格隆汇1月6日丨隆基机械(002363.SZ)在互动平台表示，公司已参与 L3 级自动驾驶汽车制动部件产品供 应，为国内首批 L3 级有条件自动驾驶车型提供配套。 针对 L3 级车型的制动产品，在质量过程控制 上，需执行更严苛的全流程管控标准，从原材料入厂到成品出厂的每一道工序均增设多轮检测节点；在 生产工艺上采用更高精度的加工及处理工艺，以此保障产品完全适配高阶自动驾驶的安全应用要求。 ...

格隆汇1月6日丨隆基机械(002363.SZ)在互动平台表示，公司已为我国首批 L3 级有条件自动驾驶车型长 安深蓝 、北汽极狐阿尔法提供制动部件配套，凭借公司过硬技术实力，历经主机厂多轮严苛性能、安 全验证，高标准通过准入考核，充分彰显我司在自动驾驶配套领域的领先地位与产品竞争力。 ...

自动驾驶车端世界模型方向 招工程师/博后/实习生 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30个 方向 学习 路线 清华大学智能绿色车辆与交通全国重点实验室招聘工程师/博后/实习生，感兴趣的可以联系柱哥投递简历或邮 箱自行投递简历。 【岗位目标】 面向端到端自动驾驶核心技术需求，从事车端世界模型的研究与工程化落地。构建融合物理先验、时序一致 性与行为预测能力的世界模型架构，实现复杂驾驶场景的理解、预测与生成，支撑自动驾驶系统的感知、预 测、规划一体化能力建设，推动端到端自动驾驶技术的工程化应用。 【核心职责及次要职责】 核心职责： 次要职责： 1. 研究与开发车端世界模型核心架构，融合物理先验、因果推理、时序一致性与行为预测能力； 2. 构建驾驶场景时空表征与预测模型，实现交通参与者行为预测、场景演化推理与长期规划； 3. 研发基于Transformer、Diffusion、Neural Fields等前沿架构的场景生成与仿真模型； 4. 设计多模态输入融合方案，实现图像、点云、地图、轨迹等多源信息的统一编码与推理； 5. 完成世界模型在车端平台的部署优化，满足实时性与资源 ...

Group 1 - Nvidia's CEO Jensen Huang envisions a future where a billion autonomous vehicles will be on the roads, offering options for both ride-hailing and personal ownership of self-driving cars [1] - Nvidia is actively collaborating with autonomous taxi operators to implement its AI chips and Drive AV software stack, aiming to support autonomous fleets by 2027 [3] - The company aims to assist partners in deploying Level 4 (L4) autonomous taxis, which can operate without human intervention in predefined areas, significantly advancing the commercialization of autonomous driving technology [3] Group 2 - Nvidia has launched a series of AI models and tools to accelerate the development of autonomous vehicles and support next-generation robotics, including a new automotive platform named "Alpamayo" [3] - The "Alpamayo" platform allows vehicles to perform reasoning in real-world scenarios, enabling potential users to retrain the model for handling unexpected situations [3] - As of October, Nvidia's automotive and robotics chip sales amounted to $592 million, representing only 1% of the company's total revenue [4]

Core Insights - NVIDIA has announced the full production of the Vera Rubin platform, which weighs nearly 2 tons and integrates six new chips, significantly enhancing inference cost and training efficiency, achieving AI computations at a trillion operations per second, marking it as a true AI factory [2] - The company has also open-sourced its first inference VLA (Vision-Language-Action) model, Alpamayo 1, designed for vehicles to "think" and solve problems in unexpected situations, utilizing a 10 billion parameter architecture [3] - The first vehicles equipped with NVIDIA technology are set to hit the roads in the US in Q1, Europe in Q2, and Asia later in the year [4][17] Production and Performance - The new Rubin platform has a performance increase of 5 times compared to the previous Blackwell version, with training performance being 3.5 times better [5][8] - The Rubin platform can reduce inference token generation costs by up to 10 times and decrease the number of GPUs required for training mixture of experts models by 4 times [8] - The Vera CPU in the Rubin platform features 88 cores, providing double the performance of its predecessor, and is designed for agent inference, making it the most energy-efficient processor in large-scale AI factories [8] Ecosystem and Deployment - Major cloud providers, including Microsoft, are expected to be among the first to deploy the new hardware in the second half of the year, with Microsoft’s next-generation Fairwater AI super factory set to utilize NVIDIA's Vera Rubin NVL72 systems [6] - NVIDIA maintains a long-term bullish outlook, predicting the total market size could reach several trillion dollars despite concerns about increasing competition and sustainability of AI spending [7] Innovations and Technologies - The Rubin platform incorporates five innovative technologies, including the sixth-generation NVLink interconnect technology and a third-generation transformer engine, which provides 50 petaflops of NVFP4 computing power for AI inference [9] - The platform's modular design allows for faster assembly and maintenance, with an 18 times quicker process compared to Blackwell [9] Open Source Initiatives - NVIDIA has released the Alpamayo model as part of a complete open ecosystem for autonomous driving development, which includes simulation frameworks and datasets [14][21] - The Alpamayo model is designed for the autonomous driving research community, allowing developers to adapt it for vehicle development and as a foundational tool for autonomous driving technology [15][18] - NVIDIA has also launched various open-source models and tools across different sectors, including the Nemotron family for agent AI and the Cosmos platform for physical AI [26][27]

