As deep neural networks revolutionize machine learning, energy consumption and throughput are emerging as fundamental limitations of complementary metal–oxide–semiconductor (CMOS) electronics. This ...

Multimodal deep learning plays a pivotal role in supporting the processing and learning of diverse data types within the realm of artificial intelligence generated content (AIGC). However, most ...

EPFL researchers have published a programmable framework that overcomes a key computational bottleneck of optics-based artificial intelligence systems. In a series of image classification experiments, ...

Researchers have published a programmable framework that overcomes a key computational bottleneck of optics-based artificial intelligence systems. In a series of image classification experiments, they ...

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...

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 ...

Research on ONNs began as early as the 1960s. To clearly illustrate the development history of ONNs, this review presents the evolution of related research work chronologically at the beginning of the ...

Fiber-optic technology revolutionized the telecommunications industry and may soon do the same for brain research. A group of researchers from Washington University in St. Louis in both the McKelvey ...

A technical paper titled “Training neural networks with end-to-end optical backpropagation” was published by researchers at University of Oxford and Lumai Ltd. “Optics is an exciting route for the ...

Fig. 1 Neural array imaging system and its principle behind its ability to break the trade-off between aperture size, ffeld of view, and imaging quality. (a) The system consists of a metalens array, a ...