内容来源：https://aibusiness.com/agentic-ai/nvidia-devises-secure-openclaw-stack-for-enterprises

内容总结：

英伟达推出企业级AI安全栈 瞄准OpenClaw生态与推理市场

在近日于圣何塞举行的GTC开发者大会上，英伟达宣布推出专为OpenClaw智能体平台设计的NemoClaw技术栈，旨在为企业用户提供更安全、可控的生成式AI应用构建环境。此举被视为英伟达在巩固其AI训练市场领导地位的同时，积极向AI推理与智能体领域拓展的关键战略布局。

随着OpenClaw开源AI智能体框架自去年11月发布后迅速获得超200万用户，其安全漏洞问题也引发关注。英伟达CEO黄仁勋指出，尽管OpenClaw推动了AI智能体迈向“ChatGPT时刻”，但其存在的API密钥泄露、缺乏密码保护等安全隐患使其尚未做好企业级应用准备。为此，英伟达推出的NemoClaw平台整合了Nemotron模型与OpenShell运行时，通过单命令部署为企业提供内置安全与治理层的开发环境。

分析人士认为，英伟达此举表明其不再满足于仅为合作伙伴提供底层硬件，而是直接参与企业级AI工具链建设。Futurum Group分析师布伦丹·伯克指出，Nemotron等智能体模型的快速发展显示英伟达正致力于成为独立的智能体编排平台提供商。

与此同时，英伟达强化了对AI推理市场的投入。除推出六款全新Vera Rubin系列芯片外，其发布的Vera Rubin DSX AI工厂设计指南进一步体现了“软硬件协同开发”理念。宾夕法尼亚大学教授本杰明·李分析称，这标志着英伟达正从训练市场向推理市场战略转移，通过提供多样化模型部署平台帮助用户降低试错成本。

市场观察人士指出，在谷歌、AWS、微软等云服务商及Cerebras等芯片厂商的竞争压力下，英伟达试图通过提升令牌生成效率与成本优势巩固市场地位。J. Gold Associates总裁杰克·戈德表示：“推理是成本敏感型计算领域，英伟达需要向市场证明其系统能帮助客户以更低成本生成更多令牌，从而创造更高收益。”

此外，英伟达还扩展了Nemotron模型家族，推出具备视觉、语音及安全能力的“全能理解”模型系列，覆盖代码助手、视频文档解析、实时对话等多类AI原生应用场景。这一系列动作显示出英伟达正围绕智能体生态构建从芯片、模型到安全框架的全栈能力，以应对企业级生成式AI应用的复杂需求。

中文翻译：

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新推出的技术栈旨在为企业创建个人智能体时提供更高安全性。
在OpenClaw大受欢迎之际，英伟达正为企业打造专属的"OpenClaw时刻"，在增强安全性与治理能力的同时，致力于从公认的AI训练市场领导者转型为推理服务提供商。

这家AI软硬件巨头于周一在圣何塞的GTC开发者大会上，推出了面向OpenClaw智能体平台的Nvidia NemoClaw技术栈。据英伟达介绍，该平台允许用户通过单一指令部署Nvidia Nemotron模型与全新的Nvidia OpenShell运行时平台。OpenShell作为开源的AI智能体安全部署环境，在AI智能体与计算基础设施之间构建了安全治理层。

NemoClaw平台的推出彰显了英伟达对OpenClaw普及程度的重视。这款隶属于OpenAI的开源智能体AI框架自去年11月发布后，短短数月内全球用户量已突破200万。

通过OpenClaw，用户可创建管理能执行现实任务、充当个人助理的AI智能体。然而其火爆背后潜藏严重安全隐患：未加密文件中的敏感API密钥和会话令牌易在主机系统遭入侵时被盗，研究还发现部分OpenClaw智能体缺乏密码保护。英伟达CEO黄仁勋指出，这些安全漏洞意味着尽管OpenClaw正推动AI智能体迈向"ChatGPT时刻"，但尚未达到企业级应用标准，不过这项技术的重要性不容忽视。

"CEO们需要思考：你们的OpenClaw战略是什么？"黄仁勋在GTC大会上强调，"正如每家企业都需要Linux战略、开启互联网时代的HTTP/HTML战略、催生移动云的Kubernetes战略，当今全球企业都必须制定OpenClaw战略。"

Futurum Group分析师布伦丹·伯克认为，英伟达对智能体AI和OpenClaw的新聚焦具有战略意义，表明这家AI巨头不再将工具开发重任完全交由合作伙伴，而是亲自助力企业构建相关工具。他指出："Nemotron等智能体模型的快速发展证明，英伟达不仅能提供硬件，更有能力成为独立的智能体编排平台。"

宾夕法尼亚大学工程学院教授本杰明·李分析称，英伟达希望复制其二十年历史的CUDA平台的成功效应。CUDA曾推动英伟达GPU高性能计算的普及并促进AI芯片发展，而OpenClaw不仅是解决复杂数学问题的AI模型，更通过处理现实任务、将训练应用于未知场景，将生成式AI智能体提升到新高度。"他们期待将CUDA的飞轮效应扩展到更广阔的计算层面——这已超越单一矩阵运算，涵盖推理与智能体协同。"

李教授补充道，除聚焦智能体AI外，英伟达还通过同日发布的六款Vera Rubin系列芯片强化AI推理布局。这些芯片可协同运作构成AI超级计算机，支撑从预训练、后训练到测试扩展、智能体推理的全流程。配合Vera Rubin DSX AI工厂设计（软硬件协同开发的数据中心AI基础设施新范式），彰显了英伟达从训练到推理的战略转向。

