北京时间1月6日早五点，英伟达CEO黄仁勋在CES 2026开幕前的 keynote 演讲中，用90分钟为全球科技产业描绘了一幅激进且完整的未来图景。 在这场信息密度极高的演讲中，他不仅宣告人工智能的发展重心正从纯粹的"数字智能"迈向与物理世界交互的"物理AI"新纪元，更以一系列开源重器—— 从世界模型Cosmos、自动驾驶系统AlphaMio到新一代AI芯片架构Vera Rubin——展示了英伟达作为全栈巨头的野心：即为这个新时代构建从底层芯片、基 础设施到顶层模型与应用的全部基石。 当AI时代的算力需求正无限放大，英伟达仍在通过对计算平台的极限升级，试图吃下这个庞大的数字世界算力基座。 摘要： "Rubin 的到来恰逢其时，因为训练和推理的 AI 计算需求正在激增。" DeepSeek带来的启示，开源是创新主引擎 演讲伊始，黄仁勋便以历史性的视角定调感慨："每隔10到15年，计算行业就会发生一次平台迁移。"他强调，当前我们正同时经历两大迁移：一是应用转 向以AI为核心构建；二是整个软件开发和运行范式被重塑——从"编程"转向"训练"，从CPU转向GPU，从执行预编译代码转向实时生成内容。 "这意味着过去十年 ...

Core Insights - NVIDIA is set to experience unprecedented spending in 2026, showcasing its absolute strength and leading advantage in the AI field [2] - The company has announced the full production of its next-generation Rubin chip architecture, significantly ahead of the expected timeline [3] Group 1: Rubin Chip Architecture - The Rubin architecture aims to create an incredible AI supercomputer, marking the next generation of artificial intelligence [3] - The architecture consists of six chips, including the NVIDIA Vera CPU and NVIDIA Rubin GPU, designed for extreme collaboration to enhance efficiency and performance in large model training and inference [4] - Compared to the current Blackwell architecture, Rubin uses four times the GPUs for parallel training of mixed experts (MoE) models, reducing average inference costs by up to 10 times and increasing training speed by 3.5 times [4] Group 2: Market Position and Competition - NVIDIA faces strong competition from Google’s TPU and other ASIC chips, which are perceived to offer lower total cost of ownership (TCO) while maintaining or exceeding performance [5] - Despite the competitive landscape, NVIDIA's CEO expressed confidence in Rubin's ability to improve the company's product delivery value and market share in data centers [5] - Major cloud providers and AI developers, including AWS, Google, and Microsoft, are interested in deploying Rubin, indicating strong customer demand [5] Group 3: Future Trends in AI - The demand for AI computing is expected to surge, with Morgan Stanley predicting a 26% year-over-year increase in data center AI chip shipments in 2026 [6] - NVIDIA aims for Rubin to counter predictions that ASIC chips will significantly outpace GPU growth, with ASIC market share expected to rise from under 41% to over 46% [6] - The company is positioning itself for the transition from generative AI to agent-based AI, which is anticipated to transform enterprise-level AI usage [6] Group 4: Physical AI Developments - NVIDIA is actively investing in physical AI, having previously introduced the NVIDIA Cosmos model and now unveiling new products in robotics and autonomous driving [6][7] - Collaborations with leading companies like Boston Dynamics and Caterpillar are underway to develop new AI robots using NVIDIA's technology [7] - The CEO declared that the "ChatGPT moment" for physical AI has arrived, indicating a significant shift in the industry [7]

硬·AI 作者 | 赵雨荷 高通基于安全级高性能SoC平台，推出了一套完整的通用机器人全栈架构，整合硬件、软件与AI能力。该架构在能效和可 扩展性方面处于行业领先水平，可支持从个人服务机器人、下一代工业自主移动机器人（AMR），到具备推理、适应和 决策能力的全尺寸人形机器人。全新的端到端架构通过赋能通用型、持续学习的机器人形态，加快了零售、物流和制造等 行业的自动化落地。作为这一架构的核心，高通同步推出Dragonwing™ IQ10系列，这是其面向人形机器人和高级自主 移动机器人的最新旗舰级机器人处理器。 对此，高通汽车、工业与嵌入式物联网及机器人业务执行副总裁兼集团总经理Nakul Duggal表示： 编辑 | 硬 AI 周一，高通在拉斯维加斯CES展上发布了一套新一代机器人"全栈式"架构，将硬件、软件以及复合式AI整 合在一起，目标是为从小型家用机器人到全尺寸人形机器人在内的各种形态提供动力。 同时，高通还同时发布了其最新的高性能机器人处理器——Qualcomm Dragonwing™ IQ10系列，面向工 业自主移动机器人（AMR）以及先进的全尺寸人形机器人。 这是该公司最新一代专为机器人打造的处理器 ...

