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

Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...

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

Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the ...

Delos also uses its model to distinguish insurable properties in areas often redlined by traditional markets. McIntyre said ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

CSIRO researchers have used quantum machine learning to enhance semiconductor fabrication—a world-first that could reshape ...

At the behest of AMD, Sony created a QA team to analyze Project Amethyst's upscaling technology and constantly give feedback ...

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior ...

A critical privilege escalation vulnerability affecting Azure Machine Learning (AML) has been discovered by cybersecurity ...

In smart grid management, ML enables dynamic control of distributed energy sources, managing real-time energy flows and ...

Increase agricultural productivity in India using machine learning-based crop recommendation systems for improved yields and ...