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---
title: RAG News &amp; Updates | daily.dev
description: Retrieval-Augmented Generation (RAG) supplies a model with retrieved documents so its answers are grounded in a source. Readers can learn about chunking and embedding strategies, vector and hybrid retrieval, reranking, evaluation, and production failure modes.
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og:title: RAG News &amp; Updates | daily.dev
og:description: Retrieval-Augmented Generation (RAG) supplies a model with retrieved documents so its answers are grounded in a source. Readers can learn about chunking and embedding strategies, vector and hybrid retrieval, reranking, evaluation, and production failure modes.
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