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Explore a seminar talk that delves into the evolution of mathematical datasets, from the AI Mathematical Olympiad (AIMO) competitions on Kaggle to potential math copilots for research. In this 49-minute presentation from the Harvard CMSA New Technologies in Mathematics Seminar, Oxford's Simon Frieder begins with an exposition of the AIMO competition, detailing available datasets and models for contestants. The talk then critically examines limitations in current mathematical datasets, including binary evaluation methods and restricted use cases, while highlighting how competition-style problem-solving differs fundamentally from actual mathematical research practices. Frieder advocates for a transformative approach to dataset structure and composition, introducing the concept of mapping mathematical workflows to data. The presentation also discusses how new thinking LLMs are reshaping evaluation methods and dataset design in mathematical contexts, concluding with proposals for improving mathematical datasets through specialized documentation adaptations.
