自动驾驶"放大招"了！ 产业进入加速期？ 2025年至今，在自动驾驶技术初步成熟与监管边际放松趋势下，网约车平台和Robotaxi厂商均逐渐加快了落地 进程，其中我国以北上广深等一、二线城市为主。 1月6日早盘，自动驾驶板块多只股票快速涨停。合众思壮在开盘后5分钟之内封死涨停板，浙江世宝在开盘后6 分钟内封死涨停。除此之外，兴民智通、北斗星通等股票亦涨停。 那么，究竟发生了什么？消息面上，英伟达宣布重大消息称，推出Alpamayo系列开源AI模型、仿真工具及数 据集，专注于推理型辅助驾驶与自动驾驶系统的研发。并预期将于2027年推出L4级Robotaxi。 自动驾驶放大招 2026年1月6日，全球消费电子展（CES）在拉斯维加斯举行。 英伟达推出Alpamayo开源人工智能，用于安全且基于推理的自动驾驶汽车。英伟达在CES 2026上宣布了 Alpamayo系列开源人工智能模型、仿真工具和数据集，以加速基于推理的自动驾驶汽车（AV）的开发。 Alpamayo 1是一个100亿参数的思维链视觉语言行动模型，使AVs能够在罕见或复杂的场景中感知、推理和行 动。AlpaSim提供了一个开放的模拟框架，物理AI开放数 ...

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 ...

Core Viewpoint - The article highlights NVIDIA's advancements in AI and computing architecture, emphasizing the dual transformation occurring in AI and computing, which is reshaping the entire technology stack and creating new applications and ecosystems [6][7]. Group 1: AI and Computing Transformation - Huang emphasized that the computing industry undergoes a platform change every 10 to 15 years, with the current shift driven by AI and computing architecture simultaneously evolving [6]. - AI is both an application and a new platform, leading to a paradigm shift in software development from coding to model training [6][7]. - The modernization of a $10 trillion computing infrastructure is underway, with billions in venture capital flowing into AI, as industries shift R&D budgets towards AI [7]. Group 2: Open Source Models - Huang noted that one of the significant changes in the industry last year was the rise of open-source models, specifically mentioning China's DeepSeek R1 as a remarkable contributor to this global movement [7][8]. - Multiple open-source models were showcased, including three from China: Kimi K2, Qwen, and DeepseekV3.2 [8]. Group 3: Physical AI and Autonomous Driving - Huang stated that the next phase of AI development involves entering the physical world, requiring AI to learn common sense about physical properties [10]. - NVIDIA is working on a system that allows AI to learn about the physical world, which is crucial for applications like autonomous driving [10][12]. - Huang believes that the transition from non-autonomous to autonomous vehicles is imminent, with a significant portion of cars expected to be autonomous in the next decade [14]. Group 4: New Chip Platform - Rubin - The Rubin platform includes six new chips, with the Rubin GPU achieving a reasoning power of 50 PFLOPS, five times that of the previous Blackwell platform [21]. - The Rubin platform's design allows for a tenfold reduction in reasoning token costs and a fourfold decrease in the number of GPUs needed for training [21][22]. - The new Vera Rubin NVL72 chip is expected to significantly enhance performance, with reasoning and training capabilities reaching 3.6 EFLOPS and 2.5 EFLOPS, respectively [24]. Group 5: Collaborations and Future Developments - NVIDIA announced a deepened collaboration with Siemens to integrate its physical AI models into Siemens' industrial software, covering the entire lifecycle from chip design to production [16]. - The first autonomous vehicles using NVIDIA's DRIVE AV software are set to hit the roads in the U.S. in the first quarter of this year, with further expansions planned for Europe and Asia [16].

