PSS Ben I loved reading your blog. Pls keep it up. If you ever have time, let us know why, of the 3 different AGI approaches you entertained, you went with Novamente instead of the Hebbian neural net (and the theorem proving one)... us scruffies would like to know... is it just your mathematical bias/background or something more fundamental?
The Hebbian neural net approach seemed like it would be dramatically more computationally expensive, requiring a whole bundle of synapses to do what we can do with a single Novamente link. I.e., it's less natural for the von Neumann infrastructure we are stuck with at the moment. And, once you get beyond simple stuff, we don't know how the brain works so we need to invent stuff anyway, even in that plan (e.g. I have a scheme for doing higher-order logic in neural nets that involves feeding a dimensionally-reduced version of a neural net's connection matrix to the same network as an input vector ... but tuning that would take a lot of work, and there is no neuroscience to guide such work, at this point...) The theorem-proving approach I rejected largely because it seemed there would be basically no way to get significant funding for any incremental results. You'd be totally at the behest of government funding establishments. Yeah, once your system has proved the Riemann Hypothesis, you're golden ... but just making "the world's best theorem prover" isn't really going to get you anything but a few graduate students.... You can paid more -- and more critically, from more different sources -- for making a virtual big-scary-monster in a video game, than for making an automated prover of moderately difficult set-theory theorems. I am frightened of being reliant on a single funding source, as NSF is moody: some years it likes theorem-proving, some years not... Also of course in the theorem-proving approach one doesn't have human developmental psych to go on, in guiding the teaching process. One can map it into the new domain, but that's harder.... PSSS :) Google is doing narrow AI, Semantic Web & NLP, IBM is doing
WebFountain (i.e. also semantic web) and autonomous computing. So neither seem to be in AGI. Anyone knows what M$ is up to? They have hired quite a few smart CS *and* psych people too...
M$ Research is pretty much a traditional "big company" research lab, and their researchers publish extensively on their work. Lots of nice stuff on Bayes nets, computational linguistics and computer vision for example. None of these firms has started hiring up AGI researchers. When they do I'll be the first to let you know ;-) -- Ben ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=e9e40a7e
