A Primer on “Autosophy”
A new science of self-assembling structures
The new science of Autosophy tries to understand the enigma of self-assembling structures, such as chemical crystals, living trees or societies. These complex structures grow by themselves without human engineering or labor. A living tree, for example, starts from a tiny seed, which selects specific molecules from a random environment to build itself into a very complex structure without human help or supervision. The resulting structures are vastly more complex than any man-made structures. Autosophy research is not concerned with specific structures but rather with the underlying mathematical principles of these processes.
“Autosophy” challenges the very foundations of modern communication, computing, manufacturing, and mathematical physics. The word “Autosophy” is a combination of two Greek words: autos (self) and “sophia” (knowledge or wisdom), which together can be translated as “self-learning” or the understanding of oneself. Self-assembling structures may be either physical (crystals, living trees or societies) or imaginary data networks that grow like data crystals or data trees in electronic memories. The immediate application of this research includes Internet communication, lossless data compression, encryption, and data archiving. The second goal is to replace the programmed data processing computer with brain-like, self-learning, and error-proof “Autosopher”. This may evolve into self-learning, failure-proof, robots and eventually into true Artificial Intelligence and machine consciousness.
Autosophy research includes imaginary “data networks” and “Information Entities” which grow like data crystals or data trees in electronic memories. This goes far beyond our present day mechanistic view of established sciences. Examples are the DNA sequences in our genes and text stories in books. The DNA in our chromosomes is contained in a double helix made of individual interlocking DNA molecules. The information in the helix is not determined by the number of molecules or the length of the helix, but rather by the specific “Sequence” of the molecules. The sequence is an imaginary Information Entity, which determines what creature will be grown. It is the “sequence” which is propagated from generation to generation in the process of evolution. A “sequence” does not have weight or mass, neither generates nor consumes energy, and is not located in space-time being both everywhere and nowhere in the helix. A “Story”, likewise, is written in a book by a progression of serial symbols, including text characters, words, and sentences. The story does not have mass or weight, does not generate or consume energy, and is located both everywhere and nowhere in the book. And yet, the story is the very purpose of the book. By reading a book the story will copy itself into our mind, which may dramatically change our behavior. The story will propagate through retelling or reprinting through the generations.
Modern micro-electronics was based on the hypothesis that unseen particles, electrons or electron holes, can flow through doped semi-conductive silicon crystals to produce all the virtual miracles of modern electronics. A similar leap of faith is required for a hypothesis that imaginary data networks and Information Entities can grow in electronic memories to eventually result in machine consciousness and true Artificial Intelligence, which may be vastly superior to our own brain. On the way to that eventual goal we may greatly improve our entire communications infrastructure and replace the programmed data processing computer with self-learning, failure-proof archives.
Founded by Klaus Holtz in June 1974, the theory was first disclosed June 1975 in an application for Patent 4,366,551. In April 1977 a paper “Here comes the brain-like self-learning no-programming computer of the future” was presented at THE FIRST WEST COAST COMPUTER FAIRE in San Francisco. A session at the NORTHCON-91 conference in Portland Oregon “Learning Networks: an alternative to data processing” explained early applications. Already implemented applications include the V.42bis compression standard in modems and the tif and gif methods for lossless still image compression. A demonstration of Autosophy Video is available in a laptop computer. A Self-learning text database was built in 1988 to verify the theoretical predictions.