Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning. Machine learning is a computational approach that allows models to uncover ...

Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...

High-entropy alloys (HEAs) are rewriting the rules of materials science, and machine learning is accelerating their design. By predicting phase stability and performance from large datasets, ...

AI-powered platforms and curricula are transforming chemistry education by blending scientific rigor with interactive tools, personalized learning, and real-world applications. From undergraduate lab ...

Constraint programming combined with machine learning provides a robust framework for addressing complex combinatorial problems across diverse domains such as energy management, production scheduling ...

The study, titled “Teach AI What It Doesn’t Know,” published in AI Magazine, presents a detailed research agenda by Sean Du of Nanyang Technological University, focused on building reliable machine ...

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly integral to database management, driving new levels of automation and intelligence in how data systems are administered. Modern ...

A non-destructive method for determining the sex of chicken embryos before incubation using hyperspectral imaging (HSI) and ...

Inference is the technology benchmark standard for solutions that may be used to run inference on real-time market data.

SMILES-2026 brings together two strong schools of thought in artificial intelligence: Skoltech, the Russian university leading by number of publications at A* conferences, and Nanjing University, a ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper publishing April 22 in the Cell Press ...