AI鈥檚 dramatic acceleration of mathematics research continues apace, with the infamous Navier-Stokes puzzle being the latest and greatest solution yet produced by artificial minds. But not everyone is happy about the discovery.

What has OpenAI discovered?

In short, a solution to the long-standing Navier-Stokes puzzle 鈥� one of the toughest and most enduring problems in mathematics. Whoever solved it stood to win $1 million from the Clay Mathematics Institute, because it was one of its six Millennium Prize Problems.

The slightly longer version is that Navier-Stokes equations are used to model fluid flows, such as air over aircraft wings and blood in veins. There has been an outstanding problem in that we don鈥檛 know聽if these equations always work, or if there are situations where they stop making sense and start spouting nonsense, what mathematicians call 鈥渂low-ups鈥�.

OpenAI has discovered they do, indeed, blow up.

Why is that controversial?

The work itself isn鈥檛 controversial. It hasn鈥檛 been peer-reviewed, but it has been formalised. This is the process of theories and proofs being turned into computer code that allows machines to grapple with them, methodically working through the logic and exposing any flaws. That means we can be fairly sure the results are correct.

The controversy arose because, shortly before OpenAI released its news, a pair of researchers,聽聽at New York University聽and 聽at AI company Anthropic, rushed out their solution to a close cousin of Navier-Stokes, the Euler equations, which experts suggested could open the door to a full solution.

Those researchers heard rumours that OpenAI was due to make its announcement, and contacted the company for clarification 鈥� knowing its own solution was on the way. Buckmaster聽claims he was met with opaque responses, and that stopped short of making any accusations but pointed out that his own work was being stored on OpenAI鈥檚 servers 鈥� as a customer, not a research partner.

OpenAI has explicitly denied any wrongdoing, pointing out that no person or AI from the company had seen Buckmaster and Alp枚ge鈥檚 work, and that its solution was, in any case, different.

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Do we know exactly what happened?

In a word, no. Although more will become clear when full papers of all the work emerge. All we know for sure is that AI is causing upheaval in the world of mathematics. In recent months, it has made rapid progress on mathematics problems, peaking with this week鈥檚 news.

Mathematicians are mixed on the impact of AI. Some are excited about the prospects; others are fearful of their own careers. All say that on some level, AI will change the field and there will be a period of adjustment. There will also be questions to answer on how results are credited when AI was used.

Are mathematicians happy that AI is accelerating mathematical research?

at the University of California, Los Angeles 鈥� arguably the world鈥檚 greatest living mathematician 鈥� certainly isn鈥檛. There has always been competition among mathematicians to be first, he says, which was fine, because mathematics is so difficult that it created a natural brake to stop things getting out of hand. AI is changing all that. 鈥淣ow there鈥檚 no speed limit, and suddenly things are breaking down,鈥� he says.

Tao fears that with this pace, new findings will keep landing. There will be no time to absorb the results and assimilate them into the wider field 鈥� to fully understand them, put them into textbooks and teach them to students, he says. That means progress could begin to hurt the field.

鈥淭hese companies are dumping carcasses of raw meat onto our communal village table and saying, 鈥榟ere you go, I solved your food problem鈥�, and then they just leave,鈥� says Tao. 鈥淭hey鈥檙e expecting us to prepare the food and cook it and eat it. All that work is left to us, to clean up, and it鈥檚 demoralising.鈥�

OpenAI has solved the Navier-Stokes Millennium problem using $15m of AI effort

One of the trickiest problems in mathematics has now fallen to AI after just days of work. The groundbreaking result was announced after similar, but less complete work, also created with AI, was announced just hours before

Who will win the $1 million prize?

It鈥檚 not clear yet if anyone will. 鈥淭he process of evaluation is deliberately unhurried, and we shall ensure that it is absolutely rigorous,鈥� , president of the Clay Mathematics Institute, wrote to聽New 女生小视频聽in an email.

If someone does win, the question will be whether it should go to Buckmaster and Alp枚ge, as some have suggested, or to OpenAI.

An interesting aside is that if it does go to OpenAI, the cost of solving the problem (if charged as a customer) would run to $15 million 鈥� many times the prize money. But such a headline may also mean the company鈥檚 upcoming IPO is a much more attractive proposition for investors, potentially recouping many times the outlay.

OpenAI claims one of its AI models has found a solution to the Navier-Stokes problem, one of the toughest and most enduring puzzles in mathematics, sitting on the list of Millennium Prize Problems, solutions for which come with a $1 million reward. The announcement came after an unusual flurry of activity around the problem, along with a dispute around how the work came about.

