Stock Markets March 16, 2026

Skild AI to Run Robots in Foxconn Plant Building Nvidia GPUs, Partners with ABB and Universal Robots

Startup’s generalized AI model will be deployed on assembly-line robots in Houston as part of a broader push to scale industrial automation

By Nina Shah
Skild AI to Run Robots in Foxconn Plant Building Nvidia GPUs, Partners with ABB and Universal Robots

Skild AI said its generalized artificial intelligence model will operate robots on Foxconn assembly lines in Houston, where Nvidia’s Blackwell GPU racks are assembled. The company also announced partnerships with ABB Robotics and Teradyne’s Universal Robots to integrate its software across industrial robots, aiming to create a general-purpose "brain" for manufacturing automation.

Key Points

  • Skild AI will run robots on Foxconn’s Houston assembly lines where Nvidia’s Blackwell GPU racks are built, representing an early commercial use of generalized physical AI.
  • Partnerships with ABB Robotics and Teradyne’s Universal Robots aim to embed Skild AI’s software across large installed bases of industrial robots to accelerate scalability and data collection.
  • The moves align with increased U.S. manufacturing investments and industry comments that reshoring advanced manufacturing will depend heavily on automation, affecting electronics, pharmaceuticals and semiconductors.

Skild AI announced that its generalized artificial intelligence model will be deployed to control robots working on Foxconn’s assembly lines in Houston, the site where Nvidia’s Blackwell GPU server racks are manufactured. The company described the move as an early commercial application of generalized physical AI.

Backed by Nvidia and SoftBank, Skild AI said on Monday it will embed its software with partners ABB Robotics and Teradyne’s Universal Robots to expand deployment across industrial robots. The startup positions its model as a single, adaptable "brain" that can be applied across different robotic platforms rather than limiting machines to one repetitive programmed task.

Skild AI’s leadership says the approach addresses a core constraint of typical robotics systems, which often require extensive engineering work to change the tasks they perform. "If we partner with robotic OEMs (original equipment manufacturers) that already have hundreds of thousands of robots deployed, it gives us a path to extreme scalability and establishes the data flywheel," Skild AI CEO Deepak Pathak said.

The planned integrations with ABB and Universal Robots are intended to broaden the data streams available to train Skild AI’s model by embedding the software into a larger installed base of robots.

The announcements come as the United States accelerates efforts to rebuild domestic manufacturing capacity. The article notes that new U.S. production investments totaling roughly $1.2 trillion were announced in 2025, driven by electronics, pharmaceutical and semiconductor manufacturers. Industry executives cited in the announcement emphasize that major reshoring of advanced manufacturing will rely heavily on automation.

Nvidia has signaled its own U.S.-focused production plans as part of the broader AI push. "We are building half a trillion dollars’ worth of infrastructure in the next three to four years in the United States. For that to happen, these factories need to be more autonomous," Nvidia’s vice president of Robotics and Edge AI, Deepu Talla, said.

SoftBank, a backer of Skild AI, disclosed in October that it intends to acquire ABB’s robotics business for $5.38 billion, a transaction the firms expect to close in mid-to-late 2026. Earlier this year, Skild AI completed a $1.4 billion funding round led by Nvidia and SoftBank that valued the company at more than $14 billion.


Skild AI and its partners present this deployment as an initial commercial step toward scaling generalized AI control across factory floors. The company framed partnerships with established robotics manufacturers as a way to accelerate adoption by leveraging existing fleets of industrial robots.

No additional operational timelines, performance metrics or quantitative outcomes for the Houston deployment were provided in the announcement. The company described the effort as part of a broader strategy to integrate its model into industrial robotics ecosystems.

Risks

  • Integration risk - The article indicates that typical robotics systems need extensive engineering to change tasks, implying potential challenges and costs when embedding a generalized AI model across diverse robotic platforms; this impacts industrial automation and manufacturing operations.
  • Execution and scalability uncertainty - While partnerships with large OEMs are cited as a path to scalability, the announcement does not provide timelines or performance outcomes, leaving uncertainty about how quickly and effectively the software will scale across deployed robots; this affects robotics suppliers and factory operators.
  • Transaction and regulatory timing - SoftBank’s planned acquisition of ABB’s robotics business is expected to close in mid-to-late 2026, introducing timing and regulatory uncertainties that could influence deployment plans tied to ABB’s business integration; this impacts investors and the robotics sector.

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