FieldAI secured $405 million across previously undisclosed rounds to build general-purpose embodied AI models for robots and autonomous vehicles. The latest $314 million tranche in August was co-led by Bezos Expedition, Prysm, and Temasek, with additional investment from Khosla Ventures, Intel Capital, and Canaan Partners. FieldAI’s Field Foundation Models are rooted in physics to provide robots with an additional information layer for decision-making, enabling quicker adaptation to new environments while explicitly accounting for risk and safety. The physics-informed approach aims to close a fundamental gap in robotics where traditional models struggle to manage safety when operating in unfamiliar, real-world settings.
FieldAI, an Irvine, California-based, has raised $405 million across multiple previously undisclosed rounds to develop what it calls "foundational embodied AI models" - essentially robot brains designed to help everything from humanoids to quadrupeds to self-driving cars adapt to new environments. The company announced the funding Wednesday; the most recent round raised $314 million in August and was co-led by Bezos Expedition, Prysm and Temasek. FieldAI's other backers include Khosla Ventures, Intel Capital, and Canaan Partners, among others.
Unlike traditional AI that processes text or images, embodied AI refers to AI that controls physical robots moving through real-world environments. FieldAI builds "Field Foundation Models" which are general-purpose embodied AI models rooted in physics. This approach gives robots the ability to quickly learn and adapt to new environments while being conscious of risk, FieldAI founder and CEO Ali Agha told TechCrunch in an interview.
"The mission is to build a single robot brain that can generalize across different robot types and a diverse set of environments," Agha said. "To get there, you need to manage risk and safety as you go to these new environments. And that has been a fundamental gap in robotics, that traditional models and traditional approaches were never designed to manage that risk and safety."
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