Reinforcement Learning from Human Feedback (RLHF) is a powerful machine learning technique that enhances the alignment of artificial intelligence (AI) systems with human preferences. By integrating human feedback into the training process, RLHF has become a cornerstone for fine-tuning large language models (LLMs) such as GPT-4 and Claude, enabling them to generate more accurate, helpful, and contextually appropriate outputs.