Core Viewpoint - NVIDIA has announced the open-source release of its first inference VLA (Vision-Language-Action) model, Alpamayo 1, aimed at enhancing autonomous driving technology by enabling vehicles to "think" and solve problems in unexpected situations [2][3][5]. Group 1: Model and Technology Overview - The Alpamayo 1 model features a 10 billion parameter architecture that processes video inputs to generate trajectories and reasoning processes [2][5][9]. - This model is designed to address the long-tail problem in autonomous driving by employing human-like reasoning to handle complex driving scenarios [3][5]. - The model is not intended to run directly in vehicles but serves as a large-scale teacher model for developers to fine-tune and integrate into their autonomous driving technology stacks [11]. Group 2: Industry Support and Collaboration - Major companies and research institutions, including Jaguar Land Rover, Lucid, Uber, and UC Berkeley's DeepDrive, have expressed support for the Alpamayo model, indicating its potential to accelerate the deployment of Level 4 autonomous driving technologies [5][16]. - Industry leaders emphasize the importance of open and transparent AI development for advancing responsible autonomous mobility, highlighting the role of Alpamayo in providing new tools for developers [16]. Group 3: Ecosystem and Additional Tools - NVIDIA has created a comprehensive open ecosystem around the Alpamayo model, including simulation tools and datasets, to support developers in building autonomous driving solutions [9][15]. - The AlpaSim framework, a fully open-source end-to-end simulation tool, has been released to facilitate high-fidelity autonomous driving development [15]. - NVIDIA also provides a large-scale open dataset with over 1,700 hours of driving data, covering a wide range of geographical locations and conditions, crucial for advancing reasoning architectures [15]. Group 4: Broader AI Developments - In addition to Alpamayo, NVIDIA has launched several other open-source models and tools across various sectors, including the Nemotron family for agent AI, the Cosmos platform for physical AI, and the Isaac GR00T model for robotics [21][22]. - These models and frameworks are available on platforms like GitHub and Hugging Face, enabling widespread access and deployment across different AI infrastructures [22].

过去两年里，英伟达因为AI芯片业务实现了惊人的增长。 从2023年前九个月的275亿美元营收跃升至2024年同期的近1480亿美元，这样的增长速度在科技行业历史上都算得上罕见。 然而黄仁勋并不满足于此。 他将英伟达的下一阶段押注在机器人和制造业上，于是就有了Omniverse。 但其结果不仅没有达到预期，甚至还让慈眉善目的黄仁勋"破防了"。 在今年拉斯维加斯的消费电子展上，他还向外界讲述这个价值数万亿美元的机会故事，展台上会有西门子CEO、敏捷机器人公司CTO等重 量级嘉宾站台。 但在这些光鲜的表面之下，隐藏着一个令人尴尬的事实。 四位现任和前任英伟达员工透露，经过四年的努力，Omniverse业务几乎没有取得实质性进展。 虽然英伟达对外公布了一长串使用Omniverse软件的公司名单，从宝马、西门子到富士康、波士顿动力，但真正签约在Omniverse Cloud服 务器上运行大规模模拟的公司寥寥无几。 开发者对Omniverse工具的评价也不尽如人意。使用过Omniverse场景构建和模拟工具的开发者经常抱怨软件难以使用，容易崩溃，功能感 觉不完整。 软件开发者Valentin Forager表示，Omni ...

