大数据ETF（515400）紧密跟踪中证大数据产业指数（930902.CSI），指数精选沪深两市50只大数 据产业主题上市公司股票样本，涉及大数据存储设备、大数据分析技术、大数据运营平台、大数据生 产、大数据应用等领域，科大讯飞、中科曙光、紫光股份等科技公司是其前十大重仓股。场外投资者的 可以通过联接基金（A类018134；C类018135）关注投资机遇。 早盘市场情绪逐步回暖，三大指数震荡攀升，AI应用端以及大数据方向集体上行，盘中智谱AI、 云计算、东数西算、AI应用、AI智能体等细分方向涨幅居前，大数据ETF（515400）盘中涨幅达 3.19%，创业板软件 ETF 富国（159107）盘中涨幅达3.01%。其中大数据ETF成分股云天励飞20cm涨 停，城地香江、云赛智联等均涨停。 每日经济新闻 近期消息面催化不断，华为2月26日发布AI代码智能体，覆盖代码生成、测试、知识问答，接入 GLM-5、DeepSeek及鸿蒙专属模型，大幅提升开发者效率。 另外，英伟达 GTC 2026 于3月16–19日在加州圣何塞举办，为全球AI算力年度盛会。黄仁勋将发布 全球首见的推理专用LPU芯片，同步推出 Feynm ...

Core Viewpoint - Nvidia's record-breaking financial report aims to counter skepticism regarding the AI bubble, showcasing significant revenue and profit growth amid concerns about capital expenditures in the AI sector [2][3]. Financial Performance - In Q4, Nvidia reported a record revenue of $68.127 billion, a 73% increase from $39.331 billion year-over-year; net profit reached $42.96 billion, up 94% from $22.091 billion [3]. - For the entire year, Nvidia's revenue was $215.938 billion, with a net profit of $120.067 billion, equating to daily earnings of approximately $32.8 million (RMB 220 million) [3]. - The data center business contributed $193.48 billion in revenue for the year, a 68% increase, and accounted for over 91% of total revenue in Q4, with Q4 revenue reaching $62.3 billion, up 75% year-over-year and 22% quarter-over-quarter [3]. Business Segments - Within the data center segment, the "compute business" (primarily GPU products) generated $51.3 billion, a 58% increase, while the "network business" contributed $11 billion, growing 263% [3]. - Nvidia plans to continue selling the Blackwell architecture and the Rubin architecture chips, while the gaming segment faces tight memory supply [4]. Market Outlook - Nvidia's guidance for Q1 of FY2027 anticipates revenue of $78 billion, exceeding analyst expectations [4]. - Concerns remain regarding the Chinese market, as Nvidia has not generated any revenue under the H200 licensing project to date [4]. Industry Context - Wall Street is worried about high capital expenditures from tech giants potentially leading to systemic credit risks, with an estimated $700 billion to be spent on AI expansion by companies like Google, Microsoft, Meta, and Amazon this year [5][6]. - Despite the positive outlook for Nvidia, analysts caution that a slowdown in tech investments could significantly impact the company [6]. Strategic Initiatives - Nvidia is working to solidify its position in the AI ecosystem, with CEO Jensen Huang indicating a near agreement with OpenAI for a potential $100 billion AI infrastructure project [7]. - The upcoming GTC 2026 conference is expected to unveil "world's first" new chips, with speculation around the Rubin and Feynman series [7][8]. Competitive Landscape - Nvidia faces competition from custom AI chips like Google's TPU and Amazon's Inferentia, which are challenging the dominance of general-purpose GPUs in data centers [8]. - TrendForce predicts that the shipment share of ASIC AI servers will rise to 27.8% by 2026, surpassing GPU AI servers in growth rate [8].

