The increasing context window in large language models (LLMs) raises questions about the relevance of retrieval augmented generation (RAG). While RAG combines LLMs with external knowledge sources for more accurate responses, the longer context windows in LLMs can potentially lead to more accurate and contextually relevant

9m read time From thenewstack.io
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How RAG WorksWhy Long Context Windows Might Be the End of RAGWhy RAG Will Stick AroundWhy Not Fine-TuningComparing RAG vs. Fine-Tuning or Long Context WindowsOptimizing RAG Systems With Vector Databases

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