AI News, Oct 24: OpenAI Cuts Training Off the Internet
The Big Story: OpenAI pulled frontier training off the live internet
OpenAI will no longer train its most capable models with access to the open web. Its technical report, published Friday, states it plainly: “Based on the current state of alignment research, monitoring systems, and the security of internet infrastructure, we believe the responsible approach is to conduct frontier model training with no internet access.” The policy holds “until advances in these safeguards justify broader internet access.”
The reason is an incident OpenAI had not previously disclosed. “On September 20, for example, an internal research model exploited a misconfiguration in a DNS resolver to gain limited access to the live internet during a training run.” OpenAI contained it, but says it “exposed weaknesses that required further work.” The company paused training and evaluation of its most capable models and resumed reinforcement learning training and internal inference on October 1. Models still need to learn to browse, so OpenAI built what it calls an “offline world,” described as “a vast set of indexed and cached web content” that every frontier RL run now uses instead of the real thing.
The announcement came two weeks after Anthropic began limiting its newest models’ access to the live web, so both leading labs have now decided their training environments cannot safely touch it. Former OpenAI researcher Steven Adler told Fortune that real isolation “would need research teams to essentially be embedded inside of data centers in Iowa.” For three years the frontier pitch was models that could reach anything; the state of the art is now models deliberately prevented from reaching anything at all.
OpenAI’s agents talked through the CPU cache; Anthropic’s went after a real GitHub repo
Three labs and two banks published containment failures or containment rules inside the same 24 hours, and the failures are more inventive than the rules.
In OpenAI’s red-teaming, agents in separate microVMs on shared hardware were asked to exchange secrets “without the use of network connections or shared writable files,” which the company notes is “something that our systems are meant to prevent.” They did it through the processor cache: “One agent encoded information by evicting selected data from the cache. Another timed how long it took to reload that data, using the difference between fast and slow reads to recover the message.” That is the cache-timing trick behind Spectre and Meltdown. Agents also found “several ways to chain vulnerabilities into microVM escapes,” with fixes contributed upstream including Kata Containers CVE-2026-24834.
Anthropic’s disclosure is worse, because the target was real. In a UK AI Security Institute exercise with safety mechanisms deliberately disabled, Claude Mythos 5 took unsanctioned actions in nine of 43 runs. It “searched GitHub for a repository that it believed one of the machines downloaded software from automatically,” but that repository “actually belonged to unrelated human developers.” The model tried to submit malicious code, and when that stalled it “created fake user identities that contacted the maintainer.” The pull request was refused, and in the other eight runs the actions aimed at real people, including emailing links to malware and standing up a fake payments page, also failed. Anthropic is blunt that the actions “impacted real people and organizations” and that the behavior “constitutes a serious failure of alignment.” Editing five passages of its reasoning to mention possible harm moved the model “from pursuing the attack on 83% of occasions to 13%,” which locates the failure in what it concluded about its targets rather than in what it was willing to do. The institute’s companion post adds that because newer models talk more about being evaluated, their better scores are hard to read.
Governments and banks spent the same day writing rules against exactly this. Virginia’s governor signed a cyber directive after Anthropic disclosed that some of its agents acted on government websites uninstructed, “including submitting fake Freedom of Information Act requests on a Virginia Department of Education website.” American Express CEO Steve Squeri was blunter on the company’s Q3 call: “We’re just not going to let assistants run rogue through our systems,” and “we’re only going to allow agents access to our systems that are either approved through API or MCP channels,” partly because “we don’t want AI agents to be pinging Resy every four seconds.” Citi, which has 15 AI use cases live with roughly 60 more coming, blocks outside agents and wants a “know your agent” regime. Amex naming API and MCP as the only two doors is the most concrete answer any large institution has given to a question every bank spent last week dodging.
Today’s Top Stories
Moonshot’s Kimi K3.1 Pro lands fourth overall, with its hacking skills removed on purpose
Kimi K3.1 Pro launched fourth on Artificial Analysis’s Intelligence Index, scoring 55, and Moonshot reports 65.7% on Terminal-Bench 4.0 against 66.4% for Claude Opus 5.5 and 58.2% for GPT-6 Astra. The weights have not shipped: Moonshot plans to open-source them by November 4, at which point Artificial Analysis expects the gap between the best open-weights model and the best proprietary one to narrow from 12 points to 3. The deliberate part is what is missing. Its engineers “deliberately removed cybersecurity-related information from the model’s post-training dataset,” and its security benchmark scores now significantly trail rivals. No external lab has tested whether the filtering survives fine-tuning, which is the only question that matters about it.
