作为国内自动驾驶领域创作的技术平台，我们期望能够在这波激流中贡献自己的力量，成为一个真的能 给行业带来价值的平台。 众人拾柴火焰高，我们需要更多优秀的伙伴加入我们。 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近15个 方向 学习 路线 大家好，我是柱哥。最近一直在做内容升级并筹划更为细致的内容输出，从以往单篇文章的解读慢慢过 渡到更深入的技术梳理、方案分析、观点讨论。自动驾驶已经进入技术深水区，行业的难点和痛点需要 更多有志之士参与进来一起突破。后面我们将陆续为大家增加圆桌访谈、实战&工业级课程、咨询等各 类输出。 这段时间特斯拉、小鹏、理想都有新的技术分享，引起了大家非常广泛和深入的讨论，非常开心能为大 家分享更多优质的内容。 岗位说明 主要面向自动驾驶培训合作（B端主要面向企业和高校、研究院所培训，C端面向较多学生、求职类人 群）、课程开发和原创文章创作。 联系我们 待遇与合作方式，欢迎添加微信wenyirumo做进一步沟通。 主要方向 包括但不限于：自动驾驶产品经理、4D标注/数据闭环、世界模型、VLA、自动驾驶大模型、强化学 习、端到端等多个方向。 ...

这几个月其实很多小伙伴联系柱哥咨询未来的建议，有工作两三年的也有硕士甚至本科生。他们在刚接触这个领域时，往往会遇到很多问题。从模块化的量产算 法发展到端到端，再到如今的VLA。核心算法涉及BEV感知、视觉语言模型VLM、扩散模型、强化学习、世界模型等等。通过学习端到端与VLA自动驾驶，可以 掌握学术界和工业界最前沿的技术方向。据现有行业的发展来看，端到端和VLA的岗位快要饱和，留下的窗口期没多久了...... 很多同学的咨询如何快速高效的入门端到端和VLA。因此自动驾驶之心联合了 工业界 和 学术界 的大佬开展了 《端到端与VLA自动驾驶小班课》 和 《自动驾驶 VLA和大模型实战课程》 ！ 扫码报名！优惠名额仅剩6个 扫码报名！抢占课程名额 课程大纲 自动驾驶VLA与大模型实战课程 由学术界大佬带队！ 这门课程聚焦在VLA领域，从VLM作为自动驾驶解释器开始，到模块化VLA、一体化VLA，再到当前主流的推理增强VLA。三大自动驾驶 VLA领域全面梳理， 非常适合刚接触大模型、VLA的同学。 课程也配套了详细的理论基础梳理，Vision/Language/Acition三大模块、强化学习、扩散模型等等基 础， ...

Group 1 - The article emphasizes the increasing demand for corporate training and job counseling in the autonomous driving sector, highlighting the need for diverse training programs ranging from technology updates to industry development summaries [2] - There is a notable interest from individuals seeking guidance, particularly those struggling with resume enhancement and project experience [3] - The company is actively seeking collaboration with professionals in the autonomous driving field to enhance training services, course development, and research guidance [4] Group 2 - The company offers competitive compensation and access to extensive industry resources, focusing on various areas such as autonomous driving product management, data annotation, world models, and reinforcement learning [5] - The primary target for training collaborations includes enterprises, universities, and research institutions, as well as students and job seekers [6] - Interested parties are encouraged to reach out for further consultation via WeChat [7]

Group 1 - The article emphasizes the increasing demand for corporate training and job counseling in the autonomous driving sector, highlighting the need for various training programs and industry insights [2][4] - There is a specific focus on assisting individuals who struggle with their resumes and require project experience and guidance [3] - The company is inviting professionals in the autonomous driving field to collaborate on technical services, training, course development, and research guidance [4][5] Group 2 - The main areas of collaboration include roles such as autonomous driving product managers, 4D annotation/data closure, world models, VLA, autonomous driving large models, reinforcement learning, and end-to-end solutions [5] - The job description targets both B-end (corporate and academic training) and C-end (students and job seekers) for training cooperation, course development, and original article creation [6] - Interested parties are encouraged to reach out for further consultation via WeChat [7]

