jayantshivnarayana
1 post
Sep 26, 2025
3:18 AM
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Reinforcement Learning from Human Feedback (RLHF) is a method that helps AI models learn from human evaluations instead of relying solely on data. After initial training on large datasets, humans review the model’s outputs, scoring them for accuracy, relevance, and safety. These scores are converted into reward signals, which guide the AI’s reinforcement learning process. RLHF is widely used in chatbots, large language models, and AI content moderation tools. By incorporating human judgment, RLHF ensures that AI systems produce outputs that are more accurate, safe, and aligned with human preferences, creating user-friendly and reliable results.
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