大事不好：机器人学会预测未来了

Core Insights - Ant Group's LingBot-VA represents a significant advancement in general robotics, enabling robots to predict future actions before executing them, thus moving beyond traditional "observe-react" models [1][3][5] Group 1: Technological Advancements - LingBot-VA introduces a causal video-action world model that allows robots to imagine future scenarios before taking action, enhancing decision-making capabilities [3][5] - The model retains memory during long sequence tasks, demonstrating strong state awareness and the ability to adapt to new tasks with minimal examples [5][6] - The architecture separates visual understanding, physical reasoning, and action control, improving sample efficiency and generalization [6][7] Group 2: Performance and Testing - In real-world tests, LingBot-VA successfully handled complex tasks such as preparing breakfast and high-precision actions like cleaning test tubes, showcasing its stability and adaptability [21][22][25] - The model achieved a success rate of 92.93% in easy scenarios and 91.55% in hard scenarios on the RoboTwin 2.0 benchmark, outperforming competitors [28][30] - In the LIBERO benchmark, LingBot-VA achieved an average success rate of 98.5%, setting a new state-of-the-art record [30][31] Group 3: Industry Impact - The continuous open-sourcing of LingBot-VA and its predecessors signals a strategic move by Ant Group to establish leadership in the global robotics field [34][38] - The integration of video as a medium for reasoning and action in robotics represents a paradigm shift, addressing challenges in long tasks and complex environments [35][36] - The emergence of LingBot-VA positions world models as a central capability in robotics, evolving from mere action to thoughtful action [36][40]