Cardiometabolic syndrome arises from intricate interactions among metabolic, cardiovascular, behavioral, and environmental factors. The convergence of ...

The manufacturing and supply chain sectors faced major disruptions in 2025 due to geopolitical uncertainty, AI adoption challenges, and data issues, all of which are shaping priorities for 2026. Over ...

Outside of tightly controlled environments, most robotic systems still struggle with reliability, generalization and cost. The gap between what we can demonstrate and what we can operate at scale ...

The Department of Energy (DOE) has released specifications for 26 artificial intelligence (AI) challenges under its Genesis ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

Michelle Lee, PhD, unpacks how physical AI that integrate scientific reasoning with the wet lab will accelerate biological discovery.

The team used an AI method known as equation discovery to develop a model to simulate the interactions between small eddies—circular, vortex-like currents—and large-scale ones. These interactions are ...

AI agents can handle physics-based modeling complexity while engineers focus on design judgment and tradeoffs.

Leading Pittsburgh medical experts say three data-focused technologies are emerging in Western Pennsylvania hospitals, ...

The company has also built an AI-enabled robotic stacking system called AmbiStack that automates the packing of items onto pallets or in containers. Meanwhile, AmbiKit is a multi-robot kitting system ...

Vision language models can help robots create effective automation in chaotic environments, augmenting human capabilities.

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...