From: Phil Goetz (firstname.lastname@example.org)
Date: Fri Sep 09 2005 - 11:31:50 MDT
--- Michael Wilson <email@example.com> wrote:
> Correct. When engineers design systems, they make extensive use of
> state relationships that act as compression functions, mapping a
> large range of input states onto a smaller range of output states
> (strictly, they enforce specific sharp or near sharp set constraints
> on the state of the cause/input and the state of the effect/output).
> fuzzy sets that aren't quite disjoint. But because we know that
> on_states is a very small subset of above_threshold, and that
> off_states is a small sharp subset of below_threshold, and that
> these two /are/ disjoint, we can string indefinite numbers of logic
> gates together and reliably predict the final state of any
> cycle-free network. Synapses are similar but less reliable.
A point for the people who believe that neurons are sloppy evolved
things that we can easily improve on:
Making this mapping onto output states consistent, clear, and
error-free requires a lot of engineering overkill. A neuron
operates at a few millivolts, and its output, as a result, is
"wrong" about 10% of the time. A silicon chip operates with
about a 10-volt difference between its two states, in order to
be almost error-free. We humans have gone from a reliability
of .9 to 1-10^-14 or whatever - about a 10% improvement - in
exchange for an increase in power requirements of 4 orders of
Because of the error rate of neurons, you need 1 or 2 orders
of magnitude more of them for reliable computation. But nature
still comes out 2 orders of magnitude ahead in terms of power
dissipation per gate. And that's what really counts.
Click here to donate to the Hurricane Katrina relief effort.
This archive was generated by hypermail 2.1.5 : Wed Jun 19 2013 - 04:01:09 MDT