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

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

The funding round has raised nearly $200 million, as revealed in a regulatory filing. This follows an earlier $400 million Series B round initiated by Radical Ventures in June, when the company was valued at $2 billion, the sources report. With this latest influx of capital, the total funding for this round has now reached $600 million.

Both Generalist and 8VC have not responded to requests for comments.

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

Up until recently, Generalist operated largely in the background, receiving minimal media coverage.

The startup is working on an AI foundation model that aims to facilitate interactions with various robots. Generalist claims its recently launched Gen 1.5 model enables robots to learn new tasks by using video demonstrations lasting between 3 to 12 seconds.

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

Generalist is not the sole contender pursuing a versatile neural framework for diverse robots. Competitors such as Physical Intelligence, valued at about $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 in the mix.

The influx of investments suggests that some investors anticipate the robotics industry may soon experience its own “ChatGPT moment,” indicating a future where robots can undertake a variety of tasks without needing specific training for each one. However, due to the complexities involved in training robots with the extensive amounts of internet data used by large language models, some venture capitalists warn that achieving a genuinely universal robotics model may still be several years away.