公开资料显示，毫末智行成立于2019年11月，致力于自动驾驶的人工智能技术，是中国首个实现自动驾 驶技术量产的企业，其前身为2015年长城汽车成立的智能驾驶系统开发部，是长城汽车内部孵化的子公 司。团队由长城汽车的内部技术人员和来自百度、华为等科技企业的工程师组成。 毫末智行早期也有过"风光岁月"：2021年A轮融资中，美团、高瓴、高通等顶级机构注资近10亿元，使 其迅速跻身独角兽行列。2021年5月起，核心产品辅助驾驶系统HPilot 1.0迅速搭载魏牌摩卡等多款车 型。2022年3月，辅助驾驶系统快速迭代至HPilot 2.0版本。2024年用户智驾里程突破2.5亿公里。 据了解，毫末智行的人事动荡由来已久。去年，毫末智行启动大规模裁员，职能部门比例高达三分之一 至近半，同期数据智能科学家贺翔也宣告离职；今年，董事长张凯于6月提出离职，还有多位中高层管 理人员离职，包括技术副总裁艾锐、产品副总裁蔡娜、智行品牌官王佳等关键人物。 智通财经APP获悉，据媒体报道，有消息称长城汽车(02333,601633.SH)旗下的自动驾驶技术公司毫末智 行11月23日突然通知员工，自11月24日起不用到岗上班，赔偿方案尚 ...

智通财经APP获悉，据媒体报道，有消息称长城汽车(02333,601633.SH)旗下的自动驾驶技术公司毫末智 行11月23日突然通知员工，自11月24日起不用到岗上班，赔偿方案尚未公布。报道引述知情人士指出， 目前毫末智行约有200多名员工，公司内部尚未就停工后有何调整给出具体说法，"可能是完全解散，也 可能只是暂时停工，但复工日期还不清楚"。 另据知情人士透露，毫末智行公司运营已基本停滞，公关等职能部门处于空缺状态，项目方面，仅余一 个与现代汽车的合作项目尚在收尾。 长城官方未对此事进行公开回复，但长城汽车智驾部门人士表示，长城汽车智驾部门已在业务上基本剥 离毫末智行的技术方案。 公开资料显示，毫末智行成立于2019年11月，致力于自动驾驶的人工智能技术，是中国首个实现自动驾 驶技术量产的企业，其前身为2015年长城汽车成立的智能驾驶系统开发部，是长城汽车内部孵化的子公 司。团队由长城汽车的内部技术人员和来自百度、华为等科技企业的工程师组成。 毫末智行早期也有过"风光岁月"：2021年A轮融资中，美团、高瓴、高通等顶级机构注资近10亿元，使 其迅速跻身独角兽行列。2021年5月起，核心产品辅助驾驶系统HP ...

Key Points - A Shanghai intern was forced to resign after refusing to return a graphics card won during a company-sponsored event, which the company claimed belonged to them [2][3] - Xiaopeng Motors faced backlash after a customer was injured by an automatic door at a dealership, with the sales staff suggesting the customer was at fault [5][6] - The autonomous driving company Haomo AI was reported to have disbanded suddenly, with around 200 employees affected and the company's accounts frozen [8][9] - Xiaomi denied rumors of a fire at its automotive factory, clarifying that a minor incident occurred during equipment testing [11][12] - ByteDance's valuation has surged to approximately $480 billion, driven by the rapid growth of its e-commerce business on Douyin, with GMV expected to reach 3.5 trillion yuan in 2024 [21][22] - The AI startup Moonlight is reportedly nearing a $4 billion valuation and plans to go public in the second half of next year [14] - Nvidia's CEO Jensen Huang stated that the company's AI chip revenue in China is currently zero, as the U.S. government considers allowing the sale of the H200 chip to China [40][41] - Tesla's CEO Elon Musk announced that the company has deployed millions of AI chips and aims to release a new chip design annually, expecting future production to exceed all other AI chips combined [42][43]

Core Insights - The article emphasizes the growing demand for end-to-end production talent in the automotive industry, highlighting a paradox where job seekers are abundant, yet companies struggle to find qualified candidates [1][3]. Course Overview - A newly designed end-to-end production course aims to address the skills gap in the industry, focusing on practical applications and real-world scenarios over three months [3][5]. - The course covers essential algorithms such as one-stage and two-stage end-to-end frameworks, reinforcement learning applications, and trajectory optimization techniques [5][10]. Course Content - **Chapter 1: Overview of End-to-End Tasks** - Discusses the integration of perception tasks and the learning-based control algorithms that are becoming mainstream in autonomous driving [10]. - **Chapter 2: Two-Stage End-to-End Algorithms** - Introduces the two-stage framework, its modeling methods, and the flow of information between perception and planning [11]. - **Chapter 3: One-Stage End-to-End Algorithms** - Focuses on one-stage frameworks that allow for lossless information transfer, enhancing performance compared to two-stage methods [12]. - **Chapter 4: Application of Navigation Information** - Explains the critical role of navigation data in autonomous driving and how it can be effectively integrated into end-to-end models [13]. - **Chapter 5: Introduction to Reinforcement Learning Algorithms** - Highlights the necessity of reinforcement learning to complement imitation learning, enabling machines to generalize better [14]. - **Chapter 6: Trajectory Output Optimization** - Covers practical projects involving imitation learning and reinforcement learning algorithms for trajectory planning [15]. - **Chapter 7: Contingency Planning - Spatiotemporal Joint Planning** - Discusses post-processing logic to ensure reliable trajectory outputs, including smoothing algorithms [16]. - **Chapter 8: Experience Sharing in End-to-End Production** - Provides insights on practical strategies and tools for enhancing system capabilities in real-world applications [17]. Target Audience - The course is designed for advanced learners with a foundational understanding of autonomous driving algorithms, reinforcement learning, and programming skills [18][19]. Course Schedule - The course is set to begin on November 30, with a structured timeline for unlocking chapters and providing support through offline videos and online Q&A sessions [20].

