The training of multilayer spiking neural networks (SNNs) using the error backpropagation algorithm has made significant progress in recent years. Among the various ...

State-of-the-art backpropagation-free learning methods employ local error feedback to direct iterative optimisation via gradient descent. Here, we examine the more ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...

Neural networks made from photonic chips can be trained using on-chip backpropagation – the most widely used approach to training neural networks, according to a new study. The findings pave the way ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

The method used to train a large language model (LLM). An AI model's neural network learns by recognizing patterns in the data and constantly adjusting its neurons to predict what comes next. With ...

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 ...