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 ...

To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

Brazilian researchers have developed a methodology that uses remote sensing to map the impact of frost on corn crops. This reduces exposure to climate risks and uncertainty regarding agricultural ...

If you ask ChatGPT about the people of Florida and Tampa Bay, it will tell you that we’re smelly, lazy and somewhat slutty. That is the verdict — or, at least, the algorithmic assumption — buried ...

A growing procession of tech industry leaders, including Elon Musk and Tim Coo,k are warning about a global crisis in the making: A shortage of memory chips is beginning to hammer profits, derail ...

Artificial Intelligence] is everywhere,” professor and vice chair of research in the University of Wisconsin Department of Radiology, Dr. Christoph Lee, said. Currently, UW is participating in a multi ...

The Edison Awards, established in 1987, recognizes and honors the world’s most innovative new products, services, and business leaders. Named after Thomas Alva Edison, the awards celebrate ...

Two researchers advocate for new AI-based measures not because they offer measurement free from error, but rather because they avoid specific problematic forms of error linked to overreliance on ...

Tool uses remote sensing to reduce uncertainties regarding agricultural losses, contributing to public policy.

AI-powered spectral sensor performs machine learning during light capture, identifying materials and chemicals in real time ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...