Richard wrote:
What Rabinovich et al appear to do is to buy some mathematical
tractability by applying their idea to a trivially simple neural model.
That means they know a lot of detail about a model that, if used for
anything realistic (like building an intelligence) would *then* beg so
many questions that .... well, it would beg virtually *all* the
questions about what it takes to be intelligent. (I.e. Show me a great
supervised NN and I will show you a very big list of begged questions
about the intelligent functions that have to be in the "supervisor").
In other words, what they have done with it is something essentially
useless. I say that purely because of all those begged questions.
According to their papers, their detailed approach seems to be useful
for modeling some behaviors of insects and mollusks.
This seems about right, given the simplicity of their equations...
I agree that their detailed approach can probably not be scaled up to
deal with more complex brains. For the decision a mollusk makes as to
whether to snap its shell shut or not, you can write a simple
equation, and this may indeed be interesting as neurophysiological
math modeling ... but the comparable equations for the human brain,
even if they display the same generic phenomena of hyperchaos and
multi-lobed strange attractors and so forth, would be totally
infeasible to write down in any detail ... so the approach of detailed
differential-equations-modeling is inapplicable in the cognitively
interesting cases...
Physics-wise, this is not so philosophically different from the
inability of equational approaches that succeed for the 2-body problem
to scale up to the n-body problem...
-- Ben G
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