Core Viewpoint - The article discusses the development and vision of the Li Auto Star Ring OS, emphasizing its role in the evolution from smart vehicles to space robots, and the importance of open-source collaboration in achieving technological advancements in the automotive industry [1][3]. Group 1: Background of Li Auto Star Ring OS - The Star Ring OS was announced as an open-source project on March 27, 2024, and has since undergone two significant version releases, gaining industry recognition [1]. - Smart vehicles are seen as the initial successful commercial application of space robots, serving as a critical step towards achieving general-purpose space robots [5][6]. Group 2: Trends in Space Robot Technology Development - The ultimate goal is to develop general-purpose space robots, with the feasibility proven by the success of smart vehicles and breakthroughs in core technologies like VLA (Vision-Language-Action Models) [7][9]. - Key trends include the pursuit of extreme hardware-software collaboration, centralized and efficient utilization of computing resources, system security as a foundational prerequisite, and embracing open-source for efficient co-construction [11][12]. Group 3: Issues with Classic Automotive Software Solutions - The classic automotive software architecture, which emerged in 2000, has led to an explosion in the number of electronic control units (ECUs), resulting in integration difficulties and poor reusability [15][18]. - The limitations of the classic approach include a modular design that creates information silos and a collaborative model that is open yet not fully open-source, hindering innovation and efficiency [18][20]. Group 4: Open Source Solutions - The Star Ring OS is designed as a cohesive system with four core components: AI computing system, intelligent real-time system, communication middleware, and information security system [25][26]. - The OS aims to provide a unified, collaborative, flexible, and secure digital foundation for space robots, addressing the identified contradictions in the development process [29][30]. Group 5: Open Source Ecosystem Construction - The open-source ecosystem aims to build a unified, open, and general intelligent system foundation for the space robot era, promoting industry collaboration and reducing costs [36][39]. - Achievements include significant cost savings, reduced development cycles, and enhanced performance, with the platform enabling efficient coordination and flexible deployment of vehicle control systems [40][41]. Group 6: Future Work Focus - Future efforts will concentrate on community building, expanding ecosystem partnerships, and enhancing industry influence, with a clear path towards open governance and robust technology development [44][48]. - The next steps include supporting new chip platforms, enhancing core capabilities, and providing efficient community development facilities [49][50].

Group 1 - The CEO of Li Auto, Li Xiang, stated that the company's future focus is on creating AI hardware terminals that are as disruptive as the iPhone, indicating a shift towards becoming a "space robot company" rather than a traditional automotive enterprise [1] - At the 2025 Global Finance Forum, experts highlighted that intelligent digital technologies are becoming a new engine for global economic growth, with AI expected to contribute up to 7% to global GDP over the next decade [2] - The Hong Kong Cyberport reported that over 90% of resources at its AI supercomputing center are now in use, with the government reserving HKD 30 billion (approximately CNY 27.38 billion) for subsidies to support AI model development and applications [2] Group 2 - The Hong Kong Cyberport announced that 20 projects have applied for funding, with 10 already approved, including a generative AI research center developing a foundational audio model and a dialogue tool similar to ChatGPT, which is already used by over 70% of government departments [2] - Japanese agricultural machinery manufacturer Kubota launched a generative AI service for farmers, aimed at answering questions related to crop cultivation, thereby lowering the entry barrier for new entrants into the agricultural sector [2]