Industrial AI Podcast
- Épisodes
- 361
- Parution
- hebdomadaire
- Dernier épisode
- 12 Nov 2026
À propos du 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, 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.
Épisodes 361
Learnings From AI on the Volcano
From agentic workflows to physical AI, we explore what industrial teams must verify, rethink, and keep safe. We also get into learnable simulation, physical AI, robot safety, and the practical business value of …
Notes de l’épisode
From agentic workflows to physical AI, we explore what industrial teams must verify, rethink, and keep safe.We also get into learnable simulation, physical AI, robot safety, and the practical business value of industrial AI. The big question isn’t just which models to use—it’s how to make the right decisions under uncertainty.
NXAI Anthropic Claudehttps://www.anthropic.com/claude
RoboDojo Ivado Labs Simcon Fraunhofer Institute for Manufacturing Engineering and Automation IPAhttps://www.ipa.fraunhofer.de/en.html
Physical AIhttps://www.nvidia.com/en-us/glossary/physical-ai/
World modelshttps://www.ibm.com/think/topics/world-models
Doppelmayr Schneider ElectricFrom Sandbox to 25,000 Users: How Bayer Scales AI
Jan Tönnissen on agent hubs, AI gateways, the EU AI Act as a catalyst, and why tokens now count as investment. How do you scale AI in a heavily regulated company with more than 100,000 employees? Jan Tönnissen …
Notes de l’épisode
Jan Tönnissen on agent hubs, AI gateways, the EU AI Act as a catalyst, and why tokens now count as investment.How do you scale AI in a heavily regulated company with more than 100,000 employees? Jan Tönnissen has spent over 18 years at Bayer, most recently leading an IT delivery platform behind MyGenesis. The internal GenAI and agentic platform grew from a few hundred users to 25,000 and more than 60,000 assistants. He also built Bayer’s AI community of 19,000 colleagues.
In this episode, Jan explains why guardrails don’t have to slow people down and can instead pave the way. He also describes how the EU AI Act became a catalyst rather than a hindrance. He walks through Bayer’s Agent Hub, a “telephone book” for every agent in the company, and the AI gateway that gives full transparency over LLM and token consumption.
We also cover:
Real use cases: research literature screening cut from weeks to days, marketing content, and “Friday,” Bayer’s new agentic assistant for every employee The token debate: from maximizing to minimizing use, self-hosted open-weight models, small language models, and counting token costs as CapEx AI-assisted engineering: where it delivers 10x and where it delivers 3x Who owns agents in production, and why ownership has to sit with the business The next wave: physical AI and agents moving closer to the shop floor Three takeaways for midsize machine builders: build a coalition of the willing, choose your first battle carefully, and define your build-vs-buy decision tree up front
And one closing reminder: if you can’t measure it, you can’t steer it.
Flat Earth: Are Engineering Tools About to Disappear?
AI agents, industrial robotics, and the future of engineering software—from factory design to robot commands. We’re seeing an explosion of AI in engineering: models turning drawings into 3D designs, agents …
Notes de l’épisode
AI agents, industrial robotics, and the future of engineering software—from factory design to robot commands.We’re seeing an explosion of AI in engineering: models turning drawings into 3D designs, agents helping create plant layouts, and new tools challenging the way engineers work. So where will the value come from next—engineering software, AI platforms, or the context data behind them? I also explore whether agents could leap across the traditional automation pyramid and connect directly with industrial systems.
Then I talk with Bosch’s Thorsten Brach about connecting AI agents to industrial robots using MCP, MHS, and SRCI. We get practical about robot integration, deterministic PLC functions, and why wheeled robots may arrive in factories before legged humanoids. The big question: how do we make these systems easier to use without losing the expertise needed to keep them safe and reliable?
Bosch Manufacturing Solutionshttps://www.bosch-manufacturing-solutions.com/
Standard Robot Command Interface (SRCI)https://www.profibus.com/technology/srcI
Model Context Protocol (MCP)https://modelcontextprotocol.io/
IEC 61131-3 OPC UAhttps://opcfoundation.org/about/opc-technologies/opc-ua/
Integrated Roboticshttps://www.boschrexroth.com/en/us/products/product-groups/automation/ctrlx-automation/
NVIDIA GTC Autodesk BenchCATThe Navier–Stokes Problem and the Agents
Gonzalo C. and Günther Klambauer on AI’s mathematical breakthroughs—and the human work still ahead. Did OpenAI really solve the Navier–Stokes problem? In this episode, we ask mathematician Gonzalo Caolabora and …
Notes de l’épisode
Gonzalo C. and Günther Klambauer on AI’s mathematical breakthroughs—and the human work still ahead.Did OpenAI really solve the Navier–Stokes problem? In this episode, we ask mathematician Gonzalo Caolabora and AI professor Günther 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?
