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, ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

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 ...

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

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