Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

The study highlights a crucial distinction between symbolic and sub-symbolic decision-making. Symbolic decisions require ...

A recent study conducted by the University of Amsterdam (Amsterdam, Netherlands) and the University of Queensland (Queensland, Australia) developed a novel prioritization strategy that directly links ...

XRM microscopy, combined with machine learning, revolutionizes materials research by enhancing imaging techniques for failure ...

In the fast-paced field of High Performance Computing (HPC), the convergence of Artificial Intelligence (AI) and Big Data Analysis signals a groundbreaking ...

AI in agriculture is rapidly shifting from being a distant concept to a practical, transformative tool. But amid all the hype, the real story that has emerged doesn’t focus on the technology itself ...

Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

We speak to Cern principal scientist Archana Sharma about pattern recognition, machine learning and quantum technology.

At TC Disrupt 2025, the AI conversation goes deeper than just the latest models and discusses the difference between ...

This project performs exploratory data analysis (EDA) on a dataset of TV shows and web series, focusing on key attributes such as IMDB ratings, vote counts, and rankings. Tools & Technologies Python ...