从"允许练习"变成了"允许正式上路"。 12月15日，工信部公布了我国首批L3级有条件自动驾驶车型准入许可，分别是来自重庆长安汽车股份 有限公司（下称"长安"）和北汽蓝谷麦格纳汽车有限公司（下称"北汽"）旗下的两款车型。 一是长安牌SC7000AAARBEV型纯电动轿车，可以实现在交通拥堵环境下高速公路和城市快速路单车 道内的自动驾驶功能（最高车速50km/h），目前该功能仅限在重庆市内环快速路、新内环快速路（高 滩岩立交—赖家桥立交）及渝都大道（人和立交—机场立交）等路段开启。 二是极狐牌BJ7001A61NBEV型纯电动轿车，可以实现高速公路和城市快速路单车道内的自动驾驶功能 （最高车速80km/h），目前该功能仅限在北京市京台高速（大兴区旧宫新桥—机场北线高速）、机场 北线高速（大渠南桥—大兴机场高速）及大兴机场高速（南六环—机场北线高速）等路段开启。 两款车型将分别由重庆长安车联科技有限公司、北京出行汽车服务有限公司两家使用主体在上述限定区 域内开展上路通行试点。 记者了解到，这两款车型分为长安汽车旗下深蓝SL03和北汽旗下极狐阿尔法S。其中，深蓝SL03搭载的 是长安自研的"天枢智能"辅助驾驶系统， ...

Core Viewpoint - The Ministry of Industry and Information Technology of China has officially approved two models of smart connected vehicles equipped with L3 level conditional autonomous driving capabilities for road use, marking a significant step in the commercialization of intelligent connected vehicles in China [1] Group 1: Approval of Vehicles - The two approved models are the Changan SC7000AAARBEV electric sedan and the Arcfox BJ7001A61NBEV electric sedan, corresponding to the Deep Blue SL03 and Arcfox Alpha S series respectively [1] - The approval process followed the regulations outlined in the "Management Measures for the Access of Road Motor Vehicle Production Enterprises and Products," involving acceptance, review, and public announcement [1] Group 2: Pilot Operations - The next step involves pilot operations in designated areas by Chongqing Changan Car Networking Technology Co., Ltd. and Beijing Mobility Automobile Service Co., Ltd., indicating that ordinary consumers cannot directly purchase L3 level vehicles yet [1] - This pilot operation will be conducted by professional operating companies within specific regions [1] Group 3: Significance of the Approval - The approval is a milestone for both Changan Automobile and BAIC Blue Valley, representing an important node in the development of China's intelligent connected vehicle industry [1] - L3 level conditional autonomous driving is a critical transition phase from assisted driving to highly automated driving, where vehicles can perform all driving operations under certain conditions, requiring human drivers to take over when requested by the system [1] - The Ministry of Industry and Information Technology stated that this initiative aims to "promote the high-quality development of China's intelligent connected new energy vehicle industry" [1]

Core Viewpoint - The article discusses the high demand for skilled talent in the autonomous driving sector, highlighting the competitive salaries and the importance of comprehensive research capabilities for candidates [2]. Group 1: Talent Demand and Requirements - High-end autonomous driving talent is in great demand, with some companies offering annual packages of up to 700,000 yuan for master's degree holders [2]. - Candidates are expected to possess complete research capabilities, which include problem identification, definition, and solution proposal, rather than just academic knowledge [2]. Group 2: Research Challenges - Many students face challenges in their research, such as lack of familiarity with the field, absence of real data, and difficulties in experimental design [7]. - The fastest way to improve research skills is to work alongside experienced researchers, as indicated by the introduction of a 1-on-1 research mentoring service [3]. Group 3: Mentoring Services Offered - The company offers guidance in various research areas including end-to-end systems, reinforcement learning, 3D object detection, and more [4]. - Services include paper topic selection, full process guidance for papers, experimental guidance, and support for doctoral applications [12]. Group 4: Publication Success - The mentoring service has a high publication rate, with multiple papers accepted in top conferences and journals such as CVPR, AAAI, and ICLR [9].

