ImageNet: Difference between revisions

On 30 September 2012, a [[convolutional neural network]] (CNN) called [[AlexNet]]<ref name=":0">{{Cite journal|last1=Krizhevsky|first1=Alex|last2=Sutskever|first2=Ilya|last3=Hinton|first3=Geoffrey E.|access-date=24 May 2017|title=ImageNet classification with deep convolutional neural networks|url=https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf|journal=Communications of the ACM|volume=60|issue=6|date=June 2017|pages=84–90|doi=10.1145/3065386|s2cid=195908774|issn=0001-0782|doi-access=free}}</ref> achieved a top-5 error of 15.3% in the ImageNet 2012 Challenge, more than 10.8 percentage points lower than that of the runner up. This was made feasible due to the use of [[graphics processing unit]]s (GPUs) during training,<ref name=":0" /> an essential ingredient of the [[deep learning]] revolution. According to ''[[The Economist]]'', "Suddenly people started to pay attention, not just within the AI community but across the technology industry as a whole."<ref name=economist/><ref>{{cite news|title=Machines 'beat humans' for a growing number of tasks|url=https://www.ft.com/content/4cc048f6-d5f4-11e7-a303-9060cb1e5f44|access-date=3 February 2018|work=Financial Times|date=30 November 2017}}</ref><ref>{{Cite web|url=https://qz.com/1307091/the-inside-story-of-how-ai-got-good-enough-to-dominate-silicon-valley/|title=The inside story of how AI got good enough to dominate Silicon Valley|last1=Gershgorn|first1=Dave|website=Quartz|access-date=10 December 2018}}</ref>