Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need ...

The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

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

image of Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Credit: ...

Parts of the brain not traditionally associated with learning science become active when people are confronted with solving physics problems, a new study shows. The researchers, led by Eric Brewe, PhD ...

Think about a weighing scale. You know that it’s going to tell you how much you weigh when you step on it, and that’s probably it. To reach that conclusion you’re mostly using the occipital cortex, in ...

Harnessing data to discover the underlying governing laws or equations that describe the behavior of complex physical systems can significantly advance our modeling, simulation and understanding of ...

A new study showed that, when confronted with physics problems, new parts of a student's brain are utilized after receiving instruction in the topic. Parts of the brain not traditionally associated ...