OpenAI Navier–Stokes existence and smoothnesshttps://www.claymath.org/millennium/navier-stokes-equation/
Lean Terry Tao EPFL Johannes Kepler University Linz TransformerTime Series: The Most Underrated Domain in Industrial AI
From time-series foundation models to factory-floor assistants, discover where industrial AI is already delivering value for Arburg. We talk with Arburg’s Stefan Lamp and Werner Faulhaber about how AI is …
Notes de l’épisode
From time-series foundation models to factory-floor assistants, discover where industrial AI is already delivering value for Arburg.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.
Schneider Electric PTC AVEVA Fakumahttps://www.fakuma-messe.de/en/
ARBURG Time-series foundation models Federated learninghttps://en.wikipedia.org/wiki/Federated_learning
OPC UAhttps://opcfoundation.org/about/opc-technologies/opc-ua/
Model Context Protocol (MCP)https://modelcontextprotocol.io/
Plus10 GitHub Copilot Mistral AIPI and AI
From PI System to Real-World Impact. 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 …
Notes de l’épisode
From PI System to Real-World Impact.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.
The Industrial Superintelligence Podcast
How AI agents are reshaping organizations, knowledge, and leadership. Brave new workflows, governance, and the future of industrial intelligence. In this episode, we dive deep into the world of agentic AI and …
Notes de l’épisode
How AI agents are reshaping organizations, knowledge, and leadership. Brave new workflows, governance, and the future of industrial intelligence.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.
Thanks to our Partner NXAI
A new System for Autonomy?
How AI agents and new mindsets are transforming quality, speed, and leadership in industry. Discover the next wave of industrial evolution. In this episode, I sit down with Nathan Gruber, co-founder and CEO of …
Notes de l’épisode
How AI agents and new mindsets are transforming quality, speed, and leadership in industry. Discover the next wave of industrial evolution.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.
Thanks to NXAI
BMW Semantic Web Tesla Siemens Mistral AI AnthropicAI Material Breakthroughs & The Missing Modality
From leaderboard battles to autonomous labs—rethinking industrial AI, physical data, and the future of how we think. In this episode, we dive deep into the evolving landscape of industrial AI—from the fierce …
Notes de l’épisode
From leaderboard battles to autonomous labs—rethinking industrial AI, physical data, and the future of how we think.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.
Thanks to our Partner NXAI
OPN by WITRON
OpenAI Anthropic Google Gemini Meta Quen (Zhipu AI) Alibabahttps://damo.alibaba.com/labs/ai/
DeepSeek Grok (xAI) Siemenshttps://www.siemens.com/global/en.html
NVIDIAhttps://www.nvidia.com/en-us/ai-data-science/
Simcon Fraunhofer Society Dunia Max WellingAgents and Simulation
Exploring how agentic and physics AI are remaking engineering. Discover the shift from code to orchestration—and what it means for industry. In this episode, I sit down with Bastiaan Oud, CEO of Simcon, to …
Notes de l’épisode
Exploring how agentic and physics AI are remaking engineering. Discover the shift from code to orchestration—and what it means for industry.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.
