In 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 [https://www.superdatascience.com/974]⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

974: When Will The AI Bubble Burst? How Bad Will It Be?

No 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 [https://agntcy.org/], by Acceldata [https://www.acceldata.io/free-trial] and by ⁠ODSC, the Open Data Science Conference [https://odsc.ai/]⁠.



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/973⁠ [https://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

973: AI Systems Performance Engineering, with Chris Fregly

Jon 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 [https://www.superdatascience.com/972]⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

972: In Case You Missed It in February 2026

Lin 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 ⁠ [https://aws.amazon.com/ai/machine-learning/trainium/]⁠⁠⁠Dell⁠⁠⁠ [http://www.dell.com/dellproaistudio], by⁠ ⁠⁠Intel⁠⁠⁠ [https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand], by ⁠Cisco⁠ [https://agntcy.org/] and by ⁠Acceldata⁠ [https://www.acceldata.io/free-trial].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/971 [https://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

971: 90% of The World’s Data is Private; Lin Qiao’s Fireworks AI is Unlocking It

Working 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 [https://www.superdatascience.com/970]⁠⁠⁠⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

970: The “100x Engineer”: How to Be One, But Should You?

Princeton 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 https://aws.amazon.com/ai/machine-learning/trainium/⁠⁠Dell⁠⁠ [http://www.dell.com/dellproaistudio], by ⁠⁠Intel⁠⁠ [https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand], by Cisco [https://agntcy.org/] and by Acceldata [https://www.acceldata.io/free-trial].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/969⁠⁠⁠⁠⁠⁠ [https://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

969: The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths

Now 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 [https://www.superdatascience.com/968]⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

968: Is AI Automating Away All Coding Jobs?

VP of Engineering at Samsara Praveen Murugesan talks to Jon Krohn about processing 20 trillion data points covering 90 billion miles across private and public sectors, how the company helps truckers who operate long hours and travel for long stretches without cellphone signal, and who they’re looking to hire to help this agile startup keep on developing high-impact solutions for real-world problems. And, if you’re looking to work for the company, there’s no better time to apply, and you’ll want to listen to the end of the show to hear exactly what Praveen looks for in new hires.


This episode is brought to you by the https://aws.amazon.com/ai/machine-learning/trainium/⁠⁠Dell⁠⁠ [http://www.dell.com/dellproaistudio], by ⁠⁠Intel⁠⁠ [https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand], by Acceldata [https://www.acceldata.io/free-trial] and by the ODSC, the Open Data Science Conference [https://odsc.ai/]⁠.



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/967⁠⁠⁠⁠⁠ [https://www.superdatascience.com/967]⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.



In this episode you will learn:

 * (01:01) The challenges of working with logistics data 

 * (16:43) Operating Edge AI in logistics and construction sectors

 * (28:43) How quantum computing might redefine logistics

 * (40:09) The real cost of swapping human heuristics for algorithmic planning

 * (44:45) How to get a job at Samsara

967: AI for the Physical World, with Samsara's Praveen Murugesan

Jon Krohn gives Five-Minute Friday listeners all the details about the new social network causing a stir, Moltbook. What makes Moltbook so unique is that this is the first network designed just for AI agents. It’s an exclusive club, only its alleged 1.5 million registered agents can post, comment, and upvote, but we can watch this real-world experiment in agent ecology from the sidelines. Listen to the episode to hear the fascinating, if disturbing, story of Moltbook’s swift turn into facilitating a digital theocracy and forms of government, and whether this development is a sign of an approaching singularity or rather AI continuing to ape human thought and turn it into slop. 


Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/966⁠ [https://www.superdatascience.com/966]⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

966: The Moltbook Phenomenon: OpenClaw Unleashed

CEO of Lightning AI Will Falcon speaks to podcast host and Lightning AI fellow Jon Krohn about the company’s merger with Voltage Park, and why Will has named it the “full-stack AI neo-cloud for enterprises and frontier labs”. Lightning AI’s offer is a secure, flexible, and collaborative environment that can run on the cloud, all essentials for early-stage startups. Listen to the episode to hear Will Falcon discuss Lightning AI Studio, founding PyTorch Lightning, and how he came to found his AI company.

This episode is brought to you by the http://www.dell.com/dellproaistudioDell⁠⁠, by ⁠⁠Intel⁠⁠ [https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand], by Fabi [https://www.fabi.ai/] and by Cisco [https://agntcy.org/].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/965⁠⁠⁠⁠ [https://www.superdatascience.com/965]⁠⁠⁠⁠⁠⁠



Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.



In this episode you will learn:

 * (02:20) Lightning AI’s merger with Voltage Park
 * (20:54) About neo-clouds
 * (43:51) How Will founded Lightning AI
 * (54:48) Current gaps in the AI in workplace

965: From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

The Super Data Science podcast with Jon Krohn brings you the latest and most
important machine learning, artificial intelligence, and broader data-world
topics from across both academia and industry. As the quantity of data on our
planet doubles every couple of years and this trend is set to continue for
decades to come, there's an unprecedented opportunity for you to make an
enormous impact in your lifetime. 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, and commercialization − everything you
need to crush it with data science.

Jon Krohn

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