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Retrieval Augmented Generation (RAG) has become the de facto way to search and navigate enterprise data for Gen AI. It is not the same as semantic search and is a popular tool for improving the quality/factuality of Language Model (LLMs). RAG is highly effective and is being used in various projects, including GenAI and vector databases.
Vector search vs. Retrieval Augmented Generation (RAG) Don't know the difference? Not sure which to pick? 🤔 Our latest blog explains the pros and cons of six search and knowledge retrieval technologies. 🏆 https://t.co/tgoqd72B0R
A Beginner's Guide to Retrieval Augmented Generation (RAG) https://t.co/CGlL7nauEp via @SingleStoreDB by @Pavan_Belagatti
🤖 From this week's issue: An article that explains how to implement an advanced RAG pipeline using embeddings, cache, hybrid search, and ensemble retriever to improve the quality and relevance of text generation. https://t.co/CShtWp8myS
As #GenAI use cases expand, vector databases have become integral to the retrieval augmented generation (#RAG) stack. Kickstart your RAG project with this comprehensive guide to #Milvus from @TheNewStack. https://t.co/kVDIF4YVSX #OpenSource #VectorDatabase https://t.co/bH8rE1VQQc
Retrieval Augmented Generation (RAG) is a popular tool for improving the quality/factuality of LLMs. Self-RAG makes RAG smarter by teaching the LLM to reflect and decide which components of RAG actually help with answering a prompt… TL;DR: RAG is highly effective, but it’s a… https://t.co/t1GS9IcBJS https://t.co/AgV1vYJNAd
When should Retrieval Augmented Generation (RAG) be part of your Generative AI architecture? Check out @EdAnuff's piece in @TheNewStack to learn more ⤵️ #VectorDB #DataStax #RAG https://t.co/TTKptn8XOe
Last week, at @OReillyMedia Book Club, @timomo1234 explained how to create RAG pipelines with Haystack. One topic that came up: Is RAG the same as semantic search? Answer: No. Retrieval Augmented Generation (RAG) isn't a traditional semantic search method. Here's more 👇
By combining vector databases and LLMs, Retrieval Augmented Generation (RAG) has become the de facto way to search and navigate enterprise data for Gen AI. RAG's inventor, @douwekiela, joins DataStax to discuss where it's headed: https://t.co/Yw496tZCwa