The challenges of reinforcement learning from human feedback (RLHF)

Reinforcement learning from human feedback (RLHF) is a technique that trains an AI agent to optimize its behavior based on human preferences. RLHF has been used to create impressive language models, such as ChatGPT and Sparrow, that can generate natural and engaging text for various tasks. But how does RLHF work and what are the difficulties involved in implementing it? In this post, I will explain the main steps and challenges of RLHF and discuss some potential solutions and directions for future research.