AlphaGeometry
AlphaGeometry is an
DeepMind published a paper about AlphaGeometry in the peer-reviewed journal Nature on 17 January 2024.[3] AlphaGeometry was featured in MIT Technology Review on the same day.[4]
Traditional geometry programs are symbolic engines that rely exclusively on human-coded rules to generate rigorous proofs, which makes them lack flexibility in unusual situations. AlphaGeometry combines such a symbolic engine with a specialized large language model trained on synthetic data of geometrical proofs. When the symbolic engine doesn't manage to find a formal and rigorous proof on its own, it solicits the large language model, which suggests a geometrical construct to move forward. However, it is unclear how applicable this method is to other domains of mathematics or reasoning, because symbolic engines rely on domain-specific rules and because of the need for synthetic data.[5]
References
- ^ "AlphaGeometry: An Olympiad-level AI system for geometry". Deepmind. Retrieved 26 January 2024.
- ^ "A.I.'s Latest Challenge: the Math Olympics". The New York Times. Retrieved 26 January 2024.
- ^ "Solving olympiad geometry without human demonstrations". Nature. Retrieved 26 January 2024.
- ^ "Google DeepMind's new AI system can solve complex geometry problems". MIT Technology Review. Retrieved 26 January 2024.
- ^ Zia, Tehseen (January 24, 2024). "AlphaGeometry: DeepMind's AI Masters Geometry Problems at Olympiad Levels". Unite.ai. Retrieved 2024-05-03.
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