特斯拉Optimus：世界模型会终结一切

Core Viewpoint - Tesla has shifted from imitation learning to video learning and is now focusing on developing a world model as the ultimate solution for its Optimus robot, which will enable it to understand and interact with the physical world like a child learns about its environment [5][12][17]. Group 1: Learning Approaches - Imitation learning achieved end-to-end processing but faced issues with data generalization [6]. - Video learning addresses data diversity but struggles with scale and cost [6]. - The world model is proposed as a solution that encompasses physical knowledge of the real world, allowing robots to learn autonomously [6][12]. Group 2: World Model Development - The world model is a large-scale model that learns from real-world videos, understanding physical laws such as gravity and material properties [6][12]. - Google's Genie3 is highlighted as an example of a world model that creates an interactive 3D physical environment, allowing users to engage with it [9][11]. Group 3: Application to Robotics - The Optimus robot will utilize a small amount of real-world video to fine-tune its understanding of physical laws and its own mechanics [12][14]. - Engineers can generate vast amounts of realistic simulation videos based on simple natural language commands, which can then be used to train the robot's AI efficiently [14][16]. - This method allows for near-zero-cost and zero-risk trial-and-error learning in virtual environments, significantly enhancing the robot's robustness and adaptability [16]. Group 4: Industry Context - Many companies in the autonomous driving sector have not yet achieved end-to-end solutions and are still in the earlier stages of data collection and imitation learning [17]. - The article emphasizes the long journey ahead for Tesla's Optimus robot to fully realize the potential of the world model, contrasting it with the current state of many domestic humanoid robot companies [17].