I got the paper it was just a browser bug. Jim Bromer
On Wed, Jun 10, 2015 at 5:41 AM, Jim Bromer <[email protected]> wrote: > Thanks for the link to Ahmed and Hawkins' paper on sparse distributed > representation as it relates to HTM. It is interesting but it is > taking me some time to read it. I also have started the white paper on > HTM. I have seen that before but I never read it very carefully. > I always thought that any kind of conceptual vector system (like a > semantic vector system) would have to be n-dimensional and that it > really would not map well to three dimensions. And if you wanted to > use a simple vector to represent every basic concept (or every basic > concept zone) then it would have to be a really big vector which would > be, for the most part, blank. So the idea of a SDR does appeal to me. > I am skeptical of the idea that, 'since the HTM is based on > neuro-science then getting it to work is just a matter of finding the > right application details' intuition. If HTM is a good model then it > would be, at best, a crude model of a detail of the mind. However, it > is an interesting concept and it does seem to be based on neural > networks which have shown some effectiveness and it does seem feasible > that it could be effective in certain areas like reconstructing an > appropriate reaction to a kind of input based on partial inputs. This, > for example, would be more feasible for a temporal stream of input > where the interference is scattered across each 'frame' of the input. > (I think research into aspects of the theory, like this one, might be > worthwhile even for a skeptic.) > > I haven't seen how it uses the characteristics of combinatorics that > you mentioned. > I just lost access to the pdf of the paper for some reason. (Cornell > is either on to me or they are doing something.) > Jim Bromer > > > On Mon, Jun 8, 2015 at 9:35 PM, Matt Lind <[email protected]> wrote: >> Jim: >> >> Agree. An interesting concept in this regard is SDR (sparse distributed >> representation) which heavily relies on those characteristics of >> combinatorics. Numenta's HTM (hierarchical temporary memory) framework uses >> SDRs to model the brain's internal communication language. Interesting read: >> http://arxiv.org/abs/1503.07469 >> >> Matt >> >> >> >> 发自我的iPhone >> >> >> ------------------ 原始邮件 ------------------ >> 发件人: Jim Bromer <[email protected]> >> 发送时间: 2015年06月09日 02:50 >> 收件人: AGI <[email protected]> >> 主题: [agi] Combinatorics Is Important to Use With Discrete-Based AI >> >> I have not been that interested in combinatorics, graph theory, >> weighted reasoning, Bayesian methods and so on because I felt that >> these were all logic based and that the simplest way to develop an AGI >> application would be to stick to basics and only use simple forms of >> these methods if I needed them. I believed that there are certain >> discreet obstacles to advancing AGI at this time and solutions to >> these problems really needed to be found before any substantial >> advances could be made. However, now that I am starting to appreciate >> how combinatorics can help with discreet based systems and may even be >> essential to using logic effectively, I am, unsurprisingly, changing >> my view about this. >> >> So I recommend that anyone in this group who feels as I felt should >> start brushing up on combinatorics, graph theory and so on. >> >> Many of us know that computers are good at working with narrow results >> and this has produced major advances in ‘narrow AI’. Developers who >> worked with probability reasoning thought that their methods should be >> sufficient to overcome the narrow AI dilemma, but I haven’t seen that. >> (I do appreciate the many advances that AI has made and I do not >> totally accept the narrow AI dismissal, but on the other hand I am >> still amazed that AI programs do not seem to exhibit the ability to >> learn even in the simple ways that we would expect from toddlers.) >> >> So why are combinatorics so important for discrete symbolic AGI? Using >> logic as an example of a tightly defined discrete system, you can see >> that multiple solutions can be held in a tightly compressed formula >> string. What is more, subclasses of these different solutions can >> often be derived from a portion of the formula or from a simple >> analysis and rearrangement using portions of the formula. >> Combinatorics is one way we can get to this logical multiplicity as it >> may relate to logical sub-relations. Right now these methods are >> limited but there is no reason to expect that this method will be >> stuck with its current limitations. >> Jim Bromer >> >> >> ------------------------------------------- >> AGI >> Archives: https://www.listbox.com/member/archive/303/=now >> RSS Feed: https://www.listbox.com/member/archive/rss/303/27149679-a7635131 >> 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-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
