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

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

This funding round raised nearly $200 million, according to a regulatory filing. It follows a $400 million Series B round led by Radical Ventures in June, which valued the company at approximately $2 billion, as reported by the same sources. With this new investment, the total amount raised in this round has now reached $600 million.

As of now, Generalist and 8VC have not responded to requests for comments.

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

Until recently, Generalist has been mostly under the radar, garnering minimal media coverage.

The startup focuses on developing an AI foundation model aimed at improving robot interactions. Generalist claims that its newly introduced Gen 1.5 model enables robots to learn new skills from short video demonstrations that last between 3 and 12 seconds.

One insider mentioned that Generalist is working with a select group of clients to tailor the model for specific uses based on their feedback.

In pursuit of a versatile neural architecture suitable for various robots, Generalist encounters competition. Notable rivals include Physical Intelligence, valued at around $11 billion, SoftBank-backed Skild AI, estimated to be worth approximately $14 billion, and Genesis AI, which reportedly sought funding last month at a valuation of $3 billion.

The uptick in investment indicates that some investors believe the robotics industry is approaching its own “ChatGPT moment,” envisioning a future where robots can execute multiple tasks without needing specific training for each role. However, due to the complexities of training robots with the extensive amounts of internet data utilized by large language models, some venture capitalists warn that a truly universal robotics model may still be years away.