Core Insights - The article highlights the increasing international presence of Chinese companies in various sectors, particularly in drone technology, electric vehicles, AI, and 3D printing, showcasing significant partnerships and market expansions. Group 1: Drone Technology - Chinese drone manufacturers showcased their products at the Dubai Airshow, with companies like United Aircraft Group demonstrating delivery drones capable of carrying 5 kg and adapting to high-temperature environments [4] - EHang completed the first urban air mobility flight in Qatar, reducing travel time from 30 minutes to 8 minutes, marking a significant milestone for eVTOL technology in the Middle East [4] Group 2: AI and Digital Solutions - Epoint and Alibaba Cloud announced a framework cooperation agreement for AI comic series, aiming to create a comprehensive solution for overseas expansion in this emerging market [4] - Alibaba International Station launched AI Mode to automate cross-border e-commerce procurement processes for SMEs, enhancing decision-making and operational efficiency [5][6] Group 3: Electric Vehicles - Didi's 99 platform in Brazil expanded its electric vehicle services to five major cities, with over 30,000 electric and hybrid vehicles registered, significantly reducing carbon emissions [7] - NIO's Firefly right-hand drive model began mass production, with the first batch set for Singapore, indicating rapid global market penetration [8] Group 4: Market Expansion and Financing - Blue Dot Touch completed over 100 million C-round financing to enhance global market expansion, focusing on robotics sensor hardware [10] - Elegoo announced a strategic financing round, with a global shipment exceeding one million units, indicating strong growth in the 3D printing market [11] Group 5: Emerging Markets - Southeast Asia, Africa, and the Middle East are identified as key growth markets for Chinese companies over the next three years, with optimism in sectors like construction, healthcare, and IT [13] - China has become the largest trading partner in the Gulf region, surpassing the combined trade of the US, UK, and Eurozone, with trade expected to grow significantly by 2028 [13]

Core Viewpoint - The article discusses the development of a driving world model by Li Auto that integrates both ego and other vehicle trajectories, enabling more realistic simulations of driving scenarios and enhancing the training of their VLA (Vehicle Learning Algorithm) through reinforcement learning [1][6]. Group 1: Model Development - The driving world model proposed by Li Auto addresses three main deficiencies of previous models: lack of interactivity, feature distribution mismatch, and spatial mapping difficulties [6]. - The new model, EOT-WM, projects trajectory points into an image coordinate system, allowing for the generation of trajectory videos that unify visual modalities [6][8]. - A spatiotemporal variational autoencoder (STVAE) is employed to encode scene and trajectory videos, achieving aligned feature spaces for effective control [7]. Group 2: Technical Innovations - The model introduces a diffusion Transformer (TiDiT) that integrates motion guidance from trajectory variables into video latent variables for improved denoising of noisy video representations [9]. - A new metric based on the similarity of control latent variables is proposed to evaluate the controllability of predicted trajectories against true trajectory variables [7][9]. Group 3: Contributions - The model is the first to include both ego and other vehicle trajectories, allowing for more realistic simulations of interactions between the ego vehicle and driving scenarios [8]. - It represents trajectories as videos and aligns each trajectory with corresponding vehicles in a unified visual space [9].

