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The Approach Behind AlexNet: A Convolutional Neural Network for Deep Learning
AlexNet, developed by a team led by Alex Krizhevsky during his PhD, along with collaborators Ilia Sutskever and Jeff Hinton, introduced a groundbreaking approach using convolutional neural networks (CNNs) for deep learning. Although deep learning concepts had existed for decades, their practical application was hindered by the significant computational demands of training deep neural networks. The algorithms required excessive compute power, making them unfeasible for traditional computer architectures at the time. Predictions about achieving sufficient computational capabilities through advancements like Moore's Law seemed distant, as the necessary resources were likened to the grains of sand on Earth, highlighting the challenges faced in implementing this technology effectively.