Core Points - Beijing Li Auto Co., Ltd. has announced a recall of certain Li MEGA 2024 electric vehicles due to safety concerns related to coolant leakage [1][2] - The recall affects a total of 11,411 vehicles produced between February 18, 2024, and December 27, 2024, starting from November 7, 2025 [1] - The issue arises from insufficient corrosion resistance of the coolant, which can lead to corrosion and leakage in the cooling circuit, potentially causing battery thermal runaway under extreme conditions [1] Summary by Sections Recall Details - The recall plan has been filed with the State Administration for Market Regulation in accordance with the relevant regulations [1] - The recall number is S2025M0174V, covering specific production dates and a total of 11,411 vehicles [1] Safety Measures - Li Auto will provide free replacement of coolant, battery, and front motor controller for the affected vehicles [2] - An emergency response system will alert users of potential coolant leakage and provide assistance through various channels [2] - Users will be notified via the Li Auto app, SMS, and phone calls regarding the recall, and they can also access information through the recall center's website [2]

Recall Information - Li Auto is recalling 11 thousand MEGA 2024 models due to insufficient anti-corrosion performance of the coolant, which may lead to thermal runaway of the power battery [1] - The fire incident on October 23rd has not yet reached a final technical conclusion [1] Internal Investigation - Internal investigation indicates that the coolant in the same batch has insufficient anti-corrosion performance [1]

本次召回范围内的车辆，由于该批次冷却液防腐性能不足，特定条件下会导致冷却回路中动力电池和前 电机控制器的冷却铝板腐蚀渗漏，导致车辆出现故障灯点亮、动力受限及无法上电的情形，极端情况下 会造成动力电池热失控，存在安全隐患。 北京理想汽车有限公司将为召回范围内车辆免费更换冷却液、动力电池和前电机控制器。应急处置措 施：针对冷却液渗漏导致的动力电池安全隐患，理想汽车云端预警程序会提前预警，并通过400客服、 车机Ecall进线联系用户并安排救援服务；当车辆出现故障时，会通过车机故障灯、文字及报警音提醒 用户，请靠边停车并等待救援。如未收到预警和车机故障信息，说明当前车辆状态正常，请放心用车， 接到邀约后请尽快进店更换。 来源｜国家市场监督管理总局网站 日前，北京理想汽车有限公司根据《缺陷汽车产品召回管理条例》和《缺陷汽车产品召回管理条例实施 办法》的要求，主动向国家市场监督管理总局备案了召回计划。 召回编号S2025M0174V：自2025年11月7日起，召回生产日期从2024年2月18日至2024年12月27 日的理想MEGA 2024款汽车，共计11411辆。 编辑｜瑜见 ...

Core Viewpoint - Beijing Li Auto Co., Ltd. has proactively filed a recall plan with the State Administration for Market Regulation due to safety concerns related to the cooling system of certain vehicle models [1] Group 1: Recall Details - Recall Number S2025M0174V involves 11,411 units of the 2024 Li MEGA model, produced between February 18, 2024, and December 27, 2024, starting from November 7, 2025 [2] - The recall is initiated due to insufficient corrosion resistance of the coolant, which may lead to leakage in the cooling circuit, potentially causing warning lights to illuminate, power limitations, and in extreme cases, thermal runaway of the power battery [2] Group 2: Remedial Actions - Li Auto will provide free replacement of coolant, power batteries, and front motor controllers for the affected vehicles [2] - Emergency measures include a cloud-based early warning system that alerts users of potential coolant leakage and offers rescue services through customer support and vehicle communication systems [2]

本报讯天眼查App显示，近日，浙江理想汽车电池有限公司成立，注册资本7000万元，经营范围包括电 池制造、电池销售、新兴能源技术研发、电动汽车充电基础设施运营、输配电及控制设备制造等。股权 全景穿透图显示，该公司由山东理想汽车电池有限公司全资持股，后者由北京理想汽车有限公司、欣旺 达动力科技股份有限公司共同持股。 （文章来源：证券日报） ...

