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Sam Lehman: What the Reinforcement Learning Renaissance Means for Decentralized AI

The Delphi Podcast

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Advancements in Reinforcement Learning for LLMs

This chapter explores the evolution of reinforcement learning (RL) in large language models (LLMs), with a focus on the innovative approaches taken by the DeepSeek team. It examines the use of Reinforcement Learning from Human Feedback (RLHF) and the impact of binary rewards on model training and reasoning abilities. Additionally, the discussion highlights the contrast between model performance and human reasoning, alongside the challenges of applying RL in creative domains.

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