Meet AlphaGeometry: Google's new AI to solve geometry problems
Google's AI research lab, DeepMind, has introduced AlphaGeometry. It is an AI system capable of tackling geometry problems at the level of an International Mathematical Olympiad gold medalist. AlphaGeometry can solve 25 Olympiad geometry questions within the standard time limit. According to Google scientists Trieu Trinh and Thang Luong, this achievement marks a significant step in developing AI systems with advanced mathematical reasoning skills.
Why geometry matters for AI
DeepMind's interest in geometry is rooted in the idea that proving mathematical theorems involves both logical reasoning and selecting the right steps to reach a solution. This approach could be beneficial for creating versatile AI systems. As DeepMind explained to TechCrunch, proving mathematical theorems demonstrates a mastery of logical reasoning and the ability to uncover new knowledge.
Overcoming challenges in AI geometry problem solving
Training AI to solve geometry problems presents unique challenges, such as converting proofs into machine-readable formats and finding suitable geometry training data. To overcome these obstacles, DeepMind combined a neural language model with a symbolic deduction engine that uses mathematical rules to deduce solutions. The neural model guides the deduction engine through potential answers, while DeepMind generated 100 million synthetic theorems and proofs for training data.
AlphaGeometry's approach and implications
AlphaGeometry's neural model can predict which constructs to add to Olympiad geometry problems, and its symbolic engine uses these predictions to make deductions about diagrams and find solutions. Trinh and Luong believe that this hybrid symbolic-neural network system could influence how future AI systems discover new knowledge in mathematics and other fields. The success of AlphaGeometry may spark discussions about whether AI should be based on symbol manipulation, neural networks, or a combination of both methods.
