A team of Georgia Tech researchers has developed a new machine-learning framework that enables ...

Previous columns in this series introduced the problem of data protection in machine learning (ML), emphasizing the real challenge that operational query data pose. That is, when you use an ML system, ...

Implantable devices in the brain have been used for about 30 years to assist people with disabilities in completing motor ...

Forbes contributors publish independent expert analyses and insights. Rachel Wells is a writer who covers leadership, AI, and upskilling. If you're looking for a job that pays six figures, is always ...

Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train ...

Machine learning is powering most of the recent advancements in AI, including computer vision, natural language processing, predictive analytics, autonomous systems, and a wide range of applications.

AI-powered systems have swept through business, surfing a rising wave of occasionally justified hype. When they're good, they're really good—take, for example, a neural net designed to help Japanese ...

Machine learning is rapidly reshaping how we model molecules, and a growing body of work suggests that neural networks are not merely statistical ...

The U.S. Air Force needs to open up its high-end training ranges and exercises to artificial intelligence and machine learning as a way to both improve AI in combat and help the service refine its own ...