What advantage does synthetic data provide in training AI models?

Synthetic data offers significant advantages in training AI models, particularly in terms of privacy and security. Using synthetic data allows organizations to create datasets that mimic the statistical properties of real data while ensuring that no real personal or sensitive information is shared. This is crucial in industries such as healthcare, finance, and law, where data privacy regulations often restrict the use of actual datasets containing sensitive information.

With synthetic data, researchers and developers can train their models without the risk of leaking confidential information, thus enabling them to comply with legal and ethical standards while still conducting valuable research or developing new technologies. This aspect not only enhances the safety of the data used but also fosters innovation, as it opens up avenues for training AI models where using real data would be impractical or forbidden.

The other options, while they may have some merit in specific contexts, do not encapsulate the core advantage of synthetic data compared to real data related to privacy and risk management.