NVIDIA Blog

The global buildout of AI infrastructure reached a new milestone today — Firebird, an emerging AI cloud, launched the CIS region’s largest AI factory in Armenia, establishing a new AI computing hub powered by NVIDIA accelerated computing and Dell Technologies high-performance AI infrastructure. Nikol Pashinyan, prime minister of the Republic of Armenia; Zhaslan Madiyev, deputy […]

August is here, bringing 26 new games for GeForce NOW members. Command the seas in World of Warships: Legends and discover what’s next in the GeForce NOW library, starting with the eight newly added games this week. In addition, GeForce NOW is at the QuakeCon gaming conference this week in Grapevine, Texas, with hands-on experiences […]

In July, NVIDIA joined more than 200 companies and organizations in signing “Open Weights and American AI Leadership,” an open letter arguing that AI leadership will be measured not by any single frontier model but by whether an open ecosystem reaches every sector.

NVIDIA is participating in the U.S. National Science Foundation’s (NSF) State and Regional Artificial Intelligence Infrastructure Hubs program, an effort launching today to expand access to the advanced computing, data, software and expertise needed for AI-enabled research and education. Consistent with the aims of the Genesis Mission, the program will support state and multistate groups […]

For robotaxis and other autonomous vehicles (AVs), the hardest problems aren’t the everyday scenarios. They’re the rare, complex situations that are difficult to anticipate and train for. Handling these long‑tail events takes more than just object detection and motion prediction. AVs must understand the situation, reason about cause and effect, choose the right action and […]

Surging AI demands are driving the need for massive datasets and context windows that burst past the confines of system memory. But rising needs aren’t met by simply adding more storage capacity. What’s needed is useful, grounded insights from AI factories and efficient, secure storage architectures that enable those insights. At this week’s Future of […]

Members of the Open Secure AI Alliance — now more than 120 organizations strong — are developing new guidelines to strengthen agentic AI cybersecurity as the annual Black Hat conference begins in Las Vegas today. The Linux Foundation today shared a Request for Comments on Shared AI Findings Exchange (SAFE), a proposed set of guidelines […]

The NVIDIA Jetson platform brings powerful edge AI and robotics compute to a palm-sized module that fits in a handbag. Venture capitalist Sarah Guo showcases the Jetson Orin Nano Super developer kit, offering 67 TOPS AI performance for students, researchers, and developers to build AI robots, autonomous machines, and more. The article highlights Jetson series models and several innovative project examples.

The Open Secure AI Alliance, building on the Linux Foundation's Akrites and OpenSSF, brings together major tech companies to develop open tools for AI cybersecurity. The alliance argues that open models are essential for defenders to inspect, adapt, and deploy AI for security, and highlights the Hugging Face incident where open-weight GLM 5.2 was used for defense. Key contributions include NVIDIA's NOOA framework, HPE's zero-trust identity, Hugging Face's Safetensors, IBM/Red Hat's Lightwell, Microsoft's MDASH, and SpaceXAI's Grok Build.

NVIDIA is collaborating with Cadence and Synopsys to optimize electronic design automation (EDA) applications for the Vera CPU, deploying it in workflows for next-gen chip design. Early tests show up to 1.5x performance improvements on Cadence Jasper and Synopsys VCS for selected workloads.

At the AI Summit in San Francisco, South Korean President Jae Myung Lee and top business leaders meet with NVIDIA to advance Korea's AI infrastructure. Key announcements include a joint AI lab with KAIST and expanded collaboration with SK Group.

NVIDIA founder and CEO Jensen Huang commissioned a DGX GB300 system at the Naval Postgraduate School in Monterey, providing one of the world's most powerful AI platforms to over 1,500 students and 600 faculty. The supercomputer will enable on-premises AI computing for applications including weather prediction, cybersecurity, and disaster resilience, marking a major step in the collaboration between NVIDIA and the military graduate university.

NVIDIA announced an open-source, GPU-accelerated Medical Physics Simulation framework for healthcare robotics, enabling developers to model anatomy-device interactions, generate edge-case scenarios, and train robots in simulated environments. The framework, part of Isaac for Healthcare, leverages CUDA and generative AI to run thousands of parallel simulations, reducing training time from hours to minutes. Early adopters include CMR Surgical, Johnson & Johnson MedTech, and Medtronic.

Wistron opened its first U.S. manufacturing facility in Fort Worth, Texas, producing NVIDIA GB300 Grace Blackwell Ultra and Vera Rubin superchips. The $700 million plant creates over 500 jobs and uses digital twin technology for virtual simulation.

NVIDIA Vera Rubin NVL72 production is ramping up with partners CoreWeave, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure. The platform delivers highest performance per watt and lowest token cost, with 10x more throughput per megawatt than Grace Blackwell NVL72 in benchmarks. It also powers Europe's open-model era through a partnership between Microsoft and Mistral.

