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Shownotes
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
new.siemens.com/global/en.html
Path Robotics
Obsidian (Path Robotics AI Model)
Yaskawa
Universal Robots
ABB
KUKA
FANUC
Reinforcement Learning
en.wikipedia.org/wiki/Reinforcement_learning
World Models (AI)
Industrial AI Podcast
Machine Learning Week
Frankfurter Allgemeine Zeitung (FAZ)
Rich Sutton's 'The Bitter Lesson'
incompleteideas.net/IncIdeas/BitterLesson.html
XLSTM Scaling Laws Paper
Embraceable AI
Deloitte Agentic Framework
www2.deloitte.com/global/en/pages/about-deloit…
Isaac Asimov's 'Sally'
en.wikipedia.org/wiki/Sally(shortstory) (en.wikipedia.org/wiki/Sally_(short_story))
