Turbulence, temperature changes, water vapor, carbon dioxide, ozone, methane, and other gases absorb, reflect, and scatter sunlight as it passes through the atmosphere, bounces off the Earth’s surface ...
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 ...
Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework ...
AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...
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 ...
John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in physics on Tuesday for their contributions to machine learning. Their research, which draws from statistical physics, helped ...
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 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 ...
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