How Synthetic Data is Accelerating Computer Vision

This article originally appeared in Hacker Noon. In the spring of 1993, a Harvard statistics professor named Donald Rubin sat down to write a paper. Rubin's paper would go on to change the way that artificial intelligence is researched and practiced, but its stated goal was more modest: analyze data from the 1990 U.S. census, while preserving the anonymity of its respondents. It wasn't feasible to simply anonymize the data, because individuals could still be identified by their home address, phone number, or social security number, all of which was crucial to the analyses that Rubin's colleagues wanted to perform. To solve the problem, Rubin generated a set of anonymized census responses whose population statistics mirrored those of the original data set.