Competition Makes Big Datasets the Winners

If there is one dataset that has become practically synonymous with deep learning, it is ImageNet. So much so that dataset creators routinely tout their offerings as "the ImageNet of …" for everything from chunks of software source code, as in IBM's Project CodeNet, to MusicNet, the University of Washington's collection of labelled music recordings. The main aim of the team at Stanford University that created ImageNet was scale. The researchers recognized the tendency of machine learning models at that time to overfit relatively small training datasets, limiting their ability to handle real-world inputs well. Crowdsourcing the job by recruiting recruiting casual workers from Amazon's Mechanical Turk website delivered a much larger dataset.