NVIDIA Blog

Summer is heating up — and GeForce NOW is taking players along for the ride. Start the month with Monopoly: Star Wars Heroes vs. Villains, bringing a galaxy far, far away to the iconic board-game franchise, alongside 12 new games joining the cloud this month. Plus, don’t let the sun set on the biggest GeForce NOW savings of the year. Level up for less before the deals disappear. Light Side, Dark Side, Cloud Side The Force is strong with this one. Rule the board, you must.

As AI moves from model development to production inference, compute demand is accelerating and shifting toward continuously operating AI factories that generate tokens at scale. This shift requires access to large‑scale, multi‑tenant accelerated computing that can come online quickly, stay highly utilized and support the economics of token‑scale AI services.

Skip to content Your browser does not support the video tag. America is a nation of builders. For 250 years, America has built railroads that connected a continent, power grids that lit up cities, factories that powered prosperity, semiconductors that made the digital age possible and the internet that opened knowledge to the world. Now, America is building again.

Life sciences has entered an era of computational scale, and for more than a decade, NVIDIA has built the full GPU-accelerated computing stack — spanning hardware, frameworks, libraries, models, microservices and domain-specific tools — to help researchers run more sophisticated workflows and iterate faster. This week, Anthropic announced Claude Science, an AI workbench for science research that lets scientists converse with agents in natural language to run their work end to end.

When Jaiveer Singh talks about robots, he doesn’t begin with spectacle. He begins with infrastructure: the boards inside machines, the software that lets developers see through a robot’s cameras and the engineering required before a robot can leave a demo floor to do something useful. As a robotics software engineer who leads the team behind NVIDIA Isaac ROS (Robot Operating System), Singh works on the connective tissue of the physical AI era.

As organizations move from AI pilots to production AI factories, infrastructure decisions have shifted from peak chip specifications to cost per token: how many useful tokens they can deliver per dollar, per watt and within required latency targets. Codesigned with NVIDIA GPUs, CPUs, networking and systems, and strengthened by a broad open source ecosystem, NVIDIA’s full-stack inference software continuously improves hardware performance.

Editor’s note: This post is part of Into the Omniverse, a series focused on how developers, 3D practitioners, and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Vision AI agents are becoming a practical way to automatically turn video data from the physical world into operational intelligence in factories, cities, warehouses and transportation systems. That shift is accelerating as more AI workloads move closer to where data is generated.

Anthropic’s Claude models in Microsoft Foundry — hosted on Microsoft Azure and running on NVIDIA GB300 Blackwell Ultra GPUs — are now generally available, giving Azure-native enterprises a powerful new way to build autonomous and domain-specific AI agents. As agentic AI continues to drive enterprise innovation and becomes more autonomous, organizations need access to computing power to build and deploy specialized agents to accelerate essential business tasks.

The NVIDIA Inception member’s Ocula moon imaging service will harness the NVIDIA Jetson platform for edge AI, running inference directly in space to significantly accelerate insights compared with downlinking all data back down to Earth. When Firefly Aerospace’s Blue Ghost Mission 1 landed on the moon in March 2025, the lander downlinked nearly 120 gigabytes of raw data back to Earth — imagery and video captured by onboard cameras that scientists are still processing today.

Showcasing the importance of open source innovation in American AI, Palantir’s new intelligent engine — introduced today — uses NVIDIA Nemotron open models to serve the needs of U.S. government agencies. Open source software has long been a pillar of U.S. technology leadership. In 1969, DARPA connected four university computers — from UCLA, Stanford, UCSB and the University of Utah — laying the infrastructure backbone that became the internet.