Build Personal AI Agents on Windows PCs with New Tools from Microsoft and NVIDIA
AI agents are changing how you interact with your PC. Creators, developers, and AI enthusiasts are already using these agents extensively to assist with...
Deploy Self-Evolving Agents for Faster, More Secure Research with a Hermes Agent and NVIDIA NemoClaw
AI agents are a powerful tool for synthesizing data to accelerate research, summarize information, and help teams make decisions faster. But combining internal...
Deploy Agentic-Ready AI at the Edge with Memory Efficiency in NVIDIA JetPack 7.2
As AI agents move from the digital world to the physical environment, they can readily use NVIDIA Jetson to accelerate real-world deployment with optimized...
Run Local AI Agents with Faster Models and Multi-Node Clustering on NVIDIA DGX Spark
The rise of autonomous, long-running AI agents has introduced a new class of compute demand, namely tasks that maintain large context windows, spawn concurrent...
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...
Automating and Optimizing Financial Signal Discovery with Multi-Agent Systems
In quantitative finance, researchers build algorithms to trade assets, derivatives, and other financial instruments. A key part of that work is finding...
Mastering Agentic Techniques: AI Agent Customization
Autonomous AI agents are taking on all types of work for businesses: routing logistics fleets, triaging support tickets, generating code, and orchestrating...
NVIDIA-Verified Agent Skills Provide Capability Governance for AI Agents
Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to...
Evaluating an AI model and evaluating an AI agent are related—but they answer fundamentally different questions. A model benchmark tests the capability of a...
Transform Video Into Instantly Searchable, Actionable Intelligence with AI Agents and SkillsÂ
In today’s data-driven world, organizations increasingly rely on video to capture critical information, yet extracting meaningful, real-time insights from...
Build AI-Powered Games with NVIDIA DLSS 4.5, RTX, and Unreal Engine 5
Today, game developers can begin integrating NVIDIA DLSS 4.5 with Dynamic Multi Frame Generation, Multi Frame Generation 6X, and the second-generation...
24/7 Simulation Loops: How Agentic AI Keeps Subsurface Engineering Moving
The subsurface industry is at a critical point in its digital evolution. For decades, unlocking reservoir potential has relied on experts performing essential...
Federated Learning Without the Refactoring Overhead Using NVIDIA FLARE
Federated learning (FL) is no longer a research curiosity—it’s a practical response to a hard constraint: the most valuable data is often the least movable....
Advancing Emerging Optimizers for Accelerated LLM Training with NVIDIA Megatron
Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have...
Mitigating Indirect AGENTS.md Injection Attacks in Agentic Environments
AI tools are significantly accelerating software development and changing how developers work with code. These tools serve as real-time copilots, automating...
Building a Zero-Trust Architecture for Confidential AI Factories
AI is moving from experimentation to production. However, most data enterprises need exists outside the public cloud. This includes sensitive information like...
