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RLHF 201 - with Nathan Lambert of AI2 and Interconnects

Latent Space: The AI Engineer Podcast

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The Evolution of RLHF in Language Models

This chapter explores the significance of Reinforcement Learning from Human Feedback (RLHF) in contemporary language models, particularly through the lens of the Llama 2 paper. The discussion addresses initial skepticism towards RLHF, the contrasting speeds of industry and open research advancements, and the philosophical foundations that guide its implementation. Additionally, it highlights key historical milestones and the importance of preference modeling in enhancing the effectiveness of reinforcement learning applications.

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