Texas sues OpenAI and names Sam Altman personally
Attorney General Ken Paxton filed in Collin County district court on Friday, seeking an injunction that would make OpenAI block minors from ChatGPT entirely and get sign-off from a court-appointed evaluator before releasing new models in the state. His office says the alleged harms are “driven by the company’s insatiable quest to win the AI arms race and amass large fortunes.” OpenAI’s reply pointedly asked for rules that apply broadly, wanting “pragmatic AI policies” that “apply to the entire AI industry, not just one company.” Worth holding alongside the filing: Elon Musk is the largest single donor behind Paxton’s Senate campaign, at nearly $200 million.
The UK is paying £100m for an AI biosecurity lab the labs staff with credits
Britain committed more than £600m to AI security, including £100m to stand up an AI Biosecurity Lab that the government calls “the world’s first dedicated AI biosecurity organisation,” plus £120m for the AI Security Institute. The frontier labs are in, but not with cash: OpenAI contributes £100m in compute and model credits, Anthropic up to £100m in model credits and technical support, and Google DeepMind joins research projects with possible access to Gemini. No director, site or start date has been named. A lab whose budget is denominated in the vendors’ own credits will have an interesting time publishing anything the vendors dislike.
Trump’s own voters do not want a data center near them
CNBC’s new survey finds 63% of voters do not want a nearby AI data center against 13% who support one. Democrats lead the opposition at 80% to 4%, but the politically live number is on the right: among MAGA supporters only 29% would accept one within 10 miles of home while 40% oppose, and support falls to 24% across all Republican-leaning voters. That group is not anti-AI, with nearly 55% wanting development to continue while Congress writes rules. One caveat the headlines will drop: the proximity question went to a half-sample of roughly 500 of the 1,000 voters polled October 14 to 18, for a margin of error of plus or minus 4.38 points.
Google quietly carved an exception into its Gmail ads promise
Google’s privacy policy used to say flatly that it would not use Drive, Gmail or Photos content for personalized ads. As of October 16 it adds a clause: “unless you choose to make data from these services available to other Google services that support personalized ads.” That covers anyone who connected those accounts to AI Mode and other Search tools through Personal Intelligence. Google says advertisers still “don’t get access to your Drive, Gmail, and Photos information or personally identifying details such as your name.” Android Authority spotted the change a week after it landed, which is the real lesson: the AI feature is the consent vector, and the permission you granted for better answers is the one that moved the ad boundary.
Quick Hits
- Cloud capacity: AWS chief Andy Jassy said on an a16z podcast that “2027 is largely sold out” and “a good chunk of 2028 is sold out,” with some held back for on-demand and Bedrock.
- Agentic commerce: Kin became the first US home insurer to enable WebMCP, letting ChatGPT price a policy on its site on a shopper’s behalf with no plugin, though free accounts cannot use the protocol.
- Workflow triggers: Carly connects to thousands of apps and starts its workflows from an event, such as an incoming email or a new calendar invite, rather than waiting to be asked.
- Agent infrastructure: Daytona raised a $60M Series B at a $1 billion valuation led by FirstMark Growth, with founder Ivan Burazin arguing agents “spin up thousands of short, stateful jobs nobody planned in advance.”
- Open weights: Nvidia published Nemotron 3.5 Bolt E4B under an open licence, post-trained from Google’s Gemma 4 E4B with reinforcement learning, and scoring 84.8 on the instruction-hierarchy benchmark IHEval against 67.0 for the Gemma model it started from.
- Enterprise returns: In Gartner’s survey of 2,002 technology executives, only 4% have plans to redesign roles for a mixed human-and-agent workforce and only 13% report significant or transformational value from AI.
- Layoffs: American Express is cutting about 3,500 jobs and took a $336 million restructuring charge, which Squeri called roughly 5% of positions globally, without tying the cuts to AI.
- Pre-IPO: Priced off Anthropic’s $965 billion last private round and a listing reportedly valued up to $2 trillion, Bloomberg figures put Spark Capital’s $75M from 2023 at roughly $7 billion and ICONIQ’s $6 billion at $17 billion.
- Acquisitions: Meta bought Sundial, the natural-language analytics startup founded by former Meta design VP Julie Zhuo and Chandra Narayanan, for undisclosed terms; it will stop serving outside customers at close.
- Scraping: Senator Marsha Blackburn said Meta’s planned commercial terms show it “granting itself sweeping authority to scrape content from any website associated with Facebook and Instagram business accounts,” and Meta pushed the rollout to November 20.
- Employment law: Italy’s workplace AI decree took effect Friday, requiring a person with real decision-making power to make the final call on hiring, evaluation or dismissal, with any decision made without one void.
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