Agent5Seven topics. One clear view.
Agent5

The latest AI news at a glance: seven topics, and a short, plain-English read on the stories. Free, no account.

Product
HomeHow it worksFAQAboutHow we fact-checkBlog
News
All newsModels & ReleasesFunding & DealsBenchmarksAgents & ProductsHardware & ComputePolicy & DramaRobotics
More
AdvertisePressPrivacyTerms
© 2026 Agent5
Agent5
Blog
Agent5
Blog
  1. Home›
  2. News›
  3. Hardware & Compute›
  4. NVIDIA expands confidential computing options
Models & Releases27Funding & Deals18Benchmarks15Agents & Products48Hardware & Compute23Policy & Drama31Robotics13
Hardware & Compute

NVIDIA expands confidential computing options

NVIDIA Blog: NVIDIA Confidential Computing Expands, Enabling Frontier Model Builders to Securely Scale Across Global Infrastructure

NVIDIA builds tools to enable safe agents across the stack. The NVIDIA OpenShell Reference Architecture, announced today, is part of NVIDIA’s growing portfolio of technologies that enables organizations to safely deploy agents at scale. NVIDIA Confidential Computing is the infrastructure layer that protects the models and data those agents depend on while running. Today, NVIDIA is expanding that layer with Confidential Bare Metal, a new deployment option with NVIDIA Confidential Computing that e

Get smart on it

NVIDIA Confidential Computing is a security layer that protects artificial intelligence models and data while they run on computing infrastructure. The company has expanded this technology with a new "Confidential Bare Metal" option that allows model builders to run sensitive workloads on dedicated infrastructure while maintaining control over their own software and data. This expansion matters because it gives organizations more deployment options, including bare-metal instances, containerized environments, and virtual machines, along with new security controls that protect data during transit and enforce hardware-level access restrictions. The technology now works across multiple NVIDIA hardware systems and is being adopted by various cloud providers and infrastructure partners globally.

Relevant courses

Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.

Browse AI courses on Maven →
Sources
NVIDIA Blog ↗
The biggest AI stories, once a day

One short email a day with the stories that matter. Free. Unsubscribe with one click.

Related news
Hardware & ComputeOpen story →

Google Cloud and NVIDIA Announce General Availability of NVIDIA Vera Rubin Infrastructure

General availability of the instances is coming next month, with planned expansion of availability to Europe — bringing an integrated platform for training, inference and large-scale reinforcement learning to cloud customers. A5X instances bring together NVIDIA Vera Rubin NVL72, NVIDIA ConnectX-9 SuperNICs, Google Cloud Virgo Network and Google Cloud’s fourth-generation advanced liquid-cooling technology for demanding agentic inference and reinforcement learning workloads at scale. Google Cloud

Hardware & ComputeOpen story →

European Leaders Turn to NVIDIA Vera CPUs to Build Local Infrastructure

Nebius and Nscale are among global technology partners looking to NVIDIA Vera CPUs to build the next wave of infrastructure. Their momentum reflects rapid advancements in agentic computing.  Agents do more than generate answers: they retrieve information, run software tools, execute code and evaluate results. Each step depends on fast CPU processing.  Vera accelerates that work, helping agents respond faster and enabling data centers to make better use of computing capacity. Vera is designed to

Hardware & ComputeOpen story →

Hugging Face ❤️ TorchTPU: TPUs, Natively

Tighter integration between the popular open-source platform and Google's specialized processors could lower barriers for researchers training large models.

Also reported by MarkTechPost and SiliconANGLE

Hardware & ComputeOpen story →

Google Cloud Ships llm-d 1.0 With Cache-Aware Routing for TPU and GPU Fleets

Google team have released llm-d 1.0, the first stable version of its distributed inference stack. This open-source, Kubernetes-native layer turns vLLM or SGLang model servers into one coordinated pool. They released it at the PyTorch Conference North America. It targets self-hosted agent and RL workloads, where round-robin load balancing breaks down. TL;DR A serving stack: Google reports a published benchmark on a 17,000-node multi-region GKE deployment. Runs on: Kubernetes with NVID

Hardware & ComputeOpen story →

Google has joined Amazon in attacking Nvidia’s stronghold with AI app developers

Google has joined Amazon in releasing a developer tool that makes it easy for PyTorch users to move their apps off Nvidia GPUs.

Hardware & ComputeOpen story →

CoreWeave’s debt is becoming the whole AI industry’s problem

CoreWeave had a bad week last week. Its bonds slipped into distressed territory by a common definition - when investors demand 1,000 basis points more in yield than they'd get from government bonds. Last Tuesady Chamath "SPAC King" Palihapitiya noticed the distressed debt, and also asked whether the AI buildout was a private credit bubble. Its shares are down more than 20 percent since Tuesday's close, which is kind of a lot! There even seemed to be some collateral damage in th