汽车是什么？答案正被颠覆。 "当前，我国正处在数据驱动产业变革的时代，汽车不再只是传统机械产品，而是集数据采集、处理、 应用于一体的智能移动终端；产业发展正从单一技术驱动，转向'技术＋数据'双轮驱动，进入以数据赋 能全链条的新阶段。"国家数据局相关负责人在2025中国汽车产业发展（泰达）国际论坛上这样表示。 数据这一科技革命孕育的新引擎，不再满足于扮演辅助角色，而是呼啸而来，全面驱动汽车的研发、生 产、服务与管理变革。 数据赋能 汽车产业新机遇 数据正赋予汽车产业前所未有的时代机遇。国家数据局相关负责人指出，汽车行业数据规模大、场景 广、跨界融合性强，是发挥数据价值、释放数据红利的重点领域。 在智能化、网联化进程中，汽车产生海量高质量感知控制与交互数据，可以广泛应用于组合驾驶辅助及 自动驾驶大模型的训练、高精度地图的测绘、实时路况的感知、交通调度的优化。汽车数据不仅推动行 业技术演进，更支撑着智慧城市、智慧交通、能源互联等更广域数字化生态的构建。汽车行业不仅是数 据的应用方，更是数据要素价值实现的关键贡献者与战略支撑点。 东风奕派科技公司总经理汪俊君表示，中国汽车产业过去5年不仅实现了产销规模的跨越式增长，更 ...

刘东（下一代互联网国家工程中心主任、2025世界互联网名人堂入选者） 智能体互联网（Internet of Agents，IoA）是指由自主智能体组成的数字生态系统，这些智能体能够彼此 发现、通信并协作，在无人直接干预下完成复杂任务。IoA以智能体为主体，支持端到端的自主交互， 在智能体互联网范式下，智能体可以根据用户意图彼此对话、协同决策，直接采取行动来完成用户委托 的目标，标志着互联网走向了由"智能体驱动"的新型业态。 智能体互联网并非凭空出现，其技术突破伴随着需求牵引，使智能体互联网迅速升温。一方面，企业和 用户面对海量信息和复杂数字流程，自动化助手的价值日益凸显。Gartner（高德纳咨询公司——编者 注）预测到2028年，将有15%的日常事务由人工智能代理自主处理，约三分之一的企业应用将内嵌代理 智能。据估计，智能体相关市场规模未来几年将以年复合46%的惊人速度增长。智能体技术被视为改变 商业模式和生产生活方式的颠覆力量，各国政府和科技巨头纷纷将其纳入战略规划。另一方面，产业界 的投入和协作推动IoA生态加速成形。华为《智能世界2035》报告就预测，到2035年全球AI智能体数量 将达9000亿，超 ...

Core Insights - The automotive industry is undergoing a significant transformation driven by data, which is reshaping the ecosystem and enhancing R&D, production, service, and management [3][4][12] - The need for collaboration among government, industry, academia, and research institutions is emphasized to establish data standards and a secure, shareable data ecosystem [3][4] Group 1: Data as a Driving Force - Data is identified as a new engine for the automotive industry, driving comprehensive upgrades across various sectors [3] - The transition from a "product-driven" to a "user-driven" era is highlighted, necessitating a shift in product definition, marketing strategies, and service models [4] - Companies are urged to leverage big data analytics to better understand user behavior and enhance product and service offerings [4] Group 2: Breaking Down Data Silos - The issue of data fragmentation and siloed systems in the bus industry is addressed, with a focus on creating a comprehensive big data system that connects all aspects of operations [6] - A case study from Xiamen King Long Bus Company illustrates how data-driven approaches have reduced order delivery times from 60 days to under 35 days and improved operational efficiency [6] Group 3: Emerging Data Infrastructure - The concept of a "data space" is introduced as a new infrastructure that allows for secure and efficient data sharing across enterprises and industries [7] - The data space is characterized by its ability to maintain data sovereignty while facilitating trusted data flow, particularly in sensitive scenarios [7] Group 4: AI Applications in the Industry - AI is being utilized to enhance efficiency across the battery lifecycle, addressing challenges in research, manufacturing, and recycling [8] - The development of an integrated platform for intelligent product design and real-time monitoring of battery health is highlighted as a significant advancement [8] Group 5: Data Security and Governance - The importance of establishing a collaborative governance framework for data security and compliance is stressed, particularly in the context of smart connected vehicles [11] - A report on data governance in the automotive industry outlines current challenges and offers recommendations for improving data security and cross-border data flow [12] Group 6: Industry Consensus and Future Directions - The forum reached a consensus that data-driven approaches are essential for the digital transformation of the automotive industry [12] - Emphasis is placed on breaking down data barriers and enhancing cross-industry collaboration to maximize data resource utilization while ensuring security and privacy [12]

