Nomagic chief scientist: master one industrial task first, then scale to general robots
lukas_m_ziegler · x · 2026-11-09
At GTC Berlin, the author interviewed Markus Wulfmeier, Chief Scientist at Nomagic, on their "mastery before generalization" approach to physical AI.
Key points:
- Physical AI today is full of shiny demos but short on real industrial deployments. Once deployed, customers care only about autonomy — robots must run on their own, not pull in a human every hour or two.
- Nomagic goes depth-first: fully master one task until customers rely on it completely, then expand from there, instead of chasing a breadth-first model that sort of does everything.
- Every deployed system generates data as it runs, which becomes the fuel for everything they build next — mastery pays for the expansion toward general-purpose robots.
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