Reinforcement learning from human feedback (RLHF) is a way to teach a computer how to write better by getting feedback from humans. This process involves three steps.

First, the computer learns about language by reading lots of books or articles.

Next, humans are asked to read what the computer writes and give feedback on whether it's good or bad. This feedback is used to train a smaller computer program that can predict if something is good or bad.

Finally, the computer uses this information to try and write better. It's like trying to get better grades in school by listening to your teacher's feedback and using that information to improve your work.

RLHF is different from regular computer learning because it uses human feedback, which is more accurate and can capture more complex aspects of language.
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