「英中对照」英伟达发布DSX Pod集装箱式AI数据中心模块，称部署可缩至14天

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The Nvidia DSX Pod.NvidiaNvidia DSX Pod。Nvidia

Nvidia today introduced DSX Pod, a containerized AI data center module that comes with seven Vera Rubin NVL72 racks, along with networking, cabling, and cooling already installed. The company says the design can cut deployment time at a prepared site from roughly six months to as little as 14 days.Nvidia 今日推出 DSX Pod，这是一款集装箱式 AI 数据中心模块，配备七个 Vera Rubin NVL72 机架，网络、布线和散热系统均已预装完成。该公司表示，该设计可将已就绪场地的部署时间从大约六个月缩短至最短 14 天。

Announced at GTC Berlin, the modular offering is aimed at organizations that need to bring large amounts of AI compute online more quickly without going through the full planning, construction, and labor demands of a traditional on-site build. Nvidia said it is working with 17 partners, including Bull, Dell Technologies, HPE, Lenovo, Eaton, Schneider Electric, and Vertiv, to make DSX Pod available in early 2027.这款模块化产品在 GTC 柏林大会上发布，面向需要更快上线大规模 AI 算力、同时又不想经历传统现场建设所需的完整规划、施工和人力投入的组织机构。Nvidia 表示，正与 Bull、Dell Technologies、HPE、Lenovo、Eaton、Schneider Electric 和 Vertiv 等 17 家合作伙伴合作，计划于 2027 年初推出 DSX Pod。

“This is a fully assembled, fully tested, fully pre-plumbed, prebuilt, pre-validated container that is the building block for AI factories,” said Ian Buck, Nvidia’s vice president of hyperscale and high-performance computing, in a media briefing. “It’s designed to accelerate Europe’s infrastructure deployment and dramatically shorten the time to first token.”“这是一个完全组装、完全测试、完全预接管路、预制且预验证的集装箱，是 AI 工厂的构建模块，”Nvidia 超大规模与高性能计算副总裁 Ian Buck 在媒体简报会上表示。“它旨在加速欧洲的基础设施部署，并大幅缩短生成首个 token 的时间。”

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Although Nvidia unveiled the reference design in Berlin, Buck said the container is intended for worldwide deployment. He said the company chose GTC Berlin for the announcement because it sees modular, faster-to-deploy infrastructure playing an important role in Europe’s expansion of AI capacity.尽管 Nvidia 在柏林发布了这一参考设计，Buck 表示该集装箱面向全球部署。他称公司选择在 GTC 柏林大会上发布，是因为看好模块化、部署更快的基础设施在欧洲 AI 算力扩张中发挥的重要作用。

Buck said the product is designed for organizations that want to bring compute online at the hundreds-of-megawatts scale more quickly while reducing the complexity of a conventional site build.Buck 表示，该产品面向希望更快上线数百兆瓦级算力、同时降低传统场地建设复杂度的组织机构。

Ashish Nadkarni, an IDC analyst, said the DSX Pod could be appealing for three use cases: sovereign AI deployments that require physical isolation, smaller-footprint AI deployments built for specific needs, and edge AI environments.IDC 分析师 Ashish Nadkarni 表示，DSX Pod 对三类应用场景具有吸引力：需要物理隔离的主权 AI 部署、针对特定需求构建的小占地 AI 部署，以及边缘 AI 环境。

“It provides accelerated compute capacity in a turnkey fashion wherever there is demand,” Nadkarni said.“它以交钥匙的方式，在任何有需求的地方提供加速计算能力，”Nadkarni 说。

Manufacturing Expansion Targets AI Supply Bottlenecks制造扩张瞄准 AI 供应瓶颈

The DSX Pod announcement came alongside a broader Nvidia update on manufacturing expansion. To support the growing demand for AI infrastructure, Nvidia and its supply chain partners said they plan to increase substrate capacity by 2.5 times over the next three years, expand advanced packaging capacity by more than 300% by 2028, and increase optical engine capacity for co-packaged optics by 15 times by mid-2027, with a goal of doubling that again by the end of 2028.DSX Pod 发布的同时，Nvidia 还公布了更广泛的制造扩张计划。为支持日益增长的 AI 基础设施需求，Nvidia 及其供应链合作伙伴表示，计划在未来三年内将基板产能提高 2.5 倍，到 2028 年将先进封装产能扩大 300% 以上，到 2027 年年中将共封装光学的光引擎产能提高 15 倍，并力争到 2028 年底在此基础上再翻一番。

OpenShell Adds Governance for AI at ScaleOpenShell 为大规模 AI 增添治理能力

Nvidia also used the event to highlight software and security controls for AI deployments at scale. The company introduced the OpenShell Reference Architecture, which it said is designed to help organizations govern AI agents by defining what they can access and do, monitoring their behavior, and enforcing policies if unsafe activity is detected.Nvidia 还借此活动重点介绍了面向大规模 AI 部署的软件与安全控制。公司推出了 OpenShell 参考架构，称其旨在帮助组织机构治理 AI 智能体——通过定义其可访问的内容和可执行的操作、监控其行为，并在检测到不安全活动时执行策略。

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Justin Boitano, Nvidia’s vice president of enterprise, said the architecture combines Vera Rubin NVL72 infrastructure for training and inference with Nvidia Vera systems that run and govern the “agent harness.” BlueField DPUs act as an isolated security monitor between the two systems, inspecting traffic and enabling policy updates that can disconnect an agent if unsafe behavior is detected.英伟达企业业务副总裁 Justin Boitano 表示，该架构将用于训练和推理的 Vera Rubin NVL72 基础设施与运行和管理“智能体执行框架”（agent harness）的 Nvidia Vera 系统 相结合。BlueField DPU 充当两套系统之间的隔离安全监控器，负责检查流量并支持策略更新，一旦检测到不安全行为即可断开智能体的连接。

Nvidia said companies using the OpenShell Reference Architecture to strengthen agent security include Anthropic, AWS, Google Cloud, Meta, Microsoft, OpenAI, and Perplexity.英伟达表示，正在使用 OpenShell 参考架构来加强智能体安全的公司包括 Anthropic、AWS、Google Cloud、Meta、微软、OpenAI 和 Perplexity。

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Wylie Wong is a journalist and freelance writer specializing in technology, business and sports. He previously worked at CNET, Computerworld and CRN and loves covering and learning about the advances and ever-changing dynamics of the technology industry. On the sports front, Wylie is co-author of Giants: Where Have You Gone, a where-are-they-now book on former San Francisco Giants. He previously launched and wrote a Giants blog for the San Jose Mercury News, and in recent years, has enjoyed writing about the intersection of technology and sports.Wylie Wong 是一名记者兼自由撰稿人，专注于科技、商业和体育领域。他曾就职于 CNET、Computerworld 和 CRN，热衷于报道和了解科技行业的进步与瞬息万变的行业动态。在体育方面，Wylie 是《Giants: Where Have You Gone》一书的合著者，这是一本讲述前旧金山巨人队球员近况的书。他曾为《圣何塞信使报》创办并撰写巨人队博客，近年来，他乐于撰写科技与体育交汇领域的文章。