Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical ...

Most working professionals already understand that AI skills are no longer optional they are a career necessity.

Physical neural networks (PNNs) are a class of neural-like networks that make use of analogue physical systems to perform computations. Although at present confined to small-scale laboratory ...

Researchers in Sweden have developed a machine-learning approach that embeds the laws of physics directly into neural ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Machine learning models energy release during heavy-element formation, enabling faster simulations of neutron star mergers and kilonova signals.

The human brain, with its billions of interconnected neurons giving rise to consciousness, is generally considered the most powerful and flexible computer in the known universe. Yet for decades ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Researchers at the University of California San Diego and the Allen Institute for AI have built a climate emulator that ...

Using a novel simulation model based on machine learning, an international research team at GSI/FAIR has succeeded in gaining ...

Researchers from Skoltech and the Shanghai Institute of Optics and Fine Mechanics have developed an approach that helps optimize the parameters of a laser-plasma source of attosecond pulses—ultrashort ...

A machine learning-powered simulation is giving researchers a new window into the processes that create some of the universe’s heaviest elements.