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Edge 345: Deep Diving Into Reinforcement Learning with Human Feedback
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Edge 345: Deep Diving Into Reinforcement Learning with Human Feedback

Details about the most important fine-tuning technique ever created.

Nov 21, 2023
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Edge 345: Deep Diving Into Reinforcement Learning with Human Feedback
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A futuristic scene depicting human evaluators fine-tuning an artificial intelligence language model using reinforcement learning with human feedback. The humans are using trial and error, interacting with a complex, holographic interface in a high-tech lab. The environment is cinematic, filled with advanced technology and glowing screens. The evaluators, a diverse group of men and women of various descents, are focused and engaged in their work, analyzing data and providing feedback to the AI system.
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💡 ML Concept of the Day: Reinforcement Learning with Human Feedback

Continuing our series about fine-tuning in foundation models, today we would like to cover what can be considered the most popular fine-tuning method ever built. Reinforcement learning with human feedback(RLHF) became a phenomenon after it enable the transition from GPT-3 to ChatGPT. RLHF, often termed "RL from human preferences." This approach has its complexities, primarily because it unfolds in multiple stages. Let me simplify it for you in three straightforward steps:

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