中金 | 具身智能系列（四）：机器人大模型，多模融智，硅基具升

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].