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What is RLHF?

A plain-English explanation of RLHF (Reinforcement Learning from Human Feedback) — what it means, why it matters, and how it is used in AI.

RLHF
Reinforcement Learning from Human Feedback
Reinforcement Learning from Human Feedback (RLHF) is a training technique where human evaluators rank or rate model outputs, and those preferences are used as a reward signal to fine-tune the model.
"Human raters compare two AI responses and indicate which is more helpful. This preference data trains a reward model, which guides further training of the language model."

Also known as: RLHF, preference learning, human preference optimisation

Fine-tuningDPOAlignment

Why does RLHF matter?

RLHF is used to align language models with human values and make them more helpful, harmless, and honest.

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Fine-tuningDPOAlignment