新浪科技讯 1月6日上午消息，在国际消费电子产品展览会（CES 2026）上，NVIDIA发布了NVIDIA Alpamayo系列开源AI模型、仿真工具及数据集，旨在推动安全可靠的推理型辅助驾驶汽车开发。 据悉，Alpamayo系列引入基于思维链的 VLA 推理模型，这是一款为应对辅助驾驶长尾场景挑战而设计 的开源视觉-语言-动作推理模型力。这些系统能够逐步推演罕见或全新场景，提升驾驶能力和可解释 性，对构建智能汽车的安全信任体系至关重要，其核心技术由 NVIDIA Halos 安全系统提供支撑。 此外，NVIDIA Alpamayo 系列还包含赋能辅助驾驶汽车开发的仿真工具和数据集。Alpamayo 1、 AlpaSim 和物理 AI 开放数据集可为开发具备感知、推理与类人决策能力的车辆提供支持，使开发者能 够进行模型调优、蒸馏和测试，从而提升安全性、鲁棒性与可扩展性。 目前，捷豹路虎、Lucid 和 Uber 等移动出行领域领先企业，以及包括伯克利 DeepDrive 在内的自动驾驶 研究社区，将依托 Alpamayo 加速推进安全的推理型 L4 级部署进程。 专题：2026年度国际消费电子展(CES) ...

下一代Rubin架构GPU 推 理、训练性能分 别是 Blackwell GB 200的5倍和3.5倍 （NVFP4数据格式）。 西风 闻乐 发自 凹非寺 量子位 | 公众号 QbitAI 刚刚，英伟达CEO黄仁勋穿着鳄鱼皮夹克，在全球最大消费电子展 CES 2026 上发布AI新品。 这是五年来，英伟达首次来到CES却没有发游戏显卡，态度很明确： 全力 搞AI。 全力搞出来的结果也让围观群众直呼：竞争对手如何追上英伟达？ 除此之外，老黄还带来了五大领域的全新发布，包括： 面向Agentic AI的 NVIDIA Nemotron 模型家族 面向物理AI的 NVIDIA Cosmos 平台 同时，英伟达宣布持续向社区 开 源训 练框架 以 及 多模 态数据 集 。其中数据集包括10万亿语言训练token、50万条机器人轨迹数据、 45.5万个蛋白质结构、100TB车辆传感器数据。 这次的核心主题，直指 物理AI 。 面向自动驾驶开发的全新 NVIDIA Alpamayo 模型家族 面向机器人领域的 NVIDIA Isaac GR00T 面向生物医学的 NVIDIA Clara 用网友的话来说： 这是英伟达将护 ...

Core Insights - The article highlights a significant shift in AI technology, moving from understanding language to transforming the physical world, as announced by NVIDIA CEO Jensen Huang at CES 2026 [2] - NVIDIA has unveiled its latest technology roadmap for "Physical AI," aiming to create a comprehensive stack of computing and software systems to enable AI to understand, reason, and act in the real world [2] Group 1: AI Development and Breakthroughs - Huang emphasized the "dual platform migration," where computing shifts from traditional CPUs to GPU-centric accelerated computing, and application development transitions from predefined code to AI-based training [4] - In 2025, open-source models achieved key breakthroughs but still lagged behind advanced models by about six months, with explosive growth in model downloads as various sectors engage in the AI revolution [3][9] - The emergence of autonomous thinking agent systems in 2024 marks a pivotal development, with models capable of reasoning, information retrieval, and future planning [8] Group 2: Physical AI and New Models - NVIDIA's Physical AI models are categorized into three series: Cosmos World models for world generation and understanding, GROOT for general robotics, and the newly released AlphaMayo for autonomous driving [12] - AlphaMayo, an open-source AI model, enables autonomous vehicles to think like humans, addressing complex driving scenarios by breaking down problems and reasoning through possibilities [16][18] - GROOT 1.6, the latest open-source reasoning model for humanoid robots, enhances reasoning capabilities and coordination for executing complex tasks [22][24] Group 3: AI Supercomputing and Vera Rubin - NVIDIA introduced the Vera Rubin supercomputer, designed to meet the escalating computational demands of AI, with the first products expected to launch in late 2026 [32] - The Vera Rubin architecture features a collaborative design of six chips, providing 100 Petaflops of AI computing power, significantly enhancing performance and efficiency [40][42] - The system incorporates advanced cooling and security features, ensuring data protection and energy efficiency, which is crucial for modern AI workloads [47][49] Group 4: Ecosystem and Collaboration - NVIDIA's collaboration with Hugging Face connects a vast community of AI developers, facilitating the integration of NVIDIA's tools into existing workflows [30] - The launch of the Isaac Lab Arena provides a framework for safely testing robot skills in simulation, addressing the challenges of verifying robotic capabilities in real-world scenarios [27] - The open-source approach to AI and robotics is driving rapid advancements across various industries, with numerous companies leveraging NVIDIA's platforms for their next-generation AI systems [29]

