Finally, the organizations that implement quantum-inspired techniques will have a headstart on quantum computing as the ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty.

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

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

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

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

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

Find out how machine learning identifies country-specific health system drivers shaping global cancer survival and highlights ...

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines. By Daniel Fusch Neel Somani, a ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Abstract: Federated learning is a distributed machine learning paradigm designed to facilitate collaborative model training while preserving user data privacy. However, in practical scenarios, data ...