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 ...

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 ...

STOCKHOLM (Reuters) -U.S. scientist John Hopfield and British-Canadian Geoffrey Hinton won the 2024 Nobel Prize in Physics on Tuesday for discoveries and inventions in machine learning that paved the ...

Two scientists have been awarded the Nobel Prize in Physics “for foundational discoveries and inventions that enable machine learning with artificial neural networks.” John Hopfield, an emeritus ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

STOCKHOLM — John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics Tuesday for discoveries and inventions that formed the building blocks of machine learning. "This year's two Nobel ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...

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 are being used more and more widely. However, they need a lot of training data to deliver good results. In industrial applications, this wealth of data is often not available ...

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...