Super Data Science: ML & AI Podcast with Jon Krohn

Jon Krohn

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

  1. 2d ago

    1039: AI for Real Estate, Walkable Cities and Climate Action, with Prof. John Renne

    In Episode #1039, Prof. John Renne (Professor of Real Estate and Urban Planning at Tulane University) joins Jon Krohn to describe what happens when a tenured full professor goes back to school for a master’s in AI. John is a world-leading expert on transit-oriented development who spent decades pushing the limits of Excel and SPSS; learning Python and then vibe coding has let him scale that research by orders of magnitude, from 4,500 American train stations to more than 110,000 worldwide. In this episode, he traces how walkable communities went from academic heresy to the most profitable form of real estate development, explains how computer vision can now put a number on how attractive a street is, describes the undergraduate course he and Jon co-teach at Tulane, and makes the case for AI-led oral exams over AI detectors. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1039⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (00:04:08) Why a tenured professor went back for a master’s in AI (00:25:34) What transit-oriented development actually is (00:45:27) Teaching AI to rate a street (01:08:29) AI-led oral exams instead of AI detectors

    1039: AI for Real Estate, Walkable Cities and Climate Action, with Prof. John Renne

  2. 6d ago

    1038: AI’s Contentious Math Breakthroughs

    In Episode #1038, Jon Krohn unpacks the remarkable and remarkably contentious run of mathematical results AI has produced in recent weeks, led by OpenAI’s claim to have cracked part of a million-dollar Millennium Prize problem. He lays out what was actually proved, the three big caveats that temper it, the chaotic bulk release of 722 manuscripts that followed, and why 25 Fields medallists are alarmed. His throughline for anyone building with AI: when generation gets cheap, verification becomes the bottleneck. Additional materials:⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1038⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

    1038: AI’s Contentious Math Breakthroughs

  3. Oct 20

    1037: Recursive Self-Improvement: The Eureka Machine, with Dr. Richard Socher

    In Episode #1037, Dr. Richard Socher (CEO and Co-Founder of Recursive) joins Jon Krohn to make the case for automating the scientific method itself. Richard’s startup came out of stealth this year with over half a billion dollars raised to build recursively self-improving superintelligence, and his new book, The Eureka Machine, is already a national bestseller. He also co-founded You.com and the venture firm AIX Ventures, was chief scientist at Salesforce, taught the first university course anywhere on neural networks for NLP, and helped build the ImageNet dataset. In this episode, he traces how AI keeps replacing hand-crafted expertise with scale, lays out the four pillars of his Eureka Machine, argues that hallucinations can be a feature for science, explains why recursive self-improvement within a year or two still rules out an overnight takeoff, and names the software and jobs he expects to endure. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1037⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (00:02:40) What Recursive is automating, and the two forms of RSI (00:19:59) The four pillars of the Eureka Machine (00:29:20) Turning sciences into engineering disciplines (00:39:28) Why RSI does not mean an overnight takeoff (00:56:05) Constructive optimism, and the future as a construction game

    1037: Recursive Self-Improvement: The Eureka Machine, with Dr. Richard Socher

  4. Oct 16

    1036: Is AI Holding Kids Back from Learning?

    In Episode #1036, Jon Krohn digs into the question parents and teachers keep asking: does AI stop children from learning? Drawing on a wave of new studies, he shows the answer turns entirely on how AI is used, as a shortcut that outsources the thinking, or as a tutor that explains and gives feedback. Along the way: a 30,000-student natural experiment in China, a striking tutoring result from Turkey, and three practical takeaways that apply just as much to adults using AI at work. Additional materials:⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1036⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

    1036: Is AI Holding Kids Back from Learning?

