OpenAI unleashes hundreds more math results upon a field already in shock!

The floodgates are open. Right on the heels of OpenAI’s new large language model producing the biggest math breakthrough in two decades, the company just released no less than 372 results from the same model. Each resolves or makes substantial progress on a major open question in mathematics or theoretical computer science, the company says, Scientific American quotes.

Among the results claimed are a solution to the four-dimensional Kakeya conjecture, improvements on some of the world’s most important computer algorithms and actual progress toward math’s scariest problem, the Riemann hypothesis.

A spokesperson for OpenAI told Scientific American that the new model — which the company has not released to the public — produced almost every one of the results in response to a single prompt handed to a single AI agent. This would be a striking difference from OpenAI’s earlier blockbuster solution to the Navier-Stokes problem, which was produced through the collective efforts of a 10,000-strong agentic swarm that cost millions of dollars in computing power. If true, it would mean that unprecedented mathematical power could soon be accessible to anyone. But OpenAI’s reputation, among mathematicians, for bold claims and little transparency is causing considerable skepticism.

“Until and unless they release the model and people can replicate their results, I think you should treat any claims about one-shotting problems with a single agent as unverified,” says Andrew Sutherland, a mathematician at the Massachusetts Institute of Technology. “We should ask for receipts.” (The OpenAI spokesperson also told Scientific American that some results might have taken multiple attempts.)

As the Navier-Stokes dispute unfolded, comments from OpenAI personnel led some mathematicians to believe the company’s model had produced additional results but that it was hesitating to publicize them. This raises a vital question: Is it more harmful to unload heaps of unexplained proofs on the community or withhold them entirely?

“If we want to know the answers to these math questions, I see no reason why we should ask the company to keep them secret from us,” says Daniel Litt, a mathematician at the University of Toronto. “To me, it’s going to be a good thing for mathematics.”

On the other hand, the famed mathematician Terence Tao has vocally criticized OpenAI and other “frontier” AI labs for the “insane” pace of their AI-generated results.

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