天娱数科：用物理AI撬动智能新时代

Core Viewpoint - The rise of physical AI represents a significant paradigm shift in artificial intelligence, moving from algorithmic interactions in virtual environments to real-world interactions, emphasizing the need for machines to understand and interact with their physical surroundings [1][2] Group 1: Physical AI Development - The company has developed the Behavision platform, which integrates a "perception-reasoning-execution" capability, positioning itself as a leader in the physical AI sector [1] - Physical AI requires a deep understanding of physical properties such as geometric structures, material characteristics, motion laws, and interaction logic [1] - The Behavision platform is focused on creating a key data paradigm called 3D hinge data, designed specifically for training physical AI, which includes understanding the mechanics of objects like doors and drawers [1] Group 2: Data Accumulation and Model Generalization - The company has established a 3D motion capture and multimodal data collection base, accumulating 1.5 million 3D data points and 650,000 multimodal data points, including 200,000 specialized data for robot task training [1][2] - The Behavision platform enhances model generalization through a Real2Sim2Real approach, combining real and simulated data to improve adaptability in complex real-world environments [2] - The platform supports a standardized classification system for robotic bodies and an atomic skill library, enabling quick adaptation across various scenarios such as service, industrial, and logistics [2]