Super Data Science: ML & AI Podcast with Jon Krohn

Dr. Vijoy Pandey returns to the show to talk to Jon Krohn about Cisco’s work to advance medicine and mitigate the impact of climate change with distributed artificial super-intelligence. Dr. Vijoy Pandey believes in a future where humans and AI agents work together to tackle our biggest challenges. For this to happen, we will need to have multi-agent systems and open-source platforms that let agents work together, avoiding the phenomenon of AI agents being “isolated geniuses” unable to collaborate. He elaborates on what Cisco is doing to close this gap.

This episode is brought to you by the⁠ ⁠⁠Dell⁠⁠⁠, by⁠ ⁠⁠Intel⁠⁠⁠, by ⁠Fabi⁠ and by ⁠⁠⁠⁠Scaylor⁠.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/961⁠⁠⁠⁠⁠⁠⁠⁠

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

In this episode you will learn:

(03:55) A definition of artificial super-intelligence

(14:03) Distributed learning through Cisco’s Outshift

(21:29) The semantic protocols for sharing intent in a distributed artificial super-intelligence framework

(37:44) The cognitive memory fabric of the distributed artificial super-intelligence framework

(46:24) Using cognitive engines as part of the distributed artificial super-intelligence framework

For 2026’s first episode of In Case You Missed It (ICYMI), Jon Krohn selects 6 clips from December for a wide-ranging look at the current state of AI in business and beyond. Hear from Joel Beasley (Episode 945), Jeff Li (Episode 947), Sandy Pentland (Episode 949), Josh Clemm (Episode 951), Penelope LaFeuille (Episode 952), and John Roese (Episode 953) on ensuring your AI systems get adopted and succeed in their goals, interesting ways to use AI for standup comedy routines, and more.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/960⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

AI entrepreneur and bestselling author Sinan Ozdemir speaks to Jon Krohn about the practical differences between agentic AI and AI workflows, why evaluating accuracy on its own won’t tell you enough about AI models, and more about his latest book Building Agentic AI. 

This episode is brought to you by the ⁠⁠Dell⁠⁠, by ⁠⁠Intel⁠⁠, by Fabi and by Cisco.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/959⁠⁠⁠⁠⁠⁠⁠

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

In this episode you will learn:

(04:57) Exploring the differences between workflows and agents

(17:03) How to work out parameter count for a given task

(25:26) The best way to evaluate LLMs

(33:12) How to run hybrid workflow + agentic projects effectively

In this #sponsored Feature Friday episode, Salesforce’s Rahul Auradkar speaks to Jon Krohn about the company’s unified data engine and how its acquisition of Informatica provides the missing context layer for AI models and agents. Hear how Salesforce’s Data 360 helps customers to get accurate and insightful information about their business, and what AI models need to benefit a company’s bottom line (hint: it’s not only large amounts of data!)

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/958⁠⁠⁠⁠⁠⁠⁠

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

AI agents, data lakes, and managing data sprawl: Ashwin Rajeeva, cofounder and CTO of Acceldata, speaks to Jon Krohn about how the agentic data management startup raised over $100 million in venture capital to expand its business in automating data quality assurance as well as cataloguing and pipeline maintenance across enterprise environments. Acceldata utilizes multiple agents to solve enterprise-grade questions with company data. It also uses autonomous data pipelines that can detect and fix issues without human intervention, and the platform’s agentic data management system ADM also lets humans stay in the loop wherever needed. 

This episode is brought to you by the ⁠⁠Dell⁠⁠, by ⁠⁠Intel⁠⁠, by Fabi and by Cisco.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/957⁠⁠⁠⁠⁠⁠

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

In this episode you will learn:

(03:25) About Acceldata and xLake

(15:03) Autonomous data pipelines

(21:02) How and when to keep humans in the AI loop

(27:43) How Acceldata solves ‘data sprawl’

(31:53) Habits of successful tech leaders