2025年12月18日理想汽车服务部转发语为：今年以来，网络上出现大量针对理想汽车及广大车主有组 织地攻击抹黑，包括但不限于侵害车主个人信息、编造虚假信息诋毁企业经营状况、恶意抹黑产品质 量等违法犯罪行为。近期，在山东省烟台市公安局的缜密侦查与强力打击下，网络黑水军组织化、产 业化的犯罪行为被彻底揭露，相关涉案人员已被依法采取强制措施。 需特别说明的是，有组织、有预谋地攻击抹黑企业，挑起车主群体之间的对立与歧视，是典型的黑水 军违法犯罪活动。这些不法行为不仅严重侵害了广大车主的个人信息与名誉权，也对我司的品牌声誉 和正常经营秩序造成恶劣影响。 转发图片为 天网恢恢，疏而不漏。任何试图通过网络黑产谋取不法利益、损害企业及用户合法权益的行为，都将 受到法律的严惩。理想汽车将坚持使用法律武器捍卫品牌和用户声誉，助力维护清朗的网络环境与公 平的市场竞争秩序。 场景,冒充消费者发布不实体验;更有甚者,通 过搬运洗稿、批量炮制,将个别问题放大渲染, 甚至剪辑成短视频广泛传播,严重侵害企业品牌 声誉,扰乱正常生产经营秩序。 烟台公安 ● +关注 2个朋友关注 ur 32 101 ~ ~ DHJVJZX Jul 1 - A ...

Core Viewpoint - The article highlights the advanced manufacturing processes and technologies employed by the company in the production of the Li Xiang i6 vehicle, showcasing automation, precision, and innovative techniques throughout various production stages. Group 1: Stamping Workshop - The i6 stamping production line features five presses with a maximum pressure of 6,600 tons, utilizing hundred-ton molds [2] - Robots equipped with dual 3D cameras perform high-precision part handling with a positioning accuracy of ±1 mm, ensuring 100% accuracy in part identification and placement [2] Group 2: Welding Workshop - The assembly of high-strength vehicle bodies requires advanced technologies, including dual main assembly processes and hundreds of positioning clamping units for high precision [6] - Robots work collaboratively to complete the main welding processes, enhancing efficiency and accuracy [7] Group 3: Painting Workshop - The vehicle body undergoes cleaning and electrophoresis treatment before painting, ensuring a high-quality finish [12] - High-precision FANUC painting robots, combined with SAMES atomizers, achieve consistent paint application and control over various parameters [15] Group 4: Final Assembly Workshop - Every operation in the final assembly workshop is recorded and uploaded to the cloud, with data retention for up to 15 years [18] - The assembly process includes precise installation of components, such as the air suspension system and tires, utilizing robotic arms for efficiency [21][23] Group 5: Quality Control - The company employs advanced blue-violet light detection technology for surface inspections, ensuring 100% quality checks on vehicle bodies [29] - Professional quality inspectors conduct thorough checks on various aspects, including paint smoothness and component functionality [30] Group 6: Testing - Each Li Xiang i6 undergoes extensive road testing across various terrains, including acceleration and maneuverability tests, to ensure performance standards [33] - The vehicle is subjected to severe weather simulations, including heavy rain tests, to validate its durability and reliability [35]

Core Insights - The article discusses the innovative SparseWorld-TC model released by Ideal, emphasizing a shift from traditional structured approaches to a more data-driven methodology that enhances performance in 3D spatial representation and prediction [1]. Group 1: De-quantized Structure - The model transitions from discrete tokens to a Sparse Occupancy Representation, allowing direct operations in continuous 3D coordinate space, which improves inference speed and scene reconstruction fidelity [2]. Group 2: Removal of Spatial Mediators - Ideal's approach eliminates the need for Bird's Eye View (BEV) projections, which impose geometric constraints and bottlenecks in information flow, by using trajectory-conditioned sparse queries that directly extract information from multi-view image features [3]. Group 3: Elimination of Temporal Serial Structures - The model adopts a feed-forward full attention architecture, enabling parallel output of multiple future frames in a single inference pass, significantly enhancing prediction accuracy and speed compared to traditional autoregressive methods [4]. Group 4: Inspiration from GPT - The model draws inspiration from GPT's attention mechanisms, aiming to understand 3D spatial physics without the limitations of discrete tokenization, thus maintaining continuous physical attributes while efficiently participating in attention calculations [5].

