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Automated Theory Formation and Interestingness in Mathematics

New Technologies in Mathematics Seminar
Speaker: George Tsoukalas, UT Austin Dept. of Computer Science and Google DeepMind.
Title: Automated Theory Formation and Interestingness in Mathematics
Abstract: Advances in modern learning systems are beginning to demonstrate utility for select problems in research mathematics. A broader challenge is that of developing new theories automatically. This area has a rich history, and is tied to some of the earliest work in AI. In particular, a central question in this study was measuring the “interestingness” of mathematical concepts.
In this talk, I will review this historical context and present our recent work on using large language models to synthesize interestingness measures that guide theory exploration in elementary number theory from scratch. I will conclude by outlining potential future research directions in this domain.
Joint work done at UT Austin with Rahul Saha, Amitayush Thakur, Sabrina Reguyal, and Swarat Chaudhuri.