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Will mathematical theorem proving be solved by scaling laws?

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BPRW03 - Big proof: formalizing mathematics at scale

Recent advances in generative models and reinforcement learning have enabled automatic theorem proving beyond the capabilities of classical methods. Scaling up data, model size, and inference compute has undeniably allowed us to prove more theorems. But is scaling alone enough to solve mathematical theorem proving? If not, what essential components might still be missing?

This talk is part of the Isaac Newton Institute Seminar Series series.

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