TechRepublic

Performance Evaluation of Error Back Propagation Algorithm for Non-Linear Classification and Function Approximation in VHDL Platform

The effect of variation of learning parameters on accuracy of the output and speed of convergence of the algorithm are presented. Improved speed of convergence without much change in accuracy was ...
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 ...
Quanta Magazine

Neuron Bursts Can Mimic Famous AI Learning Strategy

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI. Every time a human or machine learns how ...
EurekAlert!

Multiplexed neuron sets make smaller optical neural networks possible

(A) A traditional fully connected neural network. The layers are connected by black lines corresponding to weights. The neurons separately realize the summation and nonlinear activation functions ...
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 ...