Nature

Backpropagation-free spiking neural networks with the forward–forward algorithm

Spiking Neural Networks (SNNs) offer a biologically inspired computational paradigm that emulates neuronal activity through discrete spike-based processing. Despite their advantages, training SNNs ...
Nature

Loss of plasticity in deep continual learning

Artificial neural networks, deep-learning methods and the backpropagation algorithm 1 form the foundation of modern machine learning and artificial intelligence. These methods are almost always used ...
Hosted on MSN

Backpropagation with automatic differentiation from scratch in Python

Learn how backpropagation works using automatic differentiation in Python. Step-by-step implementation from scratch. #Backpropagation #Python #DeepLearning Mike Johnson gives update on Jan. 6 plaque ...
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 ...
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 ...
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 ...