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Explore how Large Language Models can process and retrieve information across multiple data types including text, images, and other modalities through Multimodal Retrieval-Augmented Generation (RAG) in this 11-minute video. Learn from IBM experts Martin Keen and Josh Spurgin as they demonstrate how vector databases enable LLMs to handle cross-modal capabilities beyond traditional text-only processing. Discover the differences between hybrid and full multimodal approaches, understanding how these advanced techniques transform AI retrieval systems to work seamlessly with diverse data formats. Gain insights into the technical implementation of multimodal RAG systems and their practical applications in modern AI workflows, equipping yourself with knowledge of cutting-edge retrieval augmentation technologies that expand the boundaries of what LLMs can accomplish.
Syllabus
What is Multimodal RAG? Unlocking LLMs with Vector Databases
Taught by
IBM Technology