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 ...

Scientists have begun applying machine learning tools to nuclear physics challenges. In the past few years, a flurry of machine learning projects has come online in nuclear physics, and researchers ...

The Nobel Prize in Physics was awarded to US scientist John Hopfield and British-Canadian researcher Geoffrey Hinton for their work in the field of machine learning, the Royal Swedish Academy of ...

The 2024 Nobel prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their work on artificial neural networks and the fundamental algorithms that let machines learn, which are key ...

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 ...

A new review in Nature chronicles the many ways machine learning is popping up in particle physics research. Experiments at the Large Hadron Collider produce about a million gigabytes of data every ...

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their foundational work in artificial intelligence. Hinton, known as the godfather of AI, is a dual citizen of Canada and Britain, ...

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 ...

Today, solar energy provides 2% of U.S. power. However, by 2050, renewables are predicted to be the most used energy source (surpassing petroleum and other liquids, natural gas, and coal) and solar ...

A schematic illustrating how a neural network is used to match data from scanning tunneling microscopy to a theoretical hypothesis. Credit: Cornell University Understanding electrons' intricate ...