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You're right and I was imprecise. 2. is how RAG is implemented in most cases. (I wouldn't call 1. 'RAG' exactly, though?)
by bambax 2y ago
You're right and I was imprecise. 2. is how RAG is implemented in most cases. (I wouldn't call 1. 'RAG' exactly, though?)
- bigfudge 2y agoHYDE is a related technique. Ask the model to generate a response with no context, then use this for semantic search agains actual data and respond by summarising these documents.
- simonw 2y agoI'd definitely call 1 (the FTS version) RAG. It's how Bing and Google Gemini and ChatGPT Browse work - they don't have a full vector index of the Web to work with (at least as far as I know), they use the model's best guess at an appropriate FTS query instead.