In this episode, I sit down with Norbert Jung, CEO of Bosch Connected Industry, to explore the evolving landscape of manufacturing co-intelligence. We dive into how AI agents and data are reshaping factories, why human expertise remains irreplaceable, and what 'industrial grade' really means in this new era. Norbert shares practical examples from Bosch's own production lines, debunks common myths, and explains how semantic data and agentic AI are driving real-world results. We also tackle the challenges of scaling innovation, the future of lights-out factories, and why Europe's workforce transformation is both a necessity and an opportunity. If you want an inside look at the practical side of AI in industry—and what it means for the people behind the machines—this conversation delivers fresh perspective and actionable insights.

In this episode, we journey from weather woes in Franconia straight into the heart of Amsterdam’s AI innovation, exploring what happens when robotics, world models, and agentic AI collide. We share our firsthand impressions from deep-dive research sessions at Lab42, where startups and researchers are joining forces to push industrial AI forward. You'll hear my conversation with John Harrington of HighByte, who breaks down the role of MCP services and why they’re critical for bridging the gap between factory data and intelligent agents.

We don’t just talk tech—we talk about the people, the practical challenges, and the evolving landscape that’s making industrial data accessible to everyone, not just engineers. If you’re curious about how symbolic AI, digital cousins, and scalable architectures are transforming manufacturing, or you want to know what’s next for AI in the Alps, this episode is your front-row seat. Tune in for insights, laughs, and a clear-eyed look at the road ahead for industrial-grade AI.

https://www.siemens.com/global/en.html

https://www.highbyte.com/

https://docs.anthropic.com/claude/docs/model-context-protocol-mcp

https://opcfoundation.org/

https://opcfoundation.org/about/opc-technologies/opc-ua/

https://en.wikipedia.org/wiki/Manufacturingexecutionsystem

https://www.anthropic.com/

https://www.snowflake.com/

https://aws.amazon.com/

https://azure.microsoft.com/

https://www.osisoft.com/pi-system/

https://www.aspentech.com/

https://www.novotek.com/

https://mqtt.org/

https://en.wikipedia.org/wiki/Representationalstatetransfer

https://www.lab42.nl/

https://opcfoundation.org/about/opc-technologies/opc-ua/opc-ua-information-model/

https://en.wikipedia.org/wiki/ANSI/ISA-95

In this episode, I dive deep into the future of industrial AI with Andreas de Jonge, exploring how inline AI is reshaping real-world manufacturing. We discuss why tailored, ultra-efficient AI models can outperform bulky, generic solutions—especially in Europe’s highly specialized industries. Andreas shares how his company’s EdgeBrain device brings intelligence directly to the data stream, enabling plug-and-play integration and unprecedented robustness for even the oldest production lines. Together, we unpack the challenges of brownfield integration, the power of synthetic data, and the path to true European digital sovereignty. If you’re curious about the next wave of industrial automation and what it means for productivity, this conversation is not to be missed.

https://www.siemens.com/global/en.html

[https://dejonge.ai/en)

https://en.wikipedia.org/wiki/Field-programmablegatearray

https://www.tensorflow.org/

https://pytorch.org/

https://onnx.ai/

https://en.wikipedia.org/wiki/Knowledge_distillation

https://en.wikipedia.org/wiki/Industrial_Ethernet

https://en.wikipedia.org/wiki/Brownfield(softwaredevelopment)

https://en.wikipedia.org/wiki/Unmannedaerialvehicle

https://en.wikipedia.org/wiki/Programmablelogiccontroller

In this episode, we dive into the evolution of AI robotics, exploring how lessons from cucumber-picking robots are now revolutionizing industrial inspection. We sit down with Wouter from VBTI to unpack the journey from complex greenhouse challenges to the development of Adam One—an inspection robot that doesn’t just automate, but truly understands the task at hand.

We reflect on the unique technical hurdles, the fusion of multiple AI models, and the potential for scalable, domain-specific foundation models. As always, we bring our authentic curiosity and skepticism to the latest industry trends, from federated learning revivals to the shifting boundaries of edge and cloud AI. Join us for a conversation that connects practical innovation with the big questions shaping industrial AI.

https://www.siemens.com/global/en.html

https://new.siemens.com/global/en/company/about/management/roland-busch.html

https://www.ces.tech/

https://www.bosch.com/

https://en.wikipedia.org/wiki/Yann_LeCun

https://en.wikipedia.org/wiki/Federated_learning

https://opcfoundation.org/

https://opcfoundation.org/about/opc-technologies/opc-ua/

https://www.w3.org/RDF/

https://www.bostondynamics.com/atlas/

https://www.hyundai.com/worldwide/en/company/newsroom/hyundai-motor-group-completes-acquisition-of-boston-dynamics-0000016337

https://www.neura-robotics.com/

https://erf2024.eu/

https://www.weforum.org/events/world-economic-forum-annual-meeting-2024/

https://en.wikipedia.org/wiki/TheMagicMountain

https://www.path-robotics.com/

https://www.asml.com/

https://www.blender.org/

https://github.com/itsnamgyu/moondream

https://www.vbti.nl/

https://www.vbti.nl/adam-one/

In this episode, I sit down with James Zhang, co-founder and CPO of OpsMate AI, to explore the game-changing role of AI agents in factory operations. We discuss why traditional human-centric manufacturing models are hitting their limits and how a hybrid workforce—combining humans, robots, and digital agents—can address the skilled labor shortage and boost productivity.

