From Math Olympiads to Navier-Stokes: How Fast Is AI Progressing? with Greg Burnham

AI systems have gone from struggling with grade-school math to helping solve research problems that have resisted mathematicians for decades, including Navier-Stokes. In this episode, Greg Burnham, who leads AI capabilities research at Epoch AI, joins us to examine what that progress says about where AI is going. We look at how these systems are solving hard math problems, how much they rely on persistence and prior human work, and whether they are starting to produce genuinely new ideas. We also discuss how to measure progress as traditional benchmarks become less useful, why capability gains appear surprisingly steady across model generations, and where models still struggle with open-ended work, learning from experience, and identifying promising new research directions.