小鹏汽车方面向记者透露，2024年3月，刘先明加入小鹏汽车，今年6月以小鹏世界基座模型负责人的身 份亮相；现为小鹏汽车自动驾驶中心组织负责人，全面负责中心业务和组织管理工作，向公司CEO何小 鹏汇报。 今年4月14日，小鹏汽车首次披露正在研发720亿参数的超大规模自动驾驶大模型，即"小鹏世界基座模 型"，未来将通过云端蒸馏小模型的方式将基模部署到车端。在即将举办的年度AI科技日上，小鹏汽车 将公布其在物理AI领域取得的技术进展，主要涉及小鹏自研的物理世界AI基座模型。 中证报中证网讯(龚梦泽熊永红)10月10日，就"小鹏汽车自动驾驶中心负责人变更，刘先明将接替李力 耘担任该职位"这一消息，小鹏汽车方面向中国证券报记者回应称"属实"。 公开信息显示，刘先明2016年博士毕业于伊利诺伊大学厄巴纳-香槟分校电气和计算机工程专业。他曾 在Facebook(现Meta)、通用汽车旗下的自动驾驶公司Cruise任职，从事机器学习与计算机视觉领域的前 沿研究工作。 ...

图片来 源：界面图库 智通财经记者 | 宋佳楠 小鹏汽车自动驾驶业务现高层调整。 公开资料显示，刘先明2016年博士毕业于伊利诺伊大学厄巴纳-香槟分校电气和计算机工程专业。曾在 Facebook（现Meta）、通用汽车旗下的自动驾驶公司Cruise任职，从事机器学习与计算机视觉领域的前 沿研究工作。2024年3月，他正式加入小鹏汽车，担任AI团队负责人，同年6月以世界基座模型负责人 的身份公开亮相。此轮调整前，他已直接向公司董事长兼CEO何小鹏汇报工作。 今年6月，在美国纳什维尔举行的全球计算机视觉顶会CVPR 2025上，刘先明作为小鹏汽车代表，讲述 了其世界基座模型的技术细节，展示了基座模型在真实城市环境复杂路面的控车能力。 暂时休息的李力耘为80后，本科毕业于清华大学电子工程系，2013年获得美国纽约大学计算机专业博士 学位。2019 年6月，李力耘加入小鹏汽车，担任自动驾驶高级总监、智能驾驶决策规划算法和模拟器方 向负责人，负责小鹏汽车高速和城市自主导航辅助驾驶系统NGP的研发。 2023年8月，在小鹏汽车自动驾驶副总裁吴新宙离职后，李力耘开始全面负责小鹏智驾方案的技术研发 与量产落地，并于次年10月 ...

新京报贝壳财经讯（记者张冰）10月10日，就"小鹏汽车自动驾驶中心负责人变更，刘先明将接替李力 耘担任该职位"这一消息，小鹏汽车方面向新京报贝壳财经回应"属实"。 公开信息显示，刘先明 2016 年博士毕业于伊利诺伊大学厄巴纳-香槟分校电气和计算机工程专业。他曾 在 Facebook（现 Meta）、通用汽车旗下的自动驾驶公司 Cruise 任职，从事机器学习与计算机视觉领域 的前沿研究工作。2024年3月，刘先明加入小鹏汽车，今年6月曾以小鹏世界基座模型负责人的身份亮 相。 今年4月14日，小鹏汽车首次披露正在研发720亿参数的超大规模自动驾驶大模型，即"小鹏世界基座模 型"，未来将通过云端蒸馏小模型的方式将基模部署到车端。在即将举办的年度AI科技日上，小鹏汽车 将公布其在物理AI领域取得的技术进展，主要涉及小鹏自研的物理世界AI基座模型。 编辑 杨娟娟 校对 赵琳 ...

Group 1 - A Chinese AI scholar, Shunyu Yao, has left the American AI startup Anthropic to join Google's DeepMind, citing the company's "anti-China rhetoric" as a significant reason for his departure [2] - Anthropic announced it would stop providing AI services to companies controlled by Chinese entities and labeled China as a "hostile nation" in internal documents [2] - Yao expressed that he believes most employees at Anthropic do not agree with this characterization, but felt he could no longer stay at the company [2] Group 2 - Alibaba Cloud has entered a multi-year partnership with NBA China, becoming the official cloud computing and AI partner, aiming to enhance fan experience through AI and cloud technology [2] - The collaboration will develop a dedicated AI model for NBA China and introduce "360-degree real-time replay technology" during NBA China games, providing an immersive viewing experience [2] - NBA China will utilize Alibaba Cloud's infrastructure to support its digital platforms, including the NBA App and official website [2] Group 3 - The return rate for domestic AI glasses exceeds 30% on platforms like JD and Tmall, with Douyin seeing rates as high as 40% to 50%, primarily due to consumer feedback on "insufficient functionality" [3] Group 4 - XPeng Motors is set to announce significant breakthroughs in the field of physical AI during its upcoming AI Technology Day, focusing on advancements in its foundational AI model [2] - The XPeng AI team has been developing this foundational model for over a year, utilizing the largest dataset ever for a physical AI model in China [2] - This initiative is seen as a critical step towards achieving large-scale Level 4 autonomous driving and will facilitate the deployment of Turing AI driving technology globally, as well as its application in AI vehicles and robots [2]

