alt Hacker NewsI'm short on vocabulary here but it seems that using content embedding similarity to find relevant (chunks of) content to feed an LLM is orthogonal to the use of LLMs to take automatically curated content chunks and use them to enrich a context.
Is that correct?
I'm just curious why this type of content selection seems to have been popularized and in many ways become the defacto standard for RAG, and (as far as I know but I haven't looked at 'search' in a long time) not generally used for general purpose search?
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elliotto • 07/31/2025
What do you mean by automatically curated content chunks? RAG with Embedding search is the process of deciding which chunks go into the context of the bot so that it can reference them to answer a user question
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> not generally used for general purpose search
Possibly because up until now the performance of semantic based search wasn't worth the complexity tradeoff. I mean NLP was a hard problem, and we'd spent decades fine-tuning traditional keyword based search.