As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Over the past decades, computer scientists have developed increasingly advanced artificial intelligence (AI) systems that ...

AI is ultimately a story about selfhood—and the answer will not be found in the machine, but in what mindful awareness allows ...

The human brain is an astonishing organ, as any neuroscientist can attest. And its ability to collect, store, analyze and use information is intriguing to physicists, engineers and computer scientists ...

Fuzzy neural networks and systems represent a synergistic integration of fuzzy logic and artificial neural networks, aiming to encapsulate human-like reasoning within powerful learning frameworks. By ...

Neural networks have emerged as powerful tools in the field of neutron spectrometry and dosimetry by offering non-linear, data‐driven approaches to reconstruct complex neutron energy spectra and ...

Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human ...

Opportunities in the hardware AI market include rising edge device deployment, demand for low latency processing, scalable AI infrastructure, and energy-efficient AI chips. Trends like edge AI ...

The future of AI points toward systems that are more general, adaptive, and integrated. Artificial General Intelligence, or ...

The foundation of an AI strategy is about vision, drivers and risks. It should focus on the essence of what an organization ...