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 ...

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 ...

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, ...

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 ...

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.

The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...

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

Adaptive systems were supposed to simplify decision-making. Instead of hard-coded rules, engineers built models that could learn from data, respond to change, and improve over time. That promise still ...