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Robotics AI startup Generalist reportedly raises $200M

Generalist AI Inc., a startup that develops artificial intelligence software for robots, has reportedly raised $200 million in funding. Axios today cited a source as saying that 8VC led the investment. It was reportedly joined by a number of unnamed existing investors. Generalist’s previous $400 million round in June included the participation of Nvidia Corp., […] The post Robotics AI startup…

Robotics AI startup Generalist reportedly raises $200M

Generalist AI Inc., a startup specializing in AI software for robots, has reportedly secured $200 million in funding, according to Axios. The investment was led by 8VC, with the participation of various unnamed existing investors. Generalist's prior $400 million funding round in June saw involvement from Nvidia Corp., Bezos Expeditions, and over a dozen additional investors.

This latest round follows the debut of Generalist's new AI model, Gen-1.5, designed to power robotic arms. The model promises to drastically cut the time required to create factory automation workflows, as developers previously had to manually program robotic arms for each task. Gen-1.5 allows users to teach robots new tasks by demonstration, either through hand gestures captured by the robot's built-in cameras or sensors, or via simulated robot footage.

When provided with a single example of a task, Gen-1.5 achieved a 59% task completion rate, which increased to 83% with additional examples. The company has tested Gen-1.5 on 10 sample tasks and claims it is the first AI model capable of learning a wide range of robotics tasks from a single or a few examples. The exact use of the new funding is not specified, but it is likely to be allocated towards AI infrastructure, given Gen-1.5's extensive training period.

Nvidia's involvement in the funding round suggests the company will utilize the chipmaker's graphics cards, specifically Nvidia's AI chips called Jetson, which are optimized for robotic applications.

Written by urgent.news from SiliconANGLE's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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