Editorial illustration for NVIDIA Releases Physical AI Datasets with 7M Robotics Trajectories and 1K Assets
NVIDIA Unveils 7M Robotics Trajectories for AI Training
NVIDIA launches Physical AI Open Datasets: 7M trajectories, 1K assets
The robotics and AI training landscape is getting a serious upgrade. NVIDIA is pushing the boundaries of machine learning datasets by releasing a massive collection of physical AI resources that could reshape how robots and AI systems understand complex environments.
The company's latest move targets one of the most challenging problems in artificial intelligence: teaching machines to interact with the physical world. By providing an unusual volume of training data, NVIDIA is giving researchers and developers a powerful new toolkit for creating more adaptive and intelligent robotic systems.
These aren't just any datasets. With over 7 million robotics trajectories and 1,000 simulation-ready assets, the collection represents a quantum leap in training materials. Developers can now access a rich, diverse set of real-world and synthetic data that could accelerate breakthroughs in robotic perception and movement.
The early response suggests the datasets are striking a chord. Already downloaded more than 6 million times, NVIDIA's release is generating serious buzz in the AI research community.
NVIDIA earlier this year released the NVIDIA Physical AI Open Datasets on Hugging Face, featuring more than 7 million robotics trajectories and 1,000 OpenUSD SimReady assets. Downloaded more than 6 million times, the datasets combines real-world and synthetic data from the NVIDIA Cosmos, Isaac, DRIVE and Metropolis platforms to kickstart physical AI development. NVIDIA Inception Startups Highlight AI Innovation 🔗 At the PyTorch Conference’s Startup Showcase, 11 startups — including members from the NVIDIA Inception program — are sharing their work developing practical AI applications and connecting with investors, potential customers and peers.
NVIDIA's latest move signals a significant boost for physical AI development. The company has unleashed an impressive collection of datasets on Hugging Face, combining a staggering 7 million robotics trajectories with 1,000 OpenUSD SimReady assets.
The datasets draw from multiple NVIDIA platforms, including Cosmos, Isaac, DRIVE, and Metropolis. Already, these resources have captured significant attention, with over 6 million downloads indicating substantial industry interest.
By making these full datasets publicly available, NVIDIA is effectively lowering barriers to entry for AI researchers and developers working on robotic and physical intelligence applications. The blend of real-world and synthetic data provides a rich training ground for emerging AI technologies.
The release coincides with NVIDIA's Startup Showcase at the PyTorch Conference, suggesting a broader strategic push to accelerate AI idea. Researchers now have access to an unusual volume of curated data that could potentially fast-track developments in robotic trajectory modeling and simulation.
Still, the true impact remains to be seen. But for now, NVIDIA has certainly thrown down an impressive gauntlet in the physical AI landscape.
Further Reading
- Nvidia CES 2026: Alpamayo Open-Source AI Marks Physical AI Era - StockTitan
- Huang Lays Out NVIDIA's Plan for the Physical AI Era at CES 2026 - TechBuzz
- NVIDIA expands open-source tools for physical AI and robotics - Engineering.com
- NVIDIA Bets Big on AI-Driven Drug Discovery, Physical AI, and a $1 Billion Eli Lilly Partnership - Bio-IT World
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Common Questions Answered
How many robotics trajectories are included in NVIDIA's Physical AI Open Datasets?
NVIDIA has released over 7 million robotics trajectories in their Physical AI Open Datasets. These trajectories are sourced from multiple NVIDIA platforms including Cosmos, Isaac, DRIVE, and Metropolis, providing a comprehensive resource for AI training.
Where are the NVIDIA Physical AI Open Datasets currently available?
The datasets are available on Hugging Face, a popular machine learning platform for sharing datasets and models. Since their release, these datasets have already been downloaded more than 6 million times, indicating significant interest from the AI and robotics research community.
What types of assets are included in NVIDIA's Physical AI Open Datasets?
The datasets include 1,000 OpenUSD SimReady assets alongside the 7 million robotics trajectories. These assets combine both real-world and synthetic data, designed to help researchers and developers advance physical AI development and machine interaction with complex environments.