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    Business

    Super Data Science: ML & AI Podcast with Jon Krohn

    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.

    Advertise

    Copyright: © 2024 Super Data Science: ML & AI Podcast with Jon Krohn

    • Apple Podcasts
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    Latest Episodes:
    965: From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story Feb 10, 2026
    Show notes

    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 Dell⁠⁠, by ⁠⁠Intel⁠⁠, by Fabi and by Cisco.


    Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠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

    964: In Case You Missed It in January 2026 Feb 06, 2026
    Show notes

    In this first of the year ICYMI episode, Jon Krohn selects his favorite moments from January’s SuperDataScience interviews. Listen to why incentivizing workers is the best way to get them to disclose their use of AI tools and pave the way for an AI-forward future, how AI continues to mimic human development in its own evolution, the importance of evaluation in building AI systems, and how to keep your best employees (and also: how to know your value) with guests Sadie St. Lawrence, Ashwin Rajeeva, Sinan Ozdemir, Vijoy Pandey, and Ethan Mollick.


    Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/964⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠


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


    963: Reinforcement Learning for Agents, with Amazon AGI Labs’ Antje Barth Feb 03, 2026
    Show notes

    Bestselling author and Gen AI instructor Antje Barth talks to Jon Krohn about her work at Amazon’s AGI Labs and their newest product Nova Act, as well as where we will see the most success with AI agents and how AI developers can reap those rewards.


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


    Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/963⁠⁠⁠⁠⁠⁠⁠⁠⁠


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


    In this episode you will learn:

    • (01:23) Amazon’s latest product, Nova Act
    • (11:05) How Nova Act tests reliability
    • (24:01) Where Amazon’s 1000s of gen AI deployments succeed
    • (31:32) How Nova Act maintains its security
    • (36:32) The increasing value of agentic AI developers

    962: Wharton Prof Ethan Mollick on Why Your AI Strategy Is Already Obsolete Jan 30, 2026
    Show notes

    Bestselling author of Co-Intelligence: Living and Working with AI Ethan Mollick speaks to Jon Krohn about just how much US firms have to gain from a willingness to adopt and experiment with AI, as well as the reality behind AI use among employees and the frontier models set to support them even further.


    Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/962⁠⁠⁠


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


    961: Distributed Artificial Superintelligence, with Dr. Vijoy Pandey Jan 27, 2026
    Show notes

    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 natalie@superdatascience.com 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

    960: In Case You Missed It in December 2025 Jan 23, 2026
    Show notes

    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 natalie@superdatascience.com for sponsorship information.


    959: Building Agents 101: Design Patterns, Evals and Optimization (with Sinan Ozdemir) Jan 20, 2026
    Show notes

    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 natalie@superdatascience.com 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

    958: Without Trusted Context, Agents are Stupid (featuring Salesforce’s Rahul Auradkar) Jan 16, 2026
    Show notes

    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 natalie@superdatascience.com for sponsorship information.


    957: How AI Agents Are Automating Enterprise Data Operations, with Ashwin Rajeeva Jan 13, 2026
    Show notes

    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 natalie@superdatascience.com 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

    956: From Agent Demo to Enterprise Product (with Ease!) feat. Salesforce’s Tyler Carlson Jan 09, 2026
    Show notes

    #Sponsored SVP, Head of Product for Salesforce’s AppExchange & Ecosystem, Tyler Carlson, talks to Jon Krohn about taking AI agents from prototype to enterprise-grade production with the Agentforce 360 Platform. Though we may now have plenty of tools to build demos for AI agents, most teams still struggle to turn early prototypes into secure and scalable products. With Salesforce’s Agentforce 360 Platform, users can build customer-focused agentic applications with a multi-LLM planner service for reasoning and logic, as well as a new scripting language for deterministic control over how agents interact with the contextual layer of the Salesforce data model. Learn how Salesforce’s WYSIWYG schema builder helps customers build fully functional applications with low- and pro-code capabilities, the common mistakes that innovators make when moving from prototype to production, and whether AI agents might replace non-agentic AI applications in this Feature Friday.


    Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/956⁠⁠⁠⁠⁠⁠⁠


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


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