Tech innovation’s dependence on economic systems, trust in technology throughout history, and job displacement through AI: The Dieter Schwartz Associate Professor of AI and work at the University of Oxford, Carl Benedikt Frey, talks to Jon Krohn about his latest book, How Progress Ends, as well as how different economic systems deal with innovation and scaling, dealing with the homogeneity of generative AI output, and how to stay afloat in the new wave of job automation.

This episode is brought to you by the ⁠Dell⁠, by ⁠Intel⁠, by ⁠ODSC, the Open Data Science Conference⁠ and by ⁠Gurobi⁠.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/925⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In this episode you will learn:

(04:00) All about How Progress Ends: Technology, Innovation, and the Fate of Nations

(14:26) The role of weak ties in driving technological innovation

(18:22) How to keep innovating as a big business

(48:05) What we can learn and apply from previous industrial revolutions

(54:33) How workers can try to ‘future-proof’ themselves

MIT lab NANDA (“Networked AI Agents in Decentralized Architecture”) reveals less than promising results for the future of AI adoption in businesses. According to “The GenAI Divide: State of AI in Business 2025”, a whopping 95% of enterprise AI projects “are getting zero return” on their $30-40 billion investment. Jon Krohn takes this Five-Minute Friday to look into why this has happened, with help from a critical response to the report written by Futuriom’s R. Scott Raynovich.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/924⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Graphs, but not as you would expect them: Graph analytics guru Amy Hodler speaks to Jon Krohn about the graph data structure and graph applications, graph algorithms, graph RAG, and graphs as memory systems for AI agents. We can use graphs in a surprising number of ways. Money laundering and fraud, as well as supply-chain crime, leave breadcrumbs at multiple “touch-points” over time, behaviors that graphs are better suited to reveal than rows and tables. Amy sees that most interest in graphs has been in the cybersecurity space. But this work isn’t only restricted to fighting crime! Listen to the episode to hear more case examples and how to get into graph work. 

This episode is brought to you by the Dell, by the Intel, by ODSC, the Open Data Science Conference and by Gurobi.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/923⁠⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In this episode you will learn:

01:49) A brief history of graphs

(10:08) Uncovering fraud with graphs

(28:31) Where graphs are most commonly applied, to date

(34:49) Retrieval augmented generation graphs

(48:04) The future of graphs

Hugo Dozois-Caouette speaks to Jon Krohn about his startup MaintainX and how he secured $254 million in venture capital, reaching a $2.5 billion valuation. MaintainX builds computerized maintenance management systems (CMMS) and enterprise asset management (EAM) software for industrial and manufacturing companies. This "digital clipboard" delivered through web and mobile apps connects machines, work orders, and frontline teams to boost productivity, reduce downtime, and prevent costly breakdowns. The platform captures knowledge from experienced workers and delivers AI-powered insights, with features like MaintainX CoPilot helping teams troubleshoot issues and make faster decisions. Listen to the episode to hear Hugo's perspective on manufacturing gaps that technology can fill, MaintainX's tech stack, and how CMMS platforms address information disconnects that slow down frontline teams.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/922⁠⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Using Windows for AI development and the bleeding edge of NPUs: Shirish Gupta and Ish Shah from Dell Technologies speak to Jon Krohn about the latest products from Dell, the future of neural-processing units (NPUs), and how AI developers can make sound hardware investments. 

This episode is brought to you by the Trainium2, the latest AI chip from AWS, by ODSC, the Open Data Science Conference and by Gurobi.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/921⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In this episode you will learn:

This month’s episode of In Case You Missed It gives us reasons to be cautiously optimistic about the future of large language models (LLMs), with guests discussing what to do about recent reports that found AI agents blackmailed human users when threatened, the importance of post-training LLMs, and the training we have available for data and AI engineers to create robust, secure, and useful AI. Jon Krohn includes clips from his interviews with Akshay Agrawal (Episode 911), Julien Launay (Episode 913), Michelle Yi (Episode 915), and Kirill Eremenko (Episode 917). 

Additional materials: ⁠⁠⁠⁠⁠www.superdatascience.com/920⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

PyTorch, AGI, and the future of alignment research: Aurélien Géron joins Jon Krohn in this live interview to talk about the fourth edition of his bestselling Hands-On Machine Learning as well as what superintelligence makes him hopeful for, as well as what concerns him about machines surpassing human intelligence.

This episode is brought to you by Gurobi and by the Dell AI Factory with NVIDIA⁠

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/919⁠⁠⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In this episode you will learn:

In this Five-Minute Friday, Jon Krohn introduces listeners to CrewAI, an open-source Python framework that can create and manage multi-agent teams. The clue is in the title: CrewAI assembles specialized agents into single “crews” that achieve complex goals between them. CrewAI’s agent teams can also learn and iterate, meaning that after the crew has achieved its goals for the first time, they can refine and tailor their approach to  future goals. 

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/918⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Founder of SuperDataScience, Kirill Eremenko, talks to Jon Krohn about how he found the best tools and approaches to help launch his 8-week AI engineering bootcamp. He breaks down the topics participants cover each week, and he also shares his tips with listeners who might want to start their own tech bootcamp or sign up for SuperDataScience’s September 2025 cohort.

This episode is brought to you by the Dell AI Factory with NVIDIA and by ODSC, the Open Data Science Conference

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/917⁠⁠⁠⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In this episode you will learn:

GPT-5 has just been released, but with not very much fanfare. In this Five-Minute Friday, Jon Krohn asks if GPT-5 deserves the community’s underwhelmed response to its release. He outlines five features of the model and explains why people might be feeling less than enthusiastic in the broader context of LLM development. Which LLMs are leading the way, and which are still playing the game of catch-up?

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/916⁠⁠⁠

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.