The models are designed to predict someone’s risk of diabetes or stroke. A few might already have been used on patients.

Security professionals can recognize the presence of drift (or its potential) in several ways. Accuracy, precision, and ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

Cirrascale runs on-prem Gemini on a Dell-made appliance running Intel and Nvidia CPUs and GPUs but doesn’t use Google’s ...

By combining the efficiency of a Mixture-of-Experts architecture with the openness of an Apache 2.0 license, OpenAI is ...

The ability to collect data from electronic medical records, medical images, devices, diagnostics, wearables and apps means that more real world data (RWD) is available to be analyzed and derive ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

Large language models can transmit harmful behavior to one another through training data, even when that data lacks any ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

The Beeck Center for Social Impact + Innovation at Georgetown University identified six archetypes of chief data officer ...

If you wandered the trade show floor at the American Baseball Coaches Association convention in Washington, D.C. this past January, it was impossible to miss the shift. Technology booths sprawled ...