In recent years, artificial intelligence technologies, especially the machine learning algorithms, have made great strides. These technologies have enabled unprecedented efficiency in tasks such as ...

Convolutional Neural Networks (CNNs), with its exceptional image recognition capabilities, have performed outstandingly in the field of AI and notably within platforms like ChatGPT. Recently, a team ...

Optical neural networks may provide the high-speed and large-capacity solution necessary to tackle challenging computing tasks. However, tapping their full potential will require further advances. One ...

An AI neural network that uses light instead of electricity. Optical neural networks (ONNs) offer the potential for higher speed because regular chips can only trigger a limited number of transistors ...

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 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 ...

AI models are power hogs. As the algorithms grow and become more complex, they’re increasingly taxing current computer chips. Multiple companies have designed chips tailored to AI to reduce power draw ...

As part of this week’s SPIE Optics & Photonics conference program Emerging Topics in Artificial Intelligence, Asst. Prof. Logan G. Wright, of Yale University, presented an invited paper, entitled ...

The idea of optical computing—the use of photons instead of electrons to perform computational operations—has been around for decades. However, interest has resurged in recent years; the potential for ...

The deep neural network models that power today’s most demanding machine-learning applications are pushing the limits of traditional electronic computing hardware, according to scientists working on a ...