Core Insights - The CEO of XPeng Motors, He Xiaopeng, revealed significant investments in AI and autonomous driving model development, specifically in the VLA technology route [1][3] - The company has invested over 2 billion in training costs for the VLA project, which faced numerous challenges and internal discussions about its viability [3] Investment and Financials - From 2024 to the present, XPeng Motors has utilized 30,000 cards of computing power for its AI research [1] - The training expenses have been substantial, with monthly bills exceeding 100 million, leading to considerable financial pressure [3] Technological Advancements - A breakthrough in the VLA project occurred in the second quarter of this year, allowing the company to shift focus from the standard VLA development to the new technology [3] - This advancement is expected to accelerate the upgrade of XPeng's autonomous driving capabilities by nearly two years [3]

Core Insights - There is a significant demand for end-to-end and VLA (Vision-Language-Action) technical talent in the automotive industry, particularly among major manufacturers and suppliers [1][3] - The industry is evolving from modular production algorithms to end-to-end solutions and now to VLA, with core algorithms involving BEV perception, VLM, diffusion models, reinforcement learning, and world models [3] Group 1: Industry Demand and Trends - The demand for end-to-end and VLA technology talent is high, with inquiries from multiple companies, including three major manufacturers and several suppliers [1] - The industry primarily operates under two paradigms: single-stage and two-stage approaches, with UniAD being a representative of the single-stage model [1] - The end-to-end approach has diversified into various subfields, especially those based on VLA, with a surge in related academic publications and industrial applications in recent years [1] Group 2: Educational Initiatives - The company has launched courses focused on end-to-end and VLA autonomous driving, aimed at helping individuals quickly and efficiently enter these fields [3][12] - The "VLA and Large Model Practical Course" covers VLA from VLM as an autonomous driving interpreter to modular and integrated VLA, including detailed theoretical foundations and practical assignments [3][12] - The "End-to-End and VLA Autonomous Driving Course" focuses on key algorithms and theoretical foundations, including BEV perception, large language models, diffusion models, and reinforcement learning [12][14] Group 3: Instructor Expertise - The courses are led by experts from both academia and industry, with backgrounds in multimodal perception, autonomous driving VLA, and large model frameworks [8][11][14] - Instructors have published numerous papers in top-tier conferences and possess extensive experience in research and practical applications in autonomous driving and large models [8][11][14] Group 4: Target Audience - The courses are designed for individuals with a foundational knowledge of autonomous driving, familiar with basic modules, and concepts such as transformer models, reinforcement learning, and BEV perception [15][16] - Participants are expected to have a background in probability theory, linear algebra, and programming skills in Python and PyTorch [15][16]

Group 1: Nuclear Energy - The "Linglong No. 1," the world's first land-based commercial modular small reactor, successfully completed its cold test on October 16, 2025, marking a significant milestone in nuclear energy development [1] - Once operational, it is expected to generate 1 billion kWh annually, meeting the electricity needs of 526,000 households in Hainan and reducing carbon emissions by approximately 880,000 tons, equivalent to planting 7.5 million trees in a year [1] Group 2: Computing and Telecommunications - The Ministry of Industry and Information Technology aims to achieve a 70% coverage rate for 1-millisecond latency in urban computing by 2027, enhancing the deployment of optical networks and new technologies [2] - The initiative includes the establishment of a monitoring mechanism for medium and large computing centers to ensure low-latency access capabilities [2] Group 3: Battery Technology - Chinese scientists have made breakthroughs in solid-state battery technology, potentially doubling the range of electric vehicles from 500 kilometers to over 1000 kilometers [3] Group 4: Automotive Industry - The Ministry of Industry and Information Technology emphasizes the importance of intelligent connected vehicles as a new driving force for industrial development, focusing on technology innovation and policy framework [4] - The development of generative autonomous driving models is prioritized to enhance vehicle safety through systematic testing and data utilization [9] - Beijing is fostering innovation platforms in areas like high computing power and environmental perception to accelerate the development of the intelligent connected vehicle industry [10] Group 5: Artificial Intelligence Market - A report indicates that the AI hardware and software market is projected to reach between $780 billion and $990 billion by 2027, with an average growth rate of 40%-55%, presenting significant global opportunities for Chinese enterprises [5] Group 6: Energy Storage - In Q3 2025, China's energy storage battery shipments reached 165 GWh, a 65% year-on-year increase, with total shipments for the first three quarters exceeding 430 GWh [6] - The industry is expected to maintain a supply-demand imbalance, with total shipments projected to reach 580 GWh for the year, reflecting a growth rate of over 75% [6] Group 7: Treasury Securities - The U.S. Treasury's issuance of treasury securities has surged, prompting speculation that the Federal Reserve may consider halting its balance sheet reduction [7]