The Navier-Stokes equations describe how fluids move in space, such as air over an aircraft wing or water out of a tap. Though the equations were first written down around 200 years ago, they aren鈥檛 well understood. The question posed by the Clay Mathematics Institute for the Millennium Prize Problem is to determine if the equations always work or if there are situations where they stop making sense and start spouting nonsense, what mathematicians call 鈥渂low-ups鈥�.

To settle the question, OpenAI first set 1000 AI agents on the Euler problem, which is a cousin of the Navier-Stokes problem and a step on the path to a full solution. It took the agents 50 hours to find blow-ups in this case. They then set 10,000 agents the task of extending the blow-ups to apply to the full Navier-Stokes problem, which took just 11 hours to finish.

OpenAI said during a press conference that if a customer wanted to run the same problem, it would cost around $15 million. OpenAI didn鈥檛 name the AI model used, but said it was 鈥渟ignificantly more capable鈥� than even its latest GPT-6 Astra model.

鈥淭his problem has remained unsolved for 200 years because the Navier-Stokes equations are just so enormously complex, and the pen-and-paper calculations you need to do in order to solve this problem are just mind-bogglingly intricate,鈥� says Venkat Chandrasekaran at OpenAI, who was also on the press conference call.

at OpenAI says the news is the 鈥渟pectacular combination of the arc we have seen over the last 12 months鈥�.

The result is the latest in a string of shocking mathematical discoveries led by AI in recent months. In May, an OpenAI model聽cracked a decades-old conjecture by Paul Erd艖s, causing a stir in mathematical circles. Later,聽the Claude Fable 5 AI聽found a counterexample to the Jacobian conjecture, which had stood for nearly a century. Last week, an AI model formalised Fermat鈥檚 last theorem in just 11 days.

OpenAI鈥檚 latest groundbreaking mathematical discovery came just hours after 聽at New York University and 聽at AI company Anthropic announced that they had cracked three significant problems considered 鈥渟tepping stones鈥� to the Navier-Stokes problem.

Buckmaster and Alp枚ge also showed that blow-ups can appear in Euler equations; OpenAI has now shown that the same is true of Navier-Stokes.

Buckmaster and Alp枚ge said they received a 鈥済reat deal of help聽from鈥� large language models (LLMs), including LLMs from Anthropic and OpenAI. But when rumours suggested that OpenAI had gone one step further and solved the wider Navier-Stokes puzzle 鈥� something the company formally announced just hours later 鈥� Buckmaster released a statement suggesting that OpenAI acted unusually and opaquely when he approached the company for clarification.

Buckmaster wrote in a that, as a result of these rumours, he emailed a prominent mathematician at OpenAI to clarify matters. He says that in a subsequent meeting with OpenAI staff, he was given no hard details about how OpenAI achieved the result, but he took what little he was told as a 鈥渞ed flag鈥�, as it appeared to describe the same technique and path that he and Levent had followed to achieve their interim findings.聽

According to Buckmaster, OpenAI then admitted it hadn鈥檛 started its own AI search for a solution until after it had heard of his and Alp枚ge鈥檚 work, and didn鈥檛 respond to questions about whether its AI model had been trained or fine-tuned on that existing work 鈥� which was being stored in OpenAI鈥檚 Codex model, where the company would theoretically have access to it.聽The pair had used Codex as a customer, not a research partner, so expected that their work should remain secure and private.

Buckmaster makes it clear in his version of events that he is making no claims or accusations about how OpenAI arrived at its solution, saying only that he wished the focus could instead be on the mathematics rather than scandal and intrigue. 鈥淚 have not seen OpenAI鈥檚 proof. I do not know what their model did, or how. I do not know whether our data was used. I am not accusing anyone of anything,鈥� he wrote in the posted document.

In a press conference announcing its discovery, OpenAI categorically denied using Buckmaster and Alp枚ge鈥檚 proof or prompts in its work. It also said that its model鈥檚 proof of Euler is different to that put forward by Buckmaster and Alp枚ge.聽

It also said that no humans accessed Codex to see work in progress within. Mark Chen at OpenAI, when asked if that also applied to any of the thousands of AI agents that had worked on the problem, said 鈥渢hat鈥檚 also our understanding鈥�.

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Though the solution to this Navier-Stokes problem has been a long time coming, AI-generated proofs are often hard to understand and rarely bring the same level of new insight than those created by humans. 鈥淭here鈥檚 been this very strange and unprecedented decoupling, this year alone, between getting answers and getting understanding,鈥� says at University of California, Los Angeles. He says that AI is coming up with new results so quickly that there is not enough time for the 鈥渟low, deliberate discussion鈥� needed to unpack them.

Something that will happen slowly is determining how the $1 million Millennium Prize money will be awarded. 鈥淭he process of evaluation is deliberately unhurried, and we shall ensure that it is absolutely rigorous,鈥� wrote , president of the Clay Mathematics Institute, to New 女生小视频 in an email.