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 financing activities and technological advancements of the company Spirit AI, which focuses on embodied intelligence and robotics, indicating a growing interest and investment in this sector. Financing and Investment - Spirit AI announced the completion of a 528 million yuan Pre-A round financing, marking its fourth round of funding [1][2]. - The company was founded in February 2024 and has rapidly completed three rounds of financing, totaling 200 million yuan in seed and angel rounds [3]. - The latest Pre-A round was led by Prosperity7 Ventures, with participation from various investors including China Merchants Venture Capital and others [3][4]. Technological Developments - Spirit AI is developing a self-research VLA Spirit v1 prototype, which has successfully performed complex tasks such as folding clothes, overcoming challenges related to the variability of fabric [9][12][13]. - The company plans to release the official version of Spirit v1 soon [14]. - Spirit AI is also set to launch its first commercial humanoid robot named Moz1, which features high precision and 26 degrees of freedom [15][18]. - Moz1's integrated joint power density is 15% higher than Tesla's humanoid robot Optimus [19]. Company Background and Vision - Spirit AI focuses on high-value sectors such as smart manufacturing, logistics, and healthcare, with plans to deliver hundreds of products by 2025 [22]. - The company collaborates with top universities for talent development and has a team with backgrounds from prestigious institutions and companies [24]. - The founder and CEO, Han Fengtao, has a strong background in robotics and aims to make robots accessible to a significant portion of the population in the future [25][30][31]. Industry Trends - The embodied intelligence sector is experiencing rapid growth, with multiple companies announcing financing and technological advancements in March 2024 [32][33]. - The article mentions a significant investment trend, with companies like ZhiYuan Robotics and others also securing substantial funding [34][38]. - A recent conference highlighted key directions for embodied intelligence, indicating a structured approach to advancing the field [45]. Market Outlook - Goldman Sachs predicts that the global humanoid robot market will reach $154 billion by 2035, reflecting the potential for growth in this industry [47]. - The article discusses the anticipated arrival of a "ChatGPT moment" for embodied intelligence, suggesting that significant advancements will come from long-term development rather than sudden breakthroughs [49].