MIT researchers designed a computationally efficient algorithm for machine learning with symmetric data that also requires fewer data for training than conventional approaches. Their work could inform ...

Compared with the secondaries market’s largely bottom-up approach to pricing portfolios, Oliver Gottschalg, professor of ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even ...

Recent research has shown that using machine learning is an efficient approach to look for these molecules. Though machine ...

From coding to hardware, LLMs are speeding up research progress in artificial intelligence. It could be the most important ...

AI has entered a new phase. It is no longer just about building larger models or accessing more data. Today’s competition ...

Supervised learning is a machine learning approach in which algorithms are trained on labelled datasets—that is, data that already includes the correct outputs or classifications. The model learns to ...

Artificial Intelligence is a controversial subject—though not for railroads when it comes to safety, if used properly. The ...

Believe it or not, Meta's AI investments made a meaningful difference to its advertising business in Q2 — it's just that those models aren't the kind that's got everyone, including the Social Network, ...

We use the Navier-Stokes equations every day, for applications from building rockets to designing drugs. But sometimes they ...

Bibek Bhattarai details Intel's AMX, highlighting its role in accelerating deep learning on CPUs. He explains how AMX ...