Simcon Cadmouldhttps://www.simcon.ai/en/solutions/cadmould-api-toolkit
Injection Moldinghttps://en.wikipedia.org/wiki/Injection_moulding
Agentic AIhttps://en.wikipedia.org/wiki/Autonomous_agent
Physics AIhttps://en.wikipedia.org/wiki/Physics-informed_neural_networks
Transformer Model Architecturehttps://en.wikipedia.org/wiki/Transformer_(machine_learning_model)
Claude (Anthropic)https://www.anthropic.com/product
OpenAI Codexhttps://openai.com/research/publications/codex
Figma McKinsey Digitalhttps://www.mckinsey.com/capabilities/mckinsey-digital/overview
ME AI Mistral AI Andrej KarpathyNVIDIA's safety strategy
Explore how AI and safety can work hand in hand. From robotics to standards, we uncover the future of industrial safety. In this episode, we dive into the evolving relationship between AI and safety in the …
Notes de l’épisode
Explore how AI and safety can work hand in hand. From robotics to standards, we uncover the future of industrial safety.In this episode, we dive into the evolving relationship between AI and safety in the industrial world. We discuss how NVIDIA is shaping new standards for physical AI and why safety is not just a requirement, but a value driver in modern automation. You'll hear insights from Ricardo Mariani of NVIDIA on the importance of end-to-end safety frameworks, the role of simulation, and the integration of AI into robotics and machinery. We also explore the latest industry moves, from NVIDIA's acquisition of Hugging Face to trends in robotics infrastructure and global competition. Join us as we break down what it means to make AI and safety true partners in the future of industry.
Bosch Event
https://www.boschrexroth.com/en/de/company/trade-shows-and-events/events/expert-days-logistics-9344.html
Agilox Event
https://www.agilox.net/en/techtalks/
Anthropic Standard
https://www.anthropic.com/news/model-hardware-standard-research-preview
NVIDIA HALOS (NVIDIA)https://developer.nvidia.com/halos
Hugging Face OPC Foundation Anthropic Model Hardware Standard (Anthropic)https://www.anthropic.com/news/model-hardware-standard
EU AI Acthttps://artificialintelligenceact.eu/
OPC UA (OPC Unified Architecture)https://opcfoundation.org/about/opc-technologies/opc-ua/
Jensen Huanghttps://en.wikipedia.org/wiki/Jensen_Huang
KION Group Bosch Agilox Unitree Robotics Schaeffler Group Neura Roboticshttps://www.neura-robotics.com/
ISO 13849https://www.iso.org/standard/69883.html
ISO/IEC TS 62443 TÜV Rheinland GTC (NVIDIA GPU Technology Conference)Calling America - Jakub Tomczak reports
What the Anthropic ban means for Europe and the next wave of industrial AI. Can Europe catch up or is the game over? In this episode, we dig into the recent Anthropic ban and what it signals for the global AI …
Notes de l’épisode
What the Anthropic ban means for Europe and the next wave of industrial AI. Can Europe catch up or is the game over?In this episode, we dig into the recent Anthropic ban and what it signals for the global AI landscape. I connect with Jakob Tomczak to get an insider’s perspective from Silicon Valley and explore how this move impacts European companies, innovation, and the future of AI ecosystems.
We also share firsthand impressions of the latest LLMs, debate whether true AI revolutions are on the horizon, and discuss the challenges Europe faces in scaling up. If you’re curious about the real dynamics behind AI development, hardware, and the shifting balance of power in tech, this conversation is for you.
More about NXAI (here)
Autonomous Data Science!?
Discover how agentic AI is reshaping time series forecasting and empowering business users. Dive into next-gen analytics with OctOpus. In this episode, we dive deep into the world of autonomous AI for data …
Notes de l’épisode
Discover how agentic AI is reshaping time series forecasting and empowering business users. Dive into next-gen analytics with OctOpus.In this episode, we dive deep into the world of autonomous AI for data science with Doudou BA, CEO and founder of Octopus. I explore how Octopus is transforming raw data into actionable business decisions using advanced time series foundation models and agentic AI. We discuss the unique reasoning capabilities of Octopus, its intuitive approach for non-technical users, and how it stands apart from traditional AutoML solutions. Along the way, I share insights from VivaTech in Paris, including thought-provoking moments with industry leaders like Yann LeCun and Jeff Bezos. Join us as we reimagine the data science workflow and uncover what’s next for AI-powered business intelligence.
More about NXAI (here)
The Soofi X Discussion (here)
Try OctOpus (here)
How a chemical engineer built an agentic manufacturing troubleshooting assistant
Discover how domain expertise and AI merge to solve complex plant problems – no coding required. Can experience be replaced by intelligence? In this episode, I sit down with Scott Duncan, a chemical engineer …
Notes de l’épisode
Discover how domain expertise and AI merge to solve complex plant problems – no coding required. Can experience be replaced by intelligence?In this episode, I sit down with Scott Duncan, a chemical engineer who built an agentic manufacturing troubleshooting assistant – without any coding background. We dive into the real-world challenges of process manufacturing and how AI is transforming the way plant issues are solved. Scott shares his journey from hands-on troubleshooting to leveraging large language models, knowledge graphs, and real-time data for smarter, faster problem-solving. We also debate the future of domain expertise in an AI-driven world and what it means for education and workforce development. Join me as we explore the potential – and the limitations – of AI in reshaping the future of industrial operations.