Core Insights - NVIDIA has accelerated its AI chip platform release schedule by unveiling the next-generation AI chip platform "Rubin" earlier than usual at CES on January 5, 2026, breaking its traditional March GTC announcement pattern [1][2] Group 1: Rubin Platform Overview - The Rubin platform, which includes six new chips, is designed for extreme collaboration and aims to meet the increasing computational demands of AI for both training and inference [4] - Compared to the previous Blackwell architecture, Rubin accelerators improve AI training performance by 3.5 times and operational performance by 5 times, featuring a new CPU with 88 cores [4] - Rubin can reduce inference token costs by up to 90% and decrease the number of GPUs required for training mixture of experts (MoE) models by 75% compared to the Blackwell platform [4] Group 2: Ecosystem and Market Response - 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] - Major cloud providers and model companies, including AWS, Microsoft, Google, OpenAI, and Meta, have responded positively to Rubin, indicating strong market interest [5] - NVIDIA aims to provide engineering samples to ecosystem partners early to prepare for subsequent deployment and scaling applications [5] Group 3: AI Strategy and Product Launches - NVIDIA's focus is shifting from "training scale" to "inference systems," as demonstrated by the introduction of the Inference Context Memory Storage Platform, designed specifically for inference scenarios [6] - The company is also advancing its long-term strategy in physical AI, releasing open-source models and frameworks that extend AI capabilities to robotics, autonomous driving, and industrial edge scenarios [6] - The launch of the Cosmos and GR00T series models aims to enhance robotic learning, reasoning, and action planning, marking a significant step in the evolution of physical AI [7] Group 4: Autonomous Driving Developments - NVIDIA introduced the Alpamayo open-source model family for autonomous driving, targeting "long-tail scenarios," along with a high-fidelity simulation framework and an open dataset for training [9] - The first autonomous vehicle from NVIDIA is set to launch in the U.S. in the first quarter, with plans for expansion to other regions [9] - The overall strategy emphasizes that the competition in AI infrastructure is moving towards "system engineering capabilities," where the complete delivery from architecture to ecosystem is crucial [9]

Group 1 - Doubao AI glasses are not set to be released as previously rumored, according to a company representative [1] - Maduro of Venezuela denies charges from the US during a court appearance, asserting his position as president [2] - The UN Security Council held an emergency meeting regarding the situation in Venezuela, expressing concerns over US military actions [5] Group 2 - Nanjing aims to attract over 300,000 young talents annually through new talent policies, including financial incentives for graduates [13][14] - The Zhengzhou Porsche Center has ceased operations due to the termination of its authorization agreement, affecting vehicle registration for some customers [16] - Tencent addressed an incident where its AI model produced inappropriate responses, confirming it was an output error and not human intervention [17][18] Group 3 - Gree Electric stated it will not raise prices for household air conditioners and has no plans to switch to aluminum instead of copper [21] - Romaishi announced a restructuring plan while continuing to operate customer service during a prolonged shutdown [22] - Xiaomi's CEO discussed the safety design of their vehicles, specifically the "wheel detachment" safety feature [23][24] Group 4 - Gold prices surged due to geopolitical events, prompting a price increase for certain gold jewelry by Chow Sang Sang [27][28] - The 2025 Hydrogen and Fuel Cell Industry Conference is set to take place, impacting the fuel cell sector [29] - Nvidia's CEO highlighted the upcoming significance of "Physical AI" in driving industrial advancements [30][31][32]