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 ...

As sensor data overwhelms the cloud, Innatera’s neuromorphic chips bring always-on, ultra-low-power AI directly to the edge. But how?

A recent white paper by a working group of the International Atomic Energy Agency (IAEA) provided a comprehensive overview of ...

Researchers developed a terahertz imaging platform that uses deep learning to separate chemical signatures from noise. The ...

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

From Deep Blue to modern AI, how chess exposed the shift from brute-force machines to learning systems, and why it matters AI ...

Dono.AI Inc. announced today that it has raised $6.5 million in new funding to accelerate its expansion of its property ...

A recent study on the development and validation of an AI-based framework for first-trimester preeclampsia risk assessment ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

A new topology-based method predicts atomic charges in metal-organic frameworks from bond connectivity alone, making large-scale computational screening practical.

Peter Grindrod CBE, Professor in Oxford University's Mathematical Institute and Co-Investigator of the Erlangen AI Hub, outlines why mathematics is ...