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 ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

Floods are some of the most devastating natural disasters communities in the United States face, causing billions of dollars ...

The new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning ...

Machine learning boosters have trumpeted victories over Go players, as well as AI getting a taste for video games. On the ...

In a first, Australian scientists turned to quantum machine learning to model semiconductor design, outperforming classical ...

Researchers from The University of Texas at Austin used machine learning and artificial intelligence to develop new materials that could keep your house cooler and reduce energy bills.

Researchers at Tohoku University used machine learning potential to create large-scale models of tin (Sn) catalysts under ...

To transition from LLMs to AGI, we need to overcome several major limitations and introduce fundamentally new capabilities ...

Innovative AI techniques in cement formulation lead to eco-friendly mixes, significantly cutting emissions and improving ...

Intel is gearing up to introduce its next-generation Xeon processors called Diamond Rapids. These server CPUs will be built ...