An old guy with deep roots in the history of cryptography going back to the WW II intelligence agencies and banking industry invented the “magnetic ink” at the bottom of your checks when he was the architect of the Burroughs banking computers in Minneapolis. He was a friend of mine and provided me with a couple of insights regarding the connection between compression and cryptography when I brought The Hutter Prize to his attention. As it turns out, his first PhD student not only was Chinese, but became the director of the CCP’s industrial planning for computation. His PhD thesis? Compression. This is relevant because Algorithmic Information is measured by the smallest number of bits it takes to comprise a binary algorithm (machine binary language) that outputs whatever data one has available – and this is the best one can do to infer the causal structure of the world being observed. This is the job of the intelligence agencies.
That this doesn’t form the basis of the funding for machine learning in the present, despite the Hutter Prize having done so for over 15 years (and incorporates Algorithmic Information as the prize incentive) and has been out there in the published literature for over a half century of Moore’s Law is pretty strong evidence that not only the AI community has been lobotomized and therefore will continue to bark up the wrong tree so as to avoid genuine Intelligence, but so have the social sciences, since they continue to bicker about “causal inference” when the solution has been known for that entire half century. Suspecting some adversarial intelligence agency involvement in this lobotomization of not only the machine learning world but also the social sciences is not only reasonable, it is practically a requirement for one to be considered reasonable.
Here’s one of the last emails my colleague gave me permission to share publicly and it is directly relevant to Enigma:
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From: John97john@aol.com
Message-ID: c4f.12626d3.32282e90@aol.com
Date: Thu, 31 Aug 2006 08:22:40 EDT
Subject: Syntopticon
To: jabowery@gmail.com
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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-------------------------------1157026960
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