Knowledge graphs add explicit knowledge to GenAI in a format that is easily understood by humans and enhances enterprise machine decisions. They are rapidly emerging as a useful & often necessary component of GenAI, complementing what is otherwise a world of statistical reasoning rooted in inferred concepts. Knowledge graphs make GenAI more dependable, transparent, and secure across a wide variety of use cases, opening the door further for GenAI adoption.

This talk presents a framework for how to think about knowledge graphs for any use case. You will hear up-to-date learnings from this evolving field, including design patterns & examples derived from working with many of the world’s largest organizations. You will come away with an understanding of how knowledge graphs can play the role of left brain to the right brain that is the universe of LLM + vectors– in an enterprise landscape where many use cases call for the use of both hemispheres.