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Building an Adaptive Agentic Cybersecurity System with NVIDIA Nemotron

An illustration showing agentic security.AI is changing the pace of cybersecurity. Agentic systems can coordinate work and pursue complex objectives over long horizons. Security teams are beginning to...An illustration showing agentic security.

AI is changing the pace of cybersecurity. Agentic systems can coordinate work and pursue complex objectives over long horizons. Security teams are beginning to apply agents across security operations, but many implementations remain anchored to existing alerts, predefined workflows, and known attack behaviors. The harder problem is identifying what defenses miss and turning those gaps into…

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NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents

A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives...

A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives context, uses tools, maintains state, responds to feedback, recovers from failure, and sustains progress over long-running tasks. The challenge is how to build the agent architecture that makes frontier language models work reliably on extended…

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Where Security Fits in an AI Agent Stack

As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important....

As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important. Drawing on work with NVIDIA OpenShell, agent developers, open-source projects, and partners across the ecosystem, AI safety and security teams at NVIDIA offer their perspective on the emerging agent stack—including the role of each layer…

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Four Ways to Deploy More Secure AI Agents

An image of an AI agent showing security.Knowledge workers are increasingly integrating AI agents into their workflows. Agents that function as "digital coworkers" offer clear benefits. For example,...An image of an AI agent showing security.

Knowledge workers are increasingly integrating AI agents into their workflows. Agents that function as “digital coworkers” offer clear benefits. For example, they can review a bug report, implement and test a fix, push a patch, and ping a human for review. By handling routine tasks, agents have the potential to deliver large productivity gains. On the other hand, connecting a large language model…

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Six Agent Harness Capabilities for Higher Model Performance

Decorative image.Building a great AI agent isn’t just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes...Decorative image.

Building a great AI agent isn’t just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes actions, manages state, and decides when a task is done shapes outcomes just as much as the model itself. Harness design alone can account for double-digit swings in benchmark results and significant differences in token cost…

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Building Faster Cryptography with Carryless Multiplication in NVIDIA CUDA 13.3 

Decorative image.For over fifteen years, x86 CPUs have shipped with a dedicated hardware instruction for carryless multiplication. It’s a small but stubborn primitive that...Decorative image.

For over fifteen years, x86 CPUs have shipped with a dedicated hardware instruction for carryless multiplication. It’s a small but stubborn primitive that sits underneath authenticated encryption, error-correcting codes, and modern zero-knowledge proofs. Until now, NVIDIA GPUs lacked native support for this operation. NVIDIA CUDA 13.3 closes that gap with , a new PTX instruction available on…

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Hardware-Rooted AI Security That Won’t Slow You Down

Decorative image.AI has transformed how organizations operate, driving unprecedented levels of productivity and innovation. However, AI adoption can be impeded by concerns...Decorative image.

AI has transformed how organizations operate, driving unprecedented levels of productivity and innovation. However, AI adoption can be impeded by concerns surrounding data privacy, sovereignty and how to secure data while it is in use, or during inference and engagement with AI models. NVIDIA Confidential Computing (CC) was engineered to be a secure and performant solution for the era of agentic…

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One-Click Multi-Tenant Security with  NVIDIA Quantum InfiniBand

NVIDIA Quantum InfiniBand now offers intent-based security profiles in Unified Fabric Manager (UFM) that enable multi-tenant fabric security in a single...

NVIDIA Quantum InfiniBand now offers intent-based security profiles in Unified Fabric Manager (UFM) that enable multi-tenant fabric security in a single click. NVIDIA Quantum InfiniBand supports three profiles: General, Bare Metal Cloud, and Secured Bare Metal Cloud. Network administrators can now auto-configure: This cuts deployment time to minutes from hours or days…

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Advancing AI Infrastructure for Agentic AI with NVIDIA DOCA In-Silicon Security

The AI era is driving a new class of infrastructure: AI factories that transform data into intelligence for autonomous AI agents operating at unprecedented...

The AI era is driving a new class of infrastructure: AI factories that transform data into intelligence for autonomous AI agents operating at unprecedented scale. Powered by accelerated computing, AI factories enable enterprises to train, fine-tune, and deploy AI with greater speed and efficiency. This new class of infrastructure also introduces a fundamentally new attack surface spanning…

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How to Automate AI Model Documentation with the NVIDIA MCG Toolkit

As AI models grow in complexity and regulatory scrutiny intensifies under frameworks including  California’s AB-2013 and the EU AI Act, software teams...

As AI models grow in complexity and regulatory scrutiny intensifies under frameworks including California’s AB-2013 and the EU AI Act, software teams face a challenge beyond delivering great code: They need to produce comprehensive, auditable model documentation before the models are released. Model cards describe how a model works, its intended use and license, training data, performance…

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