Maybe I'm missing something, but I don't see anything in your article that actually shows how to make a neural network without some sort of "grandmother coding" (e.g. in the "hidden layer").

I'm also curious to see how you consider connectionist networks to stack up against, say, the memory-prediction framework for neural organization. ISTM that "stuff happens in a distributed way across a hidden layer" says a lot less about what we should anticipate if we cut open a brain and watch it working.