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

Generalist, a startup operating in the robotics industry, has reached a valuation of $3 billion after a recent funding event led by 8VC, according to sources familiar with the investment.

This funding event has successfully garnered nearly $200 million, as outlined in a regulatory document. This follows a previous $400 million Series B funding round initiated by Radical Ventures in June, during which the company’s valuation stood at $2 billion, as per the same sources. With this new infusion of capital, the total funding for this round has now increased to $600 million.

Neither Generalist nor 8VC has replied to inquiries for comments.

Established in 2024, Generalist was founded by ex-Google DeepMind researchers Pete Florence and Andy Zeng, along with former Boston Dynamics engineer Andrew Barry. The startup originally received backing from 8VC and Radical Ventures, along with notable investors such as Nvidia, Union Square Ventures, Bezos Expeditions, and AI expert Fei-Fei Li.

Until recently, Generalist operated largely under the radar, garnering minimal media coverage.

The startup is focused on creating an AI foundation model aimed at improving robot interactions. Generalist claims its newly unveiled Gen 1.5 model enables robots to learn new tasks through video demonstrations that last between 3 to 12 seconds.

According to one source, Generalist is working with a select group of clients to tailor the model for specific usages based on their feedback.

Generalist is not the sole contender in the race for a multi-purpose neural framework applicable to various robots. Rivals such as Physical Intelligence, valued at approximately $11 billion, and SoftBank-backed Skild AI, worth around $14 billion, along with Genesis AI, which reportedly sought funding last month at a $3 billion valuation, are also players in this competitive landscape.

The surge in investment suggests that certain investors believe the robotics sector may soon witness its own “ChatGPT moment,” hinting at a future where robots can execute multiple tasks without the need for specific training for each individual task. However, due to the challenges associated with training robots using vast amounts of internet data utilized by large language models, some venture capitalists warn that realizing a truly universal robotics model may still be years away.