OpenAI claims blockbuster math breakthrough amid swirl of controversy
Scientific American · LC · trust 50/100
Prior to the announcement, rumors were circulating online among mathematicians over the proof's origins—OpenAI has denied all allegations
For the second time ever, someone has solved one of the seven Millennium Problems —math’s biggest targets, each worth a million-dollar prize. But unlike the first time, that someone is an artificial intelligence (AI) start-up.
Today, OpenAI announced that their internal model has proved that the Navier-Stokes equations, which mathematicians use to study how fluids move, are fatally flawed. The reveal comes after a mathematician, Tristan Buckmaster, alleged that OpenAI had tackled the proof after becoming aware of Buckmaster and his colleague, Levent Alpöge, using a specific method to break a related problem. OpenAI has denied the allegations.
OpenAI's proof shows that, on rare occasion, the Navier-Stokes equations “blow up,” meaning they dictate that a fluid’s speed becomes infinite at some points, something that is impossible in nature. The company says the proof has been certified using the programming language Lean, which all but guarantees its correctness.
If you're enjoying this article, consider supporting our award-winning journalism by subscribing . By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.
“We’re a little bit in shock,” says Diego Córdoba. He and Luis Martínez-Zoroa originally developed the approach the AI used to solve the problem, which is called “forcing.” “If it’s done, that will be a big surprise for us,” says Córdoba.
The night before OpenAI announced the proof, Buckmaster posted on social media that he and another mathematician and Anthropic employee Alpöge had blown up the Euler equations, widely seen by the field as a step toward solving the Navier-Stokes problem. In a statement published on Monday, Buckmaster alleged that OpenAI had found out about the pair’s progress in the last week, and had adopted the same method as Buckmaster and Alpöge were using to solve the full problem.
In a press briefing on Tuesday, OpenAI mathematician Sebastien Bubeck denied the rumors about the proof’s origins. Bubeck said OpenAI’s internal model had independently solved the Euler problem by totally different means than Buckmaster and Alpöge. However, OpenAI’s solution to the full Navier-Stokes problem does follow a similar method as that used by the two mathematicians. And the proof was developed over the weekend, according to Bubeck—that is, after Buckmaster claims the news of his and Alpöge's result reached OpenAI. Bubeck emphatically denied that the other mathematicians’ work had influenced OpenAI. “We did not use their prompt or models or proof,” he said.
It will likely take time to hash out the differences between the two proofs, and the progeny of AI’s mathematical ideas are famously difficult to trace. “Yesterday and today are crazy days,” says University of Chicago mathematician Luis Silvestre. “We’re all in the community discussing the implications of this.”
Editor's note: This is a breaking news story and may be updated.
Joseph Howlett is a senior reporter at Scientific American covering physics, math, astronomy, and more. He was previously a math staff writer at Quanta Magazine and holds a Ph.D. in particle physics from Columbia University.
Great science journalism requires human expertise, time, effort and creativity. And it costs money. That’s why I and the journalists here at Scientific American hope you’ll join our community.
When you subscribe, you are supporting staff and freelance journalists who are passionate about telling science stories that are true, important and compelling. Our editors and reporters are often experts in their fields, which means they understand the nuances of big discoveries and can untangle the breakthroughs from the hype. With a subscription, you are also supporting rigorous fact-checking to ensure the words we publish are precise and accurate. And you’re supporting original illustrations, graphics and photos that bring you closer to an advanced laboratory, an ice sheet in Antarctica or a space mission in orbit. You’re helping us craft other types of high-quality journalism as well: Our newsletters are carefully written, edited and curated by staffers you have or will come to know and love. Our Science Quickly podcast is based on original reporting, collaboration with editors and scientists and exacting production.
Subscriptions keep this engine running so we can continue to deliver thoughtful, rigorous and independent science journalism to you. In an era of viral misinformation, this work is crucial. If you value what we do, I hope you’ll consider joining us as a subscriber
Jeanna Bryner, Editor in Chief, Scientific American
Read the original at Scientific American →
Open in TruthVane →