Categories: 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.

Brain-inspired AI architecture could computing faster and far less power-hungry

Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.

June 24, 2026

In "AI/ML News"

o1’s Thoughts on LNMs and LMMs

December 14, 2024

In "FAANG"

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"

AI Generated Robotic Content