In-sensor computing could become a fundamentally new approach to the deployment of machine learning in small devices that must operate securely with limited energy resources, such as wearable medical ...

A ML-based probabilistic clustering approach for optimal CH selection based on residual energy, node density, and average network energy; A sleep scheduling mechanism to deactivate redundant nodes in ...

A new fabric-based touch sensor used machine learning to control mobile apps, video games and other devices while integrated into clothing. A new study from NC State University combines ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...

AI-powered tools are rapidly changing the automotive repair industry, shifting it from reactive fixes to predictive maintenance. Automakers and repair shops are using machine learning, sensor data, ...

Businesses can harness sensor and machine data with the generative AI speed layer. In partnership withKinetica Consider a supply chain where delivery vehicles, shipping containers, and individual ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

Intelligent organizations prioritize investments in machine learning and real-time data to improve decision making, accelerate revenue generation efforts, reduce operational expenses and protect ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

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 ...