围绕AI Car发展，白皮书提出十大关键判断，其中包括，VLA改变自动驾驶系统的设计逻辑与能力边 界，将成为驾驶智能体基础模型；世界模型将成为理解世界预测未来的基础工具；算力优化与数据闭环 将成为驾驶智能体实现高效自迭代的核心抓手；"超拟人交互"将重塑人车关系，助力座舱智能体迈向终 极形态；智能底盘与动力将成为"运动控制大脑"；AI将赋能形成"智驾＋底盘"更大的端到端系统，重构 驾乘体验等。 同时，白皮书创新性提出AI时代企业"生存三角新法则"，指出企业需从制造价值转向运营价值，战略目 标由"造好车"转型为"运营智能体"；从固定硬资产驱动转向数据软资产驱动，数据不再是成本中心，而 是影响企业竞争力的核心战略资产；从单一维度竞争转向生态体系竞争。这为行业突围提供了方法论指 导。 共话技术突破与实践 在专题演讲环节，多位专家与业界高管围绕复杂系统优化、AI与汽车产业融合、具身智能工程化落地 等议题展开深度分享。 近日，第三十二届中国汽车工程学会年会暨展览会人工智能主论坛在重庆召开。论坛以"AI＋汽车：具 身智能体的算法进化与创新实践"为主题，与会嘉宾深入探讨了人工智能（AI）如何推动汽车从交通工 具向自主决策的具 ...

Core Insights - The forum focused on how AI is transforming automobiles from mere transportation tools to autonomous decision-making entities, outlining a technological blueprint for the automotive intelligence revolution [1][9] Group 1: AI Car Development Direction - The white paper titled "Preliminary Imagination and Exploration Practice of AI Car" was released, outlining the future of automotive intelligence from an industry perspective [2] - AI Car is identified as the core carrier of the next-generation intelligent space and an ecological node for smart mobility, characterized by autonomy, interactivity, and adaptability [4] - The white paper presents ten key judgments, including the transformation of autonomous driving system design logic, the emergence of world models for future predictions, and the importance of computational optimization and data loops for efficient self-iteration [4] Group 2: Technological Breakthroughs and Practices - Experts discussed the optimization of complex systems and the integration of AI with the automotive industry, emphasizing the need for breakthroughs in problem description, multi-objective conflicts, and computational complexity [5][7] - Companies like Geely, Dongfeng, and Huawei shared their engineering practices and advancements, highlighting initiatives such as Geely's "Beidou Tian Shu" plan and Huawei's dual-driven approach of market demand and technology development [8] - The forum established a collaborative platform for academia and industry, clarifying the technological direction and industrial logic of AI Car development while showcasing China's leading practices in automotive intelligence [9]

Core Insights - The article discusses the release of the first white paper themed "AI Car" in the automotive industry, which outlines the product definition and key technological foresight for the transition to the AI Car era [3][4]. Group 1: AI Car Definition and Key Technologies - The white paper defines AI Car as a super intelligent entity composed of multiple sub-intelligent agents, including driving, cabin, chassis, and power agents [3][4]. - It emphasizes that AI technology will fundamentally reshape the development paradigm and user experience of smart terminals [3]. - The paper identifies ten key judgments regarding the future of AI Cars, including the transformation of autonomous driving system design logic and capabilities through VLA [3][4]. Group 2: Future Directions and Strategic Implications - AI will enable the formation of a larger end-to-end system combining intelligent driving and chassis, thereby redefining the driving experience [8][9]. - The transition of power batteries towards intelligent battery systems capable of real-time perception and autonomous decision-making is highlighted [9]. - The white paper suggests that the product transformation driven by AI will alter the survival and development logic of enterprises, shifting their strategic goals from "making good cars" to "operating intelligent entities" [10][11]. Group 3: Recommendations for Enterprises - Companies are advised to define the unique personality and value proposition of their intelligent entities to rejuvenate brand identity [10]. - It is recommended that enterprises enhance their data value across the entire process and establish a cross-functional AI development team to ensure systematic research and development of AI Cars [11]. - The white paper proposes that automakers should accelerate the construction of comprehensive ecological resource integration capabilities to strengthen user engagement and create competitive barriers in the AI era [11].