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

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

Some companies let you opt out of allowing your content to be used for generative AI. Here’s how to take back (at least a little) control from ChatGPT, Google’s Gemini, and more.

Below are some high-level guidelines and considerations for product managers looking to leverage MCP in their roadmap.

"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 ...

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

Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

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 ...

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