Core Points - Beijing Ideal Automotive Co., Ltd. has proactively filed a recall plan with the State Administration for Market Regulation, in accordance with the "Regulations on the Recall of Defective Automotive Products" [1] - The recall, numbered S2025M0174V, will affect a total of 11,411 units of the 2024 Ideal MEGA, produced between February 18, 2024, and December 27, 2024, starting from November 7, 2025 [1] - The recall is due to insufficient corrosion resistance of the coolant, which may lead to leakage in the cooling aluminum plates of the power battery and front motor controller under specific conditions, posing safety risks [1] Company Actions - The company will provide free replacement of coolant, power batteries, and front motor controllers for the affected vehicles [1] - Emergency measures include a cloud-based early warning system that alerts users of potential coolant leakage and offers rescue services through customer service [1] - Users will be notified of the recall through the Ideal Automotive APP, SMS, and phone calls, and can also contact the customer service hotline for more information [2]

Core Points - Beijing Li Auto Co., Ltd. has filed a recall plan with the State Administration for Market Regulation due to safety concerns related to the cooling system of certain vehicles [1] - The recall affects a total of 11,411 units of the 2024 Li MEGA model, produced between February 18, 2024, and December 27, 2024, starting from November 7, 2025 [1] - The issue arises from insufficient corrosion resistance of the coolant, which may lead to leakage and potential safety hazards, including battery thermal runaway [1] Company Actions - Li Auto will provide free replacement of coolant, battery, and front motor controller for the recalled vehicles [1] - The company has implemented an emergency response system that includes cloud-based early warning notifications and customer support services to assist affected users [1] - Users will be alerted through various channels, including vehicle warning lights and customer service, to ensure safety and prompt action [1]

Domestic News - The Ministry of Industry and Information Technology (MIIT) is promoting the transformation of the entire green industry chain, focusing on the development of new energy vehicles and energy-saving equipment. Key initiatives include green design, building green factories, creating green supply chains, and promoting green industrial parks, with a target for green factory output to reach 40% by 2030 [5]. - The "14th Five-Year" industrial collaboration development initiative for the Beijing-Tianjin-Hebei region has been released, aiming to build a modern industrial system centered on advanced manufacturing and accelerate the development of seven national-level advanced manufacturing clusters [6]. - FAW-Volkswagen plans to achieve Level 3 autonomous driving by 2027-2030, with the introduction of Level 2 driving assistance in 2026 [7]. - FAW Bestune has increased its registered capital to approximately 5.17 billion RMB, marking a 107% increase [8]. - The Guoxuan High-Tech battery factory in Slovakia has officially opened, with plans for trial production in 2026 and a capacity of 20 GWh [10]. - The autonomous driving company "萝卜快跑" has received approval for cross-district testing in Hong Kong, marking its fourth expansion of testing areas this year [11]. - The Deep Blue G318 has been launched in Colombia, indicating the company's expansion into the South American market [12]. - Li Auto has established a new battery company in Zhejiang with a registered capital of 70 million RMB, focusing on battery manufacturing and electric vehicle charging infrastructure [13]. International News - Samsung SDI has partnered with BMW Group and Solid Power to develop a solid-state battery validation project, aiming to enhance battery performance for future vehicles [14]. - Ford is planning to invest approximately 3.7 billion USD in India to produce new engines, with an annual capacity exceeding 200,000 units [15]. - Lucid Motors is set to launch a mid-sized electric vehicle equipped with NVIDIA chips, marking a significant step towards Level 4 autonomous driving technology [16]. - Nissan has confirmed the introduction of the Patrol SUV to the Japanese market in the first half of the 2027 fiscal year, marking its return to this segment [17]. Commercial Vehicles - Suzhou has launched a subsidy program for the scrapping and updating of old commercial vehicles, with an initial fund of 30 million RMB [18]. - SAIC Commercial Vehicle has opened its first nationwide store in Tianjin, marking a strategic integration of its brands [19]. - Hanma Technology has unveiled the first range-extended heavy truck in Southeast Asia, targeting the green logistics market [20]. - The Xiangtan base of Yuan Cheng has received the highest level certification for intelligent manufacturing in the new energy commercial vehicle sector, indicating its advanced capabilities [21][22].