NXAI Claude Codehttps://www.anthropic.com/news/claude-3-opus-sonnet-haiku
MATLABhttps://www.mathworks.com/products/matlab.html
OPC Foundation OPC UAhttps://opcfoundation.org/about/opc-technologies/opc-ua/
PI Systemhttps://www.aveva.com/en/products/pi-system/
RAG (Retrieval-Augmented Generation)https://en.wikipedia.org/wiki/Retrieval-augmented_generation
Knowledge Graph MCP ServerAI-Engineering Workflows
From data silos to autonomous agents—discover how AI is reshaping engineering workflows. Insights, stories, and the tools driving the next wave. We just returned from three inspiring days at AI in the Alps, and …
Notes de l’épisode
From data silos to autonomous agents—discover how AI is reshaping engineering workflows. Insights, stories, and the tools driving the next wave.We just returned from three inspiring days at AI in the Alps, and in this episode, we dive into the most exciting breakthroughs and honest challenges facing industrial AI today. I share my firsthand impressions of revolutionary tools like TiRex-2, and we unpack what agentic AI really means for engineering, from breaking down data silos to transforming anomaly detection. Alongside Stefan Suwelack from Renumics, we discuss why skepticism has given way to optimism, how data infrastructure is finally catching up, and what the future holds for AI-driven organizations. The conversation is loaded with real-world examples, candid reflections, and a look at the evolving balance between sovereignty, open source, and big tech. Whether you’re an engineer, decision-maker, or just curious about the future of AI in industry, this episode offers practical insights and a glimpse into what’s next.
TiRex-2 - a multivariate time series foundation model
Discover how TiRex-2 is revolutionizing time series AI for industry. Multivariate, streaming, and more—get the inside story. In this episode, I sit down with Levente Zolyomi, a leading PhD researcher at NXAI …
Notes de l’épisode
Discover how TiRex-2 is revolutionizing time series AI for industry. Multivariate, streaming, and more—get the inside story.In this episode, I sit down with Levente Zolyomi, a leading PhD researcher at NXAI, to unpack the next evolution in time series AI: TiRex-2. We explore how TiRex-2 builds on its predecessor by handling complex multivariate data and streaming scenarios, opening new frontiers for industrial forecasting. Levente shares the story behind TiRex-2’s architecture, its breakthrough capabilities, and what sets it apart from transformer-based models like Kronos. I ask the questions you’re thinking—about zero-shot forecasting, synthetic data, and real-world benchmarks—so you can understand what matters most for your business. If you’re navigating industrial AI or just curious about the future of time series models, this conversation is packed with the insights you need.
From Sales to Spare Parts - Festo´s AI solutions
How AI is transforming every step of the industrial customer journey – from first inquiry to predictive maintenance. Discover the future with us. In this episode, we dive deep into how AI is revolutionizing the …
Notes de l’épisode
How AI is transforming every step of the industrial customer journey – from first inquiry to predictive maintenance. Discover the future with us.In this episode, we dive deep into how AI is revolutionizing the entire industrial customer journey. We explore how large language models and digital twins are reshaping everything from initial customer inquiries to spare parts management and predictive maintenance. I’m joined by Jan Seyler and Werner Reichelt from Festo, who share firsthand insights on integrating AI with engineering tools, orchestrating multi-agent systems, and bridging the gap between digital sales and real-world manufacturing. Together, we discuss the challenges of interoperability, the evolving role of sales engineers, and the opportunities presented by data-driven automation. If you’re curious about the practical impact of AI on industry, this conversation is packed with real examples and forward-looking ideas.
