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Super Data Science: ML & AI Podcast with Jon Krohn

Super Data Science: ML & AI Podcast with Jon Krohn

Jon Krohn 998 Episodes Jul 3, 2026

The Super Data Science Podcast, hosted by Dr. Jon Krohn, covers the latest in machine learning, AI, and data science careers. It features conversations with industry experts and academics, cutting through hype to provide practical insights. Topics range from data collection and analytics to predictive modeling and entrepreneurship, suitable for both beginners and experts.

Episodes

1006: In Case You Missed It in June 2026 Jul 3, 2026 2646 In this month's episode of ICYMI, hear from Chip Huyen, Andrey Kurenkov, Frank Basso and Gilbert Eijkelenboom, discussing why moats are shifting toward physical systems and accumulated product intuition, how Astrocade built vibe coding before the term existed, what it's really like inside a deafeningly loud AI data center, why only 15% of people are technically self-aware and whether AGI requires
1005: People Skills for Analytical Thinkers, with Bestselling Author Gilbert Eijkelenboom Jun 30, 2026 4264 Gilbert Eijkelenboom, bestselling author of People Skills for Analytical Thinkers and founder of the training firm MindSpeaking joins Jon Krohn to make the case that communication is a core data skill, not an optional extra. Gilbert shares the “And, But, Therefore” framework for turning dense analysis into a story stakeholders act on, the research suggesting only around 15% of people are genuinely
1004: Recursive Self-Improvement Jun 26, 2026 600 Could an AI get good enough at AI research to build its own, more capable successor and kick off a compounding loop? That’s recursive self-improvement (RSI) and it surged into the conversation after Anthropic revealed that, as of May 2026, Claude wrote more than 80% of the code merged into its production codebase. In this Five-Minute Friday, Jon Krohn separates today’s AI-assisted coding from true
1003: Building an AI Data Center End to End, with Lightning AI’s Frank Basso Jun 23, 2026 4321 Frank Basso, VP of Infrastructure at Lightning AI, joins Jon Krohn for a rare ground-level tour of the one layer of the AI stack the show had never covered in over a thousand episodes: the physical data center. Frank explains how Lightning AI provisions its 35,000-plus GPUs through hyperscale co-location, why everything new is liquid-to-chip cooled, how GPUs talk to each other over ultra-fast east
1002: Fable 5: The Full Story from Capabilities to Drama Jun 19, 2026 984 Anthropic’s Claude Fable 5 was the most capable AI model ever released to the public and it lasted just three days before the US government forced it offline. Jon Krohn unpacks both halves of the story: what makes Fable 5 special, and why it was pulled. Fable 5 and its locked-down sibling Mythos 5 are the same model separated only by safeguards, in a new “Mythos-class” tier above Opus. Jon covers
1001: How AI Erased My Career Moat, an Episode #1001 Special: Jon Krohn interviewed by Kirill Eremenko Jun 16, 2026 6950 For this episode #1001 special, the tables are turned: SuperDataScience founder Kirill Eremenko takes the host’s chair and Jon Krohn is the guest. They trace Jon Krohn’s path from an Oxford neuroscience PhD to a New York hedge fund to founding the AI consulting firm Y Carrot, why he regrets leaving academia and how tools like Claude Code erased his hard-won technical moat and why that makes skille
1000: Ten Years of the Super Data Science Podcast, with Jon, Kirill and Special Guests Jun 12, 2026 3606 For this landmark 1,000th episode and the show’s 10-year anniversary, host Jon Krohn is joined by SuperDataScience founder Kirill Eremenko, who hosted the podcast for its first 400-plus episodes before handing over the reins. In a first for the show, the episode was recorded live with the audience invited to join on air, alongside surprise appearances from the team, longtime guests, and even Jon’s
999: What's Left to Build When Software Is Free, with Chip Huyen Jun 9, 2026 4544 Chip Huyen joins host Jon Krohn for this milestone episode 999 to talk about her record-breaking book "AI Engineering" the most-read title on the O'Reilly platform last year and how the AI landscape has shifted since her last appearance. Chip breaks down what separates AI engineering from machine learning engineering, makes the case for a "start simple" workflow, gets candid about the real costs o
998: In Case You Missed It in May 2026 Jun 5, 2026 1661 In this month’s episode of ICYMI, Jon Krohn explores how AI agents are simultaneously creating new risks and unlocking powerful new ways of working with data. Hear from Anneka Gupta, Cal Al-Dhubaib, Trevor Manz, Jazmia Henry, Jeremy Mumford, and Jacob Miller, discussing why the old cybersecurity playbook breaks down in the age of Claude Mythos, how the notebook became an AI agent’s working memory,
997: How This Text-to-Video-Game AI Startup Hit 20M Users Jun 2, 2026 4173 Dr. Andrey Kurenkov returns to the show to talk about Astrocade's astronomical growth from pre-alpha to over 20 million engaged users, what it actually takes to build a vibe-coding platform that scales, and how the broader AI landscape has shifted since his last appearance. Andrey shares behind-the-scenes lessons from building B2C user-generated content products, why the real moat is community rat
996: TrueFoundry’s Nikunj Bajaj on How to Get $100M Returns on AI Agent Deployments May 29, 2026 1783 TrueFoundry co-founder and CEO Nikunj Bajaj speaks to Jon Krohn about how enterprises like Nvidia and Siemens are realizing returns of over $100 million from single agent deployments, the AI gateway architecture that makes it possible to connect, observe, and govern agents at scale, and why the familiar advice to “start small” is the wrong way to roll out AI agents inside a large organization. Ad
995: End-to-End Foundation Models for the Energy Industry, with Jazmia Henry May 26, 2026 4155 Jazmia Henry joins Jon Krohn to break down what it actually takes to build end-to-end foundation models for the energy industry. From wrangling decades of handwritten oil-and-gas documents into usable training data, to bespoke tokenizers, reinforcement learning, and inference at scale, Jazmia walks through every stage of the stack. Along the way she explains why reinforcement learning models are "

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