MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

The tech tool has been subject to criticism and controversy since being launched by the department five years ago.

Data inconsistencies arise when formats, units, or collection practices change over time, undermining model reliability. Poor ...

AI is ubiquitous now—from interpreting medical results to driving cars, not to mention answering every question under the sun ...

An AI-powered model that analyzes electrocardiograms was able to accurately detect COPD early in internal testing and ...

For a project in Bangladesh, Prof. Mushfiq Mobarak and his team used machine-learning models applied to mobile phone records ...

This column focuses on open-weight models from China, Liquid Foundation Models, performant lean models, and a Titan from ...

Google Discover is largely a mystery to publishers and the search marketing community even though Google has published ...

AI fixes earnings forecasting when it expands coverage, standardizes signal extraction, and quantifies uncertainty. AI breaks forecasting when it creates false precision, synchronized expectations, ...

Every medication in your cabinet, every material in your phone's battery, and virtually every compound that makes modern life work started as a molecular guess, with scientists hypothesizing that a ...

It collects data on users’ range of motion and assess their balance to support them while they are standing. Read more at ...

In the narrative of Industry 4.0, the cloud has long been the protagonist. It promised infinite storage, massive computing power, and the ability to aggregate d ...