直击进博会丨具身智能的“ChatGPT时刻”何时到来？宇树王兴兴提了几个关键问题

Core Insights - The development of humanoid robots is heavily dependent on the progress of embodied intelligence models, with a focus on achieving significant breakthroughs in the next one to two years [5][6][7] Group 1: Current State of Humanoid Robots - The key technology for humanoid robots is the advancement of large models, which is currently progressing slower than expected [5] - The current stage of embodied robots is likened to the early years before the release of ChatGPT, where the direction is clear but breakthroughs have not yet been achieved [6] Group 2: Future Aspirations - A significant milestone would be achieving a humanoid robot that can complete 80% of tasks in 80% of unfamiliar scenarios using natural language commands, marking a "ChatGPT moment" for the field [6][7] Group 3: Challenges in Development - There are two main areas for improvement: model architecture and data quality. Current models lack generalization capabilities, and data collection remains a significant challenge [8] - The mainstream training paths for humanoid robots face issues with generalization, where performance drops significantly when changing objects or environments [9] Group 4: Specific Technical Issues - The alignment between video generation and robot control is a critical bottleneck, as current video models can generate high-quality scenarios but struggle to translate these into precise actions in the real world [9]