公众号记得加星标⭐️，第一时间看推送不会错过。 在 2026 年这个时间节点上，汽车芯片的讨论重心正在发生微妙变化。随着软件定义汽车进入工 程落地阶段，整车电子电气架构从分布式向集中式、域控式持续演进，车内对计算、实时控制与 系统安全的要求，开始被放到同一个技术框架下重新评估。 在此背景下，一些长期深耕汽车控制领域的老牌芯片巨头，也开始展示自己新的技术方向。它们 不再局限于传统 MCU 的定位，而是通过引入更先进的制程、更高的系统集成度以及面向软件架 构的设计思路，试图覆盖更复杂的整车控制与协同计算场景。 因此在 2026 年 CES 上，我们可以看到包括 NXP、瑞萨和TI这几个老牌汽车芯片巨头，正在以 系统级能力为核心，重新参与到软件定义汽车的核心架构竞争来，在英伟达、高通等厂商不断迭 代更新智驾与座舱芯片的今天，它们不谋而合地发动了一场新攻势。 从分布式霸主到智能化冲击 在传统汽车电子时代，整车采用的是高度分布式的 ECU 架构。一辆高端车型往往由数十甚至上百个 ECU 拼接而成，每颗芯片只服务于一个明确而稳定的功能 —— 发动机控制、车身电子、制动系统、 转向辅助，各司其职，互不干扰。这种架构在机械主 ...

以下文章来源于硬AI ，作者专注科技产研的 硬AI . AI时代，快人一步~ 来源 | 硬AI 芯片巨头的策略在CES 2026将出现显著分化，英伟达的重心明显不在传统的消费级显卡市场。 具身智能战场 从中美韩"三国杀"看执行力进阶 2026年被视为人形机器人从Demo走向工位的关键年份，核心看点在于"降本增效"与"实战验证"。 端侧 AI 与 XR 安卓阵营的反击 与中国厂商的"轻量化"突围 XR市场正在经历Apple Vision Pro发布后的"消化期"，CES 2026将是安卓阵营反击的起点。 汽车产业 从"软件定义"跃迁至"AI 定义" 芯片军备竞赛升级 汽车行业正经历技术架构的深层变革，智驾芯片的竞争格局日益清晰。 英伟达（NVIDIA） ： 市场预期的RTX 50 Super系列显卡（包括RTX 5080 SUPER等）或因GDDR7显存价格高企和供应短缺而 推迟 发布 。CEO黄仁勋的演讲将聚焦"Physical AI"， 推动AI算力向机器人与工业场景延伸 。英伟达可能转而专注于高利润产品，如96GB 显存的RTX PRO 6000 Blackwell。 AMD ： 采取稳健升级策略。 桌面 ...

CES 2026凸显芯片巨头战略分野：英伟达重心转向工业AI与机器人，而AMD与英特尔则坚守并升级传统PC市场。展会 焦点已从消费电子转向人形机器人、AI定义汽车及卷轴屏等颠覆性硬件的产业化竞速，中、美、韩厂商在各赛道展开激烈 角逐。 硬·AI 作者 |叶慧雯 编辑 | 硬 AI 2026年消费电子展（CES）将于1月4日至9日在美国拉斯维加斯举行，CES一向是科技企业发表年度新品 的重要舞台，展品涵盖即将上市的产品，以及仍处于概念阶段、未必投产的装置。 芯片巨头的策略在CES 2026将出现显著分化，英伟达的重心明显不在传统的消费级显卡市场。 中国阵营（成本与量产）： 宇树和智元继续主导成本控制。宇树或展示G1量产版在工厂流水线的 操作；智元将展示X2、A2等全系列产品及灵巧手等核心部件。 美国阵营（技术标杆）： 波士顿动力的全电动Atlas将进行首次公开演示，直接对标特斯拉 Optimus，展示商业化潜力。 韩国阵营（产业链抱团）： 韩国将展示"K-Humanoid"联盟，由三星投资的Rainbow Robotics领 衔。展品包括轮式底盘工业级人形机器人HMND 01 Alpha（身高220厘米，载荷1 ...

汽车产业：从"软件定义"跃迁至"AI 定义"，芯片军备竞赛升级 2026年消费电子展（CES）将于1月4日至9日在美国拉斯维加斯举行，CES一向是科技企业发表年度新 品的重要舞台，展品涵盖即将上市的产品，以及仍处于概念阶段、未必投产的装置。 芯片巨头的策略在CES 2026将出现显著分化，英伟达的重心明显不在传统的消费级显卡市场。 具身智能战场：从中美韩"三国杀"看执行力进阶 2026年被视为人形机器人从Demo走向工位的关键年份，核心看点在于"降本增效"与"实战验证"。 端侧 AI 与 XR：安卓阵营的反击与中国厂商的"轻量化"突围 XR市场正在经历Apple Vision Pro发布后的"消化期"，CES 2026将是安卓阵营反击的起点。 面对传统硬件的创新天花板，厂商开始探索激进的形态突破。 风险提示及免责条款 市场有风险，投资需谨慎。本文不构成个人投资建议，也未考虑到个别用户特殊的投资目标、财务状况或需要。用户应考虑本文中的任何 意见、观点或结论是否符合其特定状况。据此投资，责任自负。 芯片军备竞赛： 英伟达： 凭借Thor芯片（2000 TOPS算力）主导L4级高端市场，极氪等车企计划 2025年量 ...

