Core Viewpoint - The article emphasizes the significance of high computing power, large models, and extensive data in achieving Level 3 (L3) autonomous driving, highlighting the advancements made by XPeng with its G7 model and its proprietary AI chips [3][18][19]. Group 1: Technological Advancements - XPeng's G7 is the world's first L3 level AI car, featuring three self-developed Turing AI chips with over 2200 TOPS of effective computing power [3][18]. - The G7 introduces the VLA-OL model, which incorporates a "motion brain" for decision-making in intelligent assisted driving [4]. - The VLM (Vision Large Model) serves as the AI brain for vehicle perception, enabling new interaction capabilities and future functionalities like local chat and multi-language support [5][19]. Group 2: Industry Positioning - XPeng was the only invited Chinese car company to present at the global computer vision conference CVPR 2025, showcasing its advancements in autonomous driving models [6][13]. - The company has established a comprehensive system from computing power to algorithms and data, positioning itself as a leader in the autonomous driving sector [8][18]. Group 3: Model Development and Training - The next-generation autonomous driving base model developed by XPeng has a parameter scale of 72 billion and has been trained on over 20 million video clips [20]. - The model utilizes a large language model backbone and extensive multimodal driving data, enhancing its capabilities in visual understanding and reasoning [20][21]. - XPeng employs a distillation approach to adapt large models for vehicle-side deployment, ensuring core capabilities are retained while optimizing performance [27][28]. Group 4: Future Directions - The development of a world model is underway, which will simulate real-world conditions and enhance the feedback loop for continuous learning [36][41]. - XPeng aims to leverage its AI advancements not only for autonomous driving but also for AI robots and flying cars in the future [43][64]. - The transition to an AI company involves building a robust AI infrastructure, with a focus on optimizing the entire production process from cloud to vehicle [50][62].

Core Insights - The report focuses on the trends and market dynamics in the fields of intelligent driving and humanoid robots, highlighting the expected explosive growth in advanced driving technologies and the emergence of humanoid robots in commercial applications by 2025 [1][4]. Intelligent Driving - Advanced driving technology is anticipated to enter a phase of explosive growth, with a projected penetration rate exceeding 15% by 2025 and potentially surpassing 70% in the next 2-3 years, significantly altering the automotive landscape [1][4]. - The Robotaxi segment is reaching a critical turning point, with costs expected to align with ride-hailing services by 2025, suggesting a competitive edge for companies like Didi that integrate both self-operated and platform-based models [1][5]. - Key supply chain components such as intelligent driving chips, LiDAR, and sensor cleaning are expected to see substantial growth driven by policy, technology, and market demand, with companies like Horizon Robotics and Hesai Technology leading the way [1][5]. Humanoid Robots - The humanoid robot sector is poised for a breakthrough in mass production by 2025, with economic viability in general commercial scenarios expected by 2027, particularly in high-cost labor markets [1][6]. - The supply chain for humanoid robots is characterized by high-value components such as dexterous hands, lead screws, and sensors, which are becoming core segments due to their high barriers to entry and significant cost reduction potential [1][6]. - The domestic market for lead screws is growing, with a market share exceeding 10% and increasing, driven by the demand for lightweight materials like PEEK in humanoid robots [1][6]. Supply Chain Dynamics - The supply chain for intelligent driving and humanoid robots is evolving, with high-value segments like dexterous hands and lead screws becoming increasingly important due to their cost structure and technological barriers [1][6]. - The report emphasizes the importance of domestic production capabilities in the supply chain, particularly in the context of rising demand for humanoid robots and the need for cost-effective solutions [1][6].

Core Viewpoint - SenseTime's R-UniAD end-to-end autonomous driving solution is set to be unveiled at the Shanghai Auto Show in April, with real vehicle deployment completed and expected delivery by the end of the year [1][3]. Group 1: Company Developments - Wang Junping, former senior director of intelligent driving at Nezha Auto, joined SenseTime's autonomous driving division in February 2023, previously being part of Baidu's intelligent driving team [2]. - SenseTime has been collaborating with Nezha Auto since September 2021, focusing on intelligent driving and smart cockpit technologies [2]. - Wang Weibao, who took over from Shijianping as the head of intelligent driving, joined SenseTime at the end of 2023 and has a background in Apple's autonomous driving team and as CTO at New Stone Unmanned Vehicle Company [3]. Group 2: Industry Context - The autonomous driving sector is experiencing intensified competition, particularly for companies not in the top tier, highlighting the challenges faced by solution providers [3]. - SenseTime collaborates with over 30 automotive companies, including GAC, BYD, Honda, and NIO, with solutions already deployed in models like the Haobo and Nezha's super sedan [3].

以下文章来源于晚点Auto ，作者晚点团队 晚点Auto . 从制造到创造，从不可能到可能。《晚点LatePost》旗下汽车品牌。 目前主要服务北汽、上汽大通等车企。 文丨赵宇 编辑丨 程曼祺 我们独家获悉，智能驾驶供应商易航智能近日完成数亿元 C 轮融资，由北汽产投、浙江金控投资公司、德 清产投、财通资本联合投资。其中，浙江金控投资公司为浙江省级投资平台，德清产投为湖州德清县级投 资平台。 北汽在 2022 年与易航智能达成合作，主打越野车的北汽 BJ40 系列车型已搭载易航智能的 L2 级前视一体 机（集成摄像头等传感器的硬件套件）和 L2+ 级高速 NOA 方案。 易航智能称，本轮融资后，易航智能或将为北汽集团旗下 BEIJING、极狐品牌的车型开发智驾方案。 浙江德清县政府则正在招引智驾项目，打造智能驾驶示范区。蔚来激光雷达供应商图达通的一条产线和港口 无人驾驶公司斯年智驾总部基地已落地德清。 易航智能由陈禹行于 2015 年 8 月创立。他博士毕业于吉林大学车辆工程专业，师从中国工程院院士郭孔辉， 郭孔辉也是空气悬架公司浙江孔辉的前身 "长春孔辉" 的创始人；在美国加州伯克利大学交流期间，陈禹行还 ...

以下文章来源于晚点Auto ，作者晚点团队 晚点Auto . 从制造到创造，从不可能到可能。《晚点LatePost》旗下汽车品牌。 "有了人才之后，其他东西都会有。" 文丨赵宇 张家豪 制图丨黄帧昕 编辑丨 程曼祺 宋玮 "有了人才之后，其他东西都会有。" 一位曾在美国硅谷工作多年的自动驾驶从业者说，自动驾驶是人才密 集型产业。人才的流动直接影响一家公司的发展势头，也指示着整个行业的风向变化。 自动驾驶人才流动的最新一个例子是小鹏向英伟达的 "输血"。自小鹏前自动驾驶副总裁吴新宙去年 8 月加 入英伟达后，12 个月里，至少 6 位小鹏技术人员加入英伟达。 芯片巨头英伟达下场做方案，希望成为垂直整合的智能驾驶 Tier 1（一级供应商）。2023 年下半年，英伟 达也把目光投向了全球智驾人才最丰富、实践经验最多的中国，开始在这里组建智驾方案团队，希望挽救 进展缓慢的智驾业务。 有同样野心的还有高通、地平线等跨界选手。2022 年，高通收购了瑞典智能驾驶技术服务商 Arriver，将 其计算机视觉、驾驶辅助等资产整合进自身业务；地平线则招募了原华为智能驾驶产品部部长苏箐，基于 征程 6 开发高阶智能驾驶方案。 ...