The Foundations of AI Are Riddled with Errors

April 12, 2021

(Wired) – The current boom in artificial intelligence can be traced back to 2012 and a breakthrough during a competition built around ImageNet, a set of 14 million labeled images. In the competition, a method called deep learning, which involves feeding examples to a giant simulated neural network, proved dramatically better at identifying objects in images than other approaches. That kick-started interest in using AI to solve different problems. But research revealed this week shows that ImageNet and nine other key AI data sets contain many errors.