Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

Thick cloud cover can completely obscure the surface of the Earth from satellite view, while thinner haze and shadows distort ...

Isomorphic Lab’s proprietary drug-discovery model is a major advance, but scientists developing open-source tools are left ...

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness ...

With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...

University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a ...

The research team of Weihong Tan, Xiaohong Fang, and Tao Bing from the Hangzhou Institute of Medical Sciences, Chinese Academy of Sciences, proposed a ...

Deep Learning (DL) has emerged as a transformative approach in artificial intelligence, demonstrating remarkable capabilities in solving complex problems once considered unattainable. Its ability to ...

Abstract: Deep learning performs feature extraction through a series of data transformations. Convolutional neural networks (CNNs) are among the most representative methods in deep learning. CNNs ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...