By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...

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 ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

On 5 February, the nine projects retained for co-funding in the context of the joint call for projects "High-Performance Computing and Artificial Intelligence" were announced by the Ministry of the ...

Scientists are sending millions of questions to AI weekly, speeding up research in physics, chemistry, and biology drastically ...

A neural network is a machine learning model originally inspired by how the human brain works (Courtesy: Shutterstock/Jackie Niam) Precision measurements of theoretical parameters are a core element ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...