Core Viewpoint - The "fast-slow dual system" design in robotics is gaining attention as it allows robots to balance rapid responses to environmental changes with thoughtful, complex decision-making, inspired by human cognitive processes [1][3][4]. Group 1: Fast-Slow Dual System Concept - The fast system (System 1) operates instinctively and automatically, while the slow system (System 2) engages in deliberate and conscious thought, enabling efficient decision-making [1][4]. - This decoupling of fast and slow systems allows for independent upgrades of AI algorithms without altering the stable control framework, reducing development complexity [1][4]. Group 2: Application in Robotics - The fast-slow dual system can address the challenge of balancing generality and practicality in robotics, enabling quick visual motion strategies and end-to-end training for rapid communication and interaction [3][4]. - For example, in a task like "grabbing a red block," the slow system handles perception and planning, while the fast system calculates the necessary torque for smooth movement, allowing for immediate responses to disturbances [3][4]. Group 3: Company Implementations - Various companies are adopting the fast-slow dual system, each with unique implementations but sharing the core inspiration from human cognitive dual-process theory [4][5]. - Companies like Figure AI, PI, and智平方 are developing models that emphasize the separation of planning and execution, allowing for asynchronous parallel processing and improved task execution in complex environments [6][9][12][13]. Group 4: Data Strategies and Training Methods - Companies such as 魔法原子 and 微亿智造 focus on collecting vast amounts of real-world data to minimize the gap between simulation and reality, while others like PI utilize synthetic data for efficient model training [5][28]. - The approaches vary from general models seeking ultimate generalization to specialized models targeting specific scenarios for reliability and efficiency [5][28]. Group 5: Specific Company Models - Figure AI's Helix model integrates a dual system architecture for high-frequency control of the robot's upper body, achieving end-to-end visual-language-action capabilities [6][7]. - PI's Hi Robot system combines high-level semantic planning with low-level action execution, enabling complex task management in home environments [9][10]. - 智平方's GOVLA model enhances task understanding and execution through a three-part architecture, achieving coordination in open environments [12][13]. - 星海图's G0 model focuses on real-time control and task planning in complex scenarios, supported by a high-quality dataset [15][16]. - 擎朗's KOM2.0 model emphasizes service industry applications, utilizing a dual system for environment perception and action generation [18][19]. - 星动纪元's ERA-42 model integrates high-level planning with low-level control, enhancing execution capabilities in dynamic environments [21][22]. - 节卡's JAKA EVO platform employs a dual system for task parsing and execution, facilitating rapid adaptation to new industrial scenarios [25][26]. - 微亿智造's architecture leverages a cloud-edge-end model to ensure scalable applications in complex industrial settings [28][30]. - 魔法原子’s model simulates human cognitive processes to enhance real-time response and long-term task planning [30][31]. - 灵初智能's Psi-R1 model combines planning and execution through a layered architecture, achieving high-level task management and precise control [33][34].

Core Viewpoint - The article highlights the recent A++ round financing of Shenzhen-based intelligent robotics company "Zhi Ping Fang," which raised several hundred million yuan, led by Shenzhen Capital Group, to enhance its core models and expand its production and global market presence [2][5]. Financing Overview - Zhi Ping Fang has completed seven rounds of financing this year, with significant investments from various firms, including over 100 million yuan from Shenzhen Capital Group in the latest round [3][5]. - The company has a history of substantial funding, with previous rounds including Pre-A and A+ financing, indicating strong investor confidence and interest in the robotics sector [3][5]. Company Background - Founded in April 2023, Zhi Ping Fang focuses on developing general-purpose intelligent embodied terminals and is recognized for pioneering the systematic research of AGI in the physical world [5][6]. - The founding team comprises top talents from leading tech companies and prestigious universities, enhancing the company's innovative capabilities [7][10]. Core Technology and Products - Zhi Ping Fang is a leader in the development of the VLA (Vision-Language-Action) model, which has become mainstream in the field of embodied intelligence [8][9]. - The company has launched the Alpha Brain model, which integrates spatial interaction and advanced AI capabilities, allowing for efficient human-robot interaction across various environments [9][12]. Commercialization Progress - The company has secured approximately 500 orders for its AlphaBot 2, which is deployed in sectors such as automotive, semiconductor, and public services, demonstrating its practical application in real-world scenarios [14][16]. - Zhi Ping Fang aims to achieve significant production milestones, targeting 10,000 units by 2028 and expanding to 1 million units by 2033 across diverse applications [16]. Industry Context - The article notes a trend of significant investment in the embodied intelligence sector, particularly from automotive companies and industry veterans transitioning from autonomous driving to robotics [21][22]. - The competition in the humanoid robot market is intensifying, with numerous automotive firms entering the space, although many face challenges related to genuine innovation and market differentiation [21][22].

Group 1 - The core point of the article is that the intelligent robotics company, Zhifang Technology Co., Ltd., has recently completed a new round of financing amounting to several hundred million yuan in Series A funding [1] - Zhifang has completed seven rounds of financing in the past six months, which is considered rare in the industry in terms of both pace and scale [1] - The funds from the Series A financing will be used for the iteration of the company's core large model "GOVLA" and the general-purpose intelligent robot "Alpha Bot," as well as for expanding self-built production lines and global market development [1]