Thanks to our PARTNER NXAI
Festo Mistral AI DeepSeek NVIDIA Automate Show Claude (Anthropic)https://www.anthropic.com/claude
Prometheus JKU Linz (Johannes Kepler University Linz) Digital Product Passporthttps://single-market-economy.ec.europa.eu/sectors/ecodesign/digital-product-passport_en
Knowledge Graphhttps://en.wikipedia.org/wiki/Knowledge_Graph
Retrieval-Augmented Generation (RAG)https://www.pinecone.io/learn/retrieval-augmented-generation/
Digital Twin Predictive MaintenanceIndustrial AI: From Pilot to Profit
Meet Boris Scharinger and explore the real-world journey of AI in industry. Why expectations must meet reality for true transformation. Our guest is Boris Scharinger from Siemens. He wrote an interesting book …
Notes de l’épisode
Meet Boris Scharinger and explore the real-world journey of AI in industry. Why expectations must meet reality for true transformation.Our guest is Boris Scharinger from Siemens. He wrote an interesting book "Industrial AI: From Pilot to Profit" and in this episode, we sit down with him. He is a leading voice in industrial AI and we uncover what it really takes to move from flashy AI pilots to solutions that deliver real value on the shop floor and in product engineering. We dig into the challenges of bridging proof-of-concept and production, the unique demands of industrial environments, and why so many initiatives stall before reaching profitability. Our conversation cuts through the hype, sharing candid examples from Siemens Energy and Tesla to illustrate where AI is truly changing the game and where it’s still hitting walls.
We also tackle pressing topics like the impact of generative AI on management expectations, the evolving role of process mining, and the tough realities of deploying AI in brownfield versus greenfield environments. If you’re a startup, engineer, or decision-maker looking to understand the real mechanics—and pitfalls—of industrial AI, this episode is your inside track. Join us as we set the record straight on what it takes to turn AI ambition into sustainable success.
Order the book here
Siemens Energyhttps://www.siemens-energy.com/global/en.html
Tesla Giga Presshttps://www.tesla.com/blog/gigapress
Process Mininghttps://en.wikipedia.org/wiki/Process_mining
Will van der Aalst Google: Hidden Technical Debt in Machine Learning Systemshttps://papers.nips.cc/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html
AI for the Glass Industry
From manual chaos to smart automation—inside the future of glass industry workflows. Discover how AI is transforming custom orders. In this episode, I sit down with Georg Katzlinger to explore the surprising …
Notes de l’épisode
From manual chaos to smart automation—inside the future of glass industry workflows. Discover how AI is transforming custom orders.In this episode, I sit down with Georg Katzlinger to explore the surprising complexity of the flat glass industry and the unique challenges it faces. We dive into how AI solutions are revolutionizing the way custom glass orders are processed, from deciphering handwritten requests to integrating with legacy ERP systems. Georg shares his journey from engineering to AI entrepreneurship, revealing why deterministic, human-in-the-loop automation is essential for manufacturers. I ask the tough questions on accuracy, implementation, and industry-specific hurdles, giving you an insider’s perspective on what it takes to bring AI into traditional sectors. If you’re curious about the intersection of deep tech and real-world manufacturing, you won’t want to miss this conversation.
Lumeso Flat Glass Industryhttps://en.wikipedia.org/wiki/Flat_glass
ERP (Enterprise Resource Planning) Systemshttps://en.wikipedia.org/wiki/Enterpriseresourceplanning
OCR (Optical Character Recognition)https://en.wikipedia.org/wiki/Opticalcharacterrecognition
LLM (Large Language Models) SAP SalesforceNVIDIA´s Safety Initiative / The unique Volkswagen-Siemens joint venture
Can cutting-edge AI truly transform factories? We explore real-world challenges, success stories, and the future of intelligent automation. In this episode, we dive deep into the promise and pitfalls of …
Notes de l’épisode
Can cutting-edge AI truly transform factories? We explore real-world challenges, success stories, and the future of intelligent automation.In this episode, we dive deep into the promise and pitfalls of industrial AI with hands-on experts from a unique Volkswagen-Siemens joint venture. We challenge the hype around humanoid robots, discuss the practical impact of AI on factory design and operations, and uncover what truly drives value on the shop floor. Our guests share candid insights on scaling AI solutions, the role of synthetic data, and why safety and trust remain at the core of industrial automation. Join us as we separate fact from fiction and chart the path forward for intelligent manufacturing. If you're curious about the real impact of AI beyond the buzzwords, this conversation is for you.
