Textbook math was also made rigorous by a series of books by Bourbaki.
Now the dream of logicism is being fully realized. Jared Duker Lichtman writes:
The MAP: Mathematics Autoformalization ProjectSoon the great body of math theorems will be formalized into computer-checkable proofs. No longer will there be any doubts about whether referees have adequately checked the proofs.We are poised to translate all known math into formal code.
This is the math-equivalent of the Human Genome Project, or AlphaFold in modern times.
On September 4th, Anthropic shocked the math world by formalizing Fermat’s Last Theorem.
The proof-checking software has had some glitches, but they will soon be ironed out. Possibly some currently-accepted theorems will have to be rejected.
In the recently announced AI proof of a complex structure on the 6-sphere S6, the argument used a construction that a previously published paper supposedly proved was impossible. The AI found a flaw in that paper.
The math community has an amazingly good record of only publishing theorems that are true. It is way better than 99%. Soon it will be 100%. This is a level of precision unmatched in human history.
Not that this is the end of math. There is still plenty for humans to do. Humans need to make the works comprehensible, and to set directions for new research.
Now there are rumors of a Millennium Prize problem being solved, namely a counterexample to Navier-Stokes. A fluid flow that becomes singular in finite time. See this video. Apparently OpenAI, Anthropic, and some human mathematicians are competing for the credit, and the $1 million payoff.
If an AI LLM solved Navier-Stokes, this would be the biggest Math accomplishment yet. If the proof was mostly stolen from humans, the significance will be harder to assess.
Terry Tao, an expert on both Navier-Stokes and AI LLMs, discusses the progress. He says that finding a full counter-example looks feasible in the near future.
Update: Here is the OpenAI announcement. It complains that an NYU professor and an Anthropic employee did not agree to a joint announcement.
The journal Nature announces:
For the first time, a truly major open problem in mathematics has been solved by computer, according to OpenAI, which says it has cracked one of the ‘Millennium Problems’ related to the motion of fluids.So the AI LLM did not really solve this problem. It finished a work-in-progress by some human mathematicians.The artificial-intelligence (AI) company in San Francisco, California, announced on 8 September that it has generated a solution to the most commonly used physical model of fluids — the Navier-Stokes equations — showing that they can break down. Whether or not this could happen was one of the seven ‘Millennium Problems’ asked by the Clay Mathematics Institute at the turn of the twenty-first century. Solutions come with a prize of US$1 million....
They then decided to focus their resources on the Navier-Stokes problem on 1 September, after hearing rumours that two mathematicians, Levent Alpöge of Harvard University in Cambridge, Massachusetts, and Tristan Buckmaster of New York University, had solved some version of the fluid-motion puzzle using Anthropic AI’s models.
On 7 September, Alpöge and Buckmaster released a paper in which they say they had found a solution for the fluid equations that also achieved infinite speed, but in the simplified case in which the fluid has no viscosity.
AI LLMs have solved some major problems, but it is not so clear who deserves the credit in this case. It will be interesting to see who gets the $1 million.
Update: OpenAI says it is not claiming the million. It might have spent $50 million in computer time on it.
The counterexample is to Navier-Stokes with a forcing term. It is still not known whether the straight Navier-Stokes equation (with no forcing term) always has a solution.
Update: I should add that Professor Terry Tao is very pro-AI, and rarely gives any negative opinions. So it is significant that he criticized OpenAI's role in this matter.
