The weight patterns that convolutional neural networks develop are pretty familiar in many ways. For example, the first layer will generally end up with small-s

The weight patterns that convolutional neural networks develop are pretty familiar in many ways. For example, the first layer will generally end up with small-scale feature detectors, such as borders, gradients/color pairs and certain textures, at various scales and angles. Try an image search for "imagenet first layer" to see examples. I took the comment to mean "we have ourselves discovered certain filters being useful (e.g. https://en.wikipedia.org/wiki/Gabor_filter https://en.wikipedia.org/wiki/Gabor_filter), and the networks now also discover this same information".