Group 1: Ant Group - Ant Group upgraded its AI health application AQ to "Ant Afu," which now has over 15 million monthly active users, ranking among the top five AI apps in China and becoming the leading health management AI app [1] Group 2: Cambricon - Cambricon announced plans to use 2.778 billion yuan of its capital reserve to cover accumulated losses, with the aim of bringing its negative retained earnings to zero by the end of 2024 [2] Group 3: TCL Technology - TCL Technology's subsidiary, TCL Huaxing, intends to acquire a 10.7656% stake in Shenzhen Huaxing Semiconductor for 6.045 billion yuan, increasing its total ownership from 84.2105% to 94.9761%, which is expected to enhance the company's profitability [3] Group 4: Tongrentang - Tongrentang responded to allegations of false labeling regarding a product, initiating a full process review and traceability for the involved product, and has taken legal action against the company responsible for unauthorized use of its name [4] Group 5: Juneyao Airlines - Juneyao Airlines announced that its shareholder, Eastern Airlines Industry Investment Co., plans to reduce its stake by up to 1% of the company's total shares, amounting to approximately 21.84 million shares, between January 8 and April 7, 2026 [5] Group 6: Palantir - Palantir announced the renewal of a three-year cooperation agreement with the French National Directorate of Security, continuing a nearly ten-year partnership to provide software and technical support [6] Group 7: Fosun Pharma - Fosun Pharma's subsidiary plans to invest a total of 1.412 billion yuan in Green Valley Pharmaceutical, acquiring part of its equity and subscribing to new registered capital, resulting in a 53% ownership stake [7] Group 8: Inks - Inks, a humanoid robot and core component enterprise, completed nearly 200 million yuan in a new financing round, led by Huakong Fund and Shenzhen Capital Group, marking its third financing round this year [8] Group 9: STMicroelectronics - STMicroelectronics has delivered over 5 billion RF antenna chips to SpaceX for its Starlink satellite network, with expectations to double this number by 2027 [9] Group 10: Shenyang Xingye Machine Tool - Shenyang Xingye Machine Tool announced the completion of 50 million yuan in Series A financing, which will be used for core technology iteration, smart workshop expansion, and talent development [10] Group 11: Autonomous Driving - The Ministry of Industry and Information Technology has granted conditional approval for two L3-level autonomous driving vehicle models from Changan Automobile and BAIC Blue Valley Magna [12]

Group 1 - The Ministry of Industry and Information Technology of China has officially granted the first batch of L3-level conditional autonomous driving vehicle permits, marking a significant step towards the commercialization of autonomous driving technology in the country [1] - Two electric vehicle models from companies in Chongqing and Beijing have been approved for trial operations in designated areas, with specific design features for different driving scenarios [1] - The Chongqing model can achieve autonomous driving at a maximum speed of 50 km/h in congested traffic environments, while the Beijing model supports speeds up to 80 km/h on highways and urban expressways [1] Group 2 - Domestic autonomous driving services are advancing towards large-scale operations, with Geely's Cao Cao Mobility planning to establish five global operation centers over the next decade, aiming to promote Robotaxi services to 100 cities and achieve a total transaction value of 100 billion RMB [2] - Baidu's autonomous driving service platform "Luobo Kuaipao" has entered a phase of large-scale operations, with a reported 310 million fully autonomous driving orders by Q3 2025, representing a 212% year-on-year increase [2] - The development of autonomous driving in China is entering a new phase, starting with L3-level commercial trials and extending to the large-scale operation of Robotaxi services, accelerating the formation of a smart mobility industry ecosystem [2]

Core Viewpoint - Unisoc (002049.SZ) has announced the establishment of a Central Research Institute to enhance its research capabilities and innovation in technology, focusing on advanced technology research and industry chain development [1] Group 1: Research Directions - The Central Research Institute will focus on developing new architectures, models, and efficient algorithms for edge AI chips aimed at applications such as autonomous driving, embodied robots, and low-altitude flying vehicles [1] - Research will also include new types of memory and specialty chips based on two-dimensional material devices [1] - Additionally, the institute will conduct research on high-performance specialty sensor chips [1]

Core Viewpoint - The Ministry of Industry and Information Technology has officially announced the first batch of L3 conditional autonomous driving vehicle permits in China, marking a significant step from testing to commercial application for L3 autonomous driving [1] Summary by Categories Autonomous Driving Levels - The article outlines the differences between L0 to L5 levels of autonomous driving, detailing the driving methods, control subjects, and responsibility subjects for each level [2] - L0: Emergency assistance, human-driven, driver responsible - L1: Partial driving assistance, driver can take feet off pedals, driver responsible - L2: Combined driving assistance, driver can take hands off the wheel, driver responsible - L3: Conditional autonomous driving, driver can take eyes off the road, system responsible, with the driver as the primary responsible party in China; internationally, the vehicle manufacturer is responsible during system activation but may shift responsibility back to the driver when needed - L4: High-level autonomous driving, driver can take brain off driving, system responsible, with different responsibility structures in China and internationally - L5: Fully autonomous driving, no human intervention required, system responsible [2]

《征求意见稿》发布后，得到了众多车企的积极响应。长城、长安、小鹏、北汽、比亚迪等车企纷纷表态支 持，承诺优化价格管理体系，共同维护公平竞争环境，促进行业健康发展。 自2018年后，中国汽车销量连续三年呈现负增长，汽车市场步入"存量时代"。尽管近年来新车销售整体呈 现"短期波动、中长期向上"的现象，年均增长率约为2%-3%，但车企很难再通过提高汽车销量获得高额收益 和利润，竞争的激烈程度可想而知。 （图片来源：摄图网） 车圈价格战真的要停了。 12月12日，国家市场监督管理总局发布了 《汽车行业价格行为合规指南(征求意见稿)》 ，公开向社会征求 意见。其中，在促销与定价层面，《指南》要求返利政策清晰明确且以合同等形式约定，尊重经销商自主定 价权。《指南》还明确将依法打击不正当价格行为，细化了多种表现形式，主要包括了一些以排挤竞争对手 或者独占市场为目的实施的价格行为，总体而言，汽车生产企业需保证出厂价格不低于生产成本。 | | | 然而过去三年，市场在"以价换量"逻辑下狂奔：特斯拉率先降价，比亚迪跟进，新势力被迫应战，传统车 企仓促入局。结果是销量创新高，利润却集体塌方。 "内卷式"竞争引发的无序价格战已成为行 ...

