A new publication from Opto-Electronic Advances, 10.29026/oea.2023.230140 discusses photonic integrated neuro-synaptic core for convolutional spiking neural network. Brain science and brain-like ...

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 ...

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 ...

Two projects — one that maps the function of the brain’s neuronal network in unprecedented detail and another that combines robotics and light-based computer circuits to create safe self-driving ...

Spatially incoherent diffractive optical processors can handle data beyond non-negative values, potentially making them valuable in diverse scenarios, such as visual encryption and autonomous vehicle ...

A research team led by Prof. Qiming Zhang and Associate Prof. Haoyi Yu from the University of Shanghai for Science and Technology (USST) integrated miniaturized multilayer optical diffractive neural ...

(Nanowerk News) The deep neural network models that power today’s most demanding machine-learning applications have grown so large and complex that they are pushing the limits of traditional ...

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 ...

State-of-the-art neural networks depend on linear operations, such as matrix-vector multiplications and convolutions. While dedicated processors like GPUs and TPUs exist for these operations, they ...