NXAI Figure AI BMW NVIDIAhttps://www.nvidia.com/en-us/industries/industrial/
SICK AG OpenAI Anthropic Google Gemini Coursera Andrew Ng Siemens Volkswagen inpro Katena-X OmniverseGoverned Autonomy: Why Edge AI Needs Guardrails
Discover how local policy enforcement is reshaping industrial AI safety. What happens when your smart machines lose their connection? In this episode, I sit down with Steven Yates, CTO and co-founder of …
Notes de l’épisode
Discover how local policy enforcement is reshaping industrial AI safety. What happens when your smart machines lose their connection?In this episode, I sit down with Steven Yates, CTO and co-founder of Federant, to dive deep into the urgent need for runtime governance in edge AI. Drawing on decades of experience in embedded systems and PLC design, Steven reveals why the shift to the edge demands more than just powerful inference—it requires robust, local authority to keep operations safe when connectivity falters. We unpack real-world incidents where lack of governance led to costly mishaps, and explore how new open-source solutions are bridging the gap between cloud convenience and industrial reliability. If you think cloud SLAs are enough for industrial AI, this conversation will make you rethink the fundamentals. Join me as we explore the future of safe, autonomous operations—and why the old rules of industrial control are more relevant than ever.
Federant EU AI Acthttps://artificialintelligenceact.eu/
GE Fanuc Intel Modicon 084https://en.wikipedia.org/wiki/Programmablelogiccontroller#History
Starlink Deloitte 'Physical AI: The Moment of Acceleration'https://www2.deloitte.com/global/en/insights/industry/technology/physical-ai.html
Edge AI Foundationhttps://www.edgeaicouncil.org/
Wevolver ADI Engineering IEEEMistral acquires NXAI spin-off Emmi AI / API Calls
Unlocking value beyond APIs—where industry creativity, killer apps, and agentic engineering collide. Are we ready for the future? In this episode, we dive deep into the evolving landscape of industrial AI …
Notes de l’épisode
Unlocking value beyond APIs—where industry creativity, killer apps, and agentic engineering collide. Are we ready for the future?In this episode, we dive deep into the evolving landscape of industrial AI, exploring why simply offering an API is no longer enough for true business value. We reconnect with leading minds behind recent billion-euro deals and discuss the journey from foundational models to real-world industrial impact. Our conversation with Davy Demeyer spotlights the creativity gap in industry, the challenges of automation standards, and what it takes to build the next killer application. We share firsthand insights from pioneers, reflect on lessons learned, and debate how agents, humans, and deterministic code generation will shape tomorrow’s factories. If you want the latest and greatest in industrial AI—and why it matters for your business—this is the episode you can't miss.
SAP NXAI Mistral AI Simcon OpenAI Anthropic AWS Industrial Fundhttps://aws.amazon.com/industries/industrial/
Claude (Anthropic)https://www.anthropic.com/claude
BMW DeepSeek Quenhttps://github.com/QwenLM/Qwen
Siemens Beckhoff B&R Industrial Automationhttps://www.br-automation.com/
CODESYS Rockwell Automationhttps://www.rockwellautomation.com/
ISA-88 (Batch Control Standard)https://www.isa.org/standards-and-publications/isa-standards/isa-88-batch-control
IEC 61131-3https://en.wikipedia.org/wiki/IEC_61131-3
Module Type Package (MTP)https://www.process-worldwide.com/what-is-module-type-package-mtp-a-1053341/
Box.com Accenture Fraunhofer Societyhttps://www.fraunhofer.de/en.html
AI Association (Industrial AI Network) Boris Scharinger Industrial AI: From Pilot to Profit (Book)Exclusive News Delay
A special episode postponed for breaking news—find out why you won't want to miss Friday's reveal. It's Thursday morning and I know you're expecting a fresh episode, but today brings a twist—I have exclusive …
Notes de l’épisode
A special episode postponed for breaking news—find out why you won't want to miss Friday's reveal.It's Thursday morning and I know you're expecting a fresh episode, but today brings a twist—I have exclusive news that can't go live just yet. We're delaying our usual release by one day to bring you something truly special and timely. In the meantime, I invite you to consider joining us at this year's top AI events or reaching out for more information. Thank you for your patience and understanding as we prepare to share these exciting updates with you. I look forward to reconnecting with you tomorrow for a can’t-miss episode.
