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/

We spent time at our event in the Black Forest, where innovation met inspiration at our latest industrial AI gathering. In this episode, we share stories—from empowering autistic talent in data annotation to the technical leaps in foundation models for time series. You’ll hear from leading minds like Jakub Tomczak, who flew in from San Francisco to challenge what’s possible in generative AI, and explore how the landscape is shifting from traditional machine learning to adaptive, context-rich automation.

Join us as we question what makes AI truly intelligent, debate the role of human factors, and look ahead to the next wave of industrial transformation. If you’re curious about how AI is evolving in real factories, how new job profiles are emerging, or why continuous learning and time series matter more than ever, this conversation is for you.

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, I dive into the fascinating world of non-destructive material testing with Christian Wagner from Vogt Ultrasonics and Jan Kutnik from Evoptima. Together, we explore how AI is revolutionizing spot weld inspection in the automotive industry, making quality control smarter and more precise than ever before.

We discuss the challenges of processing massive ultrasonic datasets, adapting AI models to real-world manufacturing, and the journey from legacy systems to cutting-edge solutions. If you’re curious about how collaborative robots, vision systems, and robust AI are reshaping factory floors—and what it takes for mid-sized companies to lead the charge—this is an episode you won’t want to miss.

https://new.siemens.com/global/en/products/automation/topic-areas/industrial-ai.html

https://www.vogt-ultrasonics.de/en/

https://evoptima.com/

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

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

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

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

https://www.cvut.cz/en

https://en.ids-imaging.com/