2008/10/17 Ben Goertzel <[EMAIL PROTECTED]>: > > > The difficulty of rigorously defining practical intelligence doesn't tell > you ANYTHING about the possibility of RSI ... it just tells you something > about the possibility of rigorously proving useful theorems about RSI ... > > More importantly, you haven't dealt with my counterargument that the posited > AGI that is "qualitatively intellectually superior to humans in every way" > would > > a) be able to clone itself N times for large N > > b) have the full knowledge-base and infrastructure of human society at its > disposal > > Surely these facts will help it to self-improve far more quickly than would > otherwise be the case... > > I'm not thinking about this so abstractly, really. I'm thinking, > qualitatively, that > > 1-- The members of this list, collectively, could solve algorithmic problems > that a team of one million people with IQ 100 would not be able to solve in > a feasible period of time > > 2-- an AGI that was created by, say, the members of this list, would be > architected based on **our** algorithms > > 3-- so, if we could create an AGI that was qualitatively intellectually > superior to **us** (even if only moderately so), this AGI (or a team of > such) could probably solve algorithmic problems that one million of **us** > would not be able to solve in a feasible period of time > > 4--thus, this AGI we created would be able to create another AGI that was > qualitatively much smarter than **it** > > 5--etc. >
I don't buy the 5 step plan, either. For a few reasons. Apologies for the rather disjointed nature of this message, it is rather late, and I want to finish it before I am busy again. I don't think there is such thing as an better algorithm for intelligence, there are algorithms suited to certain problems. Human intelligences seem to adapt their main reasoning algorithms in an experimental self-changing fashion at a sub concious level. Different biases are appropriate for different problems, including at the meta-level. See deceptive functions from genetic algorithms for examples. And deceptive functions can always appear in the world, as humans can create whatever problems are needed to fool the other agents around them. What Intelligence generally measures in day to day life is the ability to adopt other peoples mental machinery, for your own purposes. It gives no guarantee of finding new solutions to problems. The search spaces are so huge that you can easily lose yourself, trying to hit a tiny point. You might have the correct biases to get to point A, but that doesn't mean you have the right biases to get to point B. True innovation is very hard. It is not hard to be bayesian optimal if you know what data you should be looking at to solve a problem, it is knowing what data is pertinent. This is not always obvious and requires trial, error and the correct bias to limit this to reasonable time scales. Copying yourself doesn't get you different biases. You would all try the same approach to start with, or if you purposefully set it so that you didn't you would all still rate certain things/approaches as very unlikely to be any good, when they might well be what you need to do. Will ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=117534816-b15a34 Powered by Listbox: http://www.listbox.com
