From: "Ben Goertzel" <[email protected]> >I think the environments existing in the real physical and social world are >drawn from a pretty specific probability distribution (compared to say, the >universal prior), and that for this reason, looking at problems of >compression or pattern recognition across general program spaces without >real-world-oriented biases, is not going to lead to real-world AGI. The >important parts of AGI design are the ones that (directly or indirectly) >reflect the specific distribution of problems that the reeal world presents >an AGI system. > >And this distribution is **really hard** to encapsulate in a text >compression database. Because, we don't know what this distribution is.
Suppose I take the universal prior and condition it on some real-world training data. For example, if you're interested in real-world vision, take 1000 frames of real video, and then the proposed probability distribution is the portion of the universal prior that explains the real video. (I can mathematically define this if there is interest, but I'm guessing the other people here can too, so maybe we can skip that. Speak up if I'm being too unclear.) Do you think the result is different in an important way from the real-world probability distribution you're looking for? -- Tim Freeman http://www.fungible.com [email protected] ------------------------------------------- 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=123753653-47f84b Powered by Listbox: http://www.listbox.com
