Key facts
- Robotics startup Generalist has raised nearly $200 million in additional capital.
- The company is now valued at $3 billion.
- The funding was led by 8VC and is an extension of a prior $400 million Series B round.
- The total funding for the Series B round now stands at $600 million.
- Generalist is developing an AI foundation model for robots capable of learning tasks from video demonstrations.
Robotics startup Generalist has achieved a $3 billion valuation following the successful closure of an extended Series B funding round, according to sources familiar with the matter. The company raised nearly $200 million in this latest capital infusion, led by venture capital firm 8VC.
This new funding is an extension of the $400 million Series B round initially announced in June, which was led by Radical Ventures and valued the company at $2 billion. With the additional $200 million, the total funding for the Series B round now amounts to $600 million.
Generalist, founded in 2024 by former Google DeepMind researchers Pete Florence and Andy Zeng, alongside former Boston Dynamics engineer Andrew Barry, is focused on developing an AI foundation model designed to work across a variety of robots. The startup recently released its Gen 1.5 model, which it claims enables robots to learn new tasks from brief video demonstrations lasting between 3 to 12 seconds.
The company has been operating with limited public visibility until recently and is currently collaborating with a select group of customers to refine its model for specific applications. Generalist's ambition to create a versatile AI for robots places it in competition with other notable startups in the field, such as Physical Intelligence, reportedly valued at $11 billion, and SoftBank-backed Skild AI, valued at $14 billion. Genesis AI was also reportedly in talks to raise capital at a $3 billion valuation.
The significant investment in Generalist reflects a broader investor confidence in the potential for robotics to experience a "ChatGPT moment," where robots could perform general tasks without explicit, individual training. However, some venture capitalists caution that achieving a truly general robotics model may still be several years away, given the inherent limitations compared to training LLMs on vast internet data.