Home; Articles; Design of spike-timing-dependent plasticity synapses based on CoPt-SOT device and its application in all-spin spiking neural network ...

An spiking neural network (SNN) classifier is an attractive option for ultra-low-power intelligent internet-of-things (IoT ... Wang D, Kim SJ, Yang M, Cerqueira JP, Kang J, Jung S, Kim S and Seok M ...

Language models typically use modern deep learning methods called neural networks, but Eshraghian is powering a language model with an alternative algorithm called a spiking neural network (SNN). He ...

While neural networks (also called “perceptrons”) have been around since the 1940s, it is only in the last several decades where they have become a major part of artificial intelligence.This ...

Creating an optimized neural network architecture is crucial for achieving high performance. “I think it’s going to continue with the trend toward larger models, but more and more they will be ...

Here’s an unusual concept: a computer-guided mechanical neural network (video, embedded below.) Why would one want a mechanical neural network? It’s essentially a tool to explore what i… ...

Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now the MIT spin-off is revealing several new ultraefficient models.