Training AI models, or running large-scale 3D simulations, requires carefully labeled and diverse datasets. It’s also time consuming and often prohibitively expensive to gather and label datasets that may contain a few thousand to tens of millions of elements.
Synthetic data, generated by algorithms, contains annotated information such as images or text, and is used with real-world data to train AI models and create 3D simulations. Synthetic data generation (SDG) saves time and reduces costs.