公众号记得加星标⭐️，第一时间看推送不会错过。 来源 ： 内容来自tomshardware 。 英伟达的 DGX Cloud，曾被定位为面向企业的直连式 AI 云服务，如今在公司战略中悄然退居二线。据 The Information 援引内部人士消息称，这 一 GPU 云平台目前大部分算力已用于英伟达自身的研究，而非继续作为面向客户的核心产品。 在英伟达 2026 财年第二季度财报中，公司已不再将数十亿美元的云支出承诺归因于 DGX Cloud，而此前的财报中这一项目曾被重点披露。虽然 DGX Cloud 仍然出现在收入分类里，但其角色显然已经转向"内部基础设施"，而不是正面迎战微软 Azure 或 AWS。换句话说，DGX Cloud 依然 存在，但已不再是市场竞争的前锋。 DGX Cloud 的兴衰 DGX Cloud 于 2023 年推出，当时的定价为每月每个 H100 实例 36,999 美元。在 GPU 严重短缺的背景下，这样的高价还算合理，但随着供应逐 步改善，这种"紧缺替代方案"的价值已大幅下降。如今，AWS 已将 H100 与 A100 的租赁价格削减高达 45%，这让 DGX Cloud 的 ...

Core Viewpoint - The importance of AI and NVIDIA's role as a foundational infrastructure provider for AI was emphasized by CEO Jensen Huang during his keynote at Computex 2025, highlighting the future necessity of ubiquitous AI similar to the internet and electricity [1]. Group 1: AI Development and Infrastructure - Huang discussed the evolution of AI, introducing concepts like Agentic AI, which possesses reasoning and perception capabilities, allowing it to understand, think, and act [5][6]. - The introduction of Physical AI, which understands the real world and its physical laws, is seen as crucial for the robotics revolution [8]. - NVIDIA's new Grace Blackwell system, which has entered full production, is designed to enhance AI capabilities, with the GB300 version offering 1.5 times the inference performance and doubled network connectivity compared to its predecessor [9][10]. Group 2: Performance and Technological Advancements - The Grace Blackwell GB300 system achieves 40 PFLOPS, equating to the performance of the 2018 Sierra supercomputer, showcasing a 4000-fold performance increase over six years [9]. - NVIDIA's AI computing power is projected to increase by approximately 1 million times every decade, supported by new manufacturing processes in collaboration with TSMC [9]. - The introduction of NVLink Fusion aims to build AI infrastructure that can scale to millions of GPUs, integrating with various cloud service providers [11][13]. Group 3: Robotics and AI Integration - Huang highlighted the need for robots to learn in virtual environments that adhere to physical laws, addressing the challenges of data strategy in robotics [24]. - The GR00T-Dreams system generates synthetic data to train AI models, enhancing the efficiency of robot training through simulated tasks [25]. - NVIDIA's humanoid robot foundational model, Isaac GR00T N1.5, has been updated to improve its adaptability in material handling and manufacturing tasks [28][29]. Group 4: Personal AI Computing - The DGX Spark personal AI computer is set to launch soon, allowing individuals to own a supercomputer, with pricing determined by companies [18]. - The DGX Station, capable of running large models with 1 trillion parameters, is also being introduced, showcasing NVIDIA's commitment to personal AI computing [18]. Group 5: Future Directions in Computing - NVIDIA is developing quantum-classical computing platforms, predicting that future supercomputers will integrate GPU, QPU, and CPU technologies [22]. - Huang emphasized the need for storage systems to evolve, integrating GPU computing nodes to handle unstructured data more effectively [22].