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TWIML · September 29, 2026 · 1h 7m

From Math Olympiads to Navier-Stokes: How Fast Is AI Progressing? with Greg Burnham - #778

Greg Burnham, AI capabilities research lead at Epoch AI, traces AI's rapid ascent in mathematical reasoning — from solving elementary problems to contributing to Navier-Stokes fluid dynamics. He examines how much of this progress relies on existing human formalizations and persistence, versus genuine novelty. The conversation covers the surprisingly steady pace of capability gains across model generations, and highlights where current systems still falter: open-ended research, iterative learning, and identifying promising future directions.

This summary was generated from show notes and public descriptions, not from a full transcript review. Details may contain inaccuracies.

Preview

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AI’s Leap from Grade-School Math to Navier-Stokes
Burnham discusses how AI systems, once limited to basic arithmetic, now assist with the Navier-Stokes equations, a long-standing challenge in fluid dynamics research.
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AI’s Heavy Reliance on Prior Human Work
Burnham notes that current AI systems succeed in math largely by leveraging existing proofs and formalizations, raising questions about when they will produce genuinely new mathematical ideas.

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