AI Infrastructure RAG in Production: Retrieval Augmented Generation That Actually Works
RAG combines large language models with external knowledge retrieval to reduce hallucinations and ground AI outputs in factual data. While the concept is straightforward, production deployment reveals critical challenges around chunking strategies, latency optimization, and retrieval accuracy that separate working systems from prototypes.
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