Core Viewpoint - Xiaopeng Motors has confirmed the appointment of Liu Xianming as the new head of its autonomous driving center, replacing Li Liyun, which indicates a strategic shift in leadership to enhance its autonomous driving capabilities [1] Group 1: Leadership Change - Liu Xianming, who holds a PhD in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign, has a background in machine learning and computer vision, having previously worked at Facebook (now Meta) and Cruise, a subsidiary of General Motors [1] - Liu joined Xiaopeng Motors in March 2024 and has been responsible for the Xiaopeng World Base Model, showcasing his expertise in the field [1] Group 2: Autonomous Driving Development - Xiaopeng Motors is developing a large-scale autonomous driving model with 72 billion parameters, referred to as the "Xiaopeng World Base Model," which will be deployed in vehicles through cloud distillation of smaller models [1] - The company plans to announce its technological advancements in physical AI at the upcoming annual AI Technology Day, focusing on its self-developed physical world AI base model [1]

Core Viewpoint - Xiaopeng Motors is undergoing a leadership change in its autonomous driving division, with Liu Xianming replacing Li Liyun as the head of the Autonomous Driving Center, while Li will take a temporary leave due to health reasons [2][3] Group 1: Leadership Changes - Liu Xianming has been appointed as the head of Xiaopeng Motors' Autonomous Driving Center, reporting directly to CEO He Xiaopeng [2] - Li Liyun, who previously led the center, will be taking a break for health reasons but remains with the company [2][3] Group 2: Background of Key Personnel - Liu Xianming holds a PhD in Electrical and Computer Engineering from the University of Illinois and has experience at Facebook (Meta) and Cruise, focusing on machine learning and computer vision [2][3] - Li Liyun, an alumnus of Tsinghua University and New York University, has been with Xiaopeng Motors since 2019 and has significantly contributed to the development of the XNGP autonomous driving system [3][4] Group 3: Achievements in Autonomous Driving - Under Li Liyun's leadership, Xiaopeng's XNGP system expanded its urban autonomous driving capabilities to cover 243 cities as of January 2023 [3] - The company has made advancements in large-scale autonomous driving models, including the development of a 720 billion parameter model [4] Group 4: Recent Performance Metrics - In September, Xiaopeng Motors delivered 41,581 vehicles, marking a 95% year-on-year increase and a record monthly high [5] - For the first nine months of 2023, the total vehicle deliveries reached 313,196, representing a 218% year-on-year growth [5] Group 5: Stock Performance - As of October 10, Xiaopeng Motors' stock price was 87.7 HKD per share, with a market capitalization of 167.2 billion HKD [6]

Core Viewpoint - Xiaopeng Motors has confirmed the appointment of Liu Xianming as the new head of its autonomous driving center, replacing Li Liyun, which indicates a strategic shift in leadership to enhance its autonomous driving capabilities [1]. Group 1: Leadership Change - Liu Xianming, who holds a PhD in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign, has a background in machine learning and computer vision, having previously worked at Meta and Cruise [1]. - Liu joined Xiaopeng Motors in March 2024 and has been involved in the development of the "Xiaopeng World Base Model" as its lead [1]. Group 2: Technological Developments - Xiaopeng Motors is developing a large-scale autonomous driving model with 72 billion parameters, referred to as the "Xiaopeng World Base Model," which will be deployed to vehicles through cloud distillation of smaller models [1]. - The company plans to announce its advancements in physical AI technology at the upcoming annual AI Technology Day, focusing on its self-developed physical world AI base model [1].