Core Viewpoint - The article discusses the transition from autonomous driving technology to robotics, highlighting the challenges and opportunities in the robotics industry, particularly in the context of embodied intelligence and the potential impact of new models like VGGT on 3D perception and robotics applications [5][7][60]. Group 1: Industry Trends - The robotics industry is at a pivotal moment, with significant technological advancements and a shift towards embodied intelligence, which is seen as the next frontier for AI [5][7]. - The article emphasizes the differences between the autonomous driving and robotics sectors, noting that while autonomous driving has reached a level of standardization, robotics is still exploring diverse hardware forms and algorithms [10][14]. - The VGGT model is introduced as a potential game-changer for 3D geometry, akin to how Transformers revolutionized natural language processing, indicating a shift towards unified solutions for 3D perception [6][67]. Group 2: Technological Migration - The migration of technology from autonomous driving to robotics is highlighted, with companies like DiGua Robotics leveraging experiences from the autonomous driving sector to enhance their robotics platforms [14][18]. - The challenges of hardware diversity in robotics are discussed, as the lack of standardization complicates data accumulation and algorithm development [10][14]. - The article outlines the evolution of autonomous driving algorithms from modular approaches to end-to-end systems, which are now being adapted for robotics applications [25][27]. Group 3: VGGT and Its Implications - VGGT is presented as a foundational model that could redefine 3D visual technology, offering a new paradigm for solving traditional geometric problems through large-scale data and models [55][67]. - The potential for VGGT to replace expensive depth cameras with cheaper RGB cameras is discussed, which could significantly reduce the cost of robotics systems [64][66]. - The article concludes that VGGT represents a significant advancement in the field of 3D vision, marking the entry of large models into the realm of geometric processing [67][68].