On Sat, Nov 29, 2008 at 1:51 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > To me the big weaknesses of modern probability theory lie in > **hypothesis generation** and **inference**. Testing a hypothesis > against data, to see if it's overfit to that data, is handled well by > crossvalidation and related methods. > > But the problem of: given a number of hypotheses with support from a > dataset, generating other interesting hypotheses that will also have > support from the dataset ... that is where traditional probabilistic > methods (though not IMO the foundational ideas of probability) fall > short, providing only unscalable or oversimplified solutions... > > -- Ben G
Could you give me a little more detail about your thoughts on this? Do you think the problem of increasing uncomputableness of complicated complexity is the common thread found in all of the interesting, useful but unscalable methods of AI? Jim Bromer ------------------------------------------- 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=120640061-aded06 Powered by Listbox: http://www.listbox.com