Core Viewpoint - The article discusses the advancements in the development of MindGPT, a multimodal cognitive model designed to enhance human-machine interaction in smart vehicles, emphasizing its capabilities in perception, understanding, and interaction [2][20][39]. Group 1: Technology and Model Architecture - MindGPT is built on a self-developed TaskFormer structure, which has been recognized for its performance in industry evaluations [2][35]. - The model incorporates multimodal perception capabilities, allowing it to process audio and visual data simultaneously, enhancing user interaction through features like voice recognition and gesture control [29][30]. - The architecture supports a complete agent capability, integrating perception, planning, memory, tools, and action [35][36]. Group 2: Training and Performance - The training strategy focuses on 15 key areas relevant to in-car scenarios, utilizing self-supervised learning and reinforcement learning from human feedback (RLHF) to cover over 110 domains and 1,000 specialized capabilities [3][35]. - The training platform, Li-PTM, achieves training speeds that are significantly faster than industry standards, with SFT phase speeds over three times better than the best open-source capabilities [46][47]. - The model's inference engine, LisaRT-LLM, has been optimized for performance, achieving a throughput increase of over 1.3 times compared to previous models under high concurrency [5][53]. Group 3: User Interaction and Experience - MindGPT aims to create a natural interaction experience by allowing users to communicate with the vehicle using simple commands and gestures, reducing the complexity of user input [10][32]. - The system is designed to understand and remember user preferences, providing personalized interactions based on historical conversations [36][39]. - The integration of advanced AI technologies aims to enhance emotional connections between users and their vehicles, creating a more immersive experience [14][18].

本文标题没有任何标题党成分，准确基于理想2025年11月17日发布的 CorrectAD: A Self-Correcting Agentic System to Improve End-to-end Planning in Autonomous Driving 西湖大学的Enhui Ma与理想的Lijun Zhou为共同一作，Enhui Ma的工作完成于理想实习期间。 论文明确指出PM-Agent是在模拟产品经理的角色(simulate the role of product manager)， 核心职责不是 简单的看见错误，而是深刻理解为什么错了并提出需要什么数据。 将 DriveSora比作数据部门(similar to the role of Data Department)， 职能是根据PM-Agent的需求，基于 DiT架构生成高保真的训练数据 。不是普通的视频生成，DriveSora 解决了传统生成模型胡乱发挥的 问题，实现精准可控。 过去面对长尾问题，内核是基于检索，广义的历史数据库里有这个场景就能解决，没有就无法解决， 处理思路一般是要么自己派车去收集，要么尝试从用户的实车数据去收据，即内核 ...

Core Insights - The article highlights the admiration for entrepreneur Li Xiang, with multiple industry leaders expressing their respect for his innovative approach and product management skills [1][3][4]. Group 1: Entrepreneurial Insights - Li Xiang is recognized as a significant role model among entrepreneurs, with figures like Jiang Zeyuan and Shang Yangxing citing his influence on their own careers [1][3]. - Jiang Zeyuan emphasizes Li Xiang's exceptional product management abilities, recalling a video from 2020 that showcased Li's entrepreneurial philosophy [3]. - The common traits of successful entrepreneurs, as discussed by Zhou Hongyi, include strong learning capabilities and resilience, which are essential for long-term success [4]. Group 2: Company Developments - Songyan Power, founded by Jiang Zeyuan, has developed three main humanoid robot products, with the N2 model priced starting at 39,900 yuan [6]. - The company secured nearly 300 million yuan in a Pre-B round led by Fangguo Capital and an additional 200 million yuan in a Pre-B+ round led by CICC [6]. - Qiaojieshuwu, founded by Shang Yangxing, has achieved profitability within its first year and has provided software solutions for over 30 robotics companies [6].

这个是RSU通用的做法，因为需要交所得税。通常都是归属时卖掉一部分交税，而不是额外自己再掏现金交税。 2025年12月11日，李铁（CFO ）持有A类普通约2437万股 售出40万股售出比例1.6%。马东辉（总裁）持有A类普通约900万股，售出20万股，售出比例 2.2%。 马东辉公告里提到 | 144: Remarks and Signature | | --- | | Remarks The securities set toth herein are being sold mainly pursuant to a sel-to-cover arrangement for the purpose of satisfing moome tax liabilities incurred upon vesting of resiri | | Date of Notice 12/11/2025 | | ATTENTION: | | The person a versen a whose accurations contribution in which the restor and the rest from t ...

