On Tue, Jun 19, 2012 at 9:31 PM, Ben Goertzel <[email protected]> wrote:
> > There's a general fallacy that misleads many AGI people, of the following > form ... > > " > -- Capability or method X, if you could do it incredibly (i.e. > unrealistically) well, would enable arbitrarily great general intelligence > -- Simple versions of X, seem to lead to interesting "narrow AI" behaviors > THEREFORE... > -- By pursuing more and more complex versions of X, we can get high > levels (e.g. human-level) of real-world general intelligence > " > > In the case we're discussing here X = Prediction .. > > In other cases, X = logical reasoning, or pattern recognition, or > automated program learning, or simulation, etc. etc. > > Unfortunately, things just don't work that way ;/ ... > > ben > > I mostly agree too but the thing is that if you want to use all the above when they are well suited to a problem then you have to better describe the complicated circumstances where they could be employed adequately. This cannot be done through abstract representations and so you end up being stuck with different kinds of narrow solutions for different types of narrow (but adequately described) problems. However, I believe that the reality is that many of these seemingly narrow situations may hide a great deal of complexity (or at least a great deal of potential complexity) that we don't fully understand. I do, however, believe that significant breakthroughs in computing are still possible. Jim Bromer ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
