Synthetic Data
Accelerating AI workflows.
What is Synthetic Data?
Training any AI model requires carefully labeled and diverse datasets that contain thousands to tens of millions of elements, some of which are beyond the visual spectrum. Collecting and labeling this data in the real world is time-consuming and expensive. This can hinder the development of AI models and slow down the time to solution.
Generated by computer simulations, synthetic data is comprised of 2D images or text, and can be used in conjunction with real-world data to train AI models. Synthetic data generation (SDG) can save significant time and greatly reduce costs.
The Benefits of Synthetic Data
Cost Savings
Overcome the data gap and reduce the overall cost of acquiring and labeling data required to train AI models.
Privacy
Address privacy issues and reduce bias by generating diverse datasets to represent the real world.
Accuracy
Create highly accurate, generalized AI models by training with data that includes rare but crucial corner cases that are otherwise impossible to collect.
Scalable
Generate data that scales with your use case across manufacturing, automotive, robotics, and more.
Synthetic Data in Action
Industrial Inspection
Synthetic data can be used for training AI models to catch defects early in the manufacturing process.
Image courtesy of Siemens
Robotics Simulation
Synthetic data can be used for training robots to move payloads, improving worker safety and streamlining operations.
Autonomous Vehicles
3D synthetic data can be used to develop and test autonomous vehicle solutions in a simulation environment, reducing testing and training times and lowering costs.
Ecosystem
See how our ecosystem is developing their own synthetic data applications and services based on NVIDIA technologies.
Synthetic Data Companies
Service Delivery Partners
Synthetic Data at NVIDIA
Use synthetic data generation applications on premises or on NVIDIA Omniverse™ Cloud.
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Omniverse Replicator
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Isaac Sim
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DRIVE Sim
Omniverse Replicator
Omniverse Replicator is an open and modular SDK that enables accurate 3D synthetic data generation (SDG) to accelerate the training and performance of AI perception networks.
Isaac Sim
Omniverse Replicator powers the synthetic data generation capabilities in the NVIDIA Isaac Sim™ robotics simulation application and can be used to generate synthetic data specific to training AI-based robots.
DRIVE Sim
NVIDIA DRIVE Sim™ leverages the capabilities of Omniverse Replicator to generate synthetic ground-truth data for autonomous vehicle (AV) training, testing, and validation.
Getting Started with Synthetic Data
Online Course
Learn How to Generate Synthetic Data to Train Computer Vision Models
Documentation
Synthetic Data Generation (SDG)
GTC Sessions
See How Developers are Generating Synthetic Data for Real-World Use Cases
See the Latest Synthetic Data News
Build SimReady Assets
Are you a technical artist that already knows 3D scripting behaviors, material creation, and lighting techniques?
Your skills are in demand by large companies paying top dollar trying to catch defective parts, train vehicles safely, track packages, and much more.
Discover Synthetic Data in NVIDIA Research
Learn more about research at NVIDIA and the latest publications on synthetic data in areas such as generative AI, computer vision, and more. Explore the research out of the NVIDIA Artificial Intelligence Lab led by Sanja Fidler for the latest in computer vision, machine learning, and computer graphics.
