Fresh off a high-profile appearance on CNBC! Jure Leskovec, Chief Scientist at Kumo and a Stanford Professor who's fundamentally reshaped how we understand networks {Replay}

Send us Fan Mail Fresh off a high-profile appearance on CNBC’s Worldwide Exchange discussing how AI will move beyond chatbots to autonomous agents that reshape jobs and productivity! Replay this episode where Jure digs into why structured data is still lagging behind the AI revolution and what comes next for predictive AI on relational data. Data’s everywhere, but so often it feels… stuck. Joining us today is Jure Leskovec , Chief Scientist at Kumo and a Stanford Professor who's fundamentally reshaped how we understand networks—from Pinterest's recommendations to tracking the spread of disease. Jure was just on CNBC , and now he’s back on the show to dive even deeper into how structured data is lagging behind the AI revolution. We’ll explore how techniques like Graph Neural Networks are finally unlocking its potential, and how this all plays out in real-world applications. 00:57 Meet Jure Leskovec 02:31 Knowing When to Move On 04:01 Academia versus Industry 07:30 Learnings from Pinterest 10:28 The Kumo Pitch 17:57 The Secret Sauce 25:51 Monetization 27:12 Only the Enterprise? 29:49 The Sandbox to Try Before Buy 31:42 The Best Use Cases 35:00 Summarizing 37:38 Predicting AI 40:15 What's True and No One Agrees 41:19 Learning LinkedIn: Website: CNBC appearance: Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

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Fresh off a high-profile appearance on CNBC! Jure Leskovec, Chief Scientist at Kumo and a Stanford Professor who's fundamentally reshaped how we understand networks {Replay} is an episode from IBM Analytics Insights Podcasts by Making Data Simple.

This episode is 42:34 long.

This episode was published on Dec 31, 2025.

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