Core Viewpoint - Nvidia's record-breaking financial report aims to counter skepticism regarding the AI bubble, showcasing significant revenue and profit growth amid concerns about capital expenditures in the AI sector [1][4]. Financial Performance - In Q4, Nvidia reported record revenue of $68.127 billion, a 73% increase from $39.331 billion year-over-year; net profit reached $42.960 billion, up 94% from $22.091 billion [3]. - For the entire year, Nvidia's revenue was $215.938 billion, with a net profit of $120.067 billion, equating to daily earnings of approximately $32.8 million (RMB 220 million) [3]. Business Segments - The data center segment generated $193.48 billion in revenue for the year, a 68% increase, and accounted for over 91% of total revenue in Q4, with $62.3 billion in revenue, up 75% year-over-year and 22% quarter-over-quarter [3]. - Within the data center segment, the "compute business" (primarily GPU products) contributed $51.3 billion, a 58% increase, while the "network business" generated $11 billion, a 263% increase [3]. Future Guidance - Nvidia's guidance for Q1 FY2027 anticipates revenue of $78 billion, exceeding analyst expectations [4]. - The CFO indicated ongoing sales of Blackwell and Rubin architecture chips, while the gaming segment faces tight memory supply [4]. Market Sentiment - Concerns persist among investors regarding potential threats from the AI bubble, with 23% of surveyed investors citing it as their primary concern, up from 9% in December [6]. - Despite positive performance, there are worries that capital expenditures by major tech firms may peak this year, impacting Nvidia [6][7]. Strategic Initiatives - Nvidia aims to solidify its position in the AI ecosystem, with plans to integrate various sectors onto its platform, including AI, robotics, and life sciences [8]. - The company is nearing an agreement with OpenAI for a potential $100 billion AI infrastructure project and has acquired technology from AI startup Groq for $20 billion [8]. Upcoming Developments - Nvidia's GTC 2026 conference is set for March 15, where new, unprecedented chips are expected to be unveiled [8][9]. - Speculation surrounds the new chips, likely from the Rubin series or the next-generation Feynman series, which are anticipated to be revolutionary [9].

在英伟达公布2026财年第四财季及全年财报前，有不少投资者担忧"AI泡沫"何时破裂，尤其是科技巨头 数千亿美元AI投资的延续性问题。英伟达的业绩对外界判断AI支出的景气度提供参照，不少人将其视 为衡量AI风险的"试金石"。 当地时间2月25日美股盘后，英伟达发布财报，交出超预期"答卷"。 Agentic AI拐点到来 财报数据显示，英伟达第四财季总营收为681.3亿美元，环比增长20%，同比增长73%，高于分析师此前 预测的662亿美元的营收额。从结构上看，数据中心营收为623亿美元，市场预期为606.2亿美元，上年 同期为355.8亿美元；网络营收109.8亿美元，分析师预期90.2亿美元；游戏营收37亿美元，分析师预期 40.1亿美元。 在财报电话会上，有分析师提问，英伟达的几大科技公司客户在2026年的资本开支已经非常高，现金流 也开始紧张，未来如果这些公司不能再继续提高资本开支，英伟达的业绩如何进一步增长？ 英伟达CEO黄仁勋表示，对客户现金流增长充满信心。他认为，现在算力就等于收入，AI能力越来越 强，谁买到了更多算力，谁就能创造更多价值，也就有了更多收入。黄仁勋认为，现在已经来到了 Agentic ...

