Generalist robots must reason, plan, and act across many environments and tasks when given instructions. To learn new tasks, developers train robot models on real world data. But human demonstrations are costly to capture.Groot Dreams is a blueprint for synthetic data generation and neural simulation built on NVIDIA Cosmos. Using a single image and natural language, developers generate synthetic world states or dreams. These passive dreams can be generated at scale, but prompting with natural language has i ...

NVIDIA’s level 4 partners are accelerating the future of autonomous vehicles. Together, we’re building an AI-driven transportation ecosystem powered by NVIDIA — from training and simulation to in-vehicle compute — to safely bring autonomy to the road. Our level 4 ecosystem includes: Uber, Stellantis, Mercedes-Benz, Lucid, Nuro, Wayve, Oxa, Pony.ai, WeRide, Waabi, and Volvo Autonomous Solutions. These innovators are redefining mobility by developing, deploying, and scaling autonomous vehicles on NVIDIA. Read ...

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America, the land of innovation, where invention shaped destiny [Music] and technology helped dreams take flight. At Bell Labs, the transistor was born, sparking the age of semiconductors and giving rise to Silicon Valley. [Music] Hedi Lamar reimagined communication, paving the way for wireless connectivity.IBM's system 360 put a universal computer at the heart of industry. Intel's microprocessor drove the digital age forward and Craig's supercomputers expanded the frontiers of science. >> So, we think we'r ...

For decades, fusion energy, the process that powers the sun, has been one of science's greatest opportunities. Cracking it would give us a safe, clean, and virtually unlimited source of power. Controlling plasma hotter than the sun's core means solving physics so complex that even the fastest supercomputers struggle to simulate it.At the forefront of this effort, General Atomics researchers and international partners at the D3D National Fusion Facility are using AI to push fusion research forward. The team ...

Quantum Computing Challenges & Solutions - Quantum bits (Qbits) are fragile and sensitive to noise, limiting their stability to a few hundred operations, while solving meaningful problems requires trillions of operations [1] - Quantum error correction is crucial, involving adding extra entangled Qbits to measure and calculate errors without damaging the core Qbits [2] NVIDIA's Solution: NVQ Link & CUDAQ - NVIDIA introduces NVQ Link, an interconnect architecture directly connecting quantum processors with NVIDIA GPUs for quantum error correction [3] - NVQ Link facilitates the transfer of terabytes of data to and from quantum hardware thousands of times per second, essential for quantum error correction [3] - CUDAQ, NVIDIA's open platform for quantum GPU computing, enables researchers to perform error correction and orchestrate quantum devices and AI supercomputers [4] Future of Quantum Computing - Quantum computing will not replace classical systems but will integrate with them to form accelerated quantum supercomputing platforms [4]

The age of AI has begun. Blackwell is its engine, an engineering marvel. In Arizona, it starts as a blank silicon wafer.Hundreds of chip processing and ultraviolet lithography steps build up each of the 200 billion transistors layer by layer on a 12in wafer. In Indiana, HBM stacks will be assembled in parallel. HBM memory dies with 1,024 IO's are fabricated using advanced EUV technology through silicon via is used in the back end to connect 12 stacks of HBM memory and base dye to produce HBM.Meanwhile, the ...

Overview of AI Factory Infrastructure - The next industrial revolution is here, marked by the emergence of a new type of factory centered around AI infrastructure [1] - AI infrastructure development requires ecosystem-scale collaboration among hundreds of companies [1] - NVIDIA Omniverse DSX serves as a blueprint for constructing and operating Gigascale AI factories [1] Design and Construction Optimization - Building, power, and cooling systems are co-designed with Nvidia's AI infrastructure stack [1] - Jacobs Engineering optimizes compute density and layout to maximize token generation based on power constraints [2] - Prefabricated modules are factory-built, tested, and ready to plug in by Nvidia partners like Bectal and Vertive, significantly reducing build time [3] Operational Efficiency and Revenue Generation - The digital twin acts as an operating system for the physical AI factory [4] - AI agents, trained in the digital twin, optimize power consumption and reduce strain on the AI factory and the grid [4] - DSX optimizations can potentially deliver billions of dollars in additional revenue per year for a one gigawatt AI factory [4] Deployment and Research - Nvidia's partners are implementing DSX across Texas, Georgia, and Nevada [5] - Nvidia is establishing an AI factory research center in Virginia using DSX to test and productize Vera Rubin [5]

Wireless networks are critical infrastructure. Connecting more devices than there are people on Earth. Soon, intelligent cameras, cars, and robots will create hundreds of billions of new connections.NVIDIA AI RAM modernizes wireless infrastructure into intelligent 5G and 6G networks, delivering scale, spectrum efficiency, and AI where the users are. In just 6 months, Nvidia and our partners built the first AI native wireless stack made in America, powered by Nvidia AI aerial. It's already running applicatio ...

America is re-industrializing, reshoring manufacturing across every industry. In Houston, Texas, Foxcon is building a state-of-the-art robotic facility for manufacturing NVIDIA AI infrastructure systems. With labor shortages and skills gaps, digitalization, robotics, and physical AI are more important than ever.The factory is born digital in Omniverse. Foxcon engineers assemble their virtual factory in a seaman's digital twin solution developed on Omniverse Technologies. Every system, mechanical, electrical ...