From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2
In Part 1 of this series, we defined the Retrieval Augmented Generation (RAG) framework to augment large language models (LLMs) with a text-only knowledge base. We gave practical tips, based on hands-on experience with customer use cases, on how to improve text-only RAG solutions, from optimizing the retriever to mitigating and detecting hallucinations. This post …
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