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.
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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.
📌 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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