记者从业内获悉，小鹏汽车有望在今年的AI科技日上宣布在物理AI领域取得的重大突破，在小鹏世界 基座模型对世界进行推演能力上取得关键进展。 "端到端"大模型火了之后，"世界模型"的出现，让高端智驾的概念变得丰富和复杂起来。特斯拉、华为 与小鹏汽车等新势力，大有决胜"世界模型"的新趋势。 今年4月，小鹏汽车在香港举办AI技术分享会，正式披露其正在研发的720亿参数超大规模自动驾驶大 模型——"小鹏世界基座模型"。这一模型不仅将为小鹏汽车提供全新的智能驾驶"大脑"，还将通过云端 蒸馏技术部署到车端，同时赋能小鹏的AI机器人、飞行汽车等多种终端设备。 据悉，小鹏AI团队已投入物理世界AI基座模型研发一年多时间，从底层的AI Infra开始重构其物理AI领 域的方法论，正在研发的基座模型使用了有史以来最大的模型数据量，是国内最领先的物理AI大模 型。 业内认为，这是攻克大规模L4的关键一步，可以快速将图灵AI智驾部署到全球其他国家，也可以将技 术复用到AI汽车、AI机器人上，利好其打造"AI+出行"生态。 自动驾驶VLA大模型是世界基座模型的一个重要应用，但更难的是让世界基座模型具备对整个世界进 行推演的能力。 据悉， ...

此前，何小鹏曾表示，小鹏汽车在2026年Q4会让全球用户都能拥有最先进、最适应本地路况的智能驾 驶体验。 据悉，小鹏AI团队已投入物理世界AI基座模型研发一年多时间，从底层的AIInfra开始重构其物理AI领 域的方法论，正在研发的基座模型使用了有史以来最大的模型数据量，是国内最领先的物理AI大模 型。此举将是攻克大规模L4的关键一步，可以快速将图灵AI智驾部署到全球其他国家，也可以将技术 复用到AI汽车、AI机器人上，利好其打造"AI+出行"生态。 凤凰网科技讯 10月9日，据第一财经消息，小鹏汽车将于今年的AI科技日上宣布在物理AI领域取得的重 大突破，在小鹏世界基座模型对世界进行推演能力上取得关键进展。 ...

小鹏汽车将于今年的AI科技日上宣布在物理AI领域取得的重大突破，在小鹏世界基座模型对世界进行 推演能力上取得关键进展。据悉，小鹏AI团队已投入物理世界AI基座模型研发一年多时间，从底层的 AI Infra开始重构其物理AI领域的方法论，正在研发的基座模型使用了有史以来最大的模型数据量，是 国内最领先的物理AI大模型。此举将是攻克大规模L4的关键一步，可以快速将图灵AI智驾部署到全球 其他国家，也可以将技术复用到AI汽车、AI机器人上，利好其打造"AI+出行"生态。（第一财经） ...

Core Viewpoint - The emergence of "World Models" has complicated the high-end intelligent driving landscape, leading to debates over the authenticity and effectiveness of various models like VLA, WEWA, and others [3][5]. Group 1: Company Perspectives - Xiaopeng Motors claims to be the only company in China that has truly developed VLA, criticizing competitors for creating modified versions [3][7]. - Huawei's CEO of Intelligent Automotive Solutions stated that the company will not pursue the VLA path, emphasizing a focus on World Action (WA) instead of language processing [3][5]. - Li Auto is developing a foundational model to support its MindVLA algorithm, which is positioned as a marketing strategy rather than a true VLA implementation [7][8]. Group 2: Technical Insights - VLA (Vision-Language-Action) is seen as an evolution of the end-to-end plus VLM (Vision-Language Model) approach, addressing some limitations of the previous models [5][7]. - Xiaopeng is developing a large-scale driving model with 720 billion parameters, utilizing cloud distillation to deploy smaller models to vehicles [8][15]. - The concept of World Models, initially proposed by Tesla, aims to create a virtual environment for autonomous driving learning and validation [9][11]. Group 3: Industry Trends - The industry is witnessing a shift from perception-driven to cognition-driven approaches, with various companies exploring different architectures for intelligent driving [12][13]. - The debate over the effectiveness of VLA versus World Models reflects a broader struggle within the industry to define the best methodologies for achieving autonomous driving capabilities [17]. - The integration of cloud and vehicle-based models is seen as essential for optimizing perception and decision-making in autonomous systems [17].

