I think we're arriving slowly at the same point but from different directions Rhythm. One thing I would like to add though is that while we may be able to optimise an artificial brain and make it more efficient in terms of the processing power and memory required to perform the same functionality as that which we can find in real brains, we actually need several orders of magnitude more processing power. This is because we also need to perform artificial evolution (or some other kind of search technique) to configure our artificial brains.
When writing any adaptive controller there are always a load of parameters that I can't even guess at so I use an evolutionary algorithm to select it for me. Even something as simple as three layers of biologically plausible neurons will take me weeks of non-stop processing. An entire evaluation of a single neural network itself will take about a second or two.
This problem is worse if you want to create an intelligence that is situated in the physical world because mechanical movement is orders of magnitude slower. And unless it is a heavily constrained environment then it will need repeated evaluations otherwise you cannot tell the difference between a good solution that was tested in a hostile environment and a poor solution that was tested in an easy environment. There are tricks and techniques you can do to get around this to some extent, but doing so makes it even more important that an adaptive function works as generically as possible. This is why we need strong AI that adapts to its environment or the use that it is put to rather than aiming to superficially emulate behaviour.
When writing any adaptive controller there are always a load of parameters that I can't even guess at so I use an evolutionary algorithm to select it for me. Even something as simple as three layers of biologically plausible neurons will take me weeks of non-stop processing. An entire evaluation of a single neural network itself will take about a second or two.
This problem is worse if you want to create an intelligence that is situated in the physical world because mechanical movement is orders of magnitude slower. And unless it is a heavily constrained environment then it will need repeated evaluations otherwise you cannot tell the difference between a good solution that was tested in a hostile environment and a poor solution that was tested in an easy environment. There are tricks and techniques you can do to get around this to some extent, but doing so makes it even more important that an adaptive function works as generically as possible. This is why we need strong AI that adapts to its environment or the use that it is put to rather than aiming to superficially emulate behaviour.
