The distinction between the actual brain and the computer model only disappears when the model is completely accurate
To save reading all of this lengthy post, my other responses to Jonathan are summarized: #2, #3 and #5 We can’t accurately describe these phenomena, let alone model them. Also, Chris has massively understated the differences between RAM and working memory. It would be cruel and severely diminish the capability of your fly. For instance, to make capacity vary you could some of your RAM unavailable sometimes. Why would you do that?
To assume that current simulations of the spreading activation of a neuron works with a lookup table – the current method – is accurate is to assume that we know all about how this addressing works. I assure you that we don’t. Some of my current work examines the effect of working memory load on inhibition (Following from but I should add that I’m not affiliated with them in any way shape or form). Are you trying to tell me that the amount of RAM available will affect how we traverse a neural network lookup table? Because then the difference between working memory (which we don’t really understand either) and RAM becomes extremely important.
Thus when Jonathan says « implement a neural network » does he mean a current neural network, in which case it isn’t really very much like the brain, and thus not in conflict with this article at all? Or does he mean implement an accurate model of all functional aspects of the brain? Because computers aren’t like that now and we have no evidence they ever will be.
The simple fact is that arguing that the brain is analogous to a Turing machine is a dangerous thing to do. More