Efficient machine learning inference is essential for the rapid adoption of artificial intelligence (AI) across various domains. On-chip optical computing has emerged as a transformative solution due ...

Optical computing holds promise for high-speed, energy-efficient information processing, with diffractive optical networks emerging as a flexible platform for implementing task-specific ...

A research team led by The Chinese University of Hong Kong (CUHK) has developed a novel integrated all-optical signal processor (OSP) to address the massive data transmission demands of ...

Researchers at Chalmers University of Technology have developed a machine learning system that learns ...

Blurry light from lens imperfections is a problem everywhere, from microscopes to telescopes to smartphone cameras. Using a ...

Studying physics can be very useful—even when it comes to machine learning. A digital "super-brain" with built-in knowledge ...

Neural networks are one typical structure on which artificial intelligence can be based. The term neural describes their learning ability, which to some extent mimics the functioning of neurons in our ...

A machine learning model has been developed that makes optical spectroscopy data easier and quicker to interpret. Researchers from Rice University (TX, USA) have developed a new machine learning ...

Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

AI-powered tiny optical device corrects distorted light in a single image, enabling sharper imaging for microscopy, astronomy ...