Moshe,

I understand, but my hypothesis is that it's more feasible to let the
generic processes handle the tasks you mention (object completion, ambiguity
resolution, invariance under transformation) in the case of a 30-30 grid
than in the case of a 1000x1000 grid.

In each case *some* customization of the generic processes will be needed in
order to make them achieve these tasks.  But I believe that the amount of
customization needed is much greater for the 1000x1000 case than for the
30x30 case.

I suspect that:

* in the 30x30 case we can get away with some minor specializations and
customizations and then let the general cognition tools do the work, whereas

* in the 1000x1000 case we badly need a more complex hierarchical
architecture in which the lower levels are dealt with by very specialized
stuff, and the higher levels are more like the
mildly-specialized-general-cognition algorithms that are *all* you need in
the 30x30 case...

-- Ben


> > If a 30x30 pixel grid is what you mean by content-richness, then I do
> > intend
> > for Novamente to deal with *this* kind of content-richness in the fairly
> > near future (how near depending on the achievement of relevant funding,
> > blah
> > blah blah).  I believe that this level of richness doesn't require the
> > kind
> > of complex, specialized pre-filtering that human-eye-level richness
> > requires...
> >
> Urgh, the adjective applies to what goes on *inside*, not what comes in
> from the outside. If you just create 30x30 PixelNodes and let the generic
> processes do the rest, you don't have content-richness (or if you do, you
> have to learn *all* of it). Its a question of what kind of build-in
> support you have for stuff like the things I mentioned (resolving
> ambiguity, object completion, invariance under transformations, temporal
> patterns).. And yeah, I know novamente can recognize temoral patterns
> ;->...
>
> Moshe


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