AGI is one of those little goofy microtrends: so far as I can tell it's essentially a rebranding of Strong AI by soft computing reactionaries responding to AI getting dominated by domain specificity (otherwise known as "being successful"). To claim, as the grandparent appears to be doing, that AI is now properly called Artificial General Intelligence, is crackpottery at its finest.
Wake me up when AGI even appears on the first results page of a Google search for "AGI".
Did you really look into AGI, for example the past conferences or those projects, and conclude that it is just invaluable holistic mumbo-jumbo?
That is so unfair and inaccurate, I can't see how you can possibly be evaluating things rationally if you really came to that conclusion.
I think it's fundamentally the difference between soft bullshit and hard calculations. Everyone can talk about AI, or linguistics, or statistics (or any complex field) in very general, undefined and bullshitty terms.
But what we need, and what the machine learning guys are bringing is hard calculation - 1 + 1 = 2 or input data, get features and make decisions well above human abilities.
My question to all the fringe folks: Where's the beef? What have they done? Where are the automatic cars built on Chomsky's theories? Where are the talking robots from the AGI? What methods have the SENS people got? Are the singularity folks just leeches off gullible rich people - selling them a future and taking their cash in the process without providing any real value?
Chomsky's a pretty substantial walker.
> Every time I fire a linguist, the performance of the speech recognizer goes up.
-- http://en.wikipedia.org/wiki/Frederick_Jelinek
I still don't see Chomsky robots walking around, Chomsky translation translating my text to French or Chomsky AI driving cars. Nope - all Google/IBM/Microsoft/DARPA/Boston Dynamics/etc. AKA Hard science-engineers utilising statistics, not soft science blowhards.
Only thing I see Chomsky doing is talk - a lot.
The model probably doesn't have a great deal of relation to what happens inside folks heads - but it was stupidly useful for making computers do stuff though. Might be better techniques now - I don't know. But saying that it wasn't applicable practical work is basically ignoring the NLP stuff that was happening in the 80's and 90's.
(let alone the more obvious useful stuff for us geeky folk - the formal grammar stuff we use and think about for compilers. Chomsky Hierarchy, etc.)
And, I'm not enough of a historian of science to know, but it seems to me that the basic results Chomsky proved on Regular Languages and CFGs paved the way for the Hidden Markov Models (HMMs) that have been so effective in language understanding. Basically, the HMMs are the natural probabilistic extension of Regular Languages.
I'm not sure if Viterbi and the other developers of the basic HMM toolkit were directly influenced by Chomsky, or if state machines were just in the air. Certainly Chomsky's basic work in the late 1950s predated Viterbi's work in the 1960s.
Mathematicians aren't - you can prove their correctness over abstract planes and use them to for example run a hedge fund or a software company into trillions of revenue when making testable predictions in macro reality.
Theoretical physicists that use mathematics to make testable predictions are too. You can use them to also make electric engines, statistical extractors and accurate physical simulations that are corroborated with empirical evidence.
If the prediction is not testable, is unfalsifiable, is unreproducible, is not independent and is not supported by overwhelming evidence - it is bullshit - no ifs, buts or ands.
It can only be 'proved' in the 'contrived' world of pure mathematics... what bullshit!
The idea being, that you'd have to back pedal, and change your qualification. Which I could then use to apply to other fields, that you deem as 'quackery', and thus undo the foundation of your argument.
Instead, you just denied the reality of what you said... I didn't count on that. Well done.