Core Viewpoint - The article discusses significant advancements in autonomous driving technology presented by XPeng Motors at CVPR 2025, highlighting the validation of Scaling Law in this field and the introduction of their AI driver technology, termed "intelligent emergence" [1][2]. Group 1: XPeng's Achievements at CVPR 2025 - XPeng Motors was the only car manufacturer invited to present at the Workshop on Autonomous Driving (WAD) during CVPR 2025, showcasing their latest SUV, the G7, which has achieved a record of over 2200 TOPS in computing power for L3 level AI [2][4]. - The G7 is defined by XPeng as a "true AI car," emphasizing its advanced capabilities in autonomous driving without relying on LiDAR technology [2][4]. Group 2: Technical Innovations - XPeng's new generation autonomous driving base model was deployed in vehicles, allowing for safe driving tasks without any rule-based code, demonstrating smooth acceleration, lane changes, and navigation through complex scenarios [4][5][7]. - The system exhibited a comprehensive understanding of the environment, making decisive and smooth driving decisions in various challenging situations, outperforming traditional models that often trigger emergency braking [15][17]. Group 3: The Autonomous Driving Base Model - XPeng's autonomous driving base model is distinct from conventional end-to-end algorithms, as it incorporates a physical world model that allows for real-time reasoning and decision-making [18][22]. - The model is built on a Vision-Language-Action (VLA) architecture, which integrates visual, linguistic, and action components, enabling a unified understanding of tasks and environments [33][36]. Group 4: Scaling Law and Model Training - The article highlights the successful verification of Scaling Law in autonomous driving VLA models, indicating that larger models yield better performance, with XPeng's model trained on over 20 million video clips [43][46]. - Knowledge distillation is employed to transfer the capabilities of large cloud models to smaller vehicle models, enhancing their performance while maintaining safety and real-time responsiveness [46][49]. Group 5: Future Directions and Industry Impact - XPeng's approach marks a significant shift in the autonomous driving landscape, focusing on developing a comprehensive AI model that transcends traditional limitations and enhances cognitive and planning capabilities [60][62]. - The advancements presented by XPeng at CVPR 2025 not only address automotive challenges but also aim to unify the fields of autonomous driving and embodied intelligence, positioning the company as a leader in AI-driven automotive technology [66].

Core Viewpoint - The article discusses significant advancements in autonomous driving technology presented by XPeng Motors at CVPR 2025, highlighting the validation of Scaling Law in this field and the introduction of their AI driver technology, termed "intelligent emergence" [1][2]. Summary by Sections CVPR 2025 Highlights - The CVPR 2025 conference took place in Nashville, Tennessee, from June 11 to June 15, featuring a workshop on autonomous driving that serves as a key technical trendsetter in the industry [2]. - XPeng Motors was the only car manufacturer invited to deliver a keynote speech, coinciding with the pre-sale of their latest SUV, the G7, which boasts a record-breaking L3-level AI computing power exceeding 2200 TOPS [2][4]. Technical Achievements - XPeng's new generation autonomous driving model was deployed in vehicles, achieving safe driving tasks without any rule-based code support [4]. - The system demonstrated smooth acceleration, lane changes, and navigation through complex scenarios, showcasing a comprehensive understanding of the environment and road conditions [5][7][14]. Model Architecture - XPeng's autonomous driving base model is distinct from traditional end-to-end algorithms, focusing on a more sophisticated understanding of driving scenarios rather than mere reactive responses [21][26]. - The model utilizes a Vision-Language-Action (VLA) architecture, integrating visual, linguistic, and action components to enhance decision-making capabilities [33][36]. Training and Learning - The base model undergoes a rigorous training process, including reinforcement learning that emphasizes safety, efficiency, and compliance, reflecting core human driving principles [38]. - XPeng is developing a world model to generate diverse traffic scenarios for continuous training, enhancing the model's adaptability and performance [40]. Cloud and Edge Computing - The cloud-based model, with a parameter count of 720 billion, is designed to leverage vast amounts of data for training, while smaller models are distilled for deployment in vehicles [42][46]. - This approach allows for ongoing learning and adaptation, ensuring that the vehicle's AI capabilities remain up-to-date and effective [42][50]. Industry Positioning - XPeng's strategy diverges from traditional approaches by focusing on large-scale models and cloud computing, positioning itself as a leader in the autonomous driving sector [50][58]. - The G7 represents a significant leap in AI-driven automotive technology, aiming to redefine user interaction with vehicles through advanced cognitive capabilities [55][62]. Conclusion - XPeng's presentation at CVPR 2025 marks a pivotal moment in the evolution of autonomous driving technology, emphasizing the importance of cognitive models and advanced AI in overcoming existing limitations in the industry [66][67].