Very, very roughly a neural network consists of a bunch of connected nodes that you propagate signals through. Each of those connections carries a weight that affects how the signal gets propagated through the rest of the network.<p>Let&#x27;s say a specific problem has only one very specific set of connections that matters. You&#x27;ll eventually add up with weights that reflects that, but that doesn&#x27;t prevent a lot of other connections from having weights set during training, but that may end up being cancelled out or reduced enough to have no meaningful impact whatsoever on the end result.