圖解人類回饋強化學習 (RLHF)：ChatGPT 背後的關鍵對齊技術
Original: Illustrating Reinforcement Learning from Human Feedback (RLHF)
The release of ChatGPT in late 2022 triggered an explosion in generative AI, and the most critical technology behind it is Reinforcement…
本文為 Hugging Face 撰寫的經典科普指南，深入淺出地解析了「人類回饋強化學習 (RLHF)」的運作機制。RLHF 是讓大型語言模型（如 ChatGPT）符合人類意圖（對齊）的核心技術。文章將其拆解為三個主要階段：預訓練與監督微調（SFT）、訓練獎勵模型（Reward Model），以及透過 PPO 演算法進行強化學習微調，並探討了其挑戰與未來展望。
The release of ChatGPT in late 2022 triggered an explosion in generative AI, and the most critical technology behind it is Reinforcement Learning from Human Feedback (RLHF). This classic blog post from Hugging Face uses richly visual diagrams to break down the complete RLHF pipeline in detail, making it an essential read for anyone seeking to understand model alignment in the AI field.
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