  5. Oct 13

    1035: Workslop, Glass Cliffs and Inviting Your Fears to Tea, with Carly Taylor

    In Episode #1035, Carly Taylor (Founder of Rebel Data Science) returns to join Jon Krohn for a wide-ranging conversation about leading engineering teams when the ground keeps moving. Carly shipped nine Call of Duty titles in roughly five years at Activision, where she led game security, and has since been a director of engineering at Microsoft and Field CTO for gaming at Databricks. She is also one of the most entertaining people in data on LinkedIn, where more than 200,000 people follow posts she cheerfully calls unhinged. In this episode, she explains why obsessing over the future produces analysis paralysis, which fundamentals never change, how to tell AI slop from AI used well, what the Buddhist practice of inviting Mara to tea has to do with public speaking, and what the glass cliff means for women being promoted into leadership. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1035⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (00:04:07) The mindsets that still work in 2026 (00:23:25) Why AI slop breaks a social contract (00:28:49) Exploring versus grinding in a career (00:54:37) The glass cliff for women in leadership

    1035: Workslop, Glass Cliffs and Inviting Your Fears to Tea, with Carly Taylor

  6. Oct 9

    1034: In Case You Missed It in September 2026

    In ICYMI Episode #1034, Jon Krohn moves from what sits underneath AI systems to what it takes to live with them every day. Hear from Aishwarya Srinivasan, Luis Serrano, Katie Malone, Ish Shah and Dilani Kahawala, discussing why the bottleneck in shipping software has moved from execution to judgment, how a physicist recast attention in transformers as words bending space, why years of managing people may be the best preparation for managing AI agents, how one weekend side project burned through billions of tokens and which three problems are hardest to solve when a product has no user interface and never stops running. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1034⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (00:57) Agentic AI Skills That Matter Now (10:51) Word Gravity: How Transformers Bend Space (17:45) How AI Brought a Podcast Back From the Dead (27:39) Tokenomics: Why Your Agentic AI Bill Is Exploding (and How to Fix It) (34:28) Building an Always-On AI Agent for Busy Parents

    1034: In Case You Missed It in September 2026

  7. Oct 6

    1033: Workslop: The Hidden Cost of AI-Generated Work, with Prof. Jeff Hancock and Dr. Kate Niederhoffer

    In Episode #1033, Prof. Jeff Hancock (Professor of Communication at Stanford) and Dr. Kate Niederhoffer (Chief Scientist at BetterUp) join Jon Krohn to explain the hidden cost of AI-generated work. A year ago they coined "workslop" in a Harvard Business Review article that went viral and landed the term among Merriam-Webster’s words of the year: content that masquerades as real work but quietly shifts the burden onto whoever receives it. Their research finds that 40% of workers have been sent workslop and 53% admit to producing it, at a cost running to millions of dollars a year for a large organisation. In this episode, they separate workslop from ordinary sloppy work, name the organisational conditions that produce it, introduce their newer concept of relation slipping, and make the case that augmenting people with AI beats automating them away. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.superdatascience.com/1033⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (00:04:03) What separates workslop from ordinary sloppy work (00:16:21) The organisational conditions that produce workslop (00:41:50) The pilot mindset, and using AI relationally (00:56:21) Jeff on the deepfake case and what it taught him about trust

    1033: Workslop: The Hidden Cost of AI-Generated Work, with Prof. Jeff Hancock and Dr. Kate Niederhoffer

  8. Oct 2

    1032: Agents Need 10x More Data Than Humans, with Salesforce’s CDO Michael Andrew

    During their #sponsored discussion, Chief Data Officer at Salesforce Michael Andrew talks to Jon Krohn about what changes for a data team when its customers are AI agents as well as people. Listen to the episode to hear Michael Andrew talk about why agents need ten times more trusted data than humans, how Salesforce untrapped its own customer data with Data 360 and what practitioners should be learning to stay effective in the agentic era! Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1032⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.⁠⁠⁠ In this episode you will learn: (02:32) How the CDO role changes when agents are customers (06:18) Why agents need ten times more data than humans (09:06) How Salesforce untrapped its own customer data (21:36) What practitioners should be learning for the agentic era

    1032: Agents Need 10x More Data Than Humans, with Salesforce’s CDO Michael Andrew
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The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

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