
Industrial AI Podcast
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, scientis...
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On the show
- Dr. Ferri Abolhassan1 ep
- Dr. Christian Heining1 ep
- Bernard1 ep
Also: Jonas Messner, Marcel Meyer, Tanmay Aggarwal, Tobias, Jakub, Georg Katzlinger, Steven Yates, Davy Demeyer, Scott Duncan, Stefan Suwelack, Levente Zolyomi, Jan Seyler, Werner Reichelt, Boris Scharinger, Ricardo Mariani, Jakub Tomczak, Doudou BA
Audience Interest
Podcast Focus
Publishing Consistency
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Most discussed topics
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Total monthly reach
Based on 1 signal.
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By chart position
- 🇩🇪Germany · TechnologyHOME#158599 to 3.2K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
599 to 3.2K🎙 Biweekly cadence·351 episodes·Last published 3d ago - Monthly Reach
Unique listeners across all episodes (30 days)
856 to 4.5K🇩🇪100% - Active Followers
Loyal subscribers who consistently listen
342 to 1.8K
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 10/21/26 | The Navier–Stokes Problem and the Agents | 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? | 27m 01s | ||||||
| 10/14/26 | Time Series: The Most Underrated Domain in Industrial AI | 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. | 1h 04m 03s | ||||||
| 10/8/26 | PI and AI | 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. | 39m 50s | ||||||
| 9/30/26 | The Industrial Superintelligence Podcast | In this episode, we dive deep into the world of agentic AI and its transformative impact on industrial organizations - thanks to Jana Kirchheim from Microsoft. We share fresh insights from our conversations with industry leaders on how hyperteams—blending humans and AI agents—are changing the rules of leadership, governance, and knowledge management. You'll hear practical examples from companies like Bayer and discover how even mid-sized firms can harness agents for real business value. We discuss the challenges of orchestrating thousands of agents, building effective governance, and capturing critical tacit knowledge before it disappears. Join us as we explore what it takes to be brave, adapt, and thrive in the era of superintelligent industrial AI. | 1h 01m 00s | ||||||
| 9/23/26 | A new System for Autonomy? | In this episode, I sit down with Nathan Gruber, co-founder and CEO of Manex AI, to explore how autonomy is reshaping the way leading organizations operate. We dig deep into the challenges of legacy manufacturing models, the rise of agent-based AI systems, and why speed and feedback loops are the new competitive edge. Nathan shares his firsthand experience at BMW, the genesis of Manex AI, and how their solutions are closing the gap between customer feedback and engineering action—faster than ever before. We also discuss what true autonomy means for the future of work, the evolving role of humans alongside AI agents, and how European industry can adapt to this seismic shift. If you’re curious about the intersection of software, hardware, and organizational change—or just want a glimpse of the autonomous enterprise in action—this conversation is not to be missed. | 36m 57s | ||||||
| 9/16/26 | AI Material Breakthroughs & The Missing Modality | In this episode, we dive deep into the evolving landscape of industrial AI—from the fierce competition on model leaderboards to the real-world impact of open versus closed AI systems. We question whether it’s necessary to follow every new model or if specialization is the future, using examples from industrial time series and the latest in material science. Alongside our guest Alexander Hammer from Dunia, we explore how AI and autonomous labs are accelerating the discovery of next-generation materials, bridging the gap between simulation and reality. As we reflect on what it means to 'think' in AI—beyond just language or images—we challenge listeners to consider the missing modalities shaping tomorrow’s technology. Join us for insightful stories, candid debates, and a glimpse into the frontier where AI meets the physical world. | 47m 30s | ||||||
