Reinforcement Learning from Human Feedback (RLHF) is used to align AI models with human preferences and ethical considerations.
It blends supervised learning with reinforcement signals gathered from human ratings or comparisons, leading to safer AI.
It brings a human touch to AI decision-making.
ChatGPT and other LLMs benefit significantly from RLHF, producing responses that are more helpful, less toxic, and better aligned.
As AI becomes more integrated in society, RLHF remains critical to ensure responsible deployment of generative tools.
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