Going Forward-Forward in Distributed Deep Learning

arXiv:2404.08573v1 Announce Type: new
Abstract: This paper introduces a new approach in distributed deep learning, utilizing Geoffrey Hinton's Forward-Forward (FF) algorithm to enhance the training of neural networks in distributed computing environments. Unlike traditional methods that rely on forward and backward passes, the FF algorithm employs a dual forward pass strategy, significantly diverging from the conventional backpropagation process. This novel method aligns more closely with the human brain's processing mechanisms, potentially offering a more efficient and biologically plausible approach to …

abstract algorithm arxiv computing cs.dc cs.lg deep learning distributed distributed computing environments hinton networks neural networks paper strategy training type