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Industrial AI Podcast

Industrial AI Podcast

Von: Robert Weber / Peter Seeberg
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The Industrial AI Podcast reports weekly on the latest developments in AI and machine learning for the engineering, robotics, automotive, process and automation industries. The podcast features industrial users, scientists, vendors and startups in the field of Industrial AI and machine learning. The podcast is hosted by Peter Seeberg, Industrial AI consultant and Robert Weber, tech journalist.Their mission: Demystify Industrial AI and machine learning, inspire industrial users. The hosts: Peter Seeberg is an Industrial AI and machine learning expert for the manufacturing industry. He worked over 25 years in IT (Intel) and 10 years in Automation. He co-initiated the Industrial Data Intelligence Startup (Softing) where he was responsible for managing machine learning projects in industrial environments. Today he advises companies when it comes to Industrial AI and machine learning. Together with Robert Weber, journalist for industrial topics, he discusses AI and ML applications, standards, and education topics, make or buy decisions as well as regulation for AI in manufacturing.Robert Weber / Peter Seeberg Management & Leadership Wissenschaft Ökonomie
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  • The Navier–Stokes Problem and the Agents

    The Navier–Stokes Problem and the Agents
    Oct 21 2026
    Did OpenAI really solve the Navier–Stokes problem? In this episode, we ask mathematician Gonzalo Caolabora. and AI professor Günter Klambauer what the proof means, why it has been difficult to verify, and whether large language models are discovering mathematics or combining ideas from existing research. We also discuss why AI can excel at problems with verifiable answers, where today’s systems still struggle, and how AI could reshape mathematical research and careers. The big question: as proofs become more automated, what will mathematicians focus on next?
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    27 Min.
  • Time Series: The Most Underrated Domain in Industrial AI

    Time Series: The Most Underrated Domain in Industrial AI
    Oct 14 2026
    We talk with Arburg’s Stefan Lamp and Werner Faulhaber about how AI is changing injection molding—from predicting process stability and quality to helping operators troubleshoot machines. They explain why time-series foundation models matter, where domain expertise makes the difference, and how simulation can shorten the setup of a new process. We also get into the practical questions: Can agents safely recommend machine settings? What holds back cloud connectivity and predictive maintenance? And how should manufacturers measure AI’s real-world value? A grounded look at what’s working now—and what still needs solving.
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    1 Std. und 4 Min.
  • PI and AI

    PI and AI
    Oct 8 2026
    In this episode, I sit down with David Rodriguez to explore how large language models are reshaping the way we interact with industrial data. We dive into the Pi System’s pivotal role across foundational industries and discuss practical strategies for integrating AI—without compromising sensitive operational information. David shares his experience on creating actionable knowledge graphs, running local LLMs, and the evolving relationship between human operators, agents, and data visualization. If you’re curious about the real-world challenges and future promise of AI in manufacturing, this conversation delivers clear insights and actionable takeaways. Join me as we unpack what it takes to move from data to decision—safely, efficiently, and intelligently.
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    40 Min.
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