AK: Intelligence is anomalous, it is not like building a hut first and a 100-story skyscraper later, it is more like building a 100 dimensional skyscraper .
Cobblers. Please explain the 100 dimensions of how a slime mould - a real AGI - solves the problems of negotiating a maze. These problems are not complex. This is the nth example of how AGI-ers, having no philosophy of intelligence, and the problems to be solved, bury themselves in n-dimensional waffle and "complexity." Ditto an infant apparently does not begin by putting one brick haphazardly on another, but by constructing a 100-dimensional Lego skyscraper. Which of Ben's multiverses are you living in? On 17 July 2013 09:12, Anastasios Tsiolakidis <[email protected]> wrote: > > On Tue, Jul 16, 2013 at 11:25 PM, Jim Bromer <[email protected]>wrote: > >> not worrying about writing something that would be scalable to adult >> human level AGI. > > > > That's OK then, Matt is bound to make you honorary member of the "without > actually accomplishing anything" club. Just joking. > > Of course all kinds of simple learning have been tried for decades, like I > said mostly without the ambition to solve AGI, very often just to publish a > paper (and as I've noted before a multitude of authors of interesting > papers and dissertations ended up working in more or less unrelated > fields). Jan above is right that a lot of engineering knowledge does come > from simple exercises that we eventually discover if and how we can > eventually scale - I should point out however that intelligence is > anomalous, it is not like building a hut first and a 100-story skyscraper > later, it is more like building a 100 dimensional skyscraper . But what may > have been missed by a collective IQ of a million or a billion? I don't know > but in my outline of RiskAI, an intellect that first and foremost manages > risk in its environment trying to survive, I proposed a rather challenging > starting point for AGI: real time intelligence! The basic idea is that risk > becomes infinite if you are too slow, and then again you may always be too > slow for some environments and activities, in which case you stay closer to > your comfort zone where your reaction times are not a handicap, but still > they would have to be relatively fixed and consistent. > > Now, Jim, this is a perspective that at least guarantees you that you > don't fall in your complexity/recursive traps. Instead of coding learning > first and waiting for a program to respond later, you first make sure the > program responds, and then build learning around it. I am not going to lie, > this can be quite an engineering challenge, and frankly I think it is an > area that will see many breakthroughs, especially if you look at the > "real-time ecosystem", for example FPGAs and HPC where you could be > guaranteed very "thin" computing power like a million agents each running > for some milliseconds. You can of course arbitrarily choose the response > time on your hardware, even 10 minutes or whatever, but the idea is to > stick to whatever limit you chose. Then you can always claim that some > hardware engineering can speed your algorithm 1000x and make it suitable > for ordinary environments. > > AT > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <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-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