Core Insights - NVIDIA has officially open-sourced its latest autonomous driving Vision-Language-Action (VLA) model, Alpamayo-R1, which can process vehicle camera images and text instructions to output driving decisions [2][3] - The Alpamayo-R1 model emphasizes "explainability," providing reasons for its decisions, which aids in safety validation and regulatory review [3][4] - The VLA model is seen as the next core technology in intelligent driving, with various companies, including Li Auto, Xpeng Motors, and Great Wall Motors, already implementing it in production [3][4] Group 1: Model Features and Benefits - Traditional end-to-end models are often "black boxes," making them difficult to interpret, especially in complex scenarios [4] - VLA introduces a language modality as an intermediary layer, enhancing the model's ability to handle complex situations and providing a more human-like decision-making process [4][5] - The Alpamayo-R1 model has shown significant performance improvements, including a 12% enhancement in trajectory planning performance and a 25% reduction in near-collision rates [5][6] Group 2: Industry Impact and Ecosystem Development - NVIDIA aims to position itself as the "Android" of the autonomous driving sector, moving beyond being just a hardware supplier [6][8] - The company has announced plans to deploy 100,000 Robotaxis starting in 2027, collaborating with firms like Uber and Mercedes to create the world's largest L4 autonomous driving fleet [7][8] - The open ecosystem proposed by NVIDIA could facilitate data sharing among companies, potentially accelerating technological advancements in the industry [8][9] Group 3: Challenges and Future Considerations - Despite the advancements, the Alpamayo-R1 model requires high-performance hardware to meet automotive-grade latency, indicating a dependency on NVIDIA's hardware solutions [10][11] - The effectiveness of VLA technology is still under evaluation, and there are concerns about the limitations imposed by NVIDIA's platform on developers [11][12] - The successful commercialization of L4 autonomous driving will also depend on regulatory frameworks and the ability to balance data privacy with operational safety [11][12]

Core Viewpoint - NVIDIA has delivered better-than-expected performance in its latest quarterly results, driven primarily by the ramp-up of its Blackwell series products, with a significant revenue increase of $10 billion quarter-over-quarter [5][9][28]. Financial Performance - For the third quarter of fiscal year 2026, NVIDIA reported total revenue of $57 billion, exceeding market expectations of $55.1 billion, with a year-over-year growth of 62% [5][28]. - The company anticipates revenue of $65 billion for the next quarter, which represents a $8 billion increase from the previous quarter, also surpassing market expectations [7][9][28]. - Gross margin for the third quarter was 73.4%, in line with market expectations, and is projected to rise to 74.8% in the next quarter [7][31][28]. Business Segments - The data center segment generated $51.2 billion in revenue, accounting for nearly 90% of total revenue, with a year-over-year growth of 66% [5][36][24]. - The gaming segment achieved revenue of $4.26 billion, reflecting a 30% year-over-year increase, maintaining NVIDIA's leading position in the discrete graphics card market [6][42][24]. Market Dynamics - The company faces competition from major cloud service providers who are increasingly investing in self-developed AI chips, which could impact NVIDIA's market share and margins in the future [19][17][22]. - Despite the competitive landscape, NVIDIA still holds over 70% of the AI chip market share, indicating its strong product advantage [17][19]. Future Outlook - NVIDIA's management has provided guidance indicating continued growth driven by the Blackwell product cycle, with expectations of significant revenue contributions from AI-related capital expenditures from major cloud providers [9][14][40]. - The company is also planning to launch new products, including Rubin and CPX, in the second half of 2026, which are expected to utilize advanced manufacturing processes [20][21].

