From industrial skepticism to breakthrough robotics—why adaptability and real-world data change everything. Discover what’s next for manufacturing AI.

In this episode, we dive into the realities behind industrial AI adoption—both the successes and the setbacks. We share candid conversations with engineers frustrated by unreliable AI and explore why real-world robustness remains the central challenge. Then, I sit down with Andy from Path Robotics, who reveals how their AI-driven welding robots are redefining adaptability and reliability on the shop floor. We unpack what makes their approach unique, from multi-modal sensors to reinforcement learning and massive real-world datasets. If you care about the future of manufacturing, data-driven automation, and the evolution of industrial roles, you won’t want to miss this discussion. Join us as we look ahead to what’s possible when AI finally delivers on its industrial promise.

Siemens

Path Robotics

Obsidian (Path Robotics AI Model)

Yaskawa

Universal Robots

ABB

KUKA

FANUC

Reinforcement Learning

World Models (AI)

Industrial AI Podcast

Machine Learning Week

Frankfurter Allgemeine Zeitung (FAZ)

Rich Sutton's 'The Bitter Lesson'

XLSTM Scaling Laws Paper

Embraceable AI

Deloitte Agentic Framework

Isaac Asimov's 'Sally'

‘Een kwestie van gevoel’: over ‘emoties en politiek

Voorproevers

Geschiedenis van de tweedeling emotie en rede

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