AlphaGeometry is an artificial intelligence (AI) program that can solve hard problems in Euclidean geometry. It was developed by DeepMind, a subsidiary of Google. The program solved 25 geometry problems out of 30 from the International Mathematical Olympiad (IMO) under competition time limits—a performance almost as good as the average human gold medallist. For comparison, the previous AI program, called Wu's method, managed to solve only 10 problems.[1][2]
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]
|
| |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| |||||||||||
| Computer programs |
| ||||||||||
| Machine learning |
| ||||||||||
| Generative AI |
| ||||||||||
| See also |
| ||||||||||
| |||||||||||
 | This artificial intelligence-related article is a stub. You can help Wikipedia by expanding it. |
