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 **