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 recent funding round has raised almost $200 million, as per a regulatory filing. It comes on the heels of a $400 million Series B round led by Radical Ventures in June, which pegged the company’s value at around $2 billion, as reported by the same sources. With this new funding, the total amount raised in this round has now reached $600 million.

Currently, neither Generalist nor 8VC has provided comments in response to inquiries.

Founded in 2024 by former Google DeepMind researchers Pete Florence and Andy Zeng, alongside ex-Boston Dynamics engineer Andrew Barry, Generalist has primarily received backing from 8VC and Radical Ventures, as well as notable investors like Nvidia, Union Square Ventures, Bezos Expeditions, and AI expert Fei-Fei Li.

Until recently, Generalist has operated largely beneath the surface, receiving minimal media attention.

The startup aims to develop an AI foundation model to improve robot-human interactions. Generalist claims that its newly introduced Gen 1.5 model enables robots to learn new skills from short video demonstrations ranging from 3 to 12 seconds.

An insider mentioned that Generalist is working with a limited number of clients to tailor the model for specific uses based on their input.

In its pursuit of a flexible neural architecture that can be adapted for different robots, Generalist faces tough competition. Major competitors include Physical Intelligence, valued at approximately $11 billion, SoftBank-backed Skild AI, estimated at around $14 billion, and Genesis AI, which reportedly sought funding last month with a valuation of $3 billion.

The uptick in investment indicates that some investors believe the robotics sector is approaching its own “ChatGPT moment,” imagining a future in which robots can handle various tasks without needing specific training for each role. However, due to the complexities involved in training robots with the extensive data required for large language models, some venture capitalists warn that a truly universal robotics model may still take years to develop.