AI has entered the gigascale era. The world’s most advanced AI factories are bringing together hundreds of thousands of GPUs and CPUs to train frontier models, power agentic AI and generate intelligence at unprecedented scale. At this level, networking becomes a critical computing power multiplier in driving token generation. Marking a networking milestone, NVIDIA Spectrum-6 — a 102.4-terabit-per-second Ethernet switch system delivering 2x the capacity of previous-generation systems and built as part of the NVIDIA Vera Rubin platform — is arriving across the world’s gigascale AI factories.

NVIDIA unveils major advancements at SIGGRAPH 2026, including MCP-connected AI agents for creative tools, a synthetic video detector NIM microservice, and the open-source Cosmos 3 Edge world model for edge physical AI. These innovations span content creation, media verification, and robotics.

Bristol Myers Squibb (BMS) is deploying its second NVIDIA DGX SuperPOD, built on eight DGX Vera Rubin NVL72 systems, making it the most powerful and energy-efficient AI cluster in life sciences. The new system will be accessible to every scientist, removing wait times and limits, and supporting AI applications across the drug discovery pipeline. BMS is also integrating the new cluster with its existing one to create a unified environment with AI-native tooling.

Lowest cost per token from extreme codesign maximizes intelligence per dollar for post-training in the agentic era.

NVIDIA announces T3000 and T2000 modules based on the Thor architecture, targeting mainstream robotics and edge AI. T3000 delivers 865 FP4 teraflops at half the size and power of T5000; T2000 offers 400 FP4 teraflops. The platform scales from 70 TOPS to 2,000 teraflops. New agent skills automate memory optimization, reducing usage by up to 15GB. Cosmos 3 Edge model enables real-time vision. Emulation available now with modules shipping in Q1 2027.

Home to leading manufacturers, robotics pioneers and infrastructure builders, Japan is one of the world’s centers of AI — building across the full stack with NVIDIA technologies. NVIDIA and its partners in Japan are this week showcasing the AI ecosystem’s latest advancements. Check back here for updates. NVIDIA and SEGA Celebrate 30 Years of Innovation, Bringing ‘VIRTUA FIGHTER CROSSROADS’ and Other Legendary SEGA Games to NVIDIA RTX Spark

Open models like NVIDIA Nemotron enable enterprises to build AI that uniquely addresses their business needs, offering full control, customization, and cost efficiency, driving the shift from AI adoption to AI ownership.

Power is AI infrastructure’s inescapable constraint. How many tokens an AI factory can generate within a fixed power budget determines its revenue and profitability. Because of this, performance per watt — a metric that can’t be gamed, only earned through real-world results — is the foundation for AI factories. As agentic AI drives token demand higher, the infrastructure decisions organizations make today will determine who scales and who doesn’t in a power-constrained world.

NVIDIA Nemotron 3 Ultra is offering leading performance at lower cost than top closed models with the largest and most widely adopted AI agent orchestration platform. LangChain tuned its Deep Agents harness for NVIDIA Nemotron 3 Ultra, achieving the highest accuracy among open models, while completing more tasks at higher throughput and running at 10x lower inference cost per run than leading closed models.

Max single-threaded CPUs at scale are a new category of CPUs built for the agentic AI era. Across the creation and deployment of an agentic system, the CPU is on the critical path for reasoning, response time and learning. CPUs are the processor which executes the work the AI model commands: the tool calling, code execution, data processing, KV-cache and result analysis.

NVIDIA and Hugging Face collaborate to integrate the NVIDIA Isaac GR00T 1.7 model and Isaac Teleop framework into LeRobot, with NVIDIA Cosmos 3 planned soon. These integrations provide developers with a more accessible and standardized path for robot development, driving innovation in the open robotics community.

At ICML 2026, over 2,000 papers cite NVIDIA GPUs, and open models like Nemotron, Cosmos, and BioNeMo are foundational to AI research across robotics, life sciences, and synthetic data generation. NVIDIA had 74 papers accepted, highlighting trends in vision, reinforcement learning, and agent training.

Nations are investing in domestic AI infrastructure including AI factories, foundation models trained on local data, and workforce development to tailor AI to local needs, driven by generative and agentic AI. Examples from Europe, Asia, and Latin America illustrate societal benefits.

As AI shifts from development to production inference, compute demand is growing and moving to continuously operating AI factories. NVIDIA introduces a new strategy to provide large-scale accelerated computing access to startups and enterprises through a revenue-sharing model, with initial deployments by Sharon AI and Firmus.

NVIDIA and its partners are investing in American manufacturing, supply chains, energy grids and skilled workforces so the U.S. can produce the infrastructure needed for better healthcare, breakthrough scientific discovery, stronger industrial productivity and global technology leadership.