Something about this reminds me of the 'Winning Ticket Hypothesis' in artifical neural networks: that some 'random' initializations prime a network far better for later faster learning. From https://arxiv.org/abs/1803.03635 - the abstract: Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of infere…
I guess I can see some parallel the way you describe it, but it is not that tight of an analogy IMO. Correct me if I'm wrong but the Lottery Ticket Hypothesis mainly means that, for many of our tasks, we start with needlessly huge networks, and thus a good portion of the learning process is just the network learning to "cope with the noise" from the extraneous connections Hence why the lottery ticket network (being a…
I think it is the other way around -- adult brain is a physically pruned version of baby brain. We start with lots of connections from everywhere to wherever and then lose a lot of them as we learn, while strengthening useful ones.