Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to move beyond generic AI responses and leverage their unique knowledge bases, RAG bridges general AI capabilities and domain-specific expertise.
Hundreds, perhaps thousands, of companies are already using RAG AI services, with adoption accelerating as the…
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https://www.zdnet.com/article/rag-can-make-ai-models-riskier-and-less-reliable-new-research-shows/
