Nvidia (NASDAQ:NVDA) and Samsung are investing a combined $35 million into Skild AI, a general-purpose robotics intelligence startup that’s rapidly gaining investor confidence. The Series B funding round, which values Skild AI at approximately $4.5 billion, is led by a $100 million investment from Japan’s SoftBank Group, Bloomberg reports.

Samsung has committed $10 million to the round, using the investment to keep strategic visibility into Skild’s technology and talent pipeline without committing to full-scale acquisition. According to Bloomberg, Nvidia is contributing $25 million, reinforcing its growing push into what CEO Jensen Huang has described as the “physical AI” revolution.

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The round follows Skild’s $300 million Series A raise in July 2024, which Skild AI says included backing from Lightspeed Venture Partners, Coatue, SoftBank, and Amazon (NASDAQ:AMZN) founder Jeff Bezos through Bezos Expeditions.

Skild AI says it is developing a shared “foundation model” that acts as a general-purpose brain for a wide range of robots across manipulation, locomotion, and navigation tasks. The startup notes that this model represents a step change in how robotic systems will scale, with long-term ambitions to build artificial general intelligence grounded in the physical world.

Skild AI positions its technology as a scalable solution to the U.S. labor shortage, particularly in high-risk industries like oil rigs and manufacturing. A study by Deloitte and The Manufacturing Institute projects that over 2.1 million U.S. manufacturing jobs could go unfilled by 2030, and the startup believes its adaptable foundation model could help rebalance labor across sectors.

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Nvidia’s investment aligns with its broader ecosystem strategy to integrate intelligent robotics into everyday environments, from homes to factories to autonomous vehicles. According to Bloomberg, the company already supports startups like Figure AI and Serve Robotics and offers the necessary semiconductors and software infrastructure to support robotics deployment at scale.