Categories: AI/ML News

Mimicking human sleep as a way to prevent catastrophic forgetting in AI systems

A trio of researchers from the University of California, working with a colleague from the Institute of Computer Science of the Czech Academy of Sciences, has found that it is possible to prevent catastrophic forgetting in AI systems by having such systems mimic human REM sleep.

Artificial neural networks learn better when they spend time not learning at all

Researchers discuss how mimicking sleep patterns of the human brain in artificial neural networks may help mitigate the threat of catastrophic forgetting in the latter, boosting their utility across a spectrum of research interests.

November 19, 2022

In "AI/ML News"

Novel memristors to overcome AI’s ‘catastrophic forgetting’

So-called "memristors" consume extremely little power and behave similarly to brain cells. Researchers from Jülich, led by Ilia Valov, have now introduced novel memristive components that offer significant advantages over previous versions: they are more robust, function across a wider voltage range, and can operate in both analog and digital…

March 21, 2025

In "AI/ML News"

Brain-inspired learning algorithm realizes metaplasticity in artificial and spiking neural networks

Catastrophic forgetting, an innate issue with backpropagation learning algorithms, is a challenging problem in artificial and spiking neural network (ANN and SNN) research.

September 2, 2023

In "AI/ML News"

AI Generated Robotic Content