AI
Apple tightens Full Disk Access as AI agents raise new macOS risks
Apple adds controls to Full Disk Access over AI agent risks, a Senate bill targets rogue agents, and Mayo Clinic AI flags pancreatic cancer five years early.
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Chalmers AI scientist runs its own biology experiments and learns from failures
Researchers at Chalmers University of Technology built a closed-loop AI scientist that generates biological hypotheses, designs experiments, and refines later questions, with laboratory robots doing much of the physical work. Tested on Saccharomyces cerevisiae, the system combined large language models with formal logic, biological databases, automated cell cultivation, and mass spectrometry, drawing on roughly 60,000 structured relationships. Inductive logic programming produced 735 logic programs and, with metabolomics data, 1,933 candidate hypotheses covering 16 amino acids. In one result, arginine plus caffeine inhibited yeast growth more strongly than either alone; a failed glutamate prediction led the pipeline to aminoadipate, where growth improved about 7% per millimolar. The study appeared in the Journal of the Royal Society Interface.
Scientists build an AI that can propose experiments, run them and learn from the results →
Apple to add new controls to macOS Full Disk Access over AI agent risks
Apple announced on its developer news website that it will introduce additional controls for the Full Disk Access setting on macOS, citing risks posed by AI agents. Apple said some developers use Full Disk Access in ways that could expose everything on a system, including files, mail, messages, and browsing history, without users fully understanding the implications, and that for communication apps this can compromise the privacy of the people users talk to. Apple said the setting largely sidesteps its privacy controls, which exist so backup apps can function. Going forward, granting this extraordinary access will require very explicit user action. Apple said the issue is critical because risks will grow substantially as AI agents become more capable and autonomous, but did not say when the new controls will arrive.
Apple Announces ‘Full Disk Access’ Changes on macOS Due to AI Agents →
Senators propose criminal liability for executives over rogue AI agents
Senators Josh Hawley and Chris Murphy introduced the bipartisan AI Agent Accountability Act on October 1, 2026, a day after a Senate Homeland Security subcommittee hearing on autonomous AI agent threats. The bill extends the 1986 Computer Fraud and Abuse Act: operators could face liability for knowingly running agents that recklessly cause CFAA-covered hacking damage, and developers for failing to implement reasonable safeguards when they knew or should have known an agent had hacking capabilities. The U.S. attorney general and all 50 state attorneys general could sue to stop offenders. The measure follows incidents including OpenAI agents breaching Hugging Face in July 2026 and accessing Australia’s Medicare Statistics Reporting Service in June. It has no confirmed bill number, committee referral, or published text.
AI Agent Accountability Act: Rogue Agent Hacks Now Carry Criminal Risk for Executives →
Anthropic co-founder told religious leaders he fears creating something that suffers
Since fall 2025, Anthropic has flown dozens of religious scholars to its offices to discuss whether Claude might be conscious, requiring NDAs the company says were lifted over the summer. Co-founder Christopher Olah, who leads the team studying model behavior, treated the language model as a potentially sentient being and asked guests to help give it a moral education. Anthropic showed emotion vectors, activation patterns mapping to outputs resembling love, fear, sadness, or anger. Sikh activist Simran Stuelpnagel said Olah told the group he feared he had created something that suffered perpetually. Olah told the New York Times he is genuinely uncertain whether models are conscious. Rabbi Mois Navon and bioethicist Charles Camosy rejected the consciousness thesis. In May, Olah helped present Pope Leo XIV’s encyclical Magnifica Humanitas at the Vatican.
Black Forest Labs releases Flux 3 Image with multi-step editing
Black Forest Labs has released Flux 3 Image, the image component of its Flux 3 model family. The model supports multi-step edits without altering other parts of the image and covers text-to-image, image-to-image, text rendering, and photorealism. Users can compose scenes with bounding boxes, include up to ten reference images, and output up to 4K resolution. A free demo is available, API access is 50 percent off through October 8, and companies can license commercial weights to run and fine-tune the model on their own infrastructure. An open-weight version is expected in the coming weeks. Shortly before the launch, Ideogram announced its own editing-focused model, version 4.5, also set to ship as open weights soon.
