InfoQ

Deep Learning Pioneer Geoffrey Hinton Publishes New Deep Learning Algorithm

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...
EurekAlert!

A backpropagation algorithm for mechanical neural networks (IMAGE)

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...
EurekAlert!

Not so simple machines: Cracking the code for materials that can learn

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...
Business Wire

NTT Research and Cornell Scientists Introduce Deep Physical Neural Networks

Deep neural networks are now pervasive in science and engineering. To train them to perform mathematical functions, such as image recognition, users rely upon a training method known as ...
Quanta Magazine

Artificial Neural Nets Finally Yield Clues to How Brains Learn

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...
Diginomica

Generative AI needs better context - you can't talk about Large Language Models without reverse neural networks and backpropagation

The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...
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Backpropagation From Scratch in Python

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! Parkinson’s Isn’t Just Bad Luck. Scientists Reveal It’s Largely Preventable—and the Culprit Is All ...