Training Data

OpenAI's Noam Brown, Ilge Akkaya and Hunter Lightman on o1 and Teaching LLMs to Reason Better

54 snips
Oct 2, 2024
Join Noam Brown, an OpenAI expert in deep reinforcement learning known for his poker-playing AI, and Hunter Lightman, a developer of O1, as they dive into the groundbreaking O1 model. They discuss the blend of LLMs and reinforcement learning, revealing how O1 excels at math and coding challenges. Discover insights on problem-solving methods, iterative reasoning, and the surprising journey from doubt to confidence in AI. With exciting applications like the International Olympiad in Informatics and beyond, the future of reasoning in AI seems bright!
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INSIGHT

Reasoning and Thinking Time

  • Reasoning problems benefit from longer thinking time, unlike factual recall.
  • These problems are easier to verify than generate solutions for, like Sudoku.
ANECDOTE

AlphaGo's Thinking Time

  • AlphaGo, a DeepRL breakthrough, significantly improved by taking longer to think (30 seconds per move).
  • This extra thinking time involved domain-specific reasoning, unlike O1's general approach.
INSIGHT

O1's General Reasoning and Iterative Deployment

  • O1's general reasoning abilities are tested through diverse problem-solving.
  • OpenAI uses iterative deployment, releasing models to observe real-world interaction and improve understanding.
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