AlexNet wins ImageNet challenge, igniting the deep learning boom
Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton's GPU-trained convolutional network won ILSVRC-2012 with a top-5 error of 15.3% vs. 26.2% for the runner-up, convincing the field that deep learning works.
Key facts
- ILSVRC-2012 top-5 test error: 15.3% (runner-up: 26.2%)
- ~60 million parameters, 5 conv + 3 fully connected layers
- Trained on two NVIDIA GTX 580 GPUs
- Used ReLU activations and dropout
- Paper presented at NeurIPS (NIPS) 2012
What happened
AlexNet crushed the ImageNet classification challenge; the team's startup DNNresearch was acquired by Google in 2013.
Why it matters
The single event most often cited as the start of the modern AI era: it established GPUs + big data + deep nets as the winning recipe and made NVIDIA central to AI.
Changelog
- 2026-09-29: created
Related events
- ImageNet dataset presented at CVPR 2009 ★★★★★
- LeCun applies backprop-trained convolutional nets to handwritten digits (LeNet) ★★★★
- ResNet: residual learning enables very deep networks ★★★★
Sources (2)
- paperImageNet Classification with Deep Convolutional Neural Networks (NeurIPS 2012)
- discussionWikipedia: AlexNet
id: 2012-09-30-alexnet · updated 2026-09-29 · open in the interactive timeline