Core Viewpoint - The all-new Lynk & Co 08 EM-P, a luxury hybrid SUV, has been officially launched with four models priced between 159,800 to 212,800 yuan, showcasing advanced technology and features aimed at enhancing competitiveness in the market [1][2]. Group 1: Product Features - The Lynk & Co 08 EM-P is equipped with the Qualcomm Snapdragon 8295 chip, featuring a 95-inch AR-HUD, a 15.4-inch central control screen, and a 12.3-inch full LCD instrument panel, providing a seamless three-screen interaction experience [2]. - It is the only hybrid SUV in its class to come standard with laser radar across all models and is the first mid-size SUV globally to feature the Thor chip, utilizing cutting-edge 4nm technology with a computing power of 700 TOPS [2]. - The vehicle is supported by the Geely Starry Smart Computing Center 2.0 cloud platform, enhancing capabilities for assisted driving training, smart cockpit iteration, and large model inference [2]. Group 2: Market Positioning and Strategy - Lynk & Co aims to establish a high-end brand identity, emphasizing the importance of distinctive features that resonate with consumers [3][6]. - The company acknowledges the competitive landscape and aims to attract a broader customer base by enhancing product capabilities, including a 1.5T engine, advanced driving assistance systems, and improved comfort and aesthetics [5][9]. - The integration of Lynk & Co and Zeekr is seen as beneficial, allowing for shared technology and reduced costs, ultimately enhancing market competitiveness [10][11]. Group 3: Sales Expectations and Future Outlook - The sales team expresses confidence in the Lynk & Co 08 EM-P's ability to maintain strong sales performance, despite challenges in pricing strategy [5]. - The company believes that the Chinese market is large enough to accommodate multiple models, fostering a collaborative environment among brands rather than a zero-sum competition [9].

Group 1 - Nvidia has established a joint research lab with the Technology Innovation Institute (TII) in the UAE, focusing on next-generation AI models and robotics platforms [1] - This lab is Nvidia's first AI technology center in the Middle East, combining TII's multidisciplinary research capabilities with Nvidia's computational power [1] - TII will utilize specific edge GPU chips to advance its research in robotics, including humanoid robots, quadrupedal robots, and robotic arms [1] Group 2 - TII's CEO, Najwa Al Raji, announced the use of a new chip named Thor, which supports the development of advanced robotic systems [1] - TII is part of the Advanced Technology Research Council, which is a key component of the UAE's efforts in the global AI competition [1] - TII has been collaborating with Nvidia for some time, using Nvidia chips to train its own language models [1] Group 3 - In May, during a visit by former US President Trump to the Middle East, the UAE signed a multi-billion dollar agreement to establish one of the world's largest data center hubs in Abu Dhabi, leveraging US technology including advanced Nvidia chips [2] - However, the agreement has not been finalized due to security concerns arising from the UAE's relationship with China [2]

Core Viewpoint - The collaboration between NVIDIA and the Technology Innovation Institute (TII) in Abu Dhabi marks a significant step in NVIDIA's expansion into the Middle East, focusing on the development of next-generation AI models and robotic platforms [1]. Group 1: Collaboration Details - The newly established AI technology center in the UAE will leverage TII's multidisciplinary research capabilities alongside NVIDIA's powerful AI models and computing power [1]. - TII's CEO, Najwa Aaraj, indicated that the institute will utilize NVIDIA's specialized "Thor" chip to advance research in humanoid robots, quadrupedal robots, and robotic arms [1][3]. - The joint laboratory will explore AI applications in various fields, including climate, energy, and genomics, while also planning specific robotic innovations in transportation and logistics [3]. Group 2: UAE's AI Ambitions - This partnership is part of the UAE's strategic goal to become a global player in AI, with the government investing billions of dollars in the AI sector [4]. - The UAE aims to leverage its close relationship with the United States to gain access to advanced technologies, as evidenced by a multi-billion dollar agreement signed during a visit by former President Trump [4]. - TII has been collaborating with NVIDIA for some time, using NVIDIA chips to train its language models, and discussions about the joint laboratory began approximately a year ago [4][5].

Core Insights - Abu Dhabi Technology Innovation Institute (TII) has established a joint research lab with NVIDIA in the UAE, focusing on the development of next-generation AI models and robotic platforms [1] - This joint research center is NVIDIA's first AI technology center in the Middle East, aiming to combine TII's multidisciplinary research with NVIDIA's AI models and computing power to accelerate global AI development [1] - TII will utilize specific edge GPU chips, including the newly introduced Thor chip, to advance its research in robotics, which includes humanoid robots, quadrupedal robots, and robotic arms [1] Group 1 - TII and NVIDIA's collaboration marks a significant step in AI research in the Middle East [1] - The establishment of the research lab aligns with a broader trend of investment in AI technology and infrastructure in the region [1] - The Thor chip is designed to support advanced robotic systems, indicating a focus on enhancing robotics capabilities [1] Group 2 - The partnership follows a multi-billion dollar agreement signed during a visit by former U.S. President Trump, which aims to build one of the largest data center hubs in Abu Dhabi using advanced American technology, including NVIDIA chips [1] - This initiative reflects the growing importance of AI and data infrastructure in the UAE's economic strategy [1] - The collaboration is expected to contribute to the rapid advancement of AI technologies globally [1]