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Edge 349: Reinforcement Learning with AI Feedback

Edge 349: Reinforcement Learning with AI Feedback

One of the most promising techniques that uses feedback from AI agents to fine tune foundation models.

Dec 05, 2023
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Edge 349: Reinforcement Learning with AI Feedback
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A scene in a futuristic classroom setting where a central AI model, designed as an advanced, humanoid robot with a sleek, metallic body and interactive digital display on its chest, is teaching a group of diverse AI models. These AI models vary in appearance, from smaller, simpler robotic forms to more complex, holographic entities. The central AI model is demonstrating a task on a large interactive screen, showing a sequence of 'trial and error' steps, with visualizations of errors and corrections. The other AI models are attentively observing, some displaying error messages on their screens, while others show corrected algorithms, illustrating the learning process.
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💡 ML Concept of the Day: Reinforcement Learning with AI Feedback

In the previous edition of this series, we reviewed Anthropic’s Constitutional AI as an AI-first alternative to traditional reinforcement learning with human feedback(RLHF) fine-tuning methods. Today, we would ilke to explore a technique that can be considered a superset of Constitutional AI: reinforcement learning with AI feedback(RLAIF).

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