In 2012, Alex Krizhevsky, then a PhD student at University of Toronto under Geoffrey Hinton, won the annual ‘ImageNet’ image labelling competition by an impressive 10.8 per cent margin. His use of a neural network-based object classification algorithm would then trigger a major shift the way computers would relate to images and the physical world more generally. ImageNet is an image database first published by computer scientist Fei-Fei Li in 2009 and labelled primarily by Amazon Mechanical Turk workers. Its intention was to ‘map out the entire world of objects’ for the sake of training machine learning systems. The first winner of the ImageNet competition in 2010 achieved a labelling accuracy of 71.8 per cent.