From d1b336208bdadd28b9a335bc528e6784f55286cc Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Mon, 6 Jan 2025 17:03:43 +0100 Subject: [PATCH] LLM -> LM because it needn't be large --- .../search-your-data/retrieval-augmented-generation.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/search/search-your-data/retrieval-augmented-generation.asciidoc b/docs/reference/search/search-your-data/retrieval-augmented-generation.asciidoc index db86aa0088cad..0d6a6533ed0f6 100644 --- a/docs/reference/search/search-your-data/retrieval-augmented-generation.asciidoc +++ b/docs/reference/search/search-your-data/retrieval-augmented-generation.asciidoc @@ -21,7 +21,7 @@ RAG sits at the intersection of https://www.elastic.co/what-is/information-retri RAG has several advantages: -* *Improved context:* Enables grounding the LLM with additional, up-to-date, and/or private data. +* *Improved context:* Enables grounding the language model with additional, up-to-date, and/or private data. * *Reduced hallucination:* Helps minimize factual errors by enabling models to cite authoritative sources. * *Cost efficiency:* Requires less maintenance compared to finetuning or continuously pretraining models. * *Enhanced security:* Controls data access by leveraging {es}'s <> features, such as role-based access control, and field/document-level security.