Artificial intelligence developers increasingly require large, diverse and accurately labeled datasets to train, evaluate and improve machine-learning systems. However, obtaining suitable real-world data can be expensive, time-consuming or restricted by privacy, security and regulatory requirements. Synthetic data generated through artificial intelligence models and simulation environments is...