据多位知情人士及一份内部备忘录透露，两年多前，英伟达首席执行官黄仁勋曾提出愿景，计划打造一 项可与亚马逊云科技（AWS）抗衡的云计算服务；如今，英伟达已放弃与这类企业的直接竞争，并于 上周对公司云计算团队进行了重组。 知情人士称，上周发布的一份员工备忘录通报了此次重组计划，英伟达云计算部门负责人及数位相关高 管被调任新职，另有部分高管离职。 备忘录显示，2023 年从Meta加盟英伟达、直接向黄仁勋汇报的高管Alexis Black Bjorlin，计划在公司内 部调任新岗位。英伟达目前正将旗下数百人规模的云计算团队，并入由高级副总裁Dwight Diercks执掌 的工程与运营部门，Diercks同时也向黄仁勋汇报工作。 备忘录及该部门内部人士均表示，这支名为DGX Cloud的团队今后将优先满足英伟达工程师对自家芯片 的需求 —— 这些芯片主要用于开源人工智能模型的开发，不再以向外部企业客户销售云计算服务为核 心目标。 作为重组的一部分，英伟达较新推出的云计算服务DGX Cloud Lepton也将并入工程团队。该服务原本 旨在帮助云服务供应商，在英伟达运营的交易平台上挂牌出售闲置的英伟达服务器算力，但自 ...

Core Viewpoint - Nvidia is gradually scaling back its nascent cloud computing business, specifically its DGX Cloud service, which indicates a shift in strategy and a response to limited demand in the cloud services market [2][3][4]. Group 1: Nvidia's Cloud Business Adjustments - Nvidia has reduced efforts to attract enterprises to use its DGX Cloud service and plans to primarily utilize this service for internal purposes, supporting its own researchers [2][3]. - The scaling back of the cloud business may reflect market resistance to Nvidia's pricing strategy, as AI developers find the DGX Cloud servers to be more expensive than traditional cloud services [3]. - Nvidia's recent quarterly report no longer specifies that its cloud spending commitments include DGX Cloud, suggesting a decreased priority for external customer service [3][4]. Group 2: Market Context and Performance - Following Nvidia's announcement, major tech stocks in the U.S. saw a rise, with Tesla surging over 7% and the Nasdaq index increasing by more than 1%, reaching a historical high [6]. - Goldman Sachs highlighted that AI-driven tech giants and loose monetary policies are the two main pillars supporting the current bull market in U.S. stocks [6]. - Despite uncertainties, Goldman Sachs projects a steady growth of 7% in earnings per share (EPS) for the S&P 500 index over the next two years, reaching $262 and $280 respectively [6][8]. Group 3: Broader Economic Indicators - The earnings growth of the "S&P 493" (excluding the tech giants) was 7%, while the tech giants experienced a remarkable 28% growth, contrasting with a generally pessimistic macro narrative [7]. - Current valuations of the S&P 500 index are high, with a price-to-earnings ratio of 22, placing it in the 96th percentile since 1980, indicating potential caution for investors [8]. - The report from Goldman Sachs also noted that the technical buying momentum supporting the market is weakening, suggesting a shift in market dynamics [8].

Core Viewpoint - Nvidia is gradually scaling back its nascent cloud computing business, specifically its DGX Cloud service, which indicates a shift in strategy and a reduction in competitive pressure with major cloud service providers like Amazon Web Services [1][2][3] Group 1: Business Strategy - Nvidia has reduced efforts to attract enterprises to use its DGX Cloud service, planning to primarily utilize it for internal purposes, including support for its own researchers [2][3] - The scaling back of the cloud business may reflect limited demand and market resistance to Nvidia's pricing strategy, as AI developers find the DGX Cloud servers to be more expensive than traditional cloud services [3] - Nvidia's recent quarterly report no longer specifies that its cloud spending commitments include DGX Cloud, suggesting a decreased priority for external customer service [3][4] Group 2: Market Performance - Following Nvidia's news, major tech stocks in the U.S. saw a rise, with Tesla surging over 7% and the Nasdaq index reaching a historical high [1][6] - Goldman Sachs highlighted that AI-driven tech giants and loose monetary policies are the two main pillars supporting the current bull market in U.S. stocks [1][6] - Despite uncertainties, Goldman Sachs projects a steady 7% growth in earnings per share for the S&P 500 over the next two years, reaching $262 and $280 respectively [6][8] Group 3: Competitive Landscape - Nvidia's CEO had previously envisioned a robust future for DGX Cloud, aiming to democratize access to AI chip servers for large enterprises [4] - The introduction of DGX Cloud Lepton, a new cloud service platform, has faced slow initial development, as it competes with existing cloud service providers [5]

