Mathematicians Can't Make Sense of How OpenAI's Agents Solved One of the Toughest Math Problems Because the AI's "Proof" Is Borderline Incomprehensible

Earlier this month, OpenAI announced that it had found a solution for one of the biggest unsolved problems in math, the Navier-Stokes equations, by directing 10,000 of its powerful AI agents to work on the enigma for 88 hours straight. It was an occasion fraught with controversy, however, as mathematicians accused the company of essentially stealing their work.

That controversy is still rippling through the math world. But what has the AI’s solution taught us? Not a lot, as it turns out, because the proof it wrote, while technically correct, is borderline incomprehensible.

“So far it’s been very difficult to really extract any human understanding from this new AI proof,” James Maynard, an Oxford mathematician, told NPR.

“The paper is not written for humans,” echoed Javier Gómez-Serrano, a mathematician at Brown University who uses AI in his own research. The AI’s proof could help the field after “some serious re-writing,” he added, but “as of today, the paper doesn’t teach us much.”

The Navier-Stokes equations mathematically describe how fluids, ranging from a rush of wind to the churn of ocean currents, move and behave. They’ve been used for nearly two centuries with reliable results, but why they work remains something of a mystery. Scientists have been eager to push the equations to their limits and see if their predictions could reach a breaking point where they describe a scenario that makes no sense in the real world. Reifying the equation’s importance, the Clay Mathematics Institute in 2000 listed the Navier-Stokes as one of its six Millennium Problems, with the prize for solving it at $1 million.