The CAD AI Hype!?
Can generative AI finally democratize industrial design? We explore with Dr. Christian Heining breakthroughs, challenges, and the future of CAD with AI. We have a new podcast partner - please welcome NXAI! In …
Notes de l’épisode
Can generative AI finally democratize industrial design? We explore with Dr. Christian Heining breakthroughs, challenges, and the future of CAD with AI.We have a new podcast partner - please welcome NXAI!
In this episode, I dive deep into the evolving world of AI-driven CAD and CAM with Dr. Christian Heining. We unpack why generative AI is capturing the attention of industrial designers and whether the latest integrations—like Anthropic’s connector for Autodesk Fusion—are truly game-changing or just another step on a long journey.
Dr. Heining shares real-world experiments, candid takes on current limitations, and what it means for both startups and big players in the industrial AI space. We discuss the speed of change, the challenges of adapting teams to new tools, and what’s still missing before AI can fully transform the machine-building industry. If you’re curious about the intersection of AI, engineering, and the future of design, this episode is a must-listen.
NXAI CAD Paperhttps://arxiv.org/abs/2604.16170v1
Anthropic Autodesk Fusionhttps://www.autodesk.com/products/fusion-360/overview
Onshape Dassault Systèmes OpenAI Gemini (Google AI)https://deepmind.google/technologies/gemini/
Opus 4.7 (OpenAI Model) Andrej KarpathyHM26: Whitelabeled AI and the hope for the API
Unpacking the buzz, the business, and the challenges of authentic industrial AI innovation. Is the industry losing its edge? In this episode, we dive straight into the heart of the industrial AI landscape …
Notes de l’épisode
Unpacking the buzz, the business, and the challenges of authentic industrial AI innovation. Is the industry losing its edge?In this episode, we dive straight into the heart of the industrial AI landscape – beyond flashy headlines and Instagram-worthy trade shows. We tackle the uncomfortable truths behind 'white label' solutions, the real value (or lack thereof) in APIs, and why simply following the hype won't cut it for true innovation. We share our candid impressions from Hannover Messe, exploring the tension between substance and showmanship, and what it means for the future of industrial-grade AI. Plus, we sit down with Dr. Ferri Abolhassan from T-Systems to uncover how Germany's new AI Factory in Munich is aiming to rewrite the rules for secure, sovereign, and scalable AI infrastructure. Join us for honest insights, pointed critiques, and a look at where industrial AI must go next if we want to deliver real value.
Causal AI on the shopfloor
From Swiss chocolate to global factories, discover how AI is turning industrial data into real manufacturing intelligence. In this episode, I sit down with Bernard, co-founder of Ethan AI, to explore the …
Notes de l’épisode
From Swiss chocolate to global factories, discover how AI is turning industrial data into real manufacturing intelligence.In this episode, I sit down with Bernard, co-founder of Ethan AI, to explore the seismic shift happening as machines move from simply reacting to truly understanding their own processes. We dive into how knowledge graphs, causal AI, and computer vision are transforming manufacturing—from chocolate factories in Switzerland to global giants like Siemens and Bosch.
We discuss the real impact of connecting siloed industrial data, the journey from correlation to causation, and what it means for the people on the shop floor. Bernard shares concrete examples of AI-driven quality control, autonomous process optimization, and the evolving role of operators. Join me for a conversation that peeks into the future of manufacturing intelligence—and what it takes to build the digital quality engineers of tomorrow.
Siemenshttps://www.siemens.com/global/en.html
ETH Zurich World Economic Forum (WEF) Bosch Lindt & Sprünglihttps://www.lindt-spruengli.com/
Knowledge Graphhttps://en.wikipedia.org/wiki/Knowledge_graph
Causal AI Computer Visionhttps://en.wikipedia.org/wiki/Computer_vision
Process Mininghttps://en.wikipedia.org/wiki/Process_mining
Siemens Accelerator Marketplacehttps://siemens.com/accelerator
Spurious Correlations (Book)https://www.tylervigen.com/spurious-correlations
MES (Manufacturing Execution System)https://en.wikipedia.org/wiki/Manufacturingexecutionsystem
OPC UA MQTTData, Memory, Gyms and Models - NEURA's strategy
Explore how real-world data, memory, and multi-modal AI are shaping the next wave of robotics. Dive into the future with us. In this episode, we dig deep into the evolving landscape of industrial AI, from April …
Notes de l’épisode
Explore how real-world data, memory, and multi-modal AI are shaping the next wave of robotics. Dive into the future with us.In this episode, we dig deep into the evolving landscape of industrial AI, from April Fool’s pranks to real advances in robotics and automation. We break down how the line between hype and reality is blurring, and why it’s more challenging than ever to separate fact from fiction in the age of agentic AI.
