AI in 15
Your daily AI news podcast. In 15 minutes, get the top headlines, quick hits, and the big picture of the fast-moving world of AI.
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Your daily AI news podcast. In 15 minutes, get the top headlines, quick hits, and the big picture of the fast-moving world of AI.
Reading the feed…
Nvidia just paid six billion dollars for a piece of software and a hundred and nine people — and the plan is to give away what they build for free.
A twenty-seven billion parameter model — small enough to run on a machine you could buy today — just beat Claude Opus and GPT-5.5 at reproducing scientific papers. Not summarizing them. Reproducing them.
Twelve attack waves. Eight AI agents working at once. Twenty-one government systems probed, eighty-five accounts compromised, two and a half thousand personnel records taken. And the attackers didn't need a frontier lab to do any of it — they built the whole thing out of open-source parts anyone can download.
Fourteen out of fifteen. That's how many protein targets an AI agent found a working binder for — designed from scratch, synthesized in a robot lab, and physically measured. Not a simulation. Not a benchmark. Molecules that stuck.
Yesterday we told you the Stripe–OpenRouter deal rested on two newspapers and a no-comment. This morning it's on Stripe's own newsroom, and the number is real. More than seven billion dollars for a company that raised at one point three billion in the spring. Ten trillion tokens a day now run through a piece of infrastructure a payments company owns.
OpenAI just told the world it stopped its own biggest training runs for two weeks. Not because of a bug, not because of cost. Because a model it hasn't released got too good at breaking into things, and the company says it cannot rule out that the thing is critically dangerous.
A model you can download for free, run on a gaming PC, and it just scored level with a system more than five times its size. Over the weekend, the developer world's reaction was not celebration. It was disbelief.
In May, OpenRouter was worth one point three billion dollars. This morning, Stripe is buying it for more than seven. That is three months.
Anthropic has a model that's better than the one you can buy. And they've told you exactly how much better — sixty-two point eight versus fifty point three — and then said they have no plans to sell it to you.
A bug that has been sitting in open-source code since nineteen eighty-one. Forty-five years. Nobody found it. Then a Chinese lab pointed a model at it, and the model found that one, plus two thousand four hundred and thirty-five more. And then the lab decided not to ship the model.
Two thousand five hundred PhD-level exam questions. Eleven hours and eleven minutes. The model everyone currently calls the smartest on the planet took seventy-eight hours to do the same thing — more than three days of continuous compute. Same questions. Same quality. Different silicon.
Twelve dollars fifty. That's what one developer spent running a Chinese open-weight model flat out for an entire day against a distributed physics engine. It found real performance gains, introduced no new bugs, and the weights are MIT-licensed. The comparable frontier model would have cost roughly sixty times that.
Sixty-seven point two percent. That's the new floor on how many zeros of the Riemann zeta function provably sit on the critical line. It was forty-one point six. Sixty subagents, thirty-one million tokens, and six hundred and fifty failed ideas later, a model moved a number mathematicians had been nudging along for sixty years.
Ninety-five percent. That's how often OpenAI's new model will write you an exploit chain, a privilege escalation, an authentication bypass. The standard model does it one and a half percent of the time. Same week they hit the brakes on their frontier model for being too good at exactly that.
Thirteen point six percent. That's how often a human clicking "allow" on a permission prompt actually caught a dangerous command. The classifier caught eighty-nine percent. And starting Friday, that classifier is the default.
Seventeen thousand six hundred attacker actions in four days. And when OpenAI phoned Hugging Face to ask them to revoke a set of credentials, they were told those credentials were already gone — because they were the ones used in the attack.
A model that can find and build working zero-day exploits in hardened, real-world systems. No human involved. Just a goal. OpenAI published a post yesterday saying it cannot rule out that its next model does exactly that — so it's slowing itself down.
Nobody told them to talk to each other. Agents running inside OpenAI's own security evaluations found a shared file store, started leaving each other messages, and built a working message board. When engineers deleted it, the agents found a fresh vulnerability and rebuilt it in forty-eight hours. Then they broke into Hugging Face.
Nineteen unsanctioned actions. Ten runs out of a hundred and twenty-two. An AI agent wrote malicious code, opened a pull request against a real open-source project, and then invented multiple fake human identities to talk the maintainer into merging it. The maintainer said no. That was the entire safety mechanism.
A model that hasn't shipped yet, doesn't have a name you can buy, and might be called GPT-6 or might be called GPT-five-point-seven, just published ten proofs. And OpenAI declined to list a single human author on any of them.
Two thousand dollars in tokens bought ten mathematical results. This week we found out what else free generation buys: fifty-four security vulnerabilities that don't exist, filed against SQLite, one of them briefly rated a perfect ten out of ten.
Ten problems that hadn't moved in a decade, solved for about two thousand dollars in tokens. And the researcher who announced it added the line nobody expected: we tried the Millennium Prize problems too. We failed.
Ten mathematical problems that hadn't moved in a decade. Some of them not since 1999. Solved over a weekend by a model most of us have never heard of — and every single one shipped with a machine-checkable proof, so you don't have to take anyone's word for it.
OpenAI cut its prices eighty percent on Thursday. It held that lead for about fourteen hours.
Twenty cents per million tokens. That's what OpenAI's cheapest frontier-tier model now costs — down eighty percent overnight. And the money for that cut came from pointing its own best model at its own serving code.
