Reinforcement learning from human feedback (RLHF)
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that integrates human input to guide the training process of reinforcement learning algorithms. Unlike traditional reinforcement learning, which relies solely on predefined reward signals, RLHF leverages human judgments to shape and refine the behavior of AI models. This approach ensures that the AI aligns more closely with human values and preferences, making it particularly useful in complex and subjective tasks.
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