We welcome Jonas Messner from Neura Robotics to unpack how their 'robot gym' is collecting real-world data, why new forms of memory and multi-modal sensing are critical, and how open platforms are redefining collaboration in physical AI. Join us as we connect industry history, current breakthroughs, and bold visions for the future—where robots learn, adapt, and even monetize their skills in dynamic environments.
Siemenshttps://new.siemens.com/global/en.html
SAP NVIDIA Bosch Schaeffler Neura Roboticshttps://www.neura-robotics.com/
Google DeepMind Agile Robots KraussMaffei Automation (formerly T-Sync Group Automation Engineering) DLR (German Aerospace Center) Modbus LLM Arena FETH Bench GiftEval Anthropic World Models (AI concept)The End of Data Leakage
Why Data Leakage Threatens AI Benchmarks—and How We're Fixing It. Discover the future of reliable model evaluation. In this episode, we dive deep into the challenges facing time series AI model leaderboards …
Notes de l’épisode
Why Data Leakage Threatens AI Benchmarks—and How We're Fixing It. Discover the future of reliable model evaluation.In this episode, we dive deep into the challenges facing time series AI model leaderboards, from hidden information leakage to the complexities of benchmarking foundation models. I sit down with Marcel Meyer to unpack why traditional approaches fall short and how our new TS Arena leaderboard is setting a new standard for fair, future-proof evaluation.
We explore the pitfalls that plague current benchmarks, the surprising ways data contamination can skew results, and the innovative pre-registration protocol we've developed to keep evaluations honest. If you've ever wondered what it takes to build a truly trustworthy AI leaderboard—or why it matters for industry and research alike—this conversation is packed with insights you won't want to miss.
Autonomous CNC programming!?
From shop floor autonomy to data-driven disruption – exploring the breakthroughs shaping tomorrow’s manufacturing. Discover how AI is transforming precision machining. In this episode, we dive into the cutting …
Notes de l’épisode
From shop floor autonomy to data-driven disruption – exploring the breakthroughs shaping tomorrow’s manufacturing. Discover how AI is transforming precision machining.In this episode, we dive into the cutting edge of industrial AI, from the latest advancements in large language model distillation to the transformative power of AI agents in manufacturing. I sit down with Tanmay Aggarwal, CEO of Lambda Function, for a deep conversation about autonomous CNC programming, real-time shop floor integration, and why memory and causal inference matter for the next wave of physical AI. We also unpack industry trends – from SD card AI accelerators to Europe’s strategic push for data sovereignty – and share candid thoughts on what it takes to move from AI-assisted workflows to true autonomy. If you’re curious about how AI is reshaping industrial strategy, or just want to hear how real-world manufacturing is meeting the future, this one’s for you. Join us as we connect the dots between research breakthroughs, practical deployments, and the evolving competitive landscape of industrial AI.
Can AI Agents Really Run the Factory?
Exploring the real impact of GenAI and agents in industrial automation. Are we ready for hands-off production? In this episode, I sit down with Tobias, a robotics and automation expert, to unpack what AI agents …
Notes de l’épisode
Exploring the real impact of GenAI and agents in industrial automation. Are we ready for hands-off production?In this episode, I sit down with Tobias, a robotics and automation expert, to unpack what AI agents and generative AI mean for the future of industrial automation. We explore how combining human expertise with advanced agents can optimize production cycles, break down technological silos, and open new possibilities for greenfield automation projects. From hands-on case studies to the hurdles of legacy systems, we dig into what works today, what doesn’t, and where the next breakthroughs might come from.
I share insights from our own experiments—what happens when you let an AI agent optimize a real automation cell, and why, for now, human know-how still matters. If you’re curious about the practical realities of AI in production lines and what’s hype versus what’s already delivering value, this conversation is for you.
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