Co-founder Lachy Groom has stressed an insatiable appetite for capital and computing power, signaling that more computing resources will be necessary to advance the company’s ambitions.

TechCrunch previously visited Physical Intelligence in January, where co-founder Sergey Levine described the robot-facing ChatGPT-like approach.

The company’s approach could transform multiple sectors, including logistics, manufacturing, healthcare, and domestic services, by enabling versatile robotic systems.

The funding round is framed as a broader vote of confidence in versatile, AI-driven robotics and its potential impact on automation and the future of work.

Physical Intelligence is reportedly seeking about $1 billion in new funding at a valuation north of $11 billion, a substantial jump from the roughly $5.6 billion valuation seen four months earlier.

The technology is being tested in practical settings, with tasks like folding laundry and automating packaging illustrating the move toward real-world deployment.

The founders describe the mission as ChatGPT for robots, emphasizing general-purpose AI models to power adaptable robots capable of diverse tasks.

The company highlights scalable AI infrastructure as essential for advancing next-generation robotic intelligence, reflecting a long-horizon strategy over short-term revenue.

Physical Intelligence says there is no fixed commercialization timeline; the focus is on foundational research and developing intelligent, general-purpose robotics, with funding intended to accelerate AI capabilities rather than push a market-ready product on a strict schedule.

The funding round is drawing prominent investors, including Founders Fund, Lightspeed Venture Partners, Thrive Capital, and Lux Capital, with ongoing discussions and potential participation from existing backers.

As of January, the company had raised over $1 billion and employed roughly 80 people, continuing to work on enabling robots to perform a wide range of tasks from household chores to more complex operations.

Industry watchers see rising momentum in the physical AI space, where machine learning is directly applied to robotics for real-world automation and strong investor interest.