Reinforcement Learning from Human Feedback (RLHF) is a method that allows large language models (LLMs) to learn directly from human feedback on their generated responses. By incorporating human preferences into training, RLHF helps develop models better aligned with user needs and values. The post covers RLHF's core concepts, implementation steps, challenges, and advanced techniques like Constitutional AI.
Sort: