此次CES上，英伟达可能带来企业AI第一次真正落地。 2026年消费电子展（CES）当地时间6日在美国拉斯维加斯正式开幕。在美股科技板块中，CES一直被 视为年初最重要的市场情绪催化节点之一，而今年，这一节点的重要性尤为突出。 多位参与CES的科技圈人士对第一财经表示，一方面，AI芯片需求仍处高景气区间；另一方面，资本市 场的关注焦点已从"算力是否紧缺"，逐步转向"AI何时、如何转化为可持续收入"，也正因如此，即使此 前英伟达股价下跌后的远期市盈率已经跌入了20倍区间，投资者大幅抄底买入的兴趣仍不如以往。在这 一背景下，英伟达在此次CES主办多场论坛——1月5日到8日每日"供应"，其CEO黄仁勋的CES演讲也 被视为一次关于AI下一阶段走向的关键定调。 综合目前释放的信息，英伟达在本届CES上的看点，或不止于新品发布，而更集中于AI商业模式的落地 路径。 企业级AI能否走向"可复制"的收入模式 过去一年，大模型能力已被充分验证。无论是文本、图像还是多模态模型，其技术上限已不再是争论焦 点。 大模型科技公司OpenAGI创始人秦增益博士对第一财经表示，目前对大语言模型仍持有乐观态度，虽然 它可能非最终技术范式， ...

Core Insights - The current AI products are limited to screens, and there is a push towards physical AI that interacts directly with the physical world, moving beyond screen dependency [1] - The investment landscape in the AI sector is rapidly evolving, with significant growth in physical AI, particularly in the areas of robotics and wearable devices [2][3] - The digital economy contributes only 15% to global GDP, indicating a vast potential for AI applications in physical industries [3] Investment Trends - In 2024, the total venture capital investment in AI in the US reached $87 billion, and by December 15, 2025, it is projected to reach $159 billion [2] - The physical AI sector saw notable investments, with robotics startups raising $6.4 billion in 2024 and over $10.3 billion in 2025, marking a 60.9% year-over-year increase [2] - Major funding rounds include Figure's $1 billion financing, FieldAI's $314 million, and Oura Ring's $900 million, with valuations reaching $39 billion, $2 billion, and $11 billion respectively [2] Company Highlights - **Figure**: Raised $1 billion in 2025, achieving a post-money valuation of $39 billion, focusing on a vertically integrated strategy for robotics [4][6] - **Physical Intelligence**: Secured $600 million in B-round funding, with a valuation of $5.6 billion, and released a foundational model enabling robots to operate in new environments without prior training [7] - **Skild AI**: Raised $135 million in B-round funding, with a valuation of $4.4 billion, focusing on developing a universal foundational model for robotics [10][11] - **Oura**: Dominates the smart ring market with over 80% share, having sold 5.5 million units and achieving a valuation of $11 billion [24][25] Systemic Gaps in Physical AI - There is a lack of native operating systems for smart wearable devices, which hinders the development of AI-native hardware [45] - The industry faces a shortage of raw data necessary for developing robust AI models, despite the initial validation of scaling laws in embodied intelligence [45] - The need for breakthroughs in world models is critical, as existing data on human actions is insufficient for training comprehensive models [45] Advantages for Chinese AI Hardware Startups - Chinese AI hardware entrepreneurs benefit from a strong manufacturing ecosystem, large market scale, and supportive government policies that prioritize embodied AI as a strategic focus [46]

A股复盘 | 大A强得陌生 / 2026.01.06 我还是想说昨天那句话， "预期到会有开门红，竟然红成这样"！连续两个交易日超百股涨停，这两天都赚肿了！ 小熊猫说：4000点收费站改成4000点加油站了 特斯拉宣布:5年0息、7年超低息 一财快讯 第一财经 2026年1月6日 11:22 上海 1月6日,特斯拉官微发布消息称,特斯拉Model 3/Y/Y L推出7年超 低息购车方案。 其中, Model 3/Y首付7.99万元起,月供可低至1918元; Model Y L首付9.99万元起，月供可低至2947元。 年! Model 3/Y/Y L ■ 年超低息购车方案来了!! Model 3/Y首付7.99万起,月供可低至1918元 Model Y L首付9.99万起,月供可低至2947元 f年轻松提新车,怎么买都划算 。 网页链接 -财经 17 30 不过市场连续收阳，也有部分资金选择离场。据中国基金报统计，1月5日，股票ETF市场总份额减少95.36亿份，按照成交均价测算，当日 净流出资金达35.33亿元，45只股票ETF净流入超过1亿元，南方中证500ETF、华泰柏瑞沪深300ETF、南方有色金属E ...

Core Insights - The CES 2026 showcased NVIDIA's strategic focus on next-generation computing platforms and advancements in physical AI, marking the first time in five years that NVIDIA did not release a new GPU at the event [2][3]. Group 1: Open Source Ecosystem - NVIDIA's CEO highlighted the significant investment of approximately $10 trillion in computing resources over the past decade, emphasizing a shift in software paradigms rather than just hardware upgrades [3]. - The presentation acknowledged the rapid development of Chinese open-source models, specifically naming Kimi K2, DeepSeek V3.2, and Qwen, which are leading the open-source ecosystem alongside OpenAI's GPT-OSS [5]. - Despite being approximately six months behind the top models, the open-source models are expected to see new iterations every six months, attracting interest from startups, giants, and researchers alike [5]. Group 2: Next-Generation Computing Platform - NVIDIA introduced the Vera Rubin computing platform, designed to accelerate AI training speeds and facilitate the development of next-generation models [7]. - The platform features a complete redesign of six chips, including Vera CPU and Rubin GPU, with the Rubin GPU achieving a performance of 50 PFLOPS, five times that of its predecessor [7][8]. - The engineering design of Vera Rubin simplifies assembly, reducing the number of cables from 43 to just six liquid cooling pipes, allowing for quicker setup times [8]. Group 3: Advancements in Physical AI - NVIDIA's CEO announced the launch of the Alpamayo open-source AI model aimed at enhancing autonomous driving capabilities, addressing complex driving scenarios through a new reasoning model [10][11]. - The Alpamayo series incorporates a "thinking chain" reasoning model, improving decision-making processes in autonomous vehicles and enhancing user trust in the technology [11]. - The first vehicles utilizing NVIDIA's technology are expected to hit the roads in the U.S. in Q1, Europe in Q2, and Asia later in the year, with interest from companies like Jaguar Land Rover and Uber [11]. Group 4: Robotics Development - NVIDIA unveiled two new open-source models for robotics, NVIDIA Cosmos and GR00T, along with a performance evaluation tool, Isaac Lab-Arena, aimed at simplifying robot training processes [12]. - The collaboration with Hugging Face integrates NVIDIA's Isaac open-source models into the LeRobot project, accelerating the development of the open-source robotics community [12]. - Companies such as Boston Dynamics and Caterpillar are developing new robots and autonomous devices based on NVIDIA's technology, indicating a significant advancement in the robotics sector [13].

刚刚的CES 2026上，老黄带着Vera Rubin超算架构向全世界走来！Rubin的推理性能比Blackwell提升了5倍，训练性能提升3.5倍，成本降低10倍，已经大 规模投产，将于2026下半年面世。没有新显卡的昨夜，老黄表示all in AI！ 天空一声巨响，全新版本的「皮衣老黄」闪亮登场。 在本次CES演讲中最为激动人心的瞬间，就是英伟达全新一代芯片架构——Vera Rubin正式登场！ 全球AI算力告急？老黄霸气回应：Vera Rubin已全面投产。 这是新一代的算力怪兽，也是对上一代霸主Blackwell的降维打击—— 英伟达在X上的一纸公告，彻底击碎了「攒机党」最后的幻想：CES 2026将没有任何新GPU发布。 这意味着，英伟达自2021年以来连续五年在CES发布新硬件的传统，就此终结。 传闻已久的RTX 50 Super系列，受困于GDDR7显存的「产能地狱」，大概率已经胎死腹中。 Rubin炸裂登场，6颗芯片，10倍推理，AI超算变工厂 推理Token成本直接暴降10倍，算力性能狂飙5倍。 就连训练MoE模型所需的GPU数量，也直接减少了4倍。 曾经，Blackwell终结了Hoppe ...

黄仁勋称"物理AI的ChatGPT时刻"即将到来。 北京时间1月6日，美国拉斯维加斯，在全球"科技春晚"——国际消费电子展（CES）展会现场，英伟达 创始人兼CEO黄仁勋发表主题演讲。他以"计算行业的双重重启"为核心，同时发布Vera Rubin AI超级计 算机、Alpamayo自动驾驶AI等一系列突破性产品与技术，并宣布与西门子、Palantir、ServiceNow等行 业巨头的深度合作。 双重平台转移重塑计算核心，10万亿美元基础设施迎来AI转型 黄仁勋在演讲中指出，计算机行业正经历每10—15年一次的历史性变革，且首次出现"双平台转移"叠 加：一方面，应用程序全面构建于AI之上，开发者不再单纯编程而是训练软件，计算核心从CPU转向 GPU；另一方面，软件的研发与运行逻辑被彻底重构，AI能够理解上下文并实时生成内容，取代了传 统预编译运行模式。 这一变革驱动着全球约10万亿美元的计算基础设施向AI化转型，数千亿美元风险投资涌入AI领域，价 值100万亿美元的全球产业正将研发预算向人工智能倾斜。黄仁勋强调："从传统IT向AI的现代化转型， 正是行业创新的资金源泉，也让AI成为驱动所有产业升级的核心引擎。 ...

Investment Rating - The report assigns a "Buy" rating for the company [7] Core Insights - The company achieved total revenue of 20.38 billion yuan in Q3 2025, a year-on-year increase of 101.8%, with net loss significantly narrowing to 0.38 billion yuan. Total deliveries reached 116,007 units, up 149.3%, marking a historical high. The comprehensive gross margin exceeded 20% for the first time, reaching 20.1%, indicating a notable improvement in profitability [1][4] - The company has launched a "dual power" strategy combining pure electric and range-extended vehicles to address user range anxiety. The first range-extended model, X9 EREV, was launched in November 2025, featuring a 63.3 kWh battery and a conversion efficiency exceeding 3.6 kWh/L, achieving a pure electric range of 452 km. Additional range-extended versions of key models are expected in Q1 2026, alongside four new models in 2026, including two SUVs based on the MONA platform [2] - The company is transitioning from "smart cars" to a "physical AI" company, showcasing its commitment and specific path at the 2025 Technology Day. The core technology, VLA 2.0, enhances reasoning efficiency by 12 times and improves average takeover mileage in complex scenarios by 13 times. The model is set to be fully deployed in Ultra models by Q1 2026 and is expected to extend to robotics and other embodied intelligence fields [3] - The company forecasts revenues of 75.8 billion yuan, 132.1 billion yuan, and 166.3 billion yuan for 2025, 2026, and 2027, respectively, with year-on-year growth rates of 85.4%, 74.3%, and 25.9%. The net profit attributable to the parent company is projected to be -1.55 billion yuan, 2.00 billion yuan, and 6.13 billion yuan for the same years [4][5]

文 | 大模型之家 北京时间1月6日凌晨，英伟达CEO黄仁勋CES 2026的开幕演讲中，系统阐述了他对人工智能产业演进 的最新判断，并正式发布了全新一代Vera Rubin计算架构。这一架构涵盖CPU、GPU、互连、网络、存 储与系统级设计，被英伟达定义为面向"下一阶段AI前沿"的基础设施平台。 在这场演讲中，黄仁勋并未将重点放在某一具体应用或模型能力上，而是反复强调一个核心命题：人工 智能正在引发一次覆盖整个计算产业的结构性重置，而英伟达的角色，是为这场重置提供底层工具与系 统能力。 AI走向"平台化"， 英伟达要做底层"卖铲人" 黄仁勋对AI市场的判断，延续了他一贯的"平台论"视角。他表示，计算产业每隔10到15年就会发生一次 底层重置：从大型机到PC，从互联网到云计算，再到移动计算。每一次重置，应用形态都会随之改 变，产业价值链也会重新分配。 但AI的特殊之处在于，它并不是单一平台的替代，而是两次平台迁移同时发生。 第一层迁移，是应用本身的重构。应用不再是被"编写"的，而是被"训练"的；不再是预设流程，而是在 运行时根据上下文实时生成每一个token、每一个像素。AI不再是应用，而是应用赖以生存的底座 ...