| 9/9/26 | Agents and Simulation | In this episode, I sit down with Bastiaan Oud, CEO of Simcon, to unpack the seismic changes AI is bringing to computer-aided engineering. We dive into how agentic and physics-based AI are revolutionizing everything from injection molding simulation to the very roles of engineers and software developers. Bastiaan shares real-world insights on shifting from traditional coding to orchestrating intelligent agents and how this is transforming both product development and organizational structures. If you’ve ever wondered what happens when agents — not just people — drive innovation, this conversation delivers a firsthand look. Join me as we explore the future of engineering, the evolving workplace, and why embracing these changes could be your biggest competitive edge. | 54m 43s | ||||||
| 9/2/26 | AI safetyindustrial automation+4 | Ricardo Mariani | NVIDIAHugging Face | — | AIsafety+5 | — | 52m 10s | ||
| 7/29/26 | AI landscapeEuropean companies+4 | Jakub Tomczak | Anthropic | Silicon ValleyEurope | Anthropic banAI development+5 | — | 24m 10s | ||
| 7/22/26 | autonomous AIdata science+4 | Doudou BA | OctopusVivaTech | — | autonomous AIdata science+5 | — | 40m 01s | ||
| 7/15/26 | manufacturingAI+5 | Scott Duncan | AIlarge language models+2 | — | chemical engineertroubleshooting assistant+6 | — | 41m 58s | ||
| 7/8/26 | industrial AIengineering+3 | Stefan Suwelack | TiRex-2 | — | industrial AIengineering workflows+5 | — | 1h 34m 56s | ||
| 7/1/26 | time series AIindustrial forecasting+3 | Levente Zolyomi | TiRex-2Kronos+1 | — | TiRex-2time series+5 | — | 49m 53s | ||
| 6/24/26 | AI in industrycustomer journey+3 | Jan SeylerWerner Reichelt | Festo | — | AI solutionsindustrial automation+3 | — | 52m 52s | ||
| 6/17/26 | industrial AIAI pilots+5 | Boris Scharinger | SiemensSiemens Energy+2 | — | industrial AIprofitability+6 | — | 44m 10s | ||
| 6/3/26 | AI in manufacturingglass industry+4 | Georg Katzlinger | flat glass industryERP systems | — | AIglass industry+5 | — | 28m 52s | ||
| 5/27/26 | industrial AIfactory design+5 | — | NVIDIAVolkswagen+1 | — | industrial AIfactory operations+5 | — | 1h 11m 00s | ||
| 5/20/26 | Edge AIGovernance+3 | Steven Yates | Federant | — | Edge AIGovernance+5 | — | 53m 27s | ||
| 5/19/26 | industrial AIAPI+4 | Davy Demeyer | MistralNXAI+1 | — | industrial AIAPI calls+5 | — | 43m 00s | ||
| 5/13/26 | podcast updateexclusive news+3 | — | — | — | exclusive newsAI events+3 | — | 1m 25s | ||
| 5/6/26 | AI-driven CADgenerative AI+4 | Dr. Christian Heining | Autodesk FusionAnthropic | — | CADCAM+5 | NXAI | 27m 50s | ||
| 4/29/26 | industrial AIwhite label solutions+3 | Dr. Ferri Abolhassan | T-Systems | GermanyMunich | industrial AIwhite label+5 | — | 38m 41s | ||
| 4/22/26 | Causal AImanufacturing+5 | Bernard | Ethon AISiemens+1 | Switzerland | Causal AImanufacturing intelligence+5 | — | 36m 19s | ||
| 4/15/26 | industrial AIrobotics+4 | Jonas Messner | NEURA Robotics | — | industrial AIrobot gym+6 | — | 51m 44s | ||
| 4/8/26 | data leakageAI model leaderboards+3 | Marcel Meyer | TS Arena | — | data leakageAI+5 | — | 24m 06s | ||
| 4/1/26 | industrial AICNC programming+5 | Tanmay Aggarwal | Lambda Function | — | industrial AICNC programming+8 | — | 43m 47s | ||
| 3/25/26 | AI agentsindustrial automation+4 | Tobias | — | — | AI agentsindustrial automation+5 | — | 51m 28s | ||
| 3/18/26 | AI-powered knowledge platformsindustrial innovation+4 | Jakub | Zeta AlphaFesto | — | AIindustrial knowledge+6 | — | 49m 30s | ||
| 3/11/26 | world modelsneurosymbolic approaches+5 | — | — | — | world modelsAI+5 | SIEMENS | 20m 39s | ||
| 3/4/26 | industrial AIautomation+5 | — | CNCAI+7 | Tel Aviv | industrial AIdigital cousins+6 | — | 40m 23s | ||
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Chart history for Industrial AI Podcast
Peaked at #158 in Germany, currently #158 in Germany.
| Market | Genre | Peak | Current | Trend |
|---|---|---|---|---|
| Germany | — | #158 | #158 | — |
Chart Positions
1 placement across 1 market.
Chart Positions
1 placement across 1 market.