Core Viewpoint - The article discusses the transition of AI into its "second half," emphasizing the need for new evaluation and configuration methods for AI to surpass human intelligence, particularly in the context of autonomous driving technology [1][5]. Group 1: AI Paradigm Shift - AI is moving from reliance on human-generated data to experience-based learning, as highlighted by Rich Sutton's paper "The Era of Experience" [1]. - OpenAI's former researcher, Yao Shunyu, asserts that AI must develop new evaluation methods to tackle real-world tasks effectively [1]. Group 2: Advancements in Autonomous Driving - At the ICCV 2025 conference, Li Auto's expert, Zhan Kun, presented a talk on evolving from data closed-loop to training closed-loop in autonomous driving [2][4]. - Li Auto introduced a systematic approach to integrate world models with reinforcement learning into mass-produced autonomous driving systems, marking a significant technological milestone [5]. Group 3: Li Auto's Technological Innovations - Li Auto's advanced driver assistance technology, LiAuto AD Max, is based on the Vision Language Action (VLA) model, showcasing a shift from rule-based algorithms to end-to-end solutions [7]. - The company has achieved significant improvements in its driver assistance capabilities, with a notable increase in the Human Takeover Mileage (MPI) over the past year [9]. Group 4: Challenges and Solutions in Data Utilization - Li Auto identified that the basic end-to-end learning approach faced diminishing returns as the training data expanded to 10 million clips, particularly due to sparse data in critical driving scenarios [11]. - The company aims to transition from a single data closed-loop to a more comprehensive training closed-loop, which includes data collection and iterative training through environmental feedback [12][14]. Group 5: World Model and Synthetic Data - Li Auto is developing a VLA vehicle model with prior knowledge and driving capabilities, supported by a cloud-based world model training environment that incorporates real, synthetic, and exploratory data [14]. - The ability to generate synthetic data has improved the training data distribution, enhancing the stability and generalization of Li Auto's driver assistance system [24]. Group 6: Research Contributions and Future Directions - Since 2021, Li Auto's research team has produced numerous papers, expanding their focus from perception tasks to advanced topics like VLM/VLA and world models [28]. - The company is addressing challenges in interactive intelligent agents and reinforcement learning engines, which are critical for the future of autonomous driving [35][38]. Group 7: Commitment to AI Development - Li Auto has committed nearly half of its R&D budget to AI, establishing multiple teams focused on various AI applications, including driver assistance and smart industrial solutions [43]. - The company has made significant strides in AI technology, with rapid iterations of its strategic AI products, including the VLA driver model launched with the Li Auto i8 [43].

Core Viewpoint - The article discusses the rapid development of the autonomous driving industry, highlighting the consensus among companies to leverage AI for improving efficiency and productivity in their operations [1][39]. Group 1: Industry Trends - By 2025, the industry is expected to experience rapid growth, with L2 assisted driving gaining significant traction and companies like Momenta and Horizon achieving substantial market presence [1]. - The penetration rate of L2 assisted driving in domestic passenger vehicles reached 63% from January to July this year, with projections indicating a 100% adoption rate by 2030 [34]. - The year 2025 is referred to as the "mass production year" for Robotaxi, driven by increased competition and investment in the sector [34]. Group 2: AI in Autonomous Driving - The autonomous driving sector is utilizing AI to enhance production processes, a concept derived from lean manufacturing principles, focusing on continuous improvement and waste reduction [3][4]. - Companies like Horizon and Momenta are leading examples of using AI to streamline their research and development processes, with Horizon managing over 700,000 documents annually [5][12]. - Momenta has developed a research efficiency engine that automates the flow of information from project initiation to delivery, significantly reducing the time required for various tasks [13][15]. Group 3: Tools and Collaboration - The adoption of Feishu (Lark) as a core platform for knowledge management and collaboration has enabled companies to efficiently utilize their knowledge assets and improve team coordination [6][10]. - Horizon has established knowledge bases for hundreds of projects using Feishu, allowing for rapid iteration and updates to products [11]. - The use of AI-driven tools within Feishu has led to a significant increase in task completion rates and improved overall efficiency in research and development [10][11]. Group 4: Cultural Shift and Competitiveness - The implementation of AI efficiency initiatives, such as the "AI Efficiency Pioneer Competition," fosters a culture of continuous improvement and knowledge sharing among employees [16][26]. - The competition encourages the dissemination of effective case studies across departments and companies, enhancing the overall efficiency of the industry [26]. - The need for efficient tools is underscored by the challenges faced in traditional communication methods, which are often cumbersome and time-consuming [35][36]. Group 5: Future Outlook - The article emphasizes that the future of physical AI will belong to companies that adopt advanced productivity tools early on, as they will be better positioned to navigate the competitive landscape [41][42]. - The integration of AI into real-world applications is seen as a critical challenge that requires comprehensive support for both software development and hardware production [40].