I haven't looked at this code, but as a guess, a good NN could learn color names rather than having them explicitly defined, it could learn to compensate for lighting and white balance in photos, and it could recognize which color in a multi-color scene is the "main" color.

I would assume it's a practical (although not entirely useful) example of a hopfield network. If you look at the wikipedia page for it[1] there is little to no information on what you would use it for, seeing an example of practical usage is great for figuring out other practical applications for a hopfield network.

[1]:http://en.wikipedia.org/wiki/Hopfield_network

It reminds me of the brain.js color contrast demo (https://harthur.github.io/brain/). Perhaps it was inspired by that.

Yeah, I really don't think so, maybe an SVM would be more adequate for this case?

It's pretty much linear and 3-dimensional (r, g, b values) you don't need a complicated structure to read that