That was the key takeaway for me from this article. I didn't know of Fei-Fei Li's ImageNet contribution which actually gave all the other researchers the essential data to train with. Her intuition that more data would probably make the accuracy of existing algorithms better i think is very much under appreciated.
Key excerpt;
So when she got to Princeton, Li decided to go much bigger. She became obsessed with an estimate by vision scientist Irving Biederman that the average person recognizes roughly 30,000 different kinds of objects. Li started to wonder if it would be possible to build a truly comprehensive image dataset—one that included every kind of object people commonly encounter in the physical world.