The recently published 2025 Machine Learning Emotional Footprint Report from global IT research and advisory firm Info-Tech Research Group highlights the top machine learning platforms that help organ ...

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.

It's notoriously difficult to consistently measure the energy usage of AI models, but DARPA wants to put an end to that uncertainty with new "energy-aware" machine learning systems. … The Mapping ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

In an era where artificial intelligence drives critical business decisions, Nikhil Dodda emphasizes that maintaining machine learning model performance is as crucial as building them. Model deployment ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

What if artificial intelligence could turn centuries of scientific literature—and just a few lab experiments—into a smarter, ...

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...