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

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

Physics AI engineering simulation tools reached production at General Motors this week, cutting a two-week aerodynamics cycle ...

Two pioneers of artificial intelligence—John Hopfield and Geoffrey Hinton—won the Nobel Prize in physics Tuesday for helping create the building blocks of machine learning that is revolutionizing the ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

AI has started to emerge as one of the most effective technologies being used in cosmology lately. The power of machine ...

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 ...

In developing drugs using a platform that joins physics with machine learning, Schrödinger sees more than a passing resemblance to the studio whose Toy Story and other computer-generated movies ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

The numerical simulation of physical models is prevalent in science and engineering. These models mathematically represent a physical system, typically by partial differential equations (PDEs) or a ...