Core Viewpoint - The automatic driving sector is experiencing significant momentum following NVIDIA's announcement of the Alpamayo series of open-source AI models and tools aimed at enhancing autonomous vehicle development, with expectations to launch L4-level Robotaxi by 2027 [1][2][3]. Group 1: NVIDIA's Announcement - NVIDIA introduced the Alpamayo series at CES 2026, which includes open-source AI models, simulation tools, and datasets to accelerate the development of reasoning-based autonomous vehicles [2]. - Alpamayo 1 features a 100 billion parameter model designed to enable autonomous vehicles to perceive, reason, and act in rare or complex scenarios [2]. - The Rubin platform, part of this announcement, offers a tenfold reduction in reasoning costs compared to the previous Blackwell platform, with training performance improved by 3.5 times and AI software performance enhanced by five times, expected to ship in the second half of the year [2]. Group 2: Industry Impact - Following NVIDIA's announcement, multiple stocks in the A-share automatic driving sector experienced rapid trading halts, indicating strong market interest and confidence [1][4]. - The automatic driving industry is entering an acceleration phase, with the Chinese government granting the first L3-level conditional autonomous driving vehicle licenses, marking a transition from testing to commercial application [4]. - By the end of 2025, Pony.ai announced that its Robotaxi fleet exceeded 1,159 vehicles, surpassing its strategic goal of 1,000 vehicles [4]. Group 3: Future Prospects - Analysts suggest that the development of the Robotaxi industry is entering a rapid growth phase, with the core of L3-level autonomous driving licenses shifting responsibility to vehicle manufacturers and system suppliers [4]. - Companies with advanced intelligent technology, engineering capabilities, and strong supply chain management are expected to benefit first from this transition [5].

Core Insights - Hesai Technology has been selected by NVIDIA as a lidar partner for the "NVIDIA DRIVE AGX Hyperion 10 platform," which aims to enable L4 autonomous driving across various vehicle types [1][6] - The partnership is expected to assist automotive manufacturers and developers in building safe, scalable, and AI-defined high-performance fleets [1][6] Market Reaction - Following the announcement, Hesai's stock price surged by 6.66% in the Hong Kong market [4][9] Company Overview - Hesai Technology is a leading global developer and manufacturer of lidar technology, with applications in advanced driver-assistance systems (ADAS) for passenger and commercial vehicles, as well as autonomous vehicles and various robotic applications [6][11] - The company integrates lidar manufacturing processes into its R&D design workflow, ensuring rapid product iteration while maintaining high performance, reliability, and low costs [11] - Hesai has significant R&D capabilities and technical expertise in optics, mechanics, and electronics, with its lidar products successfully validated in the market [11] - The company operates offices in Shanghai, Silicon Valley, and Stuttgart, serving clients in over 40 countries worldwide [11]

Core Viewpoint - The automatic driving sector is experiencing significant momentum following NVIDIA's announcement of the Alpamayo series of open-source AI models and simulation tools, aimed at enhancing the development of autonomous vehicles [1][2][3] Group 1: NVIDIA's Announcement - NVIDIA introduced the Alpamayo series, which includes open-source AI models, simulation tools, and datasets to accelerate the development of reasoning-based autonomous vehicles [2] - Alpamayo 1 features a 100 billion parameter model that enables autonomous vehicles to perceive, reason, and act in rare or complex scenarios [2] - The Rubin platform, part of this release, offers a tenfold reduction in reasoning costs compared to the previous Blackwell platform, with training performance improved by 3.5 times and AI software performance enhanced by five times, expected to ship in the second half of the year [2] Group 2: Industry Impact - Following NVIDIA's announcement, multiple stocks in the A-share automatic driving sector quickly reached their daily limit up, indicating strong market enthusiasm [4] - The automatic driving industry is entering an accelerated phase, with ride-hailing platforms and Robotaxi manufacturers speeding up their deployment processes, particularly in major cities like Beijing, Shanghai, Guangzhou, and Shenzhen [5] - The Ministry of Industry and Information Technology in China has granted the first L3-level conditional autonomous driving vehicle licenses, marking a significant step towards commercial application [5] - By the end of 2025, Pony.ai announced that its Robotaxi fleet has surpassed 1,159 vehicles, exceeding its strategic goal of 1,000 vehicles [5] - Analysts suggest that the development of the Robotaxi industry is entering a rapid growth phase, with companies possessing advanced intelligent technology and system capabilities likely to benefit first [5]

人民财讯1月6日电，企查查APP显示，近日，上海禾赛科技有限公司"激光雷达的主体(33)"专利获授 权。企查查专利摘要显示，该外观设计产品用于自动驾驶、通讯、无人机、智能机器人、能源安全检 测、资源勘探等领域的激光雷达，其设计要点在于形状。 ...

2026 年 1 月 5 日，全球激光雷达领导者禾赛科技（NASDAQ: HSAI；HKEX: 2525）今日宣布，公司已被英伟达选定为"NVIDIA DRIVE AGX Hyperion 10 平 台" 的激光雷达合作伙伴。该平台是一套参考计算与传感器架构，旨在帮助各类车型实现 L4 级自动驾驶，助力汽车制造商和开发者构建安全、可扩展且由 人工智能定义的高性能车队。 目前，禾赛正携手全球汽车制造商，基于对更安全、更智能、更普及的出行方式的共同愿景，加速推动下一代自动驾驶技术走向市场。 DRIVE Hyperion 搭载了两套基于 NVIDIA Blackwell 架构构建的 NVIDIA DRIVE AGX Thor 系统级芯片，具备超过 2,000 FP4 TFLOPS 的算力——大致相当 于每秒执行 1,000 INT8 TOPS 运算，可为完整的 360 度传感器数据融合提供实时算力。 禾赛是最新一批完成 DRIVE Hyperion 开放量产架构传感器套件适配认证的合作伙伴之一。该架构所构建的传感器生态系统正持续扩展，涵盖摄像头、毫米 波雷达、激光雷达和超声波技术，赋能汽车制造商和开发者打造并验证面 ...