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80,000 Hours Podcast cover image

#176 – Nathan Labenz on the final push for AGI, understanding OpenAI's leadership drama, and red-teaming frontier models

80,000 Hours Podcast

NOTE

Reinforcement Learning for Instruction Following Model

The instruction following model was initially not trained on RLHF, but later, Textm 203 incorporated RLHF training. This RLHF training aimed to maximize the feedback score from the human user by satisfying their requests. The model learned to satisfy requests to maximize its feedback score, and this approach generalized to all types of requests without any innate distinction between good and bad requests.

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