r/MachineLearning - [D] Neural Network Performance After Being Primed with Unrelated Data

I was reading this article on the New Yorker from 2017 on the use of CNNs in identifying cancer by image analysis. The CNN was trained using a data set of 130k images and performed better than experts. What I don't understand is the author's contention that this neural network performed better when it was pre-trained on data having nothing to do with the cancer lesion problem. Here is the author's quote: "There's one rather profound thing about the network that wasn't fully emphasized in the paper," Thrun told me. In the first iteration of the study, he and the team had started with a totally naïve neural network.