Nature

Exploring spiking neural networks for deep reinforcement learning in robotic tasks

Spiking Neural Networks (SNNs) are often regarded as the third generation of Artificial Neural Networks (ANNs) because their functionality closely resembles that of the mammalian brain compared to ...
Nature

Convolutional neural network models describe the encoding subspace of local circuits in auditory cortex

Convolutional neural networks (CNNs) provide powerful models of neural sensory encoding, but their complexity makes it difficult to discern computations that support their performance. Here, to ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
Digital Journal

Neural networks, machine learning? Nobel-winning AI science explained

British-Canadian Geoffrey Hinton, known as a ‘godfather of AI’, and American John Hopfield were given 2024’s Nobel Prize for Physics – Copyright AFP Jonathan ...
Semiconductor Engineering

In Situ Backpropagation Strategy That Progressively Updates Neural Network Layers Directly in HW (TU Eindhoven)

A new technical paper titled “Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks” was published by researchers at ...