From: Ramez Naam (mez@apexnano.com)
Date: Tue Nov 26 2002 - 10:11:56 MST
From: Anders Sandberg [mailto:asa@nada.kth.se]
> The issue here seems to be levels of modelling. In computational
> neuroscience we run into this all the time. We have good compartment
> models that mimic real neurons pretty throughly, but take a
> long time to run. So for large networks we instead use simplified
> neurons, where the simplifications become more and more radical
> as we scale things up. The important art here is to select the
> right level for the job, and the right amount of simplification
> so that you can trust the result.
I can buy that. But think about the nature of the results you get
from these simplified models. In other fields (and I'm guessing this
is true in comp. neuroscience as well) simplified models end up giving
sort of qualitative results that give you an idea for how the system
generally behaves, but not exact results that tell you what precisely
what output you'll get for a given input.
Now, combine this with the desire to use a swarm of assemblers to
build a car. We can only model a swarm of assemblers if we use many
many simplifying assumptions that strip out orders of magnitude of
complexity. As a result, all our simplified simulation can tell us is
that the swarm will probably build something car-like.
Or at least, this is the problem I perceive.
One way I do imagine out of this is sort of hybrid fabrication
techniques, where the overall manufacturing process is more of a
classical, macro-scale one of putting various subcomponents together
one by one in an assembly line, and assemblers are used to fabricate
the specific components or perhaps to actually do the work of
assembling the components, but only under the direct supervision of a
very top-down control system.
This sort of fabrication process would be effectively a successor to
current factory-based manufacturing techniques, but it could never be
used for the kind of bottoms-up, plant-a-seed-and-watch-a-car-grow
nano assembly that some dream about, and that has the greatest
potential for massive social change.
cheers,
mez
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