James shares firsthand insights into the unique challenges of deploying AI in diverse factory environments, the importance of knowledge graphs, and why empowering frontline teams is key to successful adoption. If you’re curious about the practical steps to bring AI agents onto your shop floor, or just want to understand what the future of industrial automation looks like, this conversation is for you.

https://www.siemens.com/global/en.html

https://www.opsmateai.com/reports/gartner-cool-vendor

https://www.opsmate.ai/

https://www.microsoft.com/en-us/industry/manufacturing

https://en.wikipedia.org/wiki/Generativeartificialintelligence

https://www.microsoft.com/en-us/research/blog/agentic-ai-a-new-paradigm-for-human-ai-collaboration/

https://en.wikipedia.org/wiki/Knowledge_graph

https://en.wikipedia.org/wiki/Manufacturingexecutionsystem

https://en.wikipedia.org/wiki/Enterpriseresourceplanning

https://azure.microsoft.com/en-us/products/databricks/

https://www.microsoft.com/en-us/microsoft-fabric

https://www.ptc.com/

https://www.sap.com/industries/manufacturing.html

https://chat.openai.com/

https://gemini.google.com/

In this episode, we dive into the ambitious European initiative offering up to one billion euros to fuel the next wave of AI innovation. I sit down with Johannes Otterbach, the so-called "billion euro man," to discuss how SPRIND is bridging the gap between research and industry, and what it really takes to launch a world-class AI lab in Europe. We explore the challenges of scaling, the importance of industrial-grade AI, and why Europe's unique landscape demands new strategies for success. Along the way, you'll hear our candid thoughts on talent, technology, and the future of frontier AI. If you're curious about the intersection of ambitious funding, cutting-edge research, and industrial application, this conversation is for you.

https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html

https://www.neura-robotics.com/

https://www.nvidia.com/en-us/ai-data-science/

https://www.fraunhofer.de/en.html

https://www.agilerobots.com/

https://opcfoundation.org/

https://industrial.softing.com/

https://www.audi.com/en/innovation/ai.html

https://mistral.ai/

https://www.sprind.org/en/

https://openai.com/

https://www.deepmind.com/

https://x.ai/

https://next-frontier.ai/

Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.

We thank our partner SIEMENS

Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.

We thank our partner SIEMENS

Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.

We thank our partner SIEMENS

In this episode, we dive into why sound is the next big leap for AI in industry. I share insights from recent events, including the SPS exhibition and Europe's AI scene, and discuss why edge AI is outpacing the cloud on the shop floor. Then, I sit down with Dr. Finnur Pind from Treble Technologies to explore how synthetic sound data is powering smarter machines—from voice recognition in cars to giving robots a sense of hearing.

You'll hear how simulating sound opens up new possibilities for robotics and spatial awareness, and why industries are racing to make AI models that can truly listen. We also touch on the unique AI startup scene in Reykjavik, the challenges of accurate sound modeling, and what the future holds for audio-driven innovation. Join us to discover why the future of industrial AI might just depend on what machines can hear.

https://new.siemens.com/global/en.html

https://sps.mesago.com/nuernberg/en.html

https://www.beckhoff.com/en-en/

https://www.phoenixcontact.com/online/portal/us

https://www.kuka.com/en-de/

https://www.bosch.com/

https://opcfoundation.org/

https://mqtt.org/

https://www.hibyte.com/

https://www.mathworks.com/

https://people.idsia.ch/~juergen/

http://incompleteideas.net/IncIdeas/BitterLesson.html

https://en.wikipedia.org/wiki/Longshort-termmemory

https://openai.com/

https://deepmind.google/

https://www.deepmind.com/research/highlighted-research/alphafold

https://www.bostondynamics.com/

https://nips.cc/

https://www.treble.tech/

https://www.dtu.dk/english

https://slush.org/

In this episode, I sit down once again with Professor Oliver Niggemann to unravel the world of numerical machine learning—where traditional engineering meets cutting-edge AI. We explore real-world projects from diagnosing the International Space Station to designing safer bridges, smarter batteries, and even optimizing biodiversity. Oliver breaks down how fusing symbolic knowledge and neural networks is revolutionizing simulation, design, and problem-solving across industries.

If you’ve ever wondered how AI can speed up material discovery or what the future holds for interdisciplinary engineers, this conversation is for you. We dive into the power of surrogate models, the evolution of engineering education, and why tomorrow’s innovations demand both deep technical expertise and creative collaboration. Join us for a look at the next frontier in industrial AI.

https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html

https://www.hsu-hh.de/ims/team/niggemann/

https://www.hsu-hh.de/

https://www.dlr.de/rd/en/desktopdefault.aspx/tabid-2441/3587_read-5637/

https://www.airbus.com/en/products-services/space

https://www.esa.int/ScienceExploration/HumanandRoboticExploration/Columbus

https://www.iosb.fraunhofer.de/

https://en.wikipedia.org/wiki/Physics-informedneuralnetworks

https://en.wikipedia.org/wiki/Surrogate_model

https://www.cusp.ai/

https://en.wikipedia.org/wiki/Geoffrey_Hinton

https://en.wikipedia.org/wiki/Yann_LeCun

https://www.deepmind.com/research/highlighted-research/alphafold