When reading about deep learning I often come across the rule that deep learning is only efficient when you have large amounts of data at your disposal. These statements are generally accompanied be a figure such as this:
![Deep learning and big data](https://cdn-images-1.medium.com/max/1600/0*GTzatEUd4cICPVub.)

The example (taken from https://hackernoon.com/%EF%B8%8F-big-challenge-in-deep-learning-training-data-31a88b97b282 ) is attributed to a 'famous slide from Andrew Ng'. Does anyone know what this figure is actually based upon? Is there any research that backs up this claim?