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 ...

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

The approximate logic neuron model (ALNM) is a single neural model with a dynamic dendritic structure. The ALNM uses a neural pruning function to eliminate unnecessary dendrite branches and synapses ...

Neural networks can be used to classify data and make predictions. For example, you might want to predict the political party affiliation (Democrat, Republican, Independent) of a person based on ...

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 ...

Training a neural network is the process of finding a set of weight and bias values so that for a given set of inputs, the outputs produced by the neural network are very close to some target values.