Data compression in brain-like multimedia data bases

Self-growing autosophy data networks may also be used to design brain-like trainable general data bases in which the information is stored in a highly compressed format. Any portion of the text or image data is only stored once and is recycled in subsequent data storage. This will lead to reduction in the rate of memory increase as data bases become large since the more data is already stored, the less memory space is required to store additional units of data. The data is stored in a mathematical omni dimensional hyperspace. Access to any information is fast and independent of the database size. The system may be taught very much like a human child using grammatical language and without any conventional data processing or programming. Images are stored by showing them to a television camera or scanner and associating them with written text. Compared with conventional programmed data processing databases the new autosophers can store any type of data without any need for formats or frames. Such "Black Box" systems totally organize their own internal data storage to become more and more efficient as the database size increases.