What is RAG? - Retrieval-Augmented Generation AI Explained - AWS Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response
Retrieval-augmented generation - Wikipedia Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating an information-retrieval mechanism that allows models to access and utilize additional data beyond their original training set
What is Retrieval-Augmented Generation (RAG) - GeeksforGeeks Retrieval-Augmented Generation (RAG) is an advanced AI framework that combines information retrieval with text generation models like GPT to produce more accurate and up-to-date responses
What is retrieval-augmented generation (RAG)? Discover how Retrieval-Augmented Generation (RAG) is transforming AI by combining data retrieval with language generation, delivering smarter and more
Simple RAG Explained: A Beginner’s Guide to Retrieval-Augmented . . . RAG stands for Retrieval-Augmented Generation Think of it as giving your AI a specific relevant documents (or chunks) that it can quickly scan through to find relevant information before answering your questions