So in our analogy, there would be a feature map for every letter. These feature maps would then become the input for the second layer. In this layer, the CNN would spatially align and "stack" all those maps from the previous layer. This would allow the CNN to then look for short, specific sequences of letters in all the feature maps simultaneously. So the CNN would use a new set of filters to look for specific letters that are adjacent to one another in particular sequences. In our analogy, the second layer would look for places where the letters A, D,