Companies can’t avoid working with data, but management of that data can pose serious challenges. Customer and other personal data keep escaping, courtesy of breaches that surged 78% last year in the ...

The Department of Homeland Security and Chief Data Officers Council put out calls recently for products and insight on synthetic data generation. Government agencies are on the hunt for vendors and ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

Strict data privacy regulations have compelled companies to transition to using synthetic data, the ideal substitute for real data, containing similar insights and properties yet is more privacy-safe ...

In a recent study published in the journal Nature Medicine, researchers used diffusion models for data augmentation to increase the robustness and fairness of medical machine learning (ML) models in ...

In a time when health systems are struggling to gain meaningful insights from data – and simultaneously aware that safeguarding patient privacy is essential – synthetic data offers a lot of potential.

AI and ML algorithms rely heavily on vast data for training and development. However, the availability of high-quality, diverse, and secure data can be a significant challenge. In fact, upon not being ...

MIT researchers are pioneering a novel approach to train machine learning models by utilizing synthetic imagery, surpassing the efficacy of traditional methods relying on real images. The key to this ...