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#033 RAG's Biggest Problems & How to Fix It (ft. Synthetic Data)

How AI Is Built

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Evaluating Retrieval Systems and LLM Performance Metrics

This chapter explores the creation of effective evaluation datasets for assessing retrieval systems and the quality of answers generated by large language models. It emphasizes key metrics like context precision, recall, and the concept of faithfulness in LLM responses, highlighting the importance of human-generated answers for performance comparison.

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