Domestic News - The State Administration for Market Regulation released the "Guidelines for Compliance with Pricing Behavior in the Automotive Industry (Draft for Comments)" to unify regulatory rules and clarify legal boundaries for automotive production and sales enterprises [7] - Three departments announced a notification to appropriately reduce penalties for early loan settlements during the vehicle trade-in process, aiming to boost consumer spending [8] - The "15th Five-Year Plan" proposal from Shenyang emphasizes strengthening the automotive and parts industry, enhancing the supply chain, and promoting the development of smart connected new energy vehicles [9] - FAW-Volkswagen has commenced trial production of new models in Tianjin, with plans for multiple new models to be launched between 2026 and 2027 [10] - NIO has established 500 charging and battery swap stations in Shanghai, with a daily capacity of over 60,000 kWh and a coverage rate of 95% for users within 3 kilometers of a swap station [11] - The world's largest automotive safety testing center has opened in Ningbo, Zhejiang, featuring various world records and advanced testing capabilities [12] - Changan Automobile is expanding into Italy and Spain with two new electric vehicle models, with plans to introduce plug-in hybrid versions next year [13] - XPeng Motors is negotiating with Malaysian partner EPMB to start large-scale electric vehicle production in Malaysia by 2026 [15] International News - In Indonesia, new car sales fell by 1% year-on-year in November, totaling 74,252 units [16] - Volkswagen has begun testing autonomous vehicles in Germany, focusing on its Gen.Urban model capable of driverless operation in urban conditions [17] - Nissan has signed a final agreement with Wayve to integrate AI driving software into its next-generation ProPILOT system [18] - Tesla has initiated unmanned Robotaxi road tests in Austin, Texas, aiming for fully autonomous operation without safety personnel [19] Commercial Vehicles - Dongfeng launched the "Fourth Generation High-Energy Small Card" - Dongfeng T7, which aims to redefine the small truck market with enhanced features [20] - FAW Jiefang unveiled its "Blue Path 3.0" platform for new energy products, featuring four basic models and 165 series products, with significant market interest [21] - BYD has become the leading exporter of new energy buses in November, capturing nearly 25% of the market share, with a total of 3,933 units exported from January to November, a year-on-year increase of 19.25% [22][24] - The Jinbei Haise King 2026 model has been launched in Beijing, showcasing its capabilities as a "comfortable all-purpose business cabin" [25]

Core Insights - The article discusses the transition of AI from model capability competition to execution capability in the physical world, highlighting the challenges and opportunities in this domain [2][3]. Company Summaries - Zhi Bian Liang is focused on developing embodied intelligence foundational models and general-purpose robots, emphasizing the need for a physical model that operates in the real world, distinct from virtual models [4]. - Yuan Rong Qi Xing has been involved in autonomous driving, witnessing the industry's evolution from high-precision mapping to end-to-end models, and has successfully deployed 200,000 vehicles with their driving assistance systems, with a projection of reaching one million vehicles next year [5]. Challenges in AI Implementation - The transition from simulation to real-world application presents significant challenges, including the need for extensive pre-training based on real-world data, which is not easily replicated in simulated environments [6][7]. - The physical world introduces complexities that are not present in simulations, such as the need for precise manipulation and the impact of minor errors on outcomes [9][10]. Importance of Data and Training - The collection of vast amounts of real-world data is crucial for effective pre-training, and the integration of language models can enhance learning efficiency [7][18]. - The current data generation from 200,000 vehicles is substantial, necessitating careful selection and quality control to optimize model performance [18]. Future of Commercialization - The commercialization of embodied intelligence is expected to gain momentum by 2026, with predictions of significant advancements in practical applications and return on investment [21][22]. - The industry is currently in a phase similar to early autonomous driving, with many companies still in the demo stage, but there is optimism about achieving scalable commercial applications soon [19][20]. Role of Language Models - Language models are seen as essential for providing supervisory information during training, aiding in the rapid learning of complex tasks [12][13]. - However, there is debate about the necessity of language in physical AI, with some arguing that while it enhances understanding, it may not be critical for all applications [15][26]. Technical Considerations - The development of physical AI models requires overcoming significant engineering challenges, including the need for real-time feedback and the limitations of current computational resources [25][26]. - The scaling laws in AI suggest that with sufficient data and resources, it is feasible to train models that can operate effectively in the physical world within a reasonable timeframe [24][26].