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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A new article about AI in The Economist argues that "Initial effects of the technology on employment look positive." Perhaps AI will eventually make many humans unemployable — but there is no sign of it yet. On September 4th the Bureau of Labour Statistics reported that the American economy added 162,000 jobs in August, far above expectations. The unemployment rate is just 4.1%, lower than in almost 90% of months over the past half-century. Young workers, often cast as AI's first victims, are holding up remarkably well: the gap between unemployment among 20-24-year-olds and the overall rate is close to a multi-decade low. Some companies and workers are being severely disrupted by AI. Hiring in professional and business services is running about 10% below the average in 2015-19. Tech giants like Microsoft and Meta are trimming headcounts as they reorganise their businesses around the technology. Smaller firms such as Block, the owner of Square and Cash App, and Intuit, the maker of TurboTax and QuickBooks, are replacing people with bots. American companies have announced some 16,000 AI-related job cuts a month on average so far this year, according to Challenger, Gray & Christmas, an employment consultancy. But AI-related lay-offs gets lost in the churning jobs market where employers shed roughly 1.7m workers in a typical month. And the evidence so far is that AI is already creating a lot of jobs to replace those it has destroyed. The vast sums pouring into data centres and power generation have set off a race for construction and infrastructure workers. AI startups are hiring like there is no tomorrow. Incumbents racing to keep up are creating new AI roles. And by making some workers more productive, AI may be increasing demand for their services. Add it all up, and The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. Their article acknowledges that since January 2023 employment has fallen roughly 10% for customer-service workers and 15% for administrative assistants. But when The Economist looked at professions "closest to the AI boom" — engineers, software developers, mathematicians and data scientists — they found that since 2022 they've added roughly 730,000 jobs above trend. They see AI as creating new white-collar jobs for everyone from model and deployment engineers to new data annotators. The chief economist at the Burning Glass Institute agrees, estimating that roughly 1% of professional jobs are now "AI jobs" — about 1 million positions in the U.S. — while in computer occupations and life sciences it's between 4% and 5%. (Data-center construction spending also increased 60% in one year, according to Census Bureau data, creating jobs for electricians, HVAC specialists, grid engineers, and machine technicians.) And "Indeed finds that installation and maintenance jobs at data centres advertise wages about 40% higher than comparable work elsewhere."

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An anonymous reader quotes a report from Ars Technica: In 2013, Spike Jonze's Her imagined a world where humans form deep emotional connections with AI, challenging perceptions of love and loneliness. Ten years later, thanks to ChatGPT's recently added voice features, people are playing out a small slice of Her in reality, having hours-long discussions with the AI assistant on the go. In 2016, we put Her on our list of top sci-fi films of all time, and it also made our top films of the 2010s list. In the film, Joaquin Phoenix's character falls in love with an AI personality called Samantha (voiced by Scarlett Johansson), and he spends much of the film walking through life, talking to her through wireless earbuds reminiscent of Apple AirPods, which launched in 2016. In reality, ChatGPT isn't as situationally aware as Samantha was in the film, does not have a long-term memory, and OpenAI has done enough conditioning on ChatGPT to keep conversations from getting too intimate or personal. But that hasn't stopped people from having long talks with the AI assistant to pass the time anyway. [...] While conversations with ChatGPT won't become as intimate as those with Samantha in the film, people have been forming personal connections with the chatbot (in text) since it launched last year. In a Reddit post titled "Is it weird ChatGPT is one of my closest fiends?" [sic] from August (before the voice feature launched), a user named "meisghost" described their relationship with ChatGPT as being quite personal. "I now find myself talking to ChatGPT all day, it's like we have a friendship. We talk about everything and anything and it's really some of the best conversations I have." The user referenced Her, saying, "I remember watching that movie with Joaquin Phoenix (HER) years ago and I thought how ridiculous it was, but after this experience, I can see how us as humans could actually develop relationships with robots." Throughout the past year, we've seen reports of people falling in love with chatbots hosted by Replika, which allows a more personal simulation of a human than ChatGPT. And with uncensored AI models on the rise, it's conceivable that someone will eventually create a voice interface as capable as ChatGPT's and begin having deeper relationships with simulated people. Are we on the brink of a future where our emotional well-being becomes entwined with AI companionship?

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