Scripps Research scientists used a graphical neural network-based structure building tool, ModelAngelo, to discover monoclonal antibodies (bottom) from polyclonal antibody responses produced after ...

Abstract: The principal innovative contribution of this study resides in the introduction of a category of fractional delayed large-scale neural networks characterized by intricate topological ...

The applications of neural network models, shallow or deep, to information retrieval (IR) tasks falls under the purview of neural IR. Over the years, machine learning methods-including neural networks ...

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...

Hot on the heels of apparent confirmation of a monstrous 32 GB RTX 5090 GPU from Nvidia comes news that the world's most valuable company might be plotting a major AI-enhanced upgrade that brings ...

Over the past two decades, new technologies have helped scientists generate a vast amount of biological data. Large-scale experiments in genomics, transcriptomics, proteomics, and cytometry can ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

Theoretical physicist John Hopfield is one of the winners of the 2024 Nobel Prize in Physics. Theoretical physicist John Hopfield is one of the winners of the 2024 Nobel Prize in Physics. In 1982, in ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...