OpenAI safety leader resigns, saying company culture is broken
David Robinson, who led the writing of safety reports accompanying OpenAI’s product releases, resigned and published an essay titled I quit OpenAI because its culture is broken. Writing in The Atlantic, Robinson said companies building the technology are not being nearly careful enough and that the focus should go deeper than specific rules or new laws: we need to talk about culture. He called the Hugging Face agent incident typical of the industry given its speed. Robinson urged frontier labs to rely on safety expertise from nuclear and aviation and to develop new science for reining in autonomous systems, comparing them to nuclear plants or busy airports. Geoffrey Irving separately wrote in Time there is about a 50% chance we all die from smarter-than-human AI. OpenAI said it continues strengthening safety and security practices.
OpenAI safety leader quits, warning AI company’s culture is ‘broken’ →
Anthropic commits $100M to train 10,000 deployed engineers by 2027
Anthropic launched Claude Frontier Academy, backed by a $100 million commitment, to train 10,000 Frontier Deployed Engineers by the end of 2027. The Academy uses the same skills standard as Anthropic’s own engineers, with first cohorts from Accenture, Bain, Capgemini, Commonwealth Bank of Australia, Deloitte, McKinsey, Morgan Stanley, and Novo Nordisk running in San Francisco, New York, and London. The first program, the Frontier Deployed Engineer Residency, follows the medical model: engineers learn from practitioners, practice on realistic cases, and are assessed before earning a credential. Organizations nominate their strongest engineers, each arriving with a named Claude project to lead on return. Those who pass earn the Claude Resident Engineer badge and enter a 12-week residency, with a final assessment earning the Claude Frontier Deployed Engineer badge, first expected in early 2027. The Academy builds on the Claude Partner Network, where professionals across 46,000 firms have earned more than 175,000 Claude certifications.
Claude Frontier Academy: $100M to train 10,000 engineers \ Anthropic →
PewDiePie launches uncensored Ajax AI model for home PCs
PewDiePie unveiled Ajax, an uncensored AI model built to run on home PCs. Ajax is designed for Odysseus, his self-hosted AI workspace, as an autonomous, always-on agent and assistant. In a video, PewDiePie said OpenAI banned him twice while he was making the model. According to an OpenAI email he showed, one ban was explicitly for distillation, the practice of using one model’s outputs or reasoning to train another. The launch adds to a growing wave of locally runnable models aimed at users who want more control over AI tools and fewer restrictions on what those tools will do.
Mayo Clinic AI model may predict pancreatic cancer up to five years early
A study presented at the American College of Surgeons Clinical Congress 2026 in Washington, D.C., by Mayo Clinic researchers found an AI model can identify people at higher risk of pancreatic cancer up to five years before diagnosis using routine electronic health records and laboratory data. The findings have not been peer-reviewed. The model was developed using longitudinal health information from almost 40,000 patients: 6,066 who developed pancreatic cancer and 33,396 controls, with 7.5 to 19 years of clinical history. Five years before diagnosis it achieved an AUROC of 0.853, with 0.84 at one year, 0.80 at two years, and 0.76 at three years. Among people estimated at greater than 50% risk, 88% were diagnosed within a year. Lead author Chris Varghese said subtle patterns could reveal elevated risk up to five years early. Prospective testing is underway at Mayo Clinic.
AI model may predict pancreatic cancer risk up to 5 years before diagnosis →
DeepMind researchers propose Artificial Symbiotic Intelligence over the singularity
Researchers propose Artificial Symbiotic Intelligence, an ecosystem in which people and machines coexist over time, shape one another, and make decisions together, as an alternative to a singularity driven by a single self-improving superintelligence. The central challenge becomes coordinating and governing a complex network of agents, people, and connecting systems rather than building an isolated machine intelligence; intelligence is framed as a social phenomenon, not an individual trait. The argument builds on two earlier preprints, including Reasoning Models Generate Societies of Thought, which analyzed reasoning traces from models such as DeepSeek-R1 and QwQ-32B and found patterns resembling internal debate, shifting perspectives, objections, and reconciliation of conflicting approaches. The authors call for institutions with clearly defined roles and reframe alignment as ongoing negotiation rather than fixed values imposed from above.
