Comment by krackers

The way he describes the model of neural nets almost reminds me of a decision tree, with the positive/negative poles and stuff. There's another quote from the article about the "textbook" intuition of convnets

>neurons generalize, work together, and build abstractions over layers. Somewhere along the way we overcomplicated that picture, but looking harder brought it back.

and it does seem that if what the article claims is true, then it really is that simple. To clssify e.g. fruit they first detect curves/shape, then the neurons downstream of say the "circle" detector may distinguish based on color, then the ones downstream of a specific color distinguish by texture, and so on. By the end, what you have are neurons that activate only on very specific combination of features, which map to each fruit.