"在推理领域，他们认识到存在各种规模与能力的模型，需要构建让用户快速实验、部署并验证模型适用性的平台。"李教授解释道。

J. Gold Associates总裁杰克·戈尔德指出，英伟达的推理推进战略旨在传递"Vera Rubin芯片与AI工厂将降低企业令牌使用总成本"的理念。"推理如同云托管，是成本敏感的计算架构。传递'虽系统昂贵但能生成更多令牌创造收益'的信息，对其应对谷歌、AWS、微软等超大规模厂商及Cerebras等独立芯片制造商的竞争至关重要。"

除NemoClaw与AI芯片外，英伟达还扩展了Nemotron模型家族，推出具备视觉、语音、安全等跨领域理解能力的"全能理解"模型。例如：Nemotron 3 Ultra驱动代码助手与搜索等AI原生应用；Nemotron 3 Omni通过音视频与语言理解助力智能体解析视频文档；Nemotron 3 VoiceChat则支持AI系统进行实时对话。

英文来源：

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Amid the popularity of OpenClaw, Nvidia is providing enterprises with their own OpenClaw moment, with added security and governance, while pushing to be recognized as an inference provider, not just the unquestioned leader in the AI training market.
The AI hardware and software giant, on Monday, at its GTC developer conference in San Jose, introduced the Nvidia NemoClaw stack for the OpenClaw agent platform. The platform lets users install Nvidia Nemotron models and the new Nvidia OpenShell runtime platform in a single command, according to Nvidia. OpenShell is an open source, secure environment for deploying personal AI agents. It provides a safety and governance layer between the AI agent and its compute infrastructure.
The NemoClaw platform shows just how important Nvidia considers OpenClaw's widespread popularity. The open source agentic AI framework, now under the OpenAI umbrella, has gained wide popularity in the last few months since its introduction in November, with an estimated more than two million users worldwide.
With OpenClaw, users can create and manage AI agents that can execute real-world tasks and act as personal agents. However, despite its popularity, serious security concerns have emerged. It has sensitive API keys and session tokens in unencrypted files that can be stolen if the host system is compromised. Moreover, researchers have found instances in which OpenClaw agents lacked password protection. These security holes mean that while OpenClaw is pushing AI agents toward what Nvidia CEO Jensen Huang calls "the ChatGPT moment," it is not ready for the enterprise. But the technology is too important to ignore, Huang said.
"For the CEOs, the question is what's your OpenClaw strategy?" Haung asked during his GTC on Monday. "Just as we need to all have a Linux strategy, we all need to have an HTTP/HTML strategy, which started the internet; we all needed to have a Kubernetes strategy, which made it possible for mobile cloud to happen. Every company in the world today needs to have an OpenClaw strategy."
Nvidia's new focus on agentic AI and OpenClaw is significant because it shows that the AI vendor is not leaving the heavy lifting of building tools solely to its partners; instead, it wants to help enterprises build those tools as well, said Brendan Burke, an analyst at Futurum Group.
"The rapid recent development and agentic models such as Nemotron show that the company can become a standalone agent orchestrator, along with providing hardware," Burke said.
Nvidia is also looking to get the same effect it had with its two-decade old CUDA (compute unified device architecture) platform, said Benjamin Lee, a professor at Penn Engineering, University of Pennsylvania. He noted that CUDA was easily adopted for high-performance computing on Nvidia GPUs and that it drove further development of AI chips, and that OpenClaw is more than just an AI model solving complex mathematical problems. It's addressing real-world tasks, and the models are applying training to what they’ve not seen before.
"With OpenClaw … they want to bring it up a level to look at these generative AI agents," Lee said. "They're hoping to extend what they did with CUDA and that flywheel effect to a bigger level of computation, because it's not just individual matrix operations, it's actually the inference and the agents."
Lee added that, in addition to focusing on agentic AI, Nvidia is also honing in much more on AI inference, especially with its introduction, also on Monday, of six new chips in the Nvidia Vera Rubin line to power the next stage of agentic AI. The new chips are designed to operate together as one AI supercomputer to power every phase of AI, from pretraining and post-training to test-time scaling and agentic inference, Nvidia said.
The emphasis on AI inference, not only with these new chips but also with the Nvidia Vera Rubin DSX AI Factory design -- a new guide for building codesigned AI infrastructure for data centers, in which hardware and software are developed together in a synergistic way -- illustrates Nvidia's shift from training, Lee said.
"On the inference side, what they're recognizing is that there are lots of different models of different sizes and different capabilities, and they want a platform for users to be able to experiment with different types of models quickly, deploy them and see if it meets their needs," he said.
The inference push also allows Nvidia to encourage the idea that its Vera Rubin chips and AI factory concept will lower the overall costs of tokens enterprises use, said Jack Gold, president at J. Gold Associates.
"Inference is a cost-sensitive compute structure, just like cloud hosting is," Gold said. "Promoting a message that even though our systems are expensive, we can enable you to generate lots more tokens, and hence more revenue, is a critical message for them going forward." This is particularly important given competition from hyperscalers such as Google, AWS, and Microsoft, as well as independent chipmakers such as Cerebras, he added.
In addition to NemoClaw and AI chips, Nvidia expanded its Nemotron family with what the vendor calls "omni-understanding" models for various applications, including vision, voice, and safety. For example, Nemotron 3 Ultra powers AI-native applications such as coding assistants and search; Nemotron 3 Omni uses audio, vision and language understanding to help agents gain insights from videos and documents; and Nemotron 3 VoiceChat enables the AI system to support real time conversations.