I Want Flexible Queries, Not RAG (win-vector.com)

John Mount argues that while retrieval augmented generation (RAG) attempts to address the limitations of large language models (LLMs) by supplementing them with external references, the true value of LLMs lies in their flexible natural language query interface rather than their generative capabilities, which often produce unreliable results. He illustrates this with a personal anecdote where a traditional search engine, despite its flaws, provided a more satisfactory outcome than a purely generative AI.

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