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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
** Part of RAGHack, a free global hackathon to develop RAG applications. Join at https://aka.ms/raghack **
๐ Check out the RAGHack 2024 series here!
Pre-requisites: - Read the official rules and join the hack at https://aka.ms/raghack. No Purchase Necessary. Must be 18+ to enter. Contest ends 9/16/24.
- Want more hands-on RAG training? Visit the Reactor series home page to see all the RAGHack 2024 sessions!
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