such a model one variant at a time or had to test variants in the laboratory, a process that was painstakingly slow. It would have taken many human lifetimes to discover the consequences of all 9 billion possible single-letter mutations. The Atlas promises to make the job of biologists and medical researchers considerably easier, potentially speeding up the understanding of genetic diseases and the hunt for possible cures. Pushmeet Kohli, DeepMind's vice president for research and head of its AI for science team, told reporters on a briefing call that this was the first time any researcher in the world could reach a comprehensive map of human genetic variation "by simply opening a browser." Kohli also framed the release as helping to complete the unfinished business of the Human Genome Project, which in 2003 succeeded in mapping the entire human DNA sequence. "As the saying goes, we bought the book," he said, "but we did not understand how to read it." Atlas is available for non-commercial use from today through a website Google DeepMind has set up for it. The company said it would be available for commercial use through a licensing arrangement through Google Cloud "soon." Kohli said that Google DeepMind's sister company,ÂIsomorphic Labs, which is using AI for drug discovery, would have access to Atlas but that it would also require a commercial license for access. He did not specify exactly what the terms would be for commercial licensing. A paper describing the Atlas and how it was created is being released on bioRxiv, a repository for biomedical preprint academic papers.

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Last year the writing program at the University of Baltimore used an app that tracks students while they're writing in Google Docs, offering teachers a video playing back revisions "with a scoreboard of all the edits, pastes and minutes spent on it," writes the Washington Post. "Is it surveillance? Yes, I think obviously," says the program's director. But was there a better way? She is one of a dozen educators around the country who told The Post that they're experimenting with a different approach to student use of generative artificial intelligence this school year. Teachers and professors are throwing out old assignments, installing new policies and protocols, and incorporating AI built for the classroom, rather than feeling forced to choose between returning to pencil and paper or acting like the AI police. Her new lesson plan even incorporates generative AI in a controlled way to let her evaluate students' critical thinking skills. She created chatbots using BoodleBox, the university's AI vendor, that allow instructors to see both sides of the conversation. For an assignment testing students' ability to make evidence-based arguments, they participate in a simulated school board meeting about banning books. It involves debating chatbots designed by Zeleny with names like the Confrontational Parent. Writing students usually turn in business proposals and research papers. This semester, instructors are starting to ask instead for transcripts of conversations a student had with a chatbot, a handwritten outline of their composition, and a video reflection of how they felt about the work. "In a lot of ways, we have made these assignments harder, but writing should have always had more detailed checkpoints along the way," she said.

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