History of artificial neural networks

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Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. While the computational implementations of ANNs relate to earlier discoveries in mathematics, their creation was inspired by biological neural circuitry. The first implementation of ANNs was the perceptron by Frank Rosenblatt. Despite the frequent claim that little research was conducted on ANNs in the 1970s and 1980s—the AAAI calling this period an "AI winter"—there was ongoing development of ANNs, especially connected to the development of specialized computers for simulating these networks. Later, advances in hardware and the development of the backpropagation algorithm, as well as recurrent neural networks and convolutional neural networks, renewed interest in ANNs. The 2010s saw the development of a deep neural network (i.e., one with many layers) called AlexNet. It greatly outperformed other image recognition models, and is thought to have launched the ongoing AI spring. The transformer...

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