Core Viewpoint - The collaboration between Lucid, Uber, and Nuro aims to launch a production-level autonomous taxi, Robotaxi, based on the Lucid Gravity SUV, with commercial operations expected to start in late 2026 [1][2][3]. Group 1: Product and Technology - The Robotaxi is built on the Lucid Gravity all-electric SUV platform and features a new generation sensor array, including high-resolution cameras, solid-state LiDAR sensors, and radar, providing 360-degree perception capabilities [1][3]. - The vehicle utilizes the NVIDIA Drive AGX Thor computing platform for real-time AI processing and advanced autonomous driving support, accommodating up to six passengers with interactive screens for personalized settings [1][3]. Group 2: Market Deployment and Financial Aspects - The three companies plan to deploy over 20,000 Lucid vehicles equipped with Nuro Driver Level 4 autonomous driving systems over the next six years, covering multiple global markets [1][2][3]. - Uber plans to invest hundreds of millions of dollars into Nuro and Lucid as part of this collaboration, which is significant for Lucid as it seeks cash flow support [2][4].

Group 1 - The core viewpoint is that a significant portion of cars in the next decade will be highly autonomous, as stated by NVIDIA's founder and CEO Jensen Huang at CES 2026 [1] - Huang emphasized the importance of synthetic data for autonomous driving and robotic systems, indicating that the fundamental technologies for generating and simulating synthetic data are applicable to various forms of robotic systems [1] - The next era for robotic systems will involve robots of different sizes, showcasing a variety of robotic forms within the company's collaborative ecosystem [1]

Core Insights - NVIDIA's CEO Jensen Huang announced multiple open-source models related to physical AI and detailed the performance data of the new chip platform Rubin during a keynote speech at CES [1] - The event attracted significant attention, with a full audience of 3,000 people, indicating strong interest in NVIDIA's advancements in AI technology [1] Group 1: Product Announcements - NVIDIA introduced several open-source models focused on physical AI, marking a shift from solely relying on transistor density improvements to enhancing network processing and low-precision floating-point operations [1] - The Rubin chip platform includes six new chips, such as Vera CPU and Rubin GPU, with Rubin GPU achieving a 50 PFLOPS inference performance, five times that of the previous Blackwell platform [18][20] - The new platform's design allows for a 10-fold reduction in inference token costs and a fourfold decrease in the number of GPUs required for training MoE models compared to Blackwell [20] Group 2: AI Development and Trends - Huang emphasized that AI and computing architecture are undergoing simultaneous transformations, with AI serving as both an application and a new platform [6] - The shift in software development paradigms from coding to model training signifies a complete restructuring of the computing technology stack [6] - The global industry is reallocating R&D budgets towards AI, driven by the modernization of computing infrastructure valued at approximately $10 trillion over the past decade [7] Group 3: Future of AI and Autonomous Vehicles - Huang highlighted that the next phase of AI development involves integrating AI into the physical world, with a focus on teaching AI common sense about physical properties [9] - The transition from non-autonomous to autonomous vehicles is anticipated to occur within the next decade, with a significant portion of cars expected to be fully or highly autonomous [12] - NVIDIA's DRIVE AV software will be implemented in Mercedes-Benz vehicles, with the first autonomous vehicle expected to hit the roads in the U.S. in Q1 2024 [16] Group 4: Collaborations and Industrial Applications - NVIDIA announced a deepened collaboration with Siemens to integrate its physical AI models and Omniverse simulation platform into Siemens' industrial software, covering the entire lifecycle from chip design to production operations [16] - The company is positioned at the forefront of a new industrial revolution, leveraging physical AI to enhance chip design and automation in manufacturing [16] Group 5: Open-Source Models and Global Impact - Huang noted the significant rise of open-source models in the industry, specifically mentioning China's DeepSeek R1 as a model that has surprised the world and activated a global open-source movement [7][8] - The presentation included several open-source models from China, such as Kimi K2 and Qwen, showcasing the competitive advancements in AI technology [8]

Core Viewpoint - The CEO of Nvidia, Jensen Huang, predicts that a significant portion of cars will be highly autonomous in the next decade [1][3]. Group 1: Autonomous Driving - Huang emphasizes the importance of synthetic data for autonomous driving and robotic systems [1][3]. - He states that the fundamental technologies for generating and simulating synthetic data are applicable to various forms of robotic systems, including robots, joints, mechanical hands, mobile robots, and humanoid robots [1][3]. Group 2: Robotics - Huang believes that the next era for robotic systems will involve robots of various sizes [4]. - He showcased different forms of robots within the company's collaborative ecosystem during the event [4].