Summary: A new study utilizes Koopman operator learning to prove that certain complex, chaotic systems have fundamental ...

Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

AI’s growing use in investigations raises new legal challenges, from verifying evidence authenticity to constitutional rights ...

When can we trust the results we get from AI, and when is learning impossible? Researchers have shown that there are some ...

Quantum computers lack useful functionality without the right algorithms to facilitate their operation. Currently, there are ...

University of Wisconsin professor of soil science Jingyi Huang and data scientist Maria Oros worked over the summer on a new modeling tool for soil scientists. The pair used machine learning and ...

XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Google’s Willow quantum processor ran a specific algorithm 13,000 times faster than a classical supercomputer, according to ...

Every message, financial transaction, medical record, or government document encrypted today could remain stored ...

Interest in brain-computer interfaces is rising as it promises to help people with compromised neural abilities.

Southwestern Adventist University is expanding its academic offerings with a new Machine Learning Certificate Program designed to equip students with skills in one of the fastest-growing areas of ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...