The Story of RLHF

Origins, Motivations, Techniques, and Modern Applications

  • AI development has evolved from early language models like BERT and T5 to advanced Large Language Models (LLMs) like GPT-4.
  • The shift from supervised learning to RLHF (Reinforcement Learning from Human Feedback) addresses limitations of earlier models.
  • RLHF involves collecting human feedback, training a reward model, and using it to fine-tune LLMs for more aligned outputs.
  • RLHF enables LLMs to produce higher quality, human-aligned outputs, especially in tasks like summarization.
  • Early RLHF research laid the groundwork for advanced AI systems like InstructGPT and ChatGPT, aiming for long-term alignment of AI with human goals.