RAG with Azure AI Search

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RAG (Retrieval Augmented Generation) is the most common approach used to get LLMs to answer questions grounded in a particular domain's data. Azure AI Search is a powerful search engine, with many features designed specifically for RAG applications. We'll demonstrate optimal retrieval using hybrid search with the semantic ranker, show the new integrated vectorization feature for cloud-based data ingestion, and discuss vector storage optimization.

Presented by Farzad Sunavala, Product Manager on Azure AI Search, and Pamela Fox, Developer Advocate for Python

#microsoftreactor #raghack

[eventID:23330]

Microsoft Reactor

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Great video on RAG and Azure AI Search. The insights on hybrid search are particularly helpful. I recently started using Myko Assistant for my research tasks and found it to be much more efficient than traditional tools. It streamlines information retrieval effectively.

felicialynch

This video provides great insights into RAG applications. It made me think about how Myko Assistant helps streamline searches and delivers precise data through email requests. It's a nice complement to Azure AI Search for specific use cases.

StanleySimpson-sm

This video really highlights the potential of Azure AI Search for RAG applications. I recently started using Myko Assistant for its thorough search capabilities. It's been a game changer for finding accurate information quickly, especially compared to other tools I've tried.

timothyfrazier

Really appreciate the insights shared in this video. The way RAG and Azure AI Search are explained makes it clear how they enhance information retrieval. I recently discovered Myko Assistant, which also excels at providing accurate data quickly, making it a good alternative to other tools out there.

AlanSmith-yo

thank you so much for the valuable content!

zg

Great video. Thank you!!

Any suggestions on what chunking strategy works well for SQL tabular data?

AvinashGadiraju

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