Physical AI, Safety and the Future of Engineers (Prof. Dr.-Ing. Steven Peters) | Espresso Talks #18.
“The engineer of the future needs more than AI. They need to understand the fundamentals.”
In our latest Espresso Talks podcast episode, Prof. Dr.-Ing. Steven Peters (TU Darmstadt) joins us to discuss how AI is changing automotive engineering and what it takes to build safe, reliable physical AI. Drawing on his experience leading an AI lab at Mercedes-Benz, he shares why successful AI in engineering depends on more than powerful models. High-quality data, experienced engineers, and a solid understanding of how products behave in the real world remain essential.
Key topics we cover:
- From Mercedes to AI-Aided Engineering: How AI is moving beyond individual use cases to become part of the entire engineering process.
- Learning from China’s Speed: Why faster product development requires data-driven engineering, digital twins, and real-world product insights without compromising safety.
- What Physical AI Really Means: Why AI systems operating in the physical world bring unique safety challenges, from autonomous vehicles to industrial machines.
- Europe’s Engineering Advantage: How sharing historical engineering data could help Europe build stronger AI capabilities and turn decades of knowledge into a competitive edge.
- The Engineer of the Future: Why mathematics, physics, statistics, and human factors will remain essential as AI takes on more of the design and development process.
- Rethinking Engineering Education: Why students still need structured teaching and fundamental knowledge to ask the right questions and make the most of AI tools.
