Nathan Lambert

Reinforcement Learning from Human Feedback explores the ideas, established techniques and best practices of RLHF you can use to understand what it takes to align your AI models. You’ll begin with an in-depth overview of RLHF and the subject’s leading papers, before diving into the details of RLHF training. Next, you’ll discover optimization tools such as reward models, regularization, instruction tuning, direct alignment algorithms, and more. Finally, you’ll dive into advanced techniques such as constitutional AI, synthetic data, and evaluating models, along with the open questions the field is still working to answer. All together, you’ll be at the front of the line as cutting edge AI training transitions from the top AI companies and into the hands of everyone interested in AI for their business or personal use-cases.