Robotics Startup Generalist Reaches $3 Billion Valuation, According to Reports

Generalist, a startup concentrating on robotics, has achieved a valuation of $3 billion after a new funding round led by 8VC, according to sources familiar with the investment.

The recent funding amounts to nearly $200 million, as revealed in a regulatory document. This marks an extension of a prior $400 million Series B round driven by Radical Ventures in June, at which time the company’s valuation stood at $2 billion, according to the sources. With this fresh investment, the total funding for this round has escalated to $600 million.

Neither Generalist nor 8VC has responded to requests for comments.

Founded in 2024, Generalist was launched by former Google DeepMind researchers Pete Florence and Andy Zeng, along with ex-Boston Dynamics engineer Andrew Barry. The company received early backing from 8VC and Radical Ventures, alongside notable investors like Nvidia, Union Square Ventures, Bezos Expeditions, and AI researcher Fei-Fei Li.

Until recently, Generalist had been operating mostly under the radar, attracting minimal media coverage.

The startup is developing an AI foundation model aimed at interfacing with various robots. It asserts that its newly released Gen 1.5 model enables robots to learn new tasks using video examples that last only 3 to 12 seconds.

Generalist is working with a select group of clients to enhance the model for specific applications based on their input, according to one source.

Generalist is not alone in its pursuit of a neural framework for a diverse array of robots. Rivals include Physical Intelligence, valued at approximately $11 billion, and SoftBank-supported Skild AI, worth around $14 billion, as well as Genesis AI, which reportedly engaged in discussions last month to secure funding at a $3 billion valuation.

The influx of investments signals a belief among some investors that the robotics industry might soon witness its own “ChatGPT moment,” hinting at a future where robots could perform a wide variety of tasks without needing explicit training for each one. However, due to the challenges involved in training robots with the extensive amount of internet data utilized by large language models, some venture capitalists caution that achieving a truly general robotics model may still be years in the making.