Nomagic Hires New Chief Scientist from Google DeepMind to Lead Development of Foundational Models for Robotics
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| Source: Markets Insider | Original article
Nomagic, the Swedish‑based robotics firm that has been scaling AI‑driven warehouse arms across Europe, announced today that it has hired Markus Wulfmeier as its first Chief Scientist. Wulfmeier arrives from Google DeepMind, where he led research on physical AI and embodied learning, and will head a new unit focused on building foundational models that can be transferred across a range of robotic tasks.
The appointment marks a strategic shift for Nomagic. Until now the company has relied on bespoke perception and control pipelines tuned for specific pick‑and‑place scenarios. By bringing in DeepMind’s expertise in large‑scale, multimodal models, Nomagic aims to create a single “brain” that can understand raw sensor streams, reason about object dynamics and generate motor commands for any warehouse layout. If successful, the approach could cut development cycles dramatically, lower hardware costs and enable rapid adaptation to new product lines—an advantage in a market where Amazon‑style fulfillment centers are expanding at break‑neck speed.
Industry observers see the move as a bellwether for the broader robotics sector, which has struggled to translate the recent breakthroughs in large language models into tangible physical capabilities. Nomagic’s $44 million Series B round, closed last month, gave it the capital to pursue high‑risk research that previously belonged to deep‑tech labs. The hiring also signals intensified competition among European players to capture the “foundational model” niche before the US giants consolidate their own robot‑learning platforms.
What to watch next: Nomagic has pledged to release its first cross‑task model prototype by Q4 2026, and will likely publish benchmark results on the new Physical AI Suite. Partnerships with logistics operators will test the technology at scale, while regulators keep an eye on safety standards for AI‑controlled machinery. The success—or failure—of Wulfmeier’s team could set the tempo for the next wave of intelligent automation in supply chains.
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