Investment Rating - The industry investment rating is "Positive" (maintained) [1] Core Insights - The report highlights the stability of the Double Eleven sales event, with a focus on extreme low prices and user experience as key competitive factors. AI cloud demand continues to be validated, with major cloud service providers (CSPs) increasing capital expenditure (CapEx) guidance, indicating stronger predictability in computing power demand [5][26][67] - The emergence of Mid-training is expected to enhance the predictability of computing power demand, serving as a foundational technology support for this trend. This phase is crucial for refining data and improving model capabilities, which in turn stimulates demand for professional data annotation services [6][30][38] Summary by Sections 1. Internet Sector - The Double Eleven event showed stable performance, with total online retail sales reaching nearly 2.4 trillion yuan, a year-on-year growth of over 10%. Major platforms like Tmall and JD.com maintained significant market shares [16][19] - The competition among platforms has intensified, with a return to low prices and enhanced user experience driving growth. JD.com continues to perform well in high-value categories like 3C electronics and home appliances [23][14] - Major overseas internet companies are experiencing strong growth in advertising and cloud services, with increased CapEx further supporting the AI industry's positive outlook [5][8][67] 2. AI Sector - Mid-training is gaining importance, potentially extending the Scaling Law and enhancing the predictability of this round of computing power demand. This phase focuses on providing more structured supervision signals to improve downstream capabilities [30][33] - The rise of Mid-training has led to the emergence of several unicorn companies in the data annotation space, indicating a growing market for AI-related services [38][36] 3. Automotive & Autonomous Driving - The automotive sector is facing challenges due to tightened policies affecting passenger vehicle sales, with a notable decline in weekly sales figures. However, new vehicle launches are expected to ramp up towards the end of the year [41][43] - The Robotaxi industry is witnessing significant developments, with companies like Xiaoma Zhixing and Wenyuan Zhixing successfully listing on the Hong Kong Stock Exchange. Xiaopeng Motors is also set to launch Robotaxi models by 2026, showcasing advancements in autonomous driving technology [45][53][67] 4. Investment Recommendations - The report recommends focusing on companies benefiting from the ongoing trends in the internet and AI sectors, such as Alibaba, Pinduoduo, and Tencent in the internet space, and companies like Kingdee International and Beisen Holdings in the IT spending wave [8][67]

Core Insights - The article discusses the recent dissolution of a prominent AI driving company, Maomao Zhixing, which has faced significant operational challenges and staff turnover [2][3]. Company Overview - Maomao Zhixing was established on November 29, 2019, as a subsidiary of Great Wall Motors, focusing on autonomous driving technology [6]. - The company initially made rapid advancements, launching its first autonomous delivery vehicle, "Xiao Mo Tuo," in November 2020, and developing the MANA data intelligence system by December 2021 [6][8]. Recent Developments - The company has experienced substantial layoffs, with reports indicating that nearly one-third to half of its functional departments were cut last year [5]. - Key personnel, including the Vice President of Technology and the Public Relations team, have left the company, raising concerns about its stability [5][6]. - As of June 2023, the company's official communications have ceased, with the last update being a holiday poster on October 1 [5]. Product and Technology - In April 2023, Maomao Zhixing launched the DriveGPT autonomous driving generative model, coinciding with the rise of ChatGPT [8]. - The HPilot 3.0 driver assistance system has been integrated into nearly 20 models under Great Wall Motors by 2025 [8]. - However, competition has intensified, with Yuanrong Qixing providing end-to-end smart driving solutions for Great Wall Motors, leading to speculation that Maomao Zhixing has become less favored within the company [8]. Market Reaction - Users of Maomao Zhixing's products have expressed concerns and dissatisfaction regarding their experience following the company's potential closure [9].

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Core Viewpoint - The rapid adoption of unmanned delivery vehicles in the logistics industry is driven by their cost-effectiveness and operational efficiency, particularly in remote areas where traditional delivery methods are less viable [1][3][5]. Group 1: Cost Efficiency and Operational Benefits - Unmanned vehicles can operate with lower costs compared to traditional delivery methods, saving significant amounts on fuel, labor, and maintenance [6][7]. - For instance, using unmanned vehicles can save approximately 25,000 yuan in fuel, 20,000 yuan in insurance and maintenance, and another 20,000 yuan in labor costs annually [7]. - The ability to deliver smaller quantities of packages efficiently makes unmanned vehicles particularly advantageous in sparsely populated areas [2][6]. Group 2: Market Growth and Adoption - The number of unmanned delivery vehicles is expected to exceed 6,000 by the end of 2024, significantly outpacing other autonomous vehicle applications like unmanned taxis [3]. - Major logistics companies such as Zhongtong, Jitu, and Shunfeng are investing heavily in unmanned vehicles, with Zhongtong alone deploying nearly 3,000 units [3][8]. - The cost of unmanned vehicles has decreased significantly, with prices dropping from over 1 million yuan in 2018 to around 40,000 to 70,000 yuan by 2025 [22][23]. Group 3: Technological Advancements - Continuous improvements in technology, including hardware and software, are enhancing the reliability and efficiency of unmanned vehicles [11][23]. - Companies are innovating their business models, such as offering lower hardware prices combined with software subscription services, making it more accessible for logistics providers [23] - The deployment of unmanned vehicles is not limited to rural areas; urban centers like Shenzhen and Qingdao are also integrating them into their logistics networks [8][12]. Group 4: Regulatory Environment and Challenges - The successful operation of unmanned vehicles is contingent upon local government regulations and the establishment of road rights [15][16]. - While some cities have embraced unmanned delivery vehicles, the distribution of these approvals is uneven across the country [15]. - The logistics industry is actively engaging with local governments to ensure compliance and safety measures are in place for unmanned vehicle operations [14][17]. Group 5: Future Outlook - Despite existing concerns regarding safety and operational challenges, the long-term outlook for unmanned vehicles in the logistics sector remains positive [25][26]. - The industry is witnessing a shift towards more automated and efficient delivery systems, with ongoing support from government initiatives aimed at promoting the use of unmanned vehicles [26][27].