In 2026, here's what you can expect from the AI industry: new architectures, smaller models, world models, reliable agents, ...

As AI moves from controlled experiments into real-world applications, we are entering an inflection point in the security ...

The latest offering in this area is the public availability of artificial intelligence (AI) models for use by both households and businesses. One major difference between this innovation and those ...

AI only creates lasting value when it is woven into the flow of work. Retail and CPG companies must redesign processes so AI ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

IBM has quietly built a strong presence in the open-source AI ecosystem, and its latest release shows why it shouldn’t be overlooked. The company has introduced two new embedding ...

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 ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Weather forecasting is getting cheaper and more accurate. An AI model named Aurora used machine learning to outperform current weather prediction systems, researchers report May 21 in Nature. Aurora ...

Abstract: Malware poses a significant threat to network and information system security, particularly in industrial Internet of Things (IIoT) environments, where embedded systems and edge devices ...