Zhiyuan Robotics, in partnership with InnoAcademy and the University of Hong Kong, has unveiled a significant advancement in robot learning. The collaborative team has conducted a comprehensive exploration of three crucial aspects of data diversity in robot manipulation learning: task diversity, robot morphology diversity, and expert diversity. This study challenges the conventional wisdom that "more diverse data inherently leads to better outcomes." This groundbreaking research offers innovative theoretical insights and practical strategies for developing scalable robot operating systems.