RAG, Graph RAG & Agentic RAG: How AI Retrieves and Uses Information

A language model does not know your internal documents, and it does not know what happened after it was trained. Retrieval is how you close that gap. Terms covered: - Information Retrieval: finding relevant content from a large collection in response to a query - RAG (Retrieval-Augmented Generation): retrieve relevant documents at the moment a question is asked, then generate a grounded answer from them - Graph RAG: uses a knowledge graph to retrieve, so the system navigates relationships between entities instead of matching keywords - Agentic RAG: treats retrieval as active reasoning. It rewrites queries, routes across sources, checks whether results are useful and retries when they are not. Standard RAG for direct queries. Graph RAG when relationships matter. Agentic RAG when the retrieval itself needs to reason. — AI Fundamentals Glossary | H2O.ai University Full playlist: https://www.youtube.com/playlist?list=PLAWKlIKS-66E Free courses and certifications: https://h2o.ai/university #RAG #GenerativeAI #AgenticAI #AIGlossary #H2Oai