"We have millions of miles of data collected in the most complicated urban settings possible, and that data is incredibly important for training any sort of useful and reliable real world AI systems," Rash said. "We're now at the point where we have sufficient data scale where I think we can start really accelerating a lot of the research happening around physical AI."
"[Zhou] is one of the leading researchers in the whole world on robot navigation, reinforcement learning, and a lot of the technologies and areas of research that are highly relevant for us," Rash said. "He's been already very capable of recruiting some of the top researchers in the world who he's worked with in the past to come join Coco and help accelerate things on our end"
Coco Robotics has amassed five years of operational data from its last-mile delivery robots operating in complex urban environments. The startup established a physical AI lab helmed by UCLA professor Bolei Zhou, who also joined as chief AI scientist. The company intends to leverage millions of miles of real-world data to improve robot autonomy and reduce delivery costs. Early operations relied on teleoperators to navigate obstacles, and the new research focus aims to accelerate development in robot navigation, reinforcement learning, computer vision, and recruiting top researchers to enhance physical AI capabilities.
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