AI math capabilities could be jagged for a long time – Daniel Litt episode artwork

EPISODE · Jan 29, 2026 · 2H 11M

AI math capabilities could be jagged for a long time – Daniel Litt

from Epoch After Hours · host Epoch AI

Daniel Litt is a professor of mathematics at the University of Toronto. He has been a careful observer of AI’s progress toward accelerating mathematical discovery, sometimes skeptical and sometimes enthusiastic. Topics we cover: the hardest problems models can solve today, whether there is convincing evidence that AI is speeding up math research, and what’s missing before AI might have a shot at solving Millennium Prize problems.We also discuss how to measure progress in math, including Epoch AI’s new FrontierMath: Open Problems benchmark which evaluates models on meaningful unsolved math research problems.

Daniel Litt is a professor of mathematics at the University of Toronto. He has been a careful observer of AI’s progress toward accelerating mathematical discovery, sometimes skeptical and sometimes enthusiastic. Topics we cover: the hardest problems models can solve today, whether there is convincing evidence that AI is speeding up math research, and what’s missing before AI might have a shot at solving Millennium Prize problems.We also discuss how to measure progress in math, including Epoch AI’s new FrontierMath: Open Problems benchmark which evaluates models on meaningful unsolved math research problems.

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AI math capabilities could be jagged for a long time – Daniel Litt

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This episode was published on January 29, 2026.

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Daniel Litt is a professor of mathematics at the University of Toronto. He has been a careful observer of AI’s progress toward accelerating mathematical discovery, sometimes skeptical and sometimes enthusiastic. Topics we cover: the hardest problems...

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