Hi Jean, > I have tried your solution and could not find the mental concept to relate to > my thinking.
I forgot this inductive sorting skill must be learned gradually, like touch typing, at small scale before exomind conversion. > Do we think of a tree of knowledge first? I do not think so. And there are > memory systems that DO think of plethora of various things and increase human > memory capabilities. Yes, Textmind becomes a mnemonic system. The tree associates all one's info together, making explicit one's personal implicit prioritization of info. Doing so systematically is only possible with computer plus user algorithm. > How human think -- is nowhere defined and is vague. Human thinks how they > think and there may be as many versions as humans. The brain is plastic. It adapts easily to sync with a Textmind tree. This tree's complete thought algorithm is an improvement over native thought pattern. Computer and brain meet in the middle. That is cognitive cyborg first stage. Keyboard+screen is Brain-Computer Interface. The other complete thought algorithm is Pubmind, for longform content. But it doesn't work without Textmind. Other thought methods are even less complete, and thus more dependent on the Textmind foundation. For example, pure association and search retrieval benefits greatly from Textmind de facto spaced repetition and directory scoping. > Doug Engelbart has already envisioned how files could be stored, accessed, > hyperlinked, referenced and we do not use it in that sense today after how > many years? Exactly. To the extent he was correct, his ideas have been adopted. To the extent wrong, ignored. The main problem is sustaining long-term hybrid-intelligence text-mind sync. It requires a complete OODA algorithm. Engelbart doesn't think on this scale. David Allen's GTD tries to, but is limited by paper. One can always improve the crystallized knowledge of a PIMS by adding more metadata and links. That misses the point: fluid intelligence is more important. It tells which info is worth promoting to more expensive representations.
