NVIDIA Powers Humanoid Robot Industry With Cloud-to-Robot Computing Platforms for Physical AI
- Significant reduction in development time: GR00T N1.5 developed in 36 hours vs. 3 months traditionally
- Major industry adoption with partnerships including Agility Robotics, Boston Dynamics, and Foxconn
- Up to 18x performance improvement for data processing with new Blackwell systems
- Comprehensive ecosystem with cloud-to-robot computing platforms and open-source frameworks
- None.
Insights
NVIDIA extends AI dominance into humanoid robotics with new foundation models, simulation tools, and hardware - strategically positioning for the next computing revolution.
NVIDIA's announcement represents a significant expansion of its AI ecosystem into the physical world through humanoid robotics. The company is leveraging its AI leadership position to build a comprehensive technology stack for robot development, tackling the industry's biggest challenges.
The updated Isaac GR00T N1.5 foundation model addresses a critical bottleneck in robotics development - the ability to understand context and adapt to changing environments. What's particularly notable is the 36-hour development timeframe (versus three months of traditional data collection), demonstrating how NVIDIA's synthetic data generation approach dramatically accelerates development cycles.
The GR00T-Dreams blueprint solves one of robotics' fundamental problems - the massive data requirements for training. By generating synthetic motion data from just single images, NVIDIA eliminates the need for expensive and time-consuming physical data collection, potentially democratizing robot development by lowering barriers to entry.
Strategically, NVIDIA is applying the same successful business model it used to dominate AI computing:
- Create foundation models and tools that become industry standards
- Build a comprehensive ecosystem spanning hardware to software
- Secure partnerships with key players across the value chain
- Offer cloud and on-device solutions to capture revenue at multiple points
The impressive partner list (Boston Dynamics, Foxconn, etc.) indicates NVIDIA is already establishing itself as the technology backbone for humanoid robot development. With both proprietary and open-source components, NVIDIA is positioned to become the dominant platform for physical AI just as it has for generative AI.
This move significantly expands NVIDIA's total addressable market by positioning the company at the forefront of what Jensen Huang calls "the next industrial revolution" - a strategic long-term growth vector beyond its current AI computing dominance.
- New NVIDIA Isaac GR00T Humanoid Open Models Soon Available for Download on Hugging Face
- GR00T-Dreams Blueprint Generates Data to Train Humanoid Robot Reasoning and Behavior
- NVIDIA RTX PRO 6000 Blackwell Workstations and RTX PRO Servers Accelerate Robot Simulation and Training
- Agility Robotics, Boston Dynamics, Foxconn, Lightwheel, NEURA Robotics and XPENG Robotics Among Many Robot Makers Adopting NVIDIA Isaac
TAIPEI, Taiwan, May 19, 2025 (GLOBE NEWSWIRE) -- COMPUTEX -- NVIDIA today announced NVIDIA Isaac GR00T N1.5, the first update to NVIDIA’s open, generalized, fully customizable foundation model for humanoid reasoning and skills; NVIDIA Isaac GR00T-Dreams, a blueprint for generating synthetic motion data; and NVIDIA Blackwell systems to accelerate humanoid robot development.
Humanoid and robotics developers Agility Robotics, Boston Dynamics, Fourier, Foxlink, Galbot, Mentee Robotics, NEURA Robotics, General Robotics, Skild AI and XPENG Robotics are adopting NVIDIA Isaac™ platform technologies to advance humanoid robot development and deployment.
“Physical AI and robotics will bring about the next industrial revolution,” said Jensen Huang, founder and CEO of NVIDIA. “From AI brains for robots to simulated worlds to practice in or AI supercomputers for training foundation models, NVIDIA provides building blocks for every stage of the robotics development journey.”
New Isaac GR00T Data Generation Blueprint Closes the Data Gap
Showcased in Huang’s COMPUTEX keynote address, NVIDIA Isaac GR00T-Dreams is a blueprint that helps generate vast amounts of synthetic motion data — aka neural trajectories — that physical AI developers can use to teach robots new behaviors, including how to adapt to changing environments.
Developers can first post-train Cosmos Predict world foundation models (WFMs) for their robot. Then, using a single image as the input, GR00T-Dreams generates videos of the robot performing new tasks in new environments. The blueprint then extracts action tokens — compressed, digestible pieces of data — that are used to teach robots how to perform these new tasks.
