Sign in to confirm you’re not a bot
This helps protect our community. Learn more

RAG 101: Retrieval Augmented Generation

Microsoft Reactor
106K subscribers
<__slot-el>
<__slot-el>
6.8K views Streamed 6 months ago #MicrosoftReactor #raghack
An intro to RAGHack, a global hackathon to develop apps using LLMs and RAG. A large language model (LLM) like GPT-4 can be used for summarization, translation, entity extraction, and question-answering. Retrieval Augmented Generation (RAG) is an approach that sends context to the LLM so that it can provide grounded answers. RAG apps can be developed on Azure using a wide range of programming languages and retrievers (such as AI Search, Cosmos DB, PostgreSQL, and Azure SQL). Get an overview of RAG in this session before diving deep in our follow-up streams. #MicrosoftReactor #raghack 📌Check out the RAGHack 2024 series here! https://aka.ms/RAGHack2024 [eventID:23299] ...more
...more
RAG 101: Retrieval Augmented Generation
An intro to RAGHack, a global hackathon to develop apps using LLMs and RAG. A large language model (LLM) like GPT-4 can be used for summarization, translation, entity extraction, and question-answering. Retrieval Augmented Generation (RAG) is an approach that sends context to the LLM so that it can provide grounded answers. RAG apps can be developed on Azure using a wide range of programming languages and retrievers (such as AI Search, Cosmos DB, PostgreSQL, and Azure SQL). Get an overview of RAG in this session before diving deep in our follow-up streams. #MicrosoftReactor #raghack 📌Check out the RAGHack 2024 series here! https://aka.ms/RAGHack2024 [eventID:23299]

Follow along using the transcript.

Microsoft Reactor

106K subscribers
Live chat replay is not available for this video.