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

A digital innovation initiative about fault anomalies has been selected as one of the first projects for the new Microsoft AI ...

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

Herein, a hand-drawing paper-based bipolar electrode (BPE) electrochemiluminescence (ECL) platform for M.SssI methyltransferase (M.SssI MTase) assay was proposed via employing high electrocatalytic Pt ...

Detecting botnet threats has been an ongoing research endeavor. Machine Learning (ML) techniques have been widely used for botnet detection with flow-based features. The prime challenges with ...

Artificial intelligence (AI) or machine learning (ML) based spatial/temporal-domain beam prediction was studied by Release-18 and is currently being specified by Release-19, in the 3rd Generation ...

The Large Hadron Collider is one of the biggest experiments in history, but it’s also one of the hardest to interpret. Unlike ...

While AI startups are now using first-party evaluators or contracted second parties to test their models, opening the testing ...

This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

Designing, building, and applying new technologies—especially those that include artificial intelligence—can be a double-edged sword: powerful and enabling on the one hand, but potentially biased and ...

More information: Zhenghao Yin et al, Experimental quantum-enhanced kernel-based machine learning on a photonic processor, Nature Photonics (2025). DOI: 10.1038/s41566-025-01682-5 ...