Core Viewpoint - The computing industry is undergoing a historic transformation characterized by a "dual platform shift," with AI becoming the core driver of innovation and investment across various sectors [3][4]. Group 1: Dual Platform Shift - The computing industry is experiencing a significant change every 10-15 years, marked by a dual platform shift where applications are built on AI, and the core computation moves from CPU to GPU [3]. - AI is fundamentally restructuring software development and operational logic, enabling real-time content generation and understanding of context [3]. - Approximately $10 trillion in global computing infrastructure is transitioning towards AI, with billions in venture capital flowing into the AI sector [3]. Group 2: Key Technological Breakthroughs - The Vera Rubin AI supercomputer has been launched to address the exponential growth in AI model size and inference token requirements, featuring a design that integrates six custom chips [5][6]. - Open model ecosystems are rapidly emerging, with models like DeepSeek R1 gaining traction and closing the gap with leading models through rapid iteration [6]. - Agentic systems, capable of reasoning and planning, are expected to be fully mainstream by 2025, transforming software programming practices [6]. - The "ChatGPT moment" for physical AI is approaching, with the Cosmos model enabling realistic simulations for robotics and autonomous driving [6]. - The Alpamayo autonomous driving AI has achieved "thinking driving," capable of making decisions and explaining actions, set to debut in vehicles in the US, Europe, and Asia [6]. Group 3: Industry Collaboration and Ecosystem - Strategic partnerships with companies like Siemens and Palantir aim to integrate AI into various industrial processes, addressing labor shortages and automation needs [8]. - The AI ecosystem is expanding across robotics, with applications in consumer, industrial, and medical fields, showcasing the versatility of AI technologies [8]. - Nvidia's mission is to create a comprehensive AI platform that allows participation from all sectors, promoting widespread AI innovation [9].

Core Viewpoint - NVIDIA has accelerated its AI chip platform release with the introduction of the "Rubin" platform at CES 2026, marking a shift in its product announcement strategy and emphasizing the growing demand for AI computing in both training and inference [2][4]. Group 1: Rubin Platform Overview - The Rubin platform, which integrates six chips including the NVIDIA Vera CPU and Rubin GPU, is designed for extreme collaborative performance, enhancing AI training performance by 3.5 times and operational performance by 5 times compared to the previous Blackwell architecture [4]. - The Rubin platform's inference token cost can be reduced by up to 10 times, and the number of GPUs required for training MoE models is decreased by four times [5]. - The NVL72 system, which includes 72 GPU packaging units, was also announced, with each unit containing two Rubin dies, totaling 144 Rubin dies in the system [5]. Group 2: Ecosystem and Market Response - Major cloud providers and model companies such as AWS, Microsoft, Google, OpenAI, and Meta have shown strong interest in the Rubin platform, indicating a positive market response [6]. - NVIDIA's early announcement of Rubin aims to provide engineering samples to ecosystem partners for preparation of subsequent deployment and scaling applications [6]. Group 3: Full-Stack AI Strategy - NVIDIA's presentation at CES included a range of AI products, signaling a shift from training scale to inference systems, with the introduction of the Inference Context Memory Storage Platform designed for efficient management of KV Cache [8]. - The company is expanding its focus on physical AI, releasing open-source models and frameworks that extend AI capabilities into robotics, autonomous driving, and industrial edge scenarios [8][9]. - The Cosmos and GR00T series models were introduced for robotics, enabling machines to understand and act in the physical world, while the Alpamayo model family was launched for autonomous driving, supported by a high-fidelity simulation framework [11].