Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Every crystal's shape is a mirror of the internal arrangement of its molecules, but the molecules in photoswitchable crystals ...

I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...

In the evolving world of data architecture and analytics, Gopala Krishna Subraya Pai stands out as a thought leader whose innovative integration of Artificial Intelligence (AI) with Dimensional and ...

Tension: Marketers expect consistent ad performance, but audiences process the same message with decreasing intensity over ...

Machine learning is helping neuroscientists organize vast quantities of cells’ genetic data in the latest neurobiological cartography effort.

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

A setback in growing light-responsive crystals led UB chemist Jason Benedict and his team to a novel method for mapping molecular arrangements.

The signals that drive many of the brain and body's most essential functions—consciousness, sleep, breathing, heart rate and motion—course through bundles of "white matter" fibers in the brainstem, ...

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