Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Rules-based automation (RBA) and learning are two training mechanisms in robotics. While there are many others, these are two ...

In 1930, a young physicist named Carl D. Anderson was tasked by his mentor with measuring the energies of cosmic ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...

JINAN CITY, SHANDONG PROVINCE, CHINA, January 19, 2026 /EINPresswire.com/ -- The global market for three-in-one busbar ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Financial word of the day: Heteroscedasticity describes a situation where risk (variance) changes with the level of a ...

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

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with projects that support AI development.

Non-terrestrial networks have their own challenges that cellular networks didn't have. Will AI help solve them dynamically?