2025年11月理想交付33181，其中增程18984，纯电14197。L6789分别为9434/5212/2130/2208，i6i8MEGA分别为6798/6719/680。 | 2025年11月14日 晚点说 | i6首销期毛利率约10% 详见 | 平替时代：一家车企、 | | --- | --- | --- | | 一个行业如何被自己的成功困住 | | | | | 总交付 | | 纯电 | L6 | IL7 | Г8 | La i6 | 18 | | MEGA | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 2025年11月 | 33181 | 18984 | 14197 | 9434 | 5212 | 2130 | 2208 | 6798 | 6719 | 680 | | 2025年10月 | 31767 | 18340 | 13427 | 9680 | 4347 | 2183 | 2130 | 5775 | 5749 | 1903 | | 2025年9月 | 33951 | 24554 | 9397 | ...

Core Insights - The core viewpoint emphasizes that the key to successful autonomous driving lies in the integration of the VLA model with the entire embodied intelligence system, where data plays a crucial role in determining effectiveness [1][4]. Summary by Sections VLA Model - The VLA is fundamentally a generative model, utilizing a GPT-like approach for autonomous driving, generating trajectories and control signals instead of text. User feedback indicates that VLA exhibits emergent behaviors in certain scenarios, reflecting a growing understanding of the physical world [2]. - The world model is better suited for creating "test environments" rather than acting as "test subjects," due to its high computational demands. Ideal is currently leveraging cloud-based data generation and realistic simulation testing, utilizing several exaFLOPS of computational power for simulation tests, which cannot be matched by even the most powerful vehicle chips [2]. - Discussions about model architecture are less relevant than the actual performance outcomes. In autonomous driving, focusing on vast amounts of real data is essential, and Ideal's commitment to VLA is supported by a data loop created from millions of vehicles, enabling near-human driving levels with current computational resources [2]. Embodied Intelligence - To excel in autonomous driving, it is essential to treat it as a complete embodied intelligence system, where all components must work together during development to maximize value. Human drivers do not require extraordinary abilities; rather, coordination among various parts is crucial [3]. - The embodied intelligence system comprises perception (eyes), models (brain), operating systems (nervous system), chips (heart), and the body (vehicle). Full-stack self-research is necessary, encompassing both software and hardware. Ideal's autonomous driving team collaborates with foundational model, chip, and chassis teams to create a comprehensive autonomous driving system [3]. Data Utilization - The key to effective modeling is its compatibility with the entire embodied intelligence system, with data being the decisive factor. While data acquisition is challenging in robotics, it is not a significant issue for companies in the autonomous driving sector that have established data loops. Ideal can mine and filter from over 1 billion kilometers of accumulated data and continuously gather new data from 1.5 million vehicle owners [4]. - During data filtering, interesting patterns were observed, such as nearly 40% of human driving data showing a tendency to drive on one side and not strictly adhering to speed limits. This behavior aligns with typical human driving patterns, leading to the decision not to eliminate these data samples. The VLA model is expected to serve both current and future automotive forms of embodied robots [4].

这次理想上架的L系列流媒体后视镜的主要特点为： 1.不涉及车辆外部设备改装合规上路，同样的车规级可靠性。 2.60度广角视野比普通内后视镜优秀。 这位群友明确认为很多改装用户实际体验下来会满意的，可以 解决用户开后排屏幕后无法观察车位的痛点，并且夜晚视野更清晰。 有预算额外买摄像头 模组，上嘉立创打板自己做。 中国国家法规中对于内部后视镜的要求驾驶员可以看到80米后20米宽的范 围假设后部有一个流媒体摄像头安装这个等效的摄像头的视角是30度。 3.对标24款MEGA,估计没有多少⼈体验过高亮清洗防眩､ 夜间夜视也超清晰 50Hz的刷新率对于高速的画面清晰流畅。 25款纯电和24款MEGA的最大区别就是60度广角升级为120度视野更宽。 关于200万像素 本身60度的流媒体后视镜已经比传统后视镜相比有碾压的⽤户体验了。 200万像素的摄像头传感器对应后视镜的显示器的像素是73万1920*384像素，考虑画面是长条状，截取画面的尺寸和显示的像素基本上可以映射。 简单说这个200万像素的摄像头像素是完全足够的，还多出很多像素得到的数据可以做环境光的感光计算以及画面质量的算法优化｡ 关于电子后视镜的清晰度 人眼到后视 ...