This email is from a late colleague who developed the zero address architecture for Burroughs, written to me shortly after the announcement of The Hutter Prize for Lossless Compression of Human Knowledge. If anyone knows how to get in contact with Jun Gu, let me know. I've followed up all the leads left in the West and come up with nothing but dead ends in the PRC and Hong Kong:
[email protected] Aug 31, 2006, 7:22 AM to me Jim, Syntopticon is the Britannica encyclopdedia of ideas, and the Syntopticon itself is the (one small volume) codex cross referencing all the great ideas of mankind contained in all the many other books of this reference system. I have an old copy and it is the size of the Britannica encyclopedia (ie an 8' long collection of big books). The importance of Syntopticon in the Hutter competition is that expression of ideas in different natural languages is a very different proposition. Since an idea in Chinese is typically represented by one or a few symbols, and that same idea in English may take several pages, there is a huge difference to start with in the effectiveness of searches in Chinese or English. There is also a difference in the size of the database containing say a Chinese version of Syntopticon or an English version. And a much greater difference in the effectiveness of doing automated (programmatic) searches in Chinese or English. But from the perspective of doing analyses on these databases (especially if one represents say Wikipedia in Chinese), AND I do my vector fusion conversion of that Chinese database to translate (and further compress) those symbols into an analytically tractable form, the analysis of ideas is a vastly different problem than if one attempts to do this all in English. Searches are certainly one analytic process of major interest in natural languages; drawing conclusions, making predictions, and drawing inferences are other less investigated processes. My PhD graduate student Rok Sosic's thesis was on software that understands what it is doing (title: The Many Faces of Introspection, Utah, 1992). His poem summarizing his thesis was: *The box is a secret, knotty, black It's so complex that I've lost track. If somehow it's made reflective, The box will be much more effective*. Computerdom does not have a lot of art in inference engines (making predictions). The most effective inference engine that I know of is the software done for Colossus, Turing's code breaking "computer" of WWII. The Brits still treat that software as classified even though the hardware has been declassified for years. So far as I know, nobody outside of UK knows the details of that software. My point here is that drawing understanding from natural languages is a relatively small art practiced mostly by cryptoanalysts. And my further point is that the natural language of interest (be it English, Chinese, Mayan or ...) has a major influence on how one (person or program) goes about doing analyses and making inferences. >From a practical perspective, the Hutter challenge would be much more tractable for at least me if I could do it in Chinese. My first PhD student was Jun Gu who is currently Chief Information Scientist for PRC. His thesis was on efficient compression technologies. If you wish, you can share these thoughts with whomever you please. Bob Johnson Prof. Emeritus Computer Science Univ. of Utah ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T6886ccc561eb3cf3-Mf97515246a8237e199fa6fc2 Delivery options: https://agi.topicbox.com/groups/agi/subscription
