The process of de-identifying test databases can be approached in a variety of ways, and we’re often asked how our approach differs as compared to others. In this article, we’ll explore how our ...

Data models are used to represent real-world entities, but often have limitations. Avoid common data modeling mistakes for data integrity.

Securing this environment requires moving beyond static roles, perimeter defenses and after-the-fact monitoring. Organizations need data-centric security that embeds protection at the source, adapts ...

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, adaptability and fairness.

Confidentiality, to a lesser extent, and integrity, to the greatest extent, are the most important considerations with AI ...

While not a silver bullet solution to attribution, a data-driven model provides better insights for advertisers. Learn more here.

"Model collapse is a degenerative process affecting generations of learned generative models, in which the data they generate end up polluting the training set of the next generation," Shumailov's ...

How does deploying an aircraft carrier affect the future readiness of the fleet? A new data-modeling tool aims to predict it. (MC3Hannah Kantner/Navy) When it’s time to make a decision about ...