As I started reading I thought to myself "I told you 1000 times, it depends on the criteria". Reading on, I saw that it is precisely the criteria you use as a parameter. Well, I'd like to find out the programming language that makes the most money while giving immortality :) A little more seriously, if the criteria are cognitive, as they often are in the real world, you'd be digging yourself a hole too deep to get out of. On the other hand, if the criteria are domain-specific, relating to well-behaved domains, I am afraid we are heading towards tautologies and trivialities. Something like Mathematica would be optimal for algebra, analysis, gravity, mechanics etc (though what about instead of calculating a parachute drop actually measure a real parachute drop), for economics, psychology, necromancy most things would do equally badly, and for AGI all options have so far being worse than bad. Mind you, I am in the process of defining an AGI architecture not as a compression problem but as a distributed computation problem, and I would challenge you to answer the question:
Which programming language/mechanism would be ideal for calculating X as quickly as possible. where X, for the sake of argument, is just a/any "heavy calculation" without necessarily any of the anomalies of chaotic behavior, pi's infinite series etc. It is not that I expect intelligence to arise out of PDEs and integrals, rather I am asking which is the "perfect" distributed system for calculus, as I am expecting your answer to take the form of multipliers and other exotic units all converging in an addition pipeline. I still can't help thinking that the fastest way for parallel computations is the actual experiment, after all we have the 3/n body problem and a ton of mathematics OR just an experiment with n bodies in a field. With regards to a possible language for AGI, I don't see how you can do much better than a human language. Never mind Turing completeness, we have GI completeness here (except for that part of human language, perhaps 100% of it, that gets its meaning from its grounding, its grounding from its embodiment, and its embodiment from - god?) AT On Mon, Aug 27, 2012 at 10:44 PM, Russell Wallace <[email protected]> wrote: > On Mon, Aug 27, 2012 at 9:12 PM, Ben Goertzel <[email protected]> wrote: >> For domains in which one is concerned with recognizing large ensembles >> of weak patterns, the language one uses to represent patterns can make >> a big difference... >> >> Image analysis, genetic data analysis and financial prediction are >> contexts in which I've found this to be the case >> >> In these settings, if one does pattern recognition via automated >> program learning with an Occam bias, >> the underlying language relative to which the Occam bias is expressed >> makes a big difference... > > Absolutely, but these overheads are not constants - the computational > cost of a poor choice of representation language is typically > exponential. > >> From a different direction, consider Hutter's proof that AIXI-tl is as >> good as any other reinforcement learning system ... up to an arbitrary >> constant. > > Well, much violence is being done to the word 'constant' in this case. > Sure, f(N) is constant for a given N, but... :) > > > ------------------------------------------- > AGI > Archives: https://www.listbox.com/member/archive/303/=now > RSS Feed: https://www.listbox.com/member/archive/rss/303/14050631-7d925eb1 > Modify Your Subscription: https://www.listbox.com/member/?&; > Powered by Listbox: http://www.listbox.com ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
