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 thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

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 ...

Microsoft’s recent Azure Open Source Day showed off a new reference application built using cloud-native tools and services, with a focus on Microsoft’s own open source tools. The app was built to be ...

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 ...