Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

Atmospheric aerosols influence climate forcing, air quality, visibility, and human health, but their properties vary widely across space and time. Satellite instruments equipped with multi-angle and ...

By now, ChatGPT, Claude, and other large language models have accumulated so much human knowledge that they're far from simple answer-generators; they can also express abstract concepts, such as ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Small and dense but filled with vitally important neural fibers, the brainstem has been hard for brain imaging technologies to dissect.

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. The market price of risk is taken to be λ=0. Automatic differentiation is ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.