Our team knows AI and synthetic data — now you can too!

Our customers have achieved 98+% accuracy in perception tasks with synthetic data alone. Our guided lessons will show you how!

• Learn our proven approaches developed from years of work with a diverse customer base.
• Work with new AI models and latest techniques.
  
• Build proficiency with simulation workflows and scenario design.
  
• Create Intentional, Information-rich synthetic data that is Indistinguishable from real world data (The Three I’s Framework).
• Experiment with different scenario parameters, data distributions, post processing tools, and more.
  
• Discover how varying scenario parameters can create optimal data sets that allow you to build robust AI models.

Exercise 1

Building Robust Object Detection

Object detection is a foundational task for most perception systems. Using simulation, learners generate data, train a model, and and locate an object in real-world imagery.

Exercise 2

Developing Object Detection with a New Twin

Learners create their own training simulation by downloading, promoting, and training on a new object from our Digital Twin Catalog. Additionally, they can learn to create and annotate their own images.

Exercise 3

Detecting Multiple Types of Objects

Most object detection functions require the AI model to correctly and consistently identify different types of objects, or classes. Learners train a robust AI model to detect and differentiate between multiple classes.

Coming Soon