一、事件：GTC 2026 大会是全球备受瞩目的AI盛会，开发者、研究人员和商业领袖齐聚一堂，共同探索下一波AI创新大潮。本届大会核心聚焦AI基础设施竞赛的新时代，并将 从物理AI和AI工厂到代理式AI和推理，展示正在塑造各行各业的突破性成果。 日程上，本届GTC将带来500多场会议和活动，大会首日黄仁勋将进行2小时的主题演讲，展望加速计算和人工智能的未来。其他大会活动的主题均围绕AI 展开，大会官网推荐的会议日程包括： 英伟达GTC 2026大会将在当地时间3月16日至19日在美国加利福尼亚州圣何塞举行。 展示多款"世界前所未见"的新芯片 黄仁勋近期已开始对即将到来的GTC 2026大会进行预热，其在接受媒体采访时表示："我们已准备好多款'世界前所未见'的新芯片。这些全新芯片的研发极 具挑战，所有技术都已逼近极限，但有英伟达和SK海力士内存工程师组成的技术团队，没有什么是不可能的。" 据国金证券，新芯片大概率出自两大芯片系列：一是Rubin系列的衍生产品，该系列已于2026年CES大会上亮相，包含6款全新设计芯片，目前已全面量产； 二是下一代Feynman系列芯片，该系列被称为"革命性"产品，英伟达正探索以 ...

电子周观点 存储涨价持续，关注英伟达3月GTC大会亮点。近期英伟达首席执行官黄仁勋在接受媒体采访时表示， 在3月16日GTC2026大会上，英伟达将在会上揭晓"世界前所未见"的全新芯片。黄仁勋表示，这些全新 芯片的研发极具挑战，所有技术都已逼近极限，但有英伟达和SK海力士内存工程师组成的技术团队， 没有什么是不可能的。研判大概率出自两大芯片系列：一是Rubin系列的衍生产品，该系列已于2026年 CES大会上亮相，包含6款全新设计芯片，目前已全面量产；二是下一代Feynman系列芯片，该系列被 称为"革命性"产品，英伟达正探索以SRAM为核心的广泛集成，或通过3D堆叠技术整合LPUs。此外， GTC2026英伟达将全方位展示从GPU、CPU、网络、软件到数据中心的全新系统级AI基础设施，建议关 注新技术创新方向。模型在不断升级，2月21日，谷歌发布了新一代模型-Gemini3.1Pro，推理能力、 SVG生成与多模态表现全面升级，在性能、成本与生成质量之间取得罕见平衡。这次升级最核心的变 化，在于推理与复杂任务表现。根据公开基准测试数据，Gemini3.1Pro在多项高难度测试中的表现明显 优于Gemini3 ...

黄仁勋说，"这个团队面对Vera Rubin和HBM4这一巨大挑战，真的非常努力工作，他们有资格一边享用 烧酒和炸鸡，一边度过美好的夜晚。" 黄仁勋自信表示，"我们准备了几款世界上前所未见的全新芯片。所有技术都已到达极限，所以没有容 易的事。"他补充说，"有了这样一支团队，没有什么是不可能的。" 他还认为，目前AI不存在泡沫。"我们只是站在人类历史上最大规模、规模达数十万亿美元的基础设施 项目的起点而已。" 据《韩国经济日报》18日报道，英伟达首席执行官黄仁勋14日接受该媒体采访，对3月中旬举行的GTC 2026大会进行预热，称将在会上揭晓"世界上前所未见"的全新芯片。 当天接受采访前，黄仁勋现身英伟达总部附近的一家韩式炸鸡餐厅，与30多名SK海力士和英伟达工程 师共进晚餐。 业界认为，SK海力士即将供应的HBM4被视为决定英伟达下一代AI加速器Vera Rubin性能表现的关键组 件。目前，SK海力士面临同三星电子的激烈竞争。 黄仁勋未透露所谓全新芯片的型号。有媒体猜测，大概率出自两大芯片系列：一是Rubin系列的衍生产 品（如此前曝光的Rubin CPX），该系列已于2026年CES大会上亮相，包含6款全 ...

