
MHS gives AI agents a shared way to read from and control physical devices, but physical reasoning remains a key limitation.
Robotics startup Generalist is now valued at $3 billion after nearly $200 million in additional capital, according to TechCrunch, extending a Series B round tied to major investor interest in physical AI.

Generalist is now valued at $3 billion after raising additional capital led by 8VC, according to two people with knowledge of the funding cited by TechCrunch. The new capital totals nearly $200 million, according to a regulatory filing, and extends the company’s $400 million Series B led by Radical Ventures. That earlier round was announced in June at a $2 billion valuation, bringing the total round to $600 million. Generalist and 8VC did not respond to TechCrunch’s request for comment.
Generalist was founded in 2024 by former Google DeepMind researchers Pete Florence and Andy Zeng, along with former Boston Dynamics engineer Andrew Barry. Its early backers include 8VC, Radical Ventures, Nvidia, Union Square Ventures, Bezos Expeditions, and AI researcher Fei-Fei Li. The company had operated quietly and with little publicity until recently, according to TechCrunch.
Generalist is developing an AI foundation model designed to work with various robots. The company claims its Gen 1.5 model enables robots to master new tasks from video demonstrations as short as 3 to 12 seconds. The startup is also working with a handful of customers and using their feedback to tailor the model for specific use cases, according to one source cited by TechCrunch.
Generalist is part of a broader push to build a “brain” for a wide range of robots. TechCrunch notes competitors including Physical Intelligence, reportedly valued at $11 billion; SoftBank-backed Skild AI, valued at $14 billion; and Genesis AI, which was in talks last month to raise at a $3 billion valuation. The funding wave reflects investor interest in a possible robotics “ChatGPT moment,” where robots can perform general tasks without explicit training for each one. Still, some VCs warn that truly general robotics models may be years away because robots cannot be trained on the full internet in the same way large language models can.

MHS gives AI agents a shared way to read from and control physical devices, but physical reasoning remains a key limitation.
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