Thank you very much for your explanations and interesting discussion. I understand that TimeSpaceServer could be potentially used for solving mice and cat problem with complex box structure. What bother me, however is that treatment of space is different than in human cognition, too much secondary. Small child would first create concept of cat or mouse and their behavior (running, playing) based on images and videos (both seen directly or on computer screen). Only later they may form it into predicates like "every mouse is a mammal". Predators also learn this way about classification and behavior of their victims. On the contrary OpenCog's knowledge base is filled by interpreting text, which is much more advanced human ability. It is more difficult for a human to learn about something he or she cannot imagine, like learning about files or directories if you have never used a computer. One could make a test: take a text about mice and cats suitable for OpenCog and replace every noun, verb and adjective with words from some exotic language. Then give the text to another person and ask it to reason about "how many 鼠 a 猫 would 吃". This would be a difficult task for a human and may show if there are limitation of symbolic approach.
On the contrary - image and video processing is a very complicated task itself. It is also much easier to encode rules of logic directly than teaching it to AI of the intelligence level of 3-years old child or a dog. And such intelligent AI hasn't been built yet as far as I know. I guess there are other approaches to AGI which consider imitating animal intelligence the first step for making human-level intelligence. --Jan On Sat, Aug 27, 2016 at 3:00 AM, Ed Pell <[email protected]> wrote: > A company Deephi Techis offering a FPGA/memory chip on a board that could > be used for fast searches of text based db. http://www.deephi.com/en/ > > On Thursday, August 25, 2016 at 11:27:06 PM UTC-4, linas wrote: >> >> Hi Ed, >> >> Yeah, well, there is opencog (cog prime??) the abstract architecture, and >> opencog the actual code base. I presume that the abstract architecture can >> be mapped to various nifty algos. (e.g. scatter-gather map-reduce type >> broadcasting that you allude to) although figuring out how to do this well >> is not easy (we've tried). After that, how to get that into the current >> code-base is a rather different challenge. >> >> --linas >> >> >> -- > You received this message because you are subscribed to a topic in the > Google Groups "opencog" group. > To unsubscribe from this topic, visit https://groups.google.com/d/to > pic/opencog/y--WRlIxf3s/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > [email protected]. > To post to this group, send email to [email protected]. > Visit this group at https://groups.google.com/group/opencog. > To view this discussion on the web visit https://groups.google.com/d/ms > gid/opencog/95ffa632-5687-4e98-83f9-b7a7a2b6b01d%40googlegroups.com > <https://groups.google.com/d/msgid/opencog/95ffa632-5687-4e98-83f9-b7a7a2b6b01d%40googlegroups.com?utm_medium=email&utm_source=footer> > . > > For more options, visit https://groups.google.com/d/optout. > -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/opencog. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CA%2B2nBRvaReyy8P%2BWNXrQ1cejpuJn_Kn%3DXAEFaDSchnJ7pcw7Cw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
