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.

Synthetic Data

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

Use synthetic data generation applications on-premises or on Omniverse Cloud.

Industrial Inspection

Synthetic data can be used for training AI models to catch defects early in the manufacturing process.

Image courtesy of Siemens

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.

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.

Sensors of an Autonomous Vehicle

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 lead by Sanja Fidler for the latest in computer vision, machine learning, and computer graphics.

Stay up-to-date on the latest NVIDIA Omniverse news.