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].

Core Viewpoint - The announcements from Youjia Innovation demonstrate the confidence of major shareholders and the board in the company's long-term development, aiming to boost market sentiment and protect shareholder interests [1][2]. Group 1: Shareholder Commitments - Major shareholders, including executive directors and individual shareholders, have voluntarily extended the lock-up period for their shares, with four executive directors holding a combined 18.42% of shares extending their lock-up until December 27, 2026, and individual shareholders extending theirs until June 27, 2026 [1]. - Chairman Liu Guoqing purchased 50,000 H-shares at an average price of approximately HKD 12.60 per share on January 5, 2026, signaling confidence in the company's future [1]. Group 2: Business Outlook and Market Position - Analysts highlight that these actions reflect the confidence of major shareholders in Youjia Innovation's business prospects, which is expected to positively influence market sentiment and protect shareholder rights [2]. - The company has established a differentiated advantage in technology innovation, ecosystem openness, and global expansion, which is expected to drive long-term growth [2]. - Youjia Innovation has achieved commercial success in both L2 and L4 autonomous driving sectors, with a compound annual growth rate of over 50% in revenue and a deepening business moat [2]. Group 3: Business Expansion and Revenue Growth - In the L2 pre-installation business, Youjia Innovation has expanded its customer base to 42 automakers, including leading domestic and luxury brands, and is advancing its overseas strategy [5]. - The company’s L4 autonomous driving business has entered a commercialization phase, with successful deployments in various cities and high-demand scenarios, contributing over one million yuan in revenue in the first half of the year [5]. - The introduction of the new unmanned vehicle, Xiaozhu, aims to penetrate the billion-level unmanned logistics market, securing over a thousand bulk orders and accelerating deployment in logistics and urban distribution [5]. Group 4: Industry Trends and Competitive Advantage - The opening of L3 autonomous driving in China is accelerating industry upgrades, creating opportunities for high-level autonomous driving and L4 mass production [9]. - Youjia Innovation has established a comprehensive competitive advantage through its full-dimensional technology layout and strong engineering capabilities, positioning itself to benefit from both policy and market catalysts [9]. - The company's recent inclusion in the Hang Seng Hong Kong Stock Connect electronic theme index reflects market recognition of its industry position and growth potential [9].

Core Viewpoint - Teradar has launched its first flagship terahertz sensor, named Summit, which aims to fill the gap left by traditional radar and lidar sensors, offering high performance in all weather conditions [1][10]. Group 1: Product Features and Technology - The Summit sensor is designed to operate in the terahertz frequency range, which has not been fully utilized, and features a solid-state design with no moving parts [1][4]. - Teradar claims that its sensor can provide 20 times the resolution of traditional automotive radar and maintains performance in adverse weather conditions [11][12]. - The modular design of the sensor allows customization for specific Advanced Driver Assistance Systems (ADAS) or autonomous driving needs, with an expected price range in the hundreds of dollars [7][8]. Group 2: Market Context and Competition - The launch of Teradar's sensor comes at a time when automotive sensor suppliers are facing challenges, including the bankruptcy of Luminar after losing contracts with major automakers [2]. - Chinese companies are aggressively entering the lidar market, with plans to produce over 1 million lidar sensors by 2025, increasing competition for Teradar [2]. - Other U.S. companies in the lidar space are diversifying into robotics and smart infrastructure, indicating a shift in market focus [2]. Group 3: Partnerships and Future Prospects - Teradar has secured $150 million in Series B funding, with investments from Lockheed Martin's venture capital arm and VXI Capital, indicating strong interest in its technology [2][5]. - The company is collaborating with five major automotive manufacturers and three tier-one suppliers to validate its technology, with plans to begin shipping the Summit sensor in 2028 [1][10]. - Teradar's technology is positioned as a complementary or alternative solution to existing sensor suites, addressing the limitations of current sensor technologies [10][13].

在大约40分钟的时间里，我们穿梭在旧金山一个典型的混乱路况中：送货卡车、骑自行车者、行人，甚 至偶尔还会出现Waymo自动驾驶出租车。这辆奔驰在英伟达AI驱动系统及车辆自带摄像头与雷达的引 导下，从容应对各种路况：交通信号灯、四向停车路口、并排停放的车辆，甚至偶尔遇到无信号灯指引 的左转。有一次在十字路口遇到卡车占道，系统先礼让缓行的行人通过，随后流畅地做出大半径右转绕 行。 凤凰网科技讯 北京时间1月6日，芯片巨头英伟达正在大力押注自动驾驶汽车。根据美国科技网站 TheVerge交通内容编辑安德鲁·J·霍金斯(Andrew J. Hawkins)的测试，英伟达的自动驾驶系统进展迅速， 对特斯拉的全自动驾驶系统(FSD)造成了压力。 以下是文章全文： 旧金山一个晴朗无云的日子，我坐在一辆奔驰CLA轿车的副驾驶座上。司机卢卡斯(Lucas)的手放在方 向盘上，但这实际上只是装装样子：这辆车基本上是在自动驾驶。 该车正在使用英伟达新型点对点L2++级辅助驾驶系统，该系统计划于2026年面向更多汽车制造商推 出。这是英伟达在自动驾驶领域的重大押注，该公司认为自动驾驶能帮助其规模尚小的汽车业务发展成 更庞大、更盈利的 ...