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 ...

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

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, ...

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 ...

In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...

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

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

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

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.