11月5日，第八届中国国际进口博览会在上海开幕。在第八届虹桥国际经济论坛上，针对机器人大模型 发展的核心问题，宇树科技股份有限公司创始人、董事长王兴兴指出，当前发展制约因素在于模型架构 与数据质量两方面，两者需协同改进。他认为，现有模型结构的泛化能力已显不足，需进行结构性创 新；而在数据层面，大规模、高质量数据的采集与评估仍是行业瓶颈。"希望大家花更多时间，而不是 单单一股脑去采集大量数据，或者一股脑把模型规模做大，我觉得这可能稍微有点盲目了。"王兴兴呼 吁，业界应在模型创新与数据质量上投入更多理性思考。 ...

Group 1 - The core viewpoint is that large models for robotics are key to overcoming traditional control bottlenecks and advancing towards general embodied intelligence [1][2] - The industry is currently exploring development directions based on large language models, autonomous driving models, and multimodal models, shifting focus towards "small brain + big brain" system development [1][2] - Only a few companies with full-stack technical capabilities, resource integration advantages, and long-term strategic vision are expected to define the core standards of "embodied intelligence" in the future [1][4] Group 2 - Traditional robots exhibit strong specificity in tasks, scenarios, and data, leading to weak generalization capabilities and difficulty in complex environments [2] - Large language models, while mature in natural language processing, cannot directly address physical operation issues in robotics and face challenges in integration with robotic technologies [3] - The commercial paths of "hardware-first" and "model-first" each have their characteristics and advantages, with most companies likely focusing on specific verticals to achieve "general/flexible" applications [4]

Core Viewpoint - The development of large models for robotics is seen as a key pathway to overcoming traditional control bottlenecks and advancing towards general embodied intelligence [2][4][18]. Group 1: Importance of Large Models in Robotics - Large models can address the fundamental issue of robots lacking physical "common sense" by integrating multimodal information such as vision and touch [4][18]. - The industry consensus is shifting towards the development of "small brain + big brain" systems, indicating a focus on foundational capabilities for robots to be applied in various scenarios like smart manufacturing and home services [18][36]. - The transition from humanoid robots to systems that leverage large models reflects a response to national strategies and societal needs, particularly in addressing labor shortages in service industries [18][36]. Group 2: Limitations of Existing Models - Current mature models, such as large language models, have limitations in directly solving physical operation problems for robots and often exhibit "hallucination" phenomena [4][24]. - While large language models excel in natural language processing, they cannot fully empower robots due to their inability to understand physical world causality, which is crucial for executing tasks in real environments [24][26]. - The challenges faced by robots are more complex than those in autonomous driving, requiring greater generalization and adaptability to diverse and unstructured environments [4][24]. Group 3: Commercialization Pathways - Two primary commercialization pathways are identified: "hardware-first" led by automotive and robotics companies, and "model-first" led by AI companies, each with distinct advantages [5][40]. - Most companies are likely to focus on specific vertical applications, achieving "general/flexible" capabilities, while only a few with full-stack capabilities may define the standards for "embodied intelligence" [5][40][43]. - The market is experiencing a significant increase in investment, with a reported 80% growth in financing events in the first half of 2025 compared to the same period in 2024, indicating heightened interest in the robotics sector [36]. Group 4: Future Trends and Challenges - The robotics industry is expected to evolve towards a model of specialized division of labor, moving away from the current "full-chain self-research" approach [46]. - The gap between market expectations and actual robotic capabilities continues to widen, with increasing demands for robots to perform complex tasks beyond simple automation [37][38]. - The integration of multimodal capabilities is essential for enhancing robots' perception and task execution, as traditional methods struggle to provide comprehensive environmental understanding [27][29].

Group 1 - The 2025 World Robot Conference showcased over 200 domestic and international robot companies, with more than 1,500 exhibits and over 100 new product launches, highlighting the rapid growth and innovation in the robotics industry [1] - In 2024, China's industrial robot market is projected to sell 302,000 units, maintaining its position as the largest industrial robot market globally for 12 consecutive years [1] - China accounted for two-thirds of global robot patent applications in 2024, indicating a strong focus on innovation within the industry [1] Group 2 - The complete industrial system and diverse application scenarios are driving rapid iterations in China's robotics sector, particularly in humanoid robots, following the Ministry of Industry and Information Technology's guidance on innovation [1] - Domestic companies have achieved nearly 100% self-research and development in core components like joint modules and sensors, providing a competitive edge over international counterparts [1] - The rise of large models in recent years has further supported the robotics industry, with humanoid robots aiming for "general intelligence" and emphasizing a complete chain of perception, decision-making, and execution [1][2] Group 3 - The rapid evolution of large models in robotics is attributed to breakthroughs in both architecture and data, with models now capable of understanding tasks and generating actions [2] - A structured data support system has been established, combining internet, simulation, and real machine action data to enhance model capabilities in real-world applications [2] - Future developments in embodied large models are expected to focus on modal expansion, reasoning mechanisms, and data composition, potentially incorporating additional sensory channels [2] Group 4 - At the robot conference, over 50 complete machine companies presented hundreds of humanoid robot products, expanding application scenarios [3] - The evolution of robots is anticipated to accelerate, with general-purpose robots expected to gradually enter the consumer market within the next 3 to 5 years [3] - Two key value considerations for robots in practical applications are the data value of tasks and the economic value provided to customers by automating tedious and low-value labor tasks [3]