In 1986, three scientists improved backpropagation, making neural networks learn effectively from data

A groundbreaking 1986 technique called backpropagation revolutionized artificial intelligence, enabling computers to learn ...
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 ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
Android Police

OpenAI Microscope: The neural visualization interface explained

Ryan Clancy is an engineering and tech (mainly, but not limited to those fields!!) freelance writer and blogger, with 5+ years of mechanical engineering experience and 10+ years of writing experience.
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 ...
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 ...
EurekAlert!

Team develops high-speed, ultra-low-power superconductive neuron device

Image is a microphotograph of the fabricated test circuit. Continuous single flux quantum signals are produced by the clock generators at frequencies ranging from approximately 10 GHz to 40 GHz. Each ...