What is Reinforcement Learning from Human Feedback (RLHF)?

Teaching AI to Behave: Aligning Models with Human Values

The Iterative Process of Human-Guided AI Improvement

Ensuring Safer and More Useful AI Interactions

**Reinforcement Learning from Human Feedback (RLHF)** is a crucial training technique used to **align Large Language Models (LLMs)** and other AI systems with human preferences, values, and instructions. After an LLM is pre-trained, human annotators rank or provide feedback on the quality and safety of different model outputs for a given prompt. This human feedback is then used to train a 'reward model,' which in turn guides a reinforcement learning algorithm to fine-tune the original LLM. RLHF is essential for reducing **hallucinations**, mitigating **AI bias**, and making AI models more helpful, harmless, and honest, significantly contributing to the development of **Responsible AI** in 2025. 👍👎