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In this series, we dive deep into our most popular, fully-featured, and open-source RAG solution: https://aka.ms/ragchat\n\nOur RAG solution uses Azure AI Search to find matching documents, using state-of-the-art retrieval mechanisms. We'll dive into the mechanics of vector embeddings, hybrid search with RRF, and semantic ranking. We'll also discuss the data ingestion process, highlighting the differences between manual ingestion and integrated vectorization\n\nThis session is a part of a series! To learn more, click here: https://aka.ms/RAGDeepDive\n\n#MicrosoftReactor #learnconnectbuild #RAGDeepDive\n\n[eventID:24572]