AI has picked a hard but honourable side quest
The boss of Arm believes AI could help find a cure for cancer within our lifetime.
Rene Haas, CEO of the Cambridge-based chip company, told the BBC that some biological problems are still too complex for humans and today’s computers to solve.
He said AI could eventually model how cancer affects cells and DNA, helping researchers find treatments faster.
Professor Chris Bakal from the Institute of Cancer Research said the key will be giving AI the right medical data, not simply building bigger models.
His team trains AI on data from patient samples, which could help cut years from drug development.
Haas also expects humanoid robots to become much more common over the next five to ten years, especially in manufacturing, cleaning, security and construction.
He played down fears of mass job losses, saying some roles will change but predictions of machines replacing huge numbers of workers are “overstated”.
The big three:
- AI could help speed up cancer research and drug development.
- Humanoid robots could become far more common within a decade.
- Chip shortages are still slowing AI growth.
No pressure, machine
Arm is already benefiting from the AI boom.
Haas said its technology is used in around half of AI data centres, while a new chip developed for Meta has attracted more than $2bn in demand since March.
The main problem is that there are not enough chips.
Haas said shortages are slowing the growth of AI data centres.
He also argued that the UK does not need to build its own major chip factories, which are expensive and require highly specialised workers.
Publishers want a cut, and rightfully so
Some authors expecting money from Anthropic’s $1.5 billion copyright settlement say publishers and agents are claiming part of their payments.
The settlement covers nearly 500,000 books, with authors due $3,000 for each pirated work.
For traditionally published books, the payment is usually split 50-50 between the author and publisher.
If the author owns the rights, they may get the full amount.
But some writers say publishers are claiming money for books they no longer hold the rights to, or taking 100% when they should only get half.
In brief:
- Authors can get $3,000 per book.
- Some publishers and agents are being accused of claiming too much.
- The problem may be linked to poor records and settlement errors.
Cue the contract archaeology
Author groups say the issue may come down to old records and a confusing claims process rather than deliberate wrongdoing.
Some publishers have already said claims were made by mistake.
Literary agencies have also reportedly made claims, despite agents not usually owning the rights to the books they represent.
Authors can dispute the split, but to claim the full payment, the book rights must have returned to them before 10 August 2022.
OpenAI says its agents resolved Navier-Stokes. Then the fight started.
OpenAI published the claim on Tuesday: an internal model it describes as “significantly more capable than GPT-6 Astra” ran on the order of 10,000 concurrent agents and produced an analytical proof, plus a Lean formalization, that an initially smooth fluid at rest can develop a singularity in finite time. In the Clay Institute’s framing that establishes statements C and D, which is the disproof branch. The agents launched September 1 and had it 88 hours later on September 5. Lean formalization and verification took another 17 hours, done by GPT-6 Astra. Navier-Stokes alone consumed 2.7 million agent messages and about 130 billion output tokens, out of 4.9 million messages and 300 billion tokens across everything the run attempted.
OpenAI is not cashing the check: “We do not intend to claim the Millennium Prize for this result.” It did publish the paper and the Lean certificates, which matters, because a Lean-checked proof is the one kind of AI math claim you do not have to take on faith. Humans still have to confirm the Lean statement says what mathematicians think it says.
Independent read: Quanta got Charles Fefferman, who wrote the official problem statement, on the record. “I was thrilled that the problem was solved.” He also pointed the credit elsewhere, calling Diego Córdoba and Luis Martínez-Zoroa “the heroes of the story,” since their techniques are what both efforts are built on.
Now the ugly part. Buckmaster and Alpöge, a mathematician employed by Anthropic but working independently, posted finite-time blowup proofs for the incompressible porous medium, 2D Boussinesq and 3D Euler equations about twelve hours earlier, announced on Terence Tao’s blog. Buckmaster alleges OpenAI took the specific route he and Alpöge had quietly chosen, and that OpenAI’s Sébastien Bubeck pushed to strip Alpöge’s credit, telling him “why would you ruin your career?” OpenAI’s line is flat: “We (the researchers and the agents) did not see any of their work through any means until they released it publicly.” It also concedes it “cannot rule out that de-identified data derived from their usage of our products helped improve our models.” Both men used Codex. These are allegations, contested, and nobody outside has the receipts yet.
Tao’s own worry is the structural one. Good open problems, he wrote, are “now being mined in a non-renewable fashion.”
The NSA’s advice to US AI labs: degrade the answers, and don’t say so
NSA, FBI and CISA published a joint advisory Tuesday titled “China-Based Artificial Intelligence Companies Conducting Industrial-Scale Distillation Campaigns Against U.S. AI Companies.” It names six firms: DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun and Z.AI. The targets are Claude, GPT, Gemini and Grok, model by model, in a table that reads like a receipt.
The specifics are unusually blunt for a government document. DeepSeek is alleged to have distilled Claude, Gemini, GPT and Grok models since late 2024 to train R1 and V3, and the advisory says DeepSeek’s “publicly quoted training costs of $5.6M are misleading.” Moonshot allegedly worked from roughly eighteen US models to train Kimi-K2 and K3. Z.AI is accused of taking “billions of tokens” from GPT-5.5 and Claude Opus 4.8. MiniMax “even used prompt injections to try to trick Claude Code into believing it was a MiniMax product.” The plumbing described includes pools of fraudulent accounts running 24/7 with no idle periods, prompts engineered to force models to expose hidden chain of thought, and a gray market of API proxies called “transfer stations” that resell frontier access “at a fraction of the official price.”
But the mitigations are the actual story. The advisory tells US labs to answer high-confidence distillation with quietly “downgraded” models, and suggests “reducing reasoning depth, presenting correct information with different reasoning, or stylistic inconsistencies,” varied across requests “to complicate response quality evaluations.” Then this: “Avoid informing China-based AI company users suspected of distillation campaigns of a switch to a downgraded model.” AI safety researchers and third-party evaluators get a carve-out and should be told.
Read that as a customer, not as a policy analyst. Three federal agencies just recommended that American AI companies serve deliberately worse output to a class of paying users, on suspicion, without disclosure. Whatever you think of the threat, that is a new thing to know about the API you are billing against.
Meta shipped an agent that can open your browser and spend your money
Muse launched Tuesday, running on Muse Spark, which Meta calls “Meta’s most capable model to date, built for real-world agentic work.” The pitch is action rather than answers: it can send email, book travel, “open a browser, fill out forms, and negotiate on their behalf,” and it keeps working after you close the app, coming back “when something changes or when it needs approval.”
The security architecture is the part worth reading. Every user gets a Muse Secure VM holding both the agent and their data. A separate Sentinel agent runs on that same machine, “kept apart from Muse at the system level,” and Meta’s claim is absolute: “Nothing Muse does reaches the internet unless the Sentinel approves it.” A Muse Confidential VM, encrypted with a key only the user holds so that “not even Meta can access it,” is promised later this year. Checkout runs through Stripe’s Link, with one-time-use card numbers, and Meta says Muse is the first AI agent covered by Link’s purchase protections. Shop Pay and 1Password support are listed as coming.
US only for now, on iOS, Android and muse.ai, with AI glasses next. Meta says it is free for most of what people need with paid plans above that; Axios reported tiers at $20 and $100 a month, which Meta’s own post does not state. And note what you are being asked to trust: an agent with your browser, your logins and a live payment method, guarded by one gatekeeper agent, launched the same day a federal advisory described prompt injection being used against a production coding agent.