Juan Sequeda
Knowledge graph technology has been around for decades. The benefits so far accruing to only a few big enterprises and tech companies.
Juan Sequeda sees large language models as a critical enabler for the broader adoption of KGs. With their capacity to accelerate the acquisition and use of valuable business knowledge, LLMs offer a path to a better return on your enterprise's investment in semantics.
We talked about:
his work data.world as Principal scientist and the head of the AI lab at data.world
the new discovery and knowledge-acquisition capabilities that LLMs give knowledge engineers
a variety of business benefits that unfold from these new capabilities
the payoff of investing in semantics and knowledge: "one plus one is greater than two"
how semantic understanding and the move from a data-first world to a knowledge-first world helps businesses make better decisions and become more efficient
the pendulum swings in the history of the development of AI and knowledge systems
his research with Dean Allemang on how knowledge graphs can help LLMs improve the accuracy of answers of questions posed to enterprise relational databases
the role of industry benchmarks in understanding the return on your invest in semantics
the importance of treating semantics as a first-class citizen
how business leaders can recognize and take advantage of the semantics and knowledge work that is already happening in their organizations
Juan's bio
Juan Sequeda is the Principal Scientist and Head of the AI Lab at data.world. He holds a PhD in Computer Science from The University of Texas at Austin. Juan’s research and industry work has been on the intersection of data and AI, with the goal to reliably create knowledge from inscrutable data, specifically designing and building Knowledge Graph for enterprise data and metadata management. Juan is the co-author of the book “Designing and Building Enterprise Knowledge Graph” and the co-host of Catalog and Cocktails, an honest, no-bs, non-salesy data podcast.
Connect with Juan online
LinkedIn
Catalog & Cocktails podcast
Video
Here’s the video version of our conversation:
https://youtu.be/xZq12K7GvB8
Podcast intro transcript
This is the Knowledge Graph Insights podcast, episode number 19. The AI pendulum has been swinging back and forth for many decades. Juan Sequeda argues that we're now at a point in the advancement of AI technology where businesses can fully reap its long-promised benefits. The key is a semantic understanding of your business, captured in a knowledge graph. Juan sees large language models as a critical enabler of this capability, in particular the ability of LLMs to accelerate the acquisition and use of valuable business knowledge.
Interview transcript
Larry:
Hi, everyone. Welcome to episode number 19 of the Knowledge Graph Insights podcast. I am really delighted today to welcome to the show Juan Sequeda. Juan is the principal scientist and the head of the AI lab at data.world. He's also the co-host of the really good popular podcast, Catalog & Cocktails. So welcome, Juan. Tell the folks a little bit more about what you're up to these days.
Juan:
Hey, very great. Thank you so much for having me. Great to chat with you. So what am I up to now these days? Obviously, knowledge graphs is something that is my entire life of what I've been doing. This was before it was called knowledge graphs. I would say that the last year, year-and-a-half, almost two years now, I would say, is been understanding the relationship between knowledge graphs and LLMs. If people have been following our work, what we've been doing a lot has been on understanding how to use knowledge graphs to increase the accuracy for your chat with your data system, so be able to do question answering over your structured SQL databases and how knowledge graphs increase the accuracy of that. So we can chat about that.
Juan:
