Podcast
Super Data Science: ML & AI Podcast with Jon Krohn
Hosted by Jon Krohn · EN
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.
55episodes
Episodes
Newest firstAll episodes
977: Attention, World Models and the Future of AI, with Prof. Kyunghyun Cho
Mar 2401:18:14Tap to summarizeWhat’s going to be the next big step function that blasts us forward in AI capabilities? To find out, Jon Krohn sits down with Professor Kyunghyun Cho, whose 200,000 citations and co-authorship of the first paper on attention place him among the most influential AI researchers in the world. In this episode, Kyunghyun explains why today’s models have already captured most correlations in passive data, making the real challenge about actively choosing which data to collect. He also weighs in on the open debate around world models, whether AI needs high-fidelity, step-by-step imagination or whether a high-level latent representation that lets it skip ahead is sufficient and shares the surprising discovery that 80% of his 200 computer science students had never installed a coding agent. Additional materials: www.superdatascience.com/977 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (06:43) The story behind the attention mechanism (28:43) Sample efficiency and active data collection (39:04) World models and latent planning (49:52) Teaching undergrads with coding agents (58:21) Reranking, multi-stage ranking, and the foundations of RAG
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976: NVIDIA’s Nemotron 3 Super: The Perfect LLM for Multi-Agent Systems
Mar 2000:10:12Tap to summarizeNVIDIA just dropped Nemotron 3 Super, a 120-billion-parameter open-weight model that only activates 12 billion parameters at a time and it’s built for the agentic AI era. In this Five-Minute Friday, Jon Krohn breaks down the model’s hybrid Mamba-Transformer architecture, its million-token context window, and why its combination of frontier-class reasoning with blazing-fast throughput matters for anyone building multi-agent systems. Find out how Nemotron 3 Super claimed the #1 spot on the DeepResearch Bench leaderboards, which companies are already adopting it, and where you can start using it today. Additional materials: www.superdatascience.com/976 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
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975: Unmetered Intelligence is Heralding the Next Renaissance, with Zack Kass
Mar 1701:12:50Tap to summarizeZack Kass speaks to Jon Krohn about his bestselling, tech-positive book, The Next Renaissance, that charts the rapid progress of humanity and the benefits that artificial intelligence will bring to us, as well as why a future where intelligence is a cheap and abundant resource will give humanity an edge. Elsewhere in the show, Zack discusses why it’s important to hold parents, teachers and students accountable for their education, why it is incumbent on us to build a healthier relationship with technology, and his 4 principles for thriving in the age of AI. This episode is brought to you by the Cisco, by Acceldata and by ODSC, the Open Data Science Conference. Additional materials: www.superdatascience.com/975 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (03:14) About Zack Kass’ book, The Next Renaissance (20:18) The importance of literacy skills in the age of AI (28:01) AI in education (41:01) Principles for living in the era of AI
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974: When Will The AI Bubble Burst? How Bad Will It Be?
Mar 1300:13:56Tap to summarizeIn this week’s Five-Minute Friday, Jon Krohn holds the AI bubble up to the light. He points to the deep greyzone found in AI startups like Cluely that are established on dubious ideas (Cluely’s tagline was “cheat on everything”) and funding bluster, as well as the staggering spending by companies on infrastructure and researcher salaries. Listen to the episode to hear about the historical precedents to the AI bubble that go all the way back to the invention of the railway, what to make of current investments in AI, and what you can do about these changes as an AI practitioner. Additional materials: www.superdatascience.com/974 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
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973: AI Systems Performance Engineering, with Chris Fregly
Mar 1001:12:10Tap to summarizeNo one should be manually writing code in 2026, thinks Chris Fregly, Jon Krohn’s guest on this week’s episode. In this interview about Chris’ latest book, AI Systems Performance Engineering, he explains why it’s so important to consider memory bandwidth when evaluating GPU performance, that understanding the full hardware software stack is the most valuable skill for anyone working in AI development, and which shortcuts we still shouldn’t ever take when writing code, even though we might be outsourcing a great deal to generative AI. This episode is brought to you by the Cisco, by Acceldata and by ODSC, the Open Data Science Conference. Additional materials: www.superdatascience.com/973 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (03:39) Why Chris wrote AI Systems Performance Engineering (21:39) Essential coding metrics (37:24) The importance of inference when coding (42:11) How to manage workflows while using AI agents (51:37) Where and how to invest in the AI market
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972: In Case You Missed It in February 2026
Mar 600:26:44Tap to summarizeJon Krohn recaps the month of February in this episode of In Case You Missed It. Across four interviews with Will Falcon (Episode 965), Tom Griffiths (Episode 969), Antje Barth (Episode 963), and Praveen Murugesan (Episode 967), Jon questions the brains behind some of the AI industry’s most innovative companies about launching a startup, developing a popular product, what artificial intelligence can still learn from human intelligence, and how AI might finally start to think on its own. Additional materials: www.superdatascience.com/972 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
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971: 90% of The World’s Data is Private; Lin Qiao’s Fireworks AI is Unlocking It
Mar 300:59:47Tap to summarizeLin Qiao, CEO of Fireworks AI, talks to Jon Krohn about how she builds effective models quickly, why coding agents can perform at the level of a junior engineer, and what she attributes to the success of Fireworks AI: True to its name, the company exploded into the AI industry with over $300 million secured in venture capital, as well as netting a further $250 million Series C funding. For Lin, many enterprises miss out by not being familiar with open models. Open models give a lot of control to the user, offering customizability and at a much lower price point. Listen to hear how Fireworks AI helps companies continue to save money through AI. This episode is brought to you by the Dell, by Intel, by Cisco and by Acceldata. Additional materials: www.superdatascience.com/971 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (01:19) All about Fireworks AI (24:16) Why companies need to take notice of open models (33:05) The commercial viability of slow-reasoning models (38:51) Fireworks AI’s approach to model performance evaluations
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970: The “100x Engineer”: How to Be One, But Should You?
Feb 2700:14:37Tap to summarizeWorking with code-gen models and Claude Code: In this Five-Minute Friday, Jon Krohn addresses how AI superstars like Andrej Karpathy are using AI agents in their coding work, the outlook for code-gen in 2026, and how you can get started. Hear about Karpathy’s work as well as the soaring success of Peter Steinberger and how he managed to surpass the GitHub commit rate of teams as an individual working with AI agents. Additional materials: www.superdatascience.com/970 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
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969: The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths
Feb 2401:11:15Tap to summarizePrinceton Professor Tom Griffiths talks to Jon Krohn about his new book, The Laws of Thought, which grapples with the mathematical models behind biological and artificial intelligence, and what makes the human brain so fascinating for psychologists and computer scientists to study. In this episode, he details how the mathematical principles governing the external world can also be used to explore cognitive science, or “the internal world.” This episode is brought to you by the Dell, by Intel, by Cisco and by Acceldata. Additional materials: www.superdatascience.com/969 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (01:18) Tom Griffiths’ current research (21:23) On mathematical inference in LLMs (35:19) How to engineer inductive bias (52:00) How to model curiosity into AI systems
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968: Is AI Automating Away All Coding Jobs?
Feb 2000:14:56Tap to summarizeNow that AI agents can develop new apps from product development to delivery, do AI developers have reason to worry about their careers? Podcast host Jon Krohn addresses the stark predictions that AI could “eliminate half of all entry-level white-collar jobs” by going back to the data. Find out why the numbers show a very different picture, which in-demand occupations have increased by 40% since late 2022, and Jon’s advice on why technical professionals shouldn’t panic in this latest Five-Minute Friday. Additional materials: www.superdatascience.com/968 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
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