英伟达的GTC 2026大会将在当地时间3月16日至19日在美国加利福尼亚州圣何塞举行，核心聚焦AI基础 设施竞赛的新时代。作为AI芯片领域的领军者，英伟达此次重磅预告，被认为将进一步巩固其在AI基 础设施领域的领先地位。 "我们准备了多款世界前所未见的全新芯片。这并非易事，因为所有技术都已逼近物理极限，但有了这 样一支团队（由英伟达和SK海力士的内存工程师组成），没有什么是不可能的。"黄仁勋表示。 周四美股盘前，AMD、英特尔继续下跌，盘中跌幅均一度接近1%。截至北京时间20:20，AMD跌幅收 窄至0.18%，英特尔跌0.57%，美光科技跌约0.2%。前一个交易日，AMD、英特尔均逆市跳水，收盘分 别下跌1.46%、1.56%。 有分析指出，英伟达的最新举动明确了其CPU布局野心，将对英特尔、AMD等竞争对手带来压力。 据《上海证券报》，2月19日，英伟达创始人兼首席执行官黄仁勋在接受媒体采访时，对即将到来的 GTC 2026大会进行预热，明确表示将在会上揭晓"世界前所未见"的全新芯片，引发业界广泛关注。 记者｜曾静娇 见习记者林芊蔚 编辑｜谭婷 业内猜测新产品主要方向 虽然黄仁勋尚未明确透露具体产品细节 ...

Core Viewpoint - Nvidia's CEO Jensen Huang announced the release of "unprecedented" new chip products at the upcoming GTC conference, sparking market interest in the company's next-generation product roadmap [1][3]. Group 1: New Product Expectations - The new products are speculated to involve either derivatives of the Rubin series or the revolutionary Feynman architecture chip, which is expected to be deeply optimized for inference scenarios [1][6]. - Nvidia recently showcased the Vera Rubin AI series at CES 2026, which includes six new chip designs that have entered full production, leading to expectations for cutting-edge technology announcements at GTC [4][6]. Group 2: Market Dynamics and Product Evolution - The current market environment is characterized by changing computational demands, which Huang's statements reflect regarding the direction of technological evolution [7]. - The shift from pre-training to inference capabilities has become central, with latency and memory bandwidth identified as major bottlenecks, influencing Nvidia's product design direction [8]. - The Feynman architecture is anticipated to address these inference challenges through larger SRAM integration and potential LPU integration, significantly impacting cloud service providers and enterprise customers reliant on AI inference capabilities [8]. Group 3: Strategic Partnerships and Ecosystem Development - Huang emphasized the importance of broader partnerships and investment strategies, indicating that Nvidia is transitioning from a chip supplier to an AI ecosystem builder [8]. - The company is actively investing across the entire AI stack, which encompasses energy, semiconductors, data centers, and applications built on these technologies, aiming to maintain a leading position in the AI infrastructure competition [8].

Core Viewpoint - NVIDIA's CEO Jensen Huang announced a new chip set to be revealed at the upcoming GTC 2026 conference, which is expected to further solidify the company's leadership in AI infrastructure [2][5]. Group 1: Upcoming GTC 2026 Conference - The GTC 2026 conference will take place on March 15 in San Jose, California, focusing on a new era of AI infrastructure competition [5]. - Huang acknowledged the challenges in developing these new chips, stating that "all technologies are nearing their limits," yet the industry remains optimistic due to NVIDIA's past performance [5]. Group 2: New Chip Series - The specific models of the new chips have not been disclosed, but speculation suggests they may come from two main series: the Rubin series and the next-generation Feynman series [5]. - The Rubin series includes six new chip designs that have already entered mass production, while the Feynman series is described as "revolutionary," exploring extensive integration with SRAM and potential 3D stacking technology [5]. Group 3: AI Computing Demand Adaptation - NVIDIA is adapting to quarterly changes in AI computing demands, shifting focus from the Hopper and Blackwell series, which emphasize model pre-training, to the Grace Blackwell Ultra and Vera Rubin series, which target inference scenarios [6]. - The new products are expected to address latency and memory bandwidth bottlenecks, which are critical for AI applications [6]. Group 4: Strategic Positioning - Huang emphasized that extensive collaboration and investment are key to maintaining NVIDIA's leading position, as the company is strategically positioning itself across the entire AI industry chain, including energy, semiconductors, and data centers [6].