Generative Model Insights
Nathan discusses the complexities of generative models, emphasizing the potential of integrating reward models to enhance performance and self-correction. He highlights the challenges of deploying modular systems at scale while exploring the implications of reasoning traces and the future of user control in model interactions. The conversation delves into the nuances of compute costs and the importance of backward reasoning steps in improving language model capabilities.In this clip
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Reverse engineering OpenAI's o1
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