It’s been two days since OpenAI’s “slop drop” of AI-generated results on 372 open math and computer science problems. Scientists are just beginning to parse through the heap and pick out the most exciting breakthroughs in their own fields.
It will be months, perhaps years, before we understand just how much novel mathematics was added to the literature this week, but everyone agrees it’s been a week without precedent. “Yesterday will be the day when a new era of math and mathematical physics began,” Harvard University mathematician Michael Douglas told Scientific American on Tuesday. It was an even bigger moment, he thinks, than last month’s solution of the Navier-Stokes problem, one of math’s million-dollar challenges, by the same new internal model at OpenAI.
Already certain aspects of this new era are becoming clear. Many of the results, experts say, are far better written than the Navier-Stokes proof, suggesting that OpenAI’s math team is working to overcome its model’s inability to explain its math clearly to humans. Hector Pasten, a mathematician at the Pontifical Catholic University of Chile, says the papers he’s looked at improve on the company’s notorious lack of citations. “I think they are doing a better job of doing credit,” he says.
But the quality remains extremely uneven—mathematicians are finding some papers readable and others utterly nonsensical. “Others are much, much harder to make sense of—they’re sort of this AI slop,” says Roland Bauerschmidt, a mathematician at New York University. “If I had received these by e-mail from a nobody, I probably would have deleted it, it’s so badly written.”
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