How Physical AI is Moving from Labs to the Real World
Speech Synopsis
Robots can only truly understand the world and learn to perform real tasks through long-term deployment in real-world environments, where they encounter unpredictable physical variables and complex scenarios.
- Remote Operation Network: Powered by the remote operation network, robots can continuously work in real-world applications — addressing scenarios that people are unwilling or unable to access, while collecting valuable real-world robot data for continuous learning and model improvement.
- Data as the Next Battleground: The future competition in embodied AI will be defined by access to high-quality real-world data.
- "Robots Built for Real Work": Designed from the very beginning for long-duration, reliable operation. By addressing seasonal labor shortages and replacing repetitive physical tasks, they help reduce operational risks caused by workforce fluctuations while significantly lowering overall labor costs.
Speaker
Eric Zheng holds a Master's degree in Mechanical Engineering from Beihang University. As one of the early pioneers in the collaborative robot industry in China, he has more than 10 years of experience in robotic arm technologies and industrial applications. He is recognized as a pioneer in defining ultra-lightweight humanoid robotic arms and achieving their mass production at scale. In 2018, based on his deep technical expertise and industry insights, Eric Zheng founded RealMan Intelligent.
Under his leadership, RealMan has achieved full in-house development of core robotic components, including controllers, drivers, motors, and reducers, breaking through the long-standing dependency on imported key components. Today, RealMan is positioned as a global system-level infrastructure platform company for the era of embodied intelligence, building the foundation for next-generation intelligent robots.