In this week’s episode of No Priors, Sarah and Elad sit down with the Google DeepMind team behind AlphaProof, a new reinforcement learning-based system for formal math reasoning that recently reached a silver-medal standard in solving International Mathematical Olympiad problems. They dive deep into AI and its role in solving complex mathematical problems, featuring insights into AlphaProof and its capabilities. They cover its functionality, unique strengths in reasoning, and the challenges it faces as it scales. The conversation also explores the motivations behind AI in math, practical applications, and how verifiability and human input come into play within a reinforcement learning approach. The DeepMind team shares advice and future perspectives on where math and AI are headed.
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Show Notes:
0:00 Personal introductions
2:19 Achieving silver medal in IMO competition
3:52 How AlphaProof works
5:56 AlphaProof’s strengths within mathematical reasoning
8:56 Challenges in scaling AlphaProof
13:40 Why solve math?
17:50 Pursuing knowledge versus practical applications
21:30 Insights on verifying correctness within reinforcement learning
28:27 How AI could foster more collaboration among mathematicians
30:28 Surprising insights from AI proof generation
34:17 Future of math and AI: advice for math enthusiasts and researchers