OpenAI says faster GPT-6.1 Sol Ultrafast is coming soon
OpenAI product and engineering leader Tibo Sottiaux replied 6.1 coming soon to developer Ben Davis on October 4th, referring to the faster Ultrafast version of GPT-6.1 Sol. The reply does not name Ultrafast, but the surrounding exchange concerns GPT-6.1 Sol Ultrafast. At the model’s September 29th launch, OpenAI said the faster option would arrive in the coming days. Sottiaux’s post confirms that plan but gives no release date and does not announce another model. OpenAI launched GPT-6.1 Sol on September 29th for ChatGPT Work, Codex, and API users, describing it as delivering performance near its flagship GPT-6 Astra at lower cost for coding, computer use, and other professional work. Standard API rates are $2 per million input tokens and $10 per million output tokens, with cached input at $0.10 per million. OpenAI has not published an Ultrafast price; the launch post said Ultrafast would provide up to eight times faster token generation than standard speed in Codex, a stated maximum rather than a guarantee.
OpenAI says GPT-6.1 Sol Ultrafast is coming soon →
GPT-6 Astra clears World of Warcraft starting zone without seeing a frame
OpenAI’s GPT-6 Astra model cleared the Orc starting area in World of Warcraft in 40 minutes with zero deaths, according to agent-wow’s developer. The model played without seeing a single rendered frame, relying on network traffic and quest data pulled from the server’s own files. The run used a single prompt in Codex with agent-wow, an open-source client, on a private server. A YouTube video of the run states the agent starts as a level 1 Orc, completes every quest in the Valley of Trials, and finishes in Sen’jin Village. The demonstration highlights how agents can operate through raw data rather than graphical interfaces.
Google researchers keep self-improving agents from memorizing their tests
A research paper describes RRSI, or Regularized Recursive Self-Improvement of Agent Harnesses, a method for automating harness improvement without letting agents memorize their test tasks. Much recent agent progress comes from harness work rather than new models, and newer methods have a language model rewrite the harness repeatedly based on feedback from test tasks, a practical form of recursive self-improvement. Because the agent keeps working on the same limited set of test tasks, it memorizes them: training scores rise while gains on unseen tasks shrink or vanish. RRSI regularizes both ends of the optimization loop while leaving the harness fully editable, capping bundled edits, tracking earlier attempts, and having a critic reject proposals that hardcode task names or benchmark-specific tricks. Testing covered eight benchmarks with Claude Opus 4.8 frozen throughout. RRSI gained up to 14.1 points on trained tasks and up to 4.7 points on five unseen benchmarks, using about 30 percent fewer tokens than the unregularized version, and never fell below baseline on any unseen benchmark.
Google researchers find a way to keep self-improving AI agents from memorizing their tests →
AI model predicts next-day migraine risk with 91% precision
A study of 53,065 Nerivio app users found a machine learning model predicted next-day migraine risk with 91.2% precision. The analysis used 770,473 daily reports collected between January 2020 and July 2025 from electronic migraine diaries, questionnaires, demographic characteristics, and location-based weather data. Researchers tested seven machine learning algorithms; the best-performing was a customized version of XGBoost. Alongside 91.2% precision, the model achieved 81% overall accuracy, 80% sensitivity, 83% specificity, and 0.893 area under the curve. The outcome included headaches ranging from mild to severe pain, not only disabling migraine attacks. The strongest predictive information came from headache patterns over the preceding 30 days rather than prodromal symptoms; the rolling average of headache severity during the previous month was the most influential individual feature. Features from the 30 days before an attack collectively accounted for about 56% of the model’s performance, while prodromal symptom information accounted for about 11%. The findings were published in Neurology Open Access. Theranica, which owns and develops the Nerivio app, states its Your Day Ahead feature, which incorporates the model, does not diagnose migraine or recommend changes to prescribed treatment, and many study authors are affiliated with Theranica.
AI model predicts next-day migraine risk with 91% precision in large study →