Core Viewpoint - Nvidia is scaling back its cloud computing business due to limited demand for its DGX Cloud services, which were initially aimed at attracting enterprise customers [3][4] Group 1: Strategic Adjustments - Nvidia plans to use most of its DGX Cloud server capacity for internal research rather than for external customers, indicating a shift in focus [4] - The company previously committed to spending $13 billion to rent its AI chips from large cloud service providers, aiming for $150 billion in revenue through a rental business model [3][4] Group 2: Market Challenges - AI developers are resistant to the high prices of DGX Cloud servers, which are typically more expensive than those offered by traditional cloud service providers [3][4] - The reduction in cloud business efforts may alleviate competitive pressure from major cloud service providers, which account for half of Nvidia's revenue [3] Group 3: Future Prospects - Nvidia's CEO had previously expressed ambitious goals for DGX Cloud, envisioning direct rentals of AI chip servers to large enterprises [6] - Despite earlier claims of success, recent disclosures indicate a lack of prioritization for external customer services in the cloud segment [4][6] Group 4: New Service Models - Nvidia is exploring new service models, such as the DGX Cloud Lepton platform, which allows companies to access GPU resources through a network of cloud service providers [7] - Unlike the original DGX Cloud, the Lepton platform allows cloud service providers to list available GPU server capacity independently, which may create competition with Nvidia's own offerings [8]

Core Viewpoint - Nvidia is scaling back its nascent cloud computing business, particularly its DGX Cloud service, which indicates limited demand and potential pricing resistance in the market [2][4][3]. Group 1: Nvidia's Cloud Business Strategy - Nvidia is reducing efforts to attract enterprises to its DGX Cloud service, planning to primarily use it for internal purposes [2][3]. - The shift in strategy alleviates competitive pressure with major cloud service providers, particularly Amazon Web Services, which accounts for half of Nvidia's revenue [2][4]. - The company has stopped disclosing its cloud spending commitments for DGX Cloud in its latest quarterly report, suggesting a decreased focus on external customers [4][5]. Group 2: Market Context and Performance - Following Nvidia's announcement, major tech stocks in the U.S. saw a significant rise, with Tesla surging over 7% and the Nasdaq index reaching a historical high [2][9]. - Goldman Sachs highlighted that AI-driven tech giants and loose monetary policies are the two main pillars supporting the current bull market in U.S. stocks [2][9]. - Despite uncertainties, Goldman Sachs projects a steady 7% growth in earnings per share (EPS) for the S&P 500 index over the next two years, reaching $262 and $280 respectively [9][10]. Group 3: Financial Performance and Future Outlook - Nvidia's CEO previously expressed ambitious goals for DGX Cloud, aiming to democratize access to AI infrastructure for large enterprises [5]. - The company's software business, including DGX Cloud, was reported to have an annualized revenue of $2 billion as of late 2023 [5]. - The performance of the "Tech Seven" index, which includes major tech companies, showed a remarkable 28% growth in earnings, contrasting with a 7% growth in the broader S&P 493 index [10].

AI Technology & Infrastructure - NVIDIA is accelerating AI across Europe, focusing on agentic AI that can understand, reason, and act, envisioning AI factories as engines of transformation [2] - NVIDIA partners with European technology leaders to increase AI infrastructure investment by 10x over the next two years, supporting digital sovereignty, economic growth, and industrial competitiveness [3] - NVIDIA's Blackwell platform is in full production, with new benchmarks showcasing GB200 integrated with cuQuantum libraries and CUDA-Q platform to accelerate quantum algorithms [4] - Grace Blackwell MBL72 is designed to meet the computing demands of advanced reasoning AI models [5] - New RTX Pro servers, with integrated ConnectX-8 networking and optimized for NVIDIA AI software, offer a foundation for enterprise-scale generative AI and industrial digitalization [5] - NVIDIA introduced DGX Cloud Lepton, a unified AI platform designed to connect developers to global accelerated compute with multicloud, multi-tenant, and global scaling capabilities [6] AI Model Development & Deployment - NVIDIA supports Europe's model builders and cloud providers in developing sovereign LLMs using NVIDIA and NeMoTron, optimized for cost and cultural relevance [7] - These models will soon be available on Perplexity and deployable via NVIDIA NIM's microservices [7] Training & Innovation - New NVIDIA AI technology centers are training talent, supporting researchers, and seeding innovation [4] - Thousands of attendees at GTC Paris gained practical tools and a vision of what's next through sessions, demos, and technical workshops on NIM, NeMo, and TensorRT [8]

