TAIPAI, Taiwan (COMPUTEX), May 19, 2025 – NVIDIA has announced NVIDIA Isaac GR00T N1.5, the first update to NVIDIA’s open, generalized, 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 framework that generates synthetic motion data, called neural trajectories. Physical AI developers use the data to teach robots new behaviors, including how to adjust to changing environments.
Developers can first post-train Cosmos Predict world foundation models (WFMs) for their robot. Then, using a single image as input, GR00T-Dreams generates videos of the robot performing tasks in new environments. The blueprint then extracts action tokens – compressed, digestible pieces of data – that teach robots how to perform these 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 adapts to new environments and workspace layouts. It can also identify objects based on user instructions. This update improves the model’s success rate in common material handling and manufacturing tasks like sorting and storing objects.
Early adopters of GR00T N models include AeiRobot, Foxlink, Lightwheel, and NEURA Robotics. AeiRobot employs the models to aid ALICE4 understand natural language instructions and perform complex pick-and-place tasks 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 humanoid robot deployment in factories. NEURA Robotics is testing models to speed up home automation.
New Robot Simulation and Data Generation Frameworks Accelerate Training Pipelines
Developing skilled humanoid robots requires diverse data, which is costly to capture and process. Robots require real-world testing, which adds cost 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 synthetic data for physical AI model training, is available on Hugging Face.
- Cosmos Predict 2, used in GR00T-Dreams, is coming soon to Hugging Face, featuring performance enhancements for world generation and reduced hallucination.
- NVIDIA Isaac GR00T-Mimic, a blueprint for generating synthetic motion trajectories for robot manipulation, using few human demonstrations.
- Open-Source Physical AI Dataset, which includes 24,000 humanoid robot motion trajectories used to develop GR00T N models.
- NVIDIA Isaac Sim 5.0, a simulation and synthetic data generation framework, will be 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 use the GR00T-Mimic blueprint for synthetic motion manipulation to speed up their robotics training pipelines. Agility Robotics, Boston Dynamics, Fourier, Mentee Robotics, NEURA Robotics, and XPENG Robotics simulate and train their humanoid robots with NVIDIA Isaac Sim and Isaac Lab. Skild AI uses the simulation frameworks to develop general robot intelligence. General Robotics integrates these frameworks 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 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 on the NVIDIA Jetson Thor platform, coming soon. This will enable instant on-robot inference and improved runtime performance.
Source: NVIDIA
About NVIDIA
NVIDIA Corporation, based in Santa Clara, CA, is a U.S. technology company specializing in the design and production of graphics processing units (GPUs). Its hardware and software solutions support a range of applications and simulation. Operating for over 30 years, NVIDIA has seen strong financial growth, reporting $39.3 billion in revenue and $22.1 billion in net income for the fiscal quarter ending January 2025. Its headquarters are designed to promote a flat organizational structure that encourages open communication and collaboration between leadership and staff across industries. In gaming, its GPUs power high-performance visual rendering. In artificial intelligence and high-performance computing, NVIDIA provides the infrastructure needed for training and deploying large-scale models. The company also contributes to the automotive sector with systems for autonomous driving and supports robotics with tools for AI-based perception.