AI predictions, and how to act on them: Data Science Strategist at Gurobi, Jerry Yurchisin, speaks to Jon Krohn about how mathematical optimization helps enterprises automate decisions for business success and where to find the resources to make it happen.  


This episode is brought to you by the ⁠ODSC, the Open Data Science Conference [http://odsc.ai/], by Fabi [http://fabi.ai/], by ⁠Dell⁠ [http://www.dell.com/dellproaistudio], and by ⁠Intel⁠ [https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/931⁠⁠⁠ [https://www.superdatascience.com/931]⁠



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



In this episode you will learn:

 * (02:34) What mathematical optimization is
 * (13:58) How to get started with mathematical optimization
 * (45:56) Gurobi’s use cases
 * (56:29) Quantum computing and mathematical optimization  

931: Boost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin

Jon Krohn’s highlights from this month of interviews focus on ways to future-proof your career, looking at the hardware that will get you the most mileage, the emerging roles that are well worth a look, and the developments in AI that will endure in a field constantly testing the durability of its own breakthroughs.


Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/930⁠⁠⁠⁠⁠⁠⁠⁠ [https://www.superdatascience.com/930]



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

 930: In Case You Missed It in September 2025  

Breaking news: Jon Krohn welcomes Adrian Kosowski to the show to talk about the groundbreaking research happening at Pathway. Adrian and his team demonstrate how they have brought attention in AI closer to the way the brain functions, creating, in essence, a “massively parallel system of [artificial] neurons” that communicate with one another and exhibit properties similar to natural neurons. The goal is to move beyond the current limitations of transformers, where reasoning can be generalized across more complex and extended reasoning patterns, approximating a more human-like approach to problem-solving.


This episode is brought to you by the Trainium2, the latest AI chip from AWS [https://aws.amazon.com/ai/machine-learning/trainium/], by ⁠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 and ⁠Gurobi⁠ [http://gurobi.com/learn].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/929⁠⁠ [https://www.superdatascience.com/929]⁠



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



In this episode you will learn:

 * (01:27) Pathway’s ground-breaking new biologically inspired architecture
 * (20:40) Limitless context windows
 * (34:39) BDH architecture as positive space
 * (53:11) Building multilingual models
 * (1:01:07) How to access the BDH architecture

 929: Dragon Hatchling: The Missing Link Between Transformers and the Brain, with Adrian Kosowski

Prompt injections, malicious code, and AI agents: In this week’s Five-Minute Friday, Jon Krohn looks into the current security weaknesses found in AI systems. A structural vulnerability that The Economist dubs a “lethal trifecta” could cause havoc for AI users, unless we take the necessary steps to contain our systems. 


Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/928⁠⁠⁠⁠⁠⁠⁠ [https://www.superdatascience.com/928]



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

928: The “Lethal Trifecta”: Can AI Agents Ever Be Safe?

Earlier this year, David Loker joined CodeRabbit as their Director of AI. As more people come to write code with the help of large language models, David believes CodeRabbit will become a helpful assistant for code reviewing and pull requests. He tells Jon Krohn how CodeRabbit assists developers with real-time feedback, as well as the reality of vibe coding, the optimization challenges of agentic AI, and other pressing questions in AI and tech. 


This episode is brought to you by the ⁠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 ⁠Gurobi⁠ [http://gurobi.com/learn] and by ⁠ODSC, the Open Data Science Conference⁠ [http://odsc.ai/].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/927⁠ [https://www.superdatascience.com/927]⁠



In this episode you will learn:

 * (01:26) How CodeRabbit helps with coding   

 * (17:30) Context engineering in context    

 * (40:40) How CodeRabbit keeps data secure     

 * (46:10) David’s thoughts on “vibe coding”                             

 * (1:03:04) If machines will ever be truly creative 

927: Automating Code Review with AI, feat. CodeRabbit’s David Loker

In this Five-Minute Friday, Jon Krohn explores how AI is reshaping the legal industry. He investigates how AI tools are helping lawyers make conclusions faster, how paralegals are being retrained, and the latest in-demand role in law (hint: It concerns AI). Listen to hear how Harvey AI and Thomson Reuters’ CoCounsel are using AI to help lawyers get ahead.


Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/926⁠⁠⁠⁠⁠⁠ [https://www.superdatascience.com/926]



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

926: AI is Disrupting the Legal Industry: Are Paralegals Doomed?

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 [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 ⁠ODSC, the Open Data Science Conference⁠ [http://odsc.ai/] and by ⁠Gurobi⁠ [http://gurobi.com/learn].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/925 [https://www.superdatascience.com/925]⁠⁠⁠⁠⁠



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

925: AI, Automation and the Future of Work, with Oxford’s Prof. Carl Benedikt Frey

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 [https://www.superdatascience.com/924]



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

924: 95% of Enterprise AI Projects Fail (Per MIT Research)

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 [http://www.dell.com/dellproaistudio], by the Intel [https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand], by ODSC, the Open Data Science Conference [http://odsc.ai/] and by Gurobi [http://gurobi.com/learn].



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/923⁠ [https://www.superdatascience.com/923]⁠⁠⁠⁠⁠



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

923: Graph Algorithms, GraphRAG and Causal Graphs, with Graph Guru Amy Hodler

Hugo Dozois-Caouette speaks to Jon Krohn about his startup MaintainX and how he secured $100 million in venture capital. MaintainX manages and maintains computerized maintenance management systems (CMSs), or work-execution software, for the industrial and manufacturing industries. This “digitized version of a clipboard” with the help of web and mobile applications, provide a list of procedures, guidelines and regulations to help increase worker productivity and give a company the data-driven insights it needs to refine its processes. Listen to the episode to hear Hugo’s thoughts on the gaps in the manufacturing industry that technology can fill, the tech stack used by MaintainX, and the discrepancy of information in manufacturing environments.



Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/922⁠ [https://www.superdatascience.com/922]⁠⁠⁠⁠⁠



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

922: AI for Manufacturing and Industry, with Hugo Dozois-Caouette

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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