>>Ben Goertzel wrote: >> >> But the different trials need not be independent --- we can save the >> trajectory of each AI's development continuously, and then restart a new >> branch of "AI x at time y" for any recorded AI x at any recorded time point >> y. >> >> Also, we can intentionally form composite AI's by taking portions of AI x's >> mind and portions of AI y's mind and fusing them together into a new AI z... >> >> So we don't need to follow a strict process of evolutionary trial and error, >> which may accelerate things considerably ---- particularly if, as >> experimentation progresses, we are able to learn abstract theories about >> what makes some AI's smarter or stabler or friendlier than others.
It seems to me this will not reduce the complexity of the problem of AGI as a whole, if we're using a really meaningful measure of that complexity. It also seems that this trick will NOT accelerate evolution of the AGI, unless given *additional* space-time resources. Secondly, fusion of two trained AIs may be a very costly procedure. I'm beginning to study this topic and it seems that the complexity is generally polynomial with small exponents such as O(n^3) but with EXTREMELY large n's like 1 billion. I'm mainly studying ANNs, maybe other architectures are superior in this respect... YKY ____________________________________________________________ Find what you are looking for with the Lycos Yellow Pages http://r.lycos.com/r/yp_emailfooter/http://yellowpages.lycos.com/default.asp?SRC=lycos10 ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
