Human Feedback in AI
The use of human feedback has significantly enhanced the training of language models, allowing for better evaluation and refinement of responses. By implementing reinforcement learning from human feedback, models can identify acceptable outputs while rejecting harmful content. This process, combined with the attention mechanism, enables the model to weigh the importance of each token in context, leading to more nuanced and accurate text generation.In this clip
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AI Today Podcast
AI Today Podcast: Generative AI Series: Generative AI & Large Language Models (LLMs) – How Do They Work?
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