1989
Yann LeCun and a team of researchers at AT&T Bell Labs achieve a breakthrough by successfully applying the backpropagation algorithm to a multilayer neural network to recognize handwritten ZIP code images.24 This is one of the first practical applications of deep learning using convolutional neural networks. Despite the limited hardware of the time, it takes about three days to train the network, a meaningful improvement over earlier attempts. The system's success in handwritten digit recognition, a key task for automating postal services, demonstrates the potential of neural networks for image recognition tasks and laid the foundation for the explosive growth of deep learning in the following decades.
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