Machine learning, with its ability to analyze large datasets and identify patterns, is particularly well-suited to address the challenges presented by the vast and complex data generated in ...

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 ...

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 ...

A trajectory (movie) is represented by a matrix X. This matrix is the input to a neural network, which detects the direction of time’s arrow. Credit: Seif, Hafezi & Jarzynski. The second law of ...

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 — 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 ...

A mathematics professor at The University of Manchester has developed a novel machine-learning method to detect sudden ...

Prefer Newsweek on Google to see more of our trusted coverage when you search. John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in physics on Tuesday for their contributions to ...

The Nobel Prize in physics has been awarded to John J. Hopfield of Princeton University and Geoffrey E. Hinton of the University of Toronto for discoveries and inventions that formed the building ...