Core Insights - Multiple leading companies, including Huawei, China Unicom, and China Telecom, participated in the IDS data space testing certification ceremony in Beijing, highlighting the importance of data space technology development and practice [1] Group 1: Company Initiatives - Huawei and Digital China, as the first batch of companies to receive IDS component certification, emphasized that this certification is a crucial step towards promoting international data circulation standards and accelerating the globalization of the digital economy [1] - Other participating companies expressed their intention to leverage the IDS certification to expedite key technology upgrades and enhance data circulation support capabilities [1] Group 2: Industry Impact - The global data space is rapidly penetrating various industries such as manufacturing, healthcare, and finance, becoming a vital foundation for driving digital transformation across sectors [1] - The National Engineering Center for Next Generation Internet stated its commitment to enhancing the service capabilities of the IDS data space certification laboratory and developing more component and platform environment certification projects [1]

Core Insights - The data space is transitioning from a "technical concept" to an "international consensus" and "industry practice" [1] - Establishing a data circulation system based on trust is essential for unlocking the systemic value of the digital economy [1] - The construction of data spaces aims to create bridges rather than barriers, addressing the trends of fragmentation, involution, and reconstruction in global data circulation [1] Group 1: Standards and Frameworks - The "IEEE P1988 Cross-Border Data Space Architecture Standard" was officially launched, aiming to establish a unified framework and protocol for cross-border data flow [2] - The development of data spaces is characterized as both a technical and trust engineering endeavor, with an emphasis on embedding governance mechanisms and rule systems into the data space [2] Group 2: Testing and Certification - The IDS testing and certification system is highlighted as a crucial trust mechanism for data spaces, facilitating interoperability and ecological collaboration [3] - A rigorous and fair testing certification process is essential for measuring technological maturity and building a trust system [3] Group 3: Ecosystem Development - The next key tasks in data space development are focused on "verifying mechanisms" and "organizing ecosystems" rather than merely proposing concepts [4] - Data spaces are viewed as a new type of public good in the global digital era, requiring open collaboration and mutual trust for robust industry growth [4]

Core Insights - The establishment of the China Automotive Data Cross-Border Working Group aims to address common challenges in global automotive data flow and empower the international expansion of the Chinese automotive industry [1][5] - Liu Dong emphasized that data circulation is crucial for the global digital economy and technological innovation, particularly in enhancing international cooperation, optimizing supply chain management, and improving product intelligence in the automotive sector [2] Group 1: Data Circulation Challenges and Solutions - Liu Dong identified several challenges in data circulation, including institutional conflicts, trust crises, technological gaps, and a lack of standardization, which have resulted in data being trapped in "data islands" [2] - The proposed "IPv6 + Data Space" solution aims to create a logical data private network that facilitates cross-border data management, ensuring data autonomy and transforming automotive data from a resource into an asset [2][3] - The solution incorporates advanced technologies such as SRv6, APN6, and iFIT, and emphasizes dynamic compliance to ensure that outbound data protection levels are not lower than domestic standards [2] Group 2: Future Directions and Ecosystem Development - Liu Dong highlighted the ongoing development of an international standard system for data spaces, with the establishment of the IEEE1988 standard working group to support cross-border data flow in the automotive industry [3] - The future data space is envisioned as an ecosystem that integrates multiple operational platforms, distributed terminals, and specialized data services, underpinned by a high-speed intelligent network based on IPv6 [3][4] - The open data space network is expected to evolve from closed systems to interconnected frameworks, enhancing global collaboration in the automotive industry [4] Group 3: Global Data Ecosystem and Opportunities - The formation of a global data ecosystem that integrates rules, business, and technology is essential for the cross-border development of the Chinese automotive industry [5] - The establishment of the China Automotive Data Cross-Border Working Group signifies a shift from isolated efforts to a systematic approach in addressing data circulation challenges [5] - The global data ecosystem is anticipated to drive collaborative development in the automotive sector, enabling the industry to navigate the complexities of data-driven advancements [5]

Core Insights - The IDC report highlights the current challenges and scenarios in data space construction, predicting rapid growth in the urban data space market by 2025 due to government initiatives for data resource integration and sharing [1][2] Group 1: Data Space Market Analysis - Data space is defined as an operational model focusing on control capabilities, typically constructed by one or more entities based on business needs [1] - The report emphasizes that despite being in an exploratory phase, the urban data space market is expected to expand significantly by 2025 [1] Group 2: Company Initiatives - Inspur Cloud has actively explored various data space constructions, leveraging distributed intelligent cloud technology to create trusted data space products [1][3] - The company provides distributed data infrastructure services that support the entire lifecycle of data collection, calculation, and utilization, addressing security and trust issues among participants [1][2] Group 3: Case Studies - The Jinan Trusted Data Space, developed with the Jinan Big Data Bureau, integrates services like digital identity, privacy computing, and data authorization to enhance data utilization and drive digital transformation [2] - In the electricity sector, Inspur Cloud has built a trusted data space to manage the entire lifecycle of power data, facilitating intelligent operations and improving power supply-demand balance through advanced analytics [2] Group 4: Future Directions - The report suggests that technology providers should focus on privacy computing and gradually create a data industry ecosystem, leveraging large models within data spaces [3] - Inspur Cloud aims to accelerate the application of data elements and promote the widespread implementation of trusted data spaces through innovative models [3]