Core Viewpoint - Nvidia is at the forefront of the AI revolution, designing highly sought-after AI chips and expanding into a comprehensive range of AI products and services [1][5][7] Financial Performance - Nvidia achieved record revenue of $130 billion in the latest fiscal year, a significant increase from $27 billion two years ago, showcasing its success in the AI boom [2] - The company's stock price has surged 1,500% over the past five years, reaching new highs recently [3] Market Position and Innovation - Nvidia is a key player in the AI sector, offering powerful GPUs and various accompanying products, which are essential for AI development [5][7] - The recent launch of DGX Cloud Lepton allows developers to access GPUs from multiple cloud providers, further solidifying Nvidia's market position [6] Risks and Challenges - Nvidia's gross margin has remained above 70%, but it recently dropped to 60% due to a charge related to lost sales in China, which accounted for 13% of sales last year [9][10] - U.S. export controls on chips to China have led Nvidia to exclude this market from its sales forecasts, although U.S. customers represent nearly half of total sales [10] Investment Considerations - Nvidia's stock trades at 35 times forward earnings estimates, which is higher than a few weeks ago but lower than its peak of over 50 [11] - Despite the current high stock price, Nvidia's strong earnings track record and market position suggest it remains a reasonable investment for long-term holders [12][13]

Core Offering - DJX Cloud Leptin provides on-demand access to a global network of GPUs across clouds, regions, and partners [1] - Multicloud GPU clusters are managed through a single unified interface [1] - Connects developers to GPU compute, powering a virtual global AI factory [3] Key Features - Fast provisioning allows developers to quickly scale up the number of nodes without complex setups [2] - Pre-integrated tools and training-ready infrastructure enable developers to start training immediately [2] - Real-time progress monitoring provides insights into GPU performance, convergence, and throughput [2] - Supports deployment of NIM endpoints or models in multiple clouds or regions for fast distributed inference [2]

Core Insights - Nvidia is positioning itself as a key player in the global AI infrastructure landscape through partnerships with European countries and companies [1][5] - The company aims to enhance AI computing capacity in Europe by a factor of 10 over the next two years, amidst challenges from U.S. export restrictions [5] Partnerships and Projects - Nvidia announced a partnership with French startup Mistral to create an "AI cloud" utilizing 18,000 Nvidia Grace Blackwell chips [6] - Infrastructure projects are also being developed in Italy and Armenia [6] - Collaborations with telecommunications companies like Orange and Telefonica focus on deploying AI applications and large language models [7] Infrastructure Development - Nvidia is building an "industrial cloud" in Germany featuring 10,000 GPUs tailored for European manufacturers [7] - The concept of "sovereign AI" emphasizes the importance of regional data centers and servers for EU users [8] - Nvidia is establishing "tech centers" across Europe to promote advanced research and workforce upskilling in countries such as the U.K., France, Spain, and Germany [8] Product Expansion - The company expanded its DGX Cloud Lepton product, integrating it with AI model repository Hugging Face, allowing global access to GPUs for AI applications [9]

Core Insights - NVIDIA announced the expansion of its DGX Cloud Lepton, an AI platform that connects developers with a global compute marketplace for building AI applications [1][5] - The platform now includes contributions from various cloud providers, enhancing access to high-performance computing resources [2][8] - Hugging Face introduced Training Cluster as a Service, integrating with DGX Cloud Lepton to facilitate AI model training for researchers [3][10] Company Developments - NVIDIA collaborates with European venture capital firms to provide marketplace credits to startups, promoting regional development in AI [4][11] - The DGX Cloud Lepton platform simplifies access to GPU resources, supporting data governance and sovereign AI requirements [5][6] - The platform integrates with NVIDIA's software suite, streamlining AI application development and deployment [6][7] Industry Impact - The DGX Cloud Lepton marketplace aims to meet the growing demand for AI compute resources, with major cloud providers like AWS and Microsoft Azure participating [2][8] - Early-access customers include various AI companies leveraging the platform for strategic initiatives [8][9] - The integration with Hugging Face allows for scalable AI training, enhancing the capabilities of researchers in various scientific fields [10][11]