The GR00T-Dreams blueprint complements the Isaac GR00T-Mimic blueprint, which was released at the NVIDIA GTC conference in March. While GR00T-Mimic uses the NVIDIA Omniverse™ and NVIDIA Cosmos™ platforms to augment existing data, GR00T-Dreams uses Cosmos to generate entirely new data.
New Isaac GR00T Models Advance Humanoid Robot Development
NVIDIA Research used the GR00T-Dreams blueprint to generate synthetic training data to develop GR00T N1.5 — an update to GR00T N1 — in just 36 hours, compared with what would have taken nearly three months of manual human data collection.
GR00T N1.5 can better adapt to new environments and workspace configurations, as well as recognize objects through user instructions. This update significantly improves the model’s success rate for common material handling and manufacturing tasks like sorting or putting away objects.
Early adopters of GR00T N models include AeiRobot, Foxlink, Lightwheel and NEURA Robotics. AeiRobot employs the models to enable ALICE4 to understand natural language instructions and execute complex pick-and-place workflows in industrial settings. Foxlink Group is using them to improve industrial robot manipulator flexibility and efficiency, while Lightwheel is harnessing them to validate synthetic data for faster humanoid robot deployment in factories. NEURA Robotics is evaluating the models to accelerate its development of household automation systems.
New Robot Simulation and Data Generation Frameworks Accelerate Training Pipelines
Developing highly skilled humanoid robots requires a massive amount of diverse data, which is costly to capture and process. Robots need to be tested in the physical world, which can present costs and risk.
To help close the data and testing gap, NVIDIA unveiled the following simulation technologies:
- NVIDIA Cosmos Reason, a new WFM that uses chain-of-thought reasoning to help curate accurate, higher-quality synthetic data for physical AI model training, is now available on Hugging Face.
- Cosmos Predict 2, used in GR00T-Dreams, is coming soon to Hugging Face, featuring performance enhancements for high-quality world generation and reduced hallucination.
- NVIDIA Isaac GR00T-Mimic, a blueprint for generating exponentially large quantities of synthetic motion trajectories for robot manipulation, using just a few human demonstrations.
- Open-Source Physical AI Dataset, which now includes 24,000 high-quality humanoid robot motion trajectories used to develop GR00T N models.
- NVIDIA Isaac Sim™ 5.0, a simulation and synthetic data generation framework, will soon be openly available on GitHub.
- NVIDIA Isaac Lab 2.2, an open-source robot learning framework, which will support new evaluation environments to help developers test GR00T N models.
Foxconn and Foxlink are using the GR00T-Mimic blueprint for synthetic motion manipulation generation to accelerate their robotics training pipelines. Agility Robotics, Boston Dynamics, Fourier, Mentee Robotics, NEURA Robotics and XPENG Robotics are simulating and training their humanoid robots using NVIDIA Isaac Sim and Isaac Lab. Skild AI is using the simulation frameworks to develop general robot intelligence, and General Robotics is integrating them into its robot intelligence platform.
Universal Blackwell Systems for Robot Developers
Global systems manufacturers are building NVIDIA RTX PRO™ 6000 workstations and servers, offering a single architecture to easily run every robot development workload across training, synthetic data generation, robot learning and simulation.
Cisco, Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro announced NVIDIA RTX PRO-powered servers, and Dell Technologies, HPI and Lenovo announced NVIDIA RTX PRO 6000 Blackwell-powered workstations.
When more compute is required to run large-scale training or data generation workloads, developers can tap into NVIDIA Blackwell systems like GB200 NVL72 — available with NVIDIA DGX™ Cloud on leading cloud providers and NVIDIA Cloud Partners — to achieve up to 18x greater performance for data processing.
Developers can deploy their robot foundation models to the NVIDIA Jetson Thor platform, coming soon — enabling accelerated on-robot inference and runtime performance.
Watch the COMPUTEX keynote from Huang and learn more at NVIDIA GTC Taipei.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing.
For further information, contact:
Paris Fox
Corporate Communications
NVIDIA Corporation
+1-408-242-0035
pfox@nvidia.com
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FAQ
What is NVIDIA's GR00T N1.5 and how does it improve humanoid robotics?
How much faster is NVIDIA's new robotics development process with GR00T-Dreams?
Which major companies are adopting NVIDIA's Isaac platform for robotics?
What performance improvement do NVIDIA's new Blackwell systems offer for robot development?
Which manufacturers are building NVIDIA RTX PRO 6000 workstations and servers?
