Eugene Leitl wrote:
> Absolutely. One of the major points of uploading is that you
> don't need to
> make your reconstruction verbatim (in the flesh), just run a number of
> (pretty smart) data filters over a (pretty large) dataset.
Hmm. Not exactly. At an absolute minimum level of understanding, you need a simulation program that can duplicate the interaction of all the molecules in the brain. That requires a very sophisticated program incorporating pretty much everything we now know about chemistry and non-relativistic physics, with some special corrections in the areas where quantum effects creep in. That is perfectly doable, of course, but it isn't just a 'data filter'.
It also isn't very practical - as I pointed out in a previous post, running it would require a computer faster than anything we are likely to get before the era of advanced nanotech. It should actually be much easier to do the upload at a higher level of understanding.
> > It is interesting, but I question the assumption that uploading will
> > automatically imply the ability to re-engineer minds..
> Agree. One could imagine some incremental morphing, but this
> seems to be
> an invasive enough process to blow away the personality we so
> laboriously set out to conserve during the upload.
The obvious first step in taming the computation problem is to move up to the cellular level. Once we really understand all of the details of how neurons work, it should be possible to write a program that can simulate the behavior of one. This is an ambitious exercise in molecular biology, but it can be done in the near future even under conservative technology projections.
Of course, once you have a computer simulation of a neuron there is no reason to stop there. Figuring out which behaviors are relevant to computation, and which are not, should also be just a matter of experimentation. Once you can weed out the irrelevant processes you should end up with something that can run on a few hundred MIPS at most.
At that point you could simulate an entire brain with something like 10^10 MIPS, which should be feasible by then. Of course, what you are running is now a fancy neural-net program, not an impenetrable blob of mysterious data. Figuring out how everything works is still a big job, but there is nothing impossible about it.
As for making improvements, well, the brain does appear to have specialized functional regions. Once you can map the connections between one region and the rest of the brain, you can improve that module in isolation. An evolutionary process is the obvious technique to use, but you could also use traditional programming techniques in well-understood areas. You don't have to have a complete understanding of everything in the brain to do this - you just need an approximate understanding of one specific region.
Billy Brown, MCSE+I