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    Both RAG and LLM fine-tuning allow institutions to enhance their LLMs, but in different ways. Fine-tuning modifies an LLM’s internal parameters using additional training data. RAG, on the other hand, supplements the model’s internal memory with non-parametric data retrieved from external sources.

     

    As someone who’s spent years both on the sidelines analyzing game footage and in the stands as a passionate fan, I’ve come to a simple conclusion: the right

     


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