Optimize RAG with AI Agents and Vector Databases

Learn how to enhance Retrieval Augmented Generation (RAG) systems by combining AI agents with vector databases in this 33-minute tutorial from IBM. David Levy demonstrates techniques for improving query accuracy, streamlining context retrieval, and enhancing response generation to solve the common problem of irrelevant data in RAG implementations. Discover practical approaches to building smarter AI pipelines through agentic research that can tackle complex challenges more effectively. The tutorial includes code examples that viewers can explore to implement these optimization strategies in their own projects.