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

In this episode, I sit down with Richard Rovner, Vice President of Marketing at MathWorks, to explore the fascinating evolution of AI in engineering. We trace the technology’s journey from its early days in the 1980s, through transformative milestones like deep learning and code generation, all the way to today's AI-driven design tools and copilots.

Richard shares insider perspectives on how AI is changing the engineer’s workflow, what generative AI means for the future, and why the human touch remains essential in a world of accelerating automation. If you’re curious about where engineering and AI are headed—or how to stay ahead in this rapidly shifting landscape—this conversation is packed with insights you won’t want to miss.

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

https://www.mathworks.com/

https://www.mathworks.com/products/matlab.html

https://www.mathworks.com/products/simulink.html

https://www.mathworks.com/products/neural-network.html

https://www.mathworks.com/products/deep-learning.html

https://www.mathworks.com/products/statistics.html

https://www.mathworks.com/products/text-analytics.html

https://www.mathworks.com/products/matlab-copilot.html

https://www.sas.com/

https://www.faw-ulm.de/

https://www.coca-colafreestyle.com/

https://www.arm.com/products/silicon-ip-cpu/cortex-m

https://www.mpg.de/en

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

https://www.mathworks.com/solutions/model-based-design.html

In this episode, we dive deep into the real-world state of AI adoption across industries, unpacking the findings of a major new survey with Gabriel Krummenacher. We explore which AI use cases actually move the needle—hint: operational efficiency tops the list—and why simply chasing the latest GenAI trends won't deliver results without a solid data science foundation.

You'll hear our honest takes on what separates hype from impact, why ethical frameworks and governance drive innovation (not stifle it), and how US and European companies are taking very different paths with AI. If you're wondering where AI is truly transforming business—and what it really takes to succeed—this episode is for you.

https://www.quantum-systems.com/

https://www.kaggle.com/

https://www.anthropic.com/

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

https://www.trumpf.com/

https://www.asml.com/

https://www.qualcomm.com/

https://ethz.ch/en.html

https://www.zuehlke.com/

https://openai.com/

https://www.cse.unsw.edu.au/~tw/

In this episode, I sit down with Schunk CTO Timo Gessmann and Google DeepMind’s Phillip Lippe to explore how AI is transforming the world of robotics and industrial automation. We kick things off with Timo, who shares his vision for merging mechanical expertise with AI, the challenges of attracting top talent, and why Europe needs its own world-class robotics models.

Then, I’m joined by Phillip Lippe from the Gemini team, who dives into the latest advances in generative AI, the power of foundation models, and what the future holds for scalable, domain-specific intelligence. Whether you’re fascinated by embodied AI, curious about industry trends, or want a peek into the minds shaping tomorrow’s robots, this episode is packed with insights you won’t want to miss.

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

https://schunk.com/

https://deepmind.google/technologies/gemini/

https://deepmind.google/

https://www.nvidia.com/

https://www.ros.org/

https://automatica-munich.com/en/

https://www.bosch.com/

https://www.european-processor-initiative.eu/

https://www.nvidia.com/gtc/

https://www.nxai.io/

https://research.samsung.com/artificial-intelligence

https://nips.cc/