Inside the mind of the machine

I have been doing AI like I do everything else. I start with the assumption that it is wrong and must be fixed. That doesn't mean that it isn't true, it just means that I am looking for new ways to implement the same effect that may be more usable. You can't get to a new place by following the path that has been travelled many times. At some point you must take a left or right into the unknown to explore.
In the process and with the experience that I have, it seems that there is a correlation between AI, neurophysiology, computers, math, and logic. It can't be made without knowledge of all the subjects. Shakespeare, Ludwig van, Mozart, or DaVinci would have appreciated this fact almost immediately. I can even make a concerto that explains AI in music. I am listening to "Fur Elise" by Ludwig right now and it speaks volumes of information without a single word.
It makes many things clear that were formerly hidden. It is possible to speak in languages without form across the ages. Hidden in plain sight. How very odd. At the moment it is Vivaldi. In terms of AI it is that hidden valley that can only be found by raining on the entire parade ( not an option ) or knowing all things, ( also not an option ). The infinite dimensions can hide many things.
Life begins by accident ( some more than others ) and the guiding principle has to work with local minima of a gradient climbing process primarily, except in the case of some random stochastic rain.
Wikipedia has many classical composers in ogg format at this link.
Now I can make a synthetic mind that learns and explains what it has found. Google page rank, and various other techniques give a great advantage in dealing with the vast amounts of data. I expect that there will be a change in the Google algorithm very soon. It is a game of cat and mouse that goes on forever. The cat always has the advantage as it can observe the moves of the mouse and learn from it.
It really is a remarkable thing, a data set that explains itself and can't be understood without the understanding of the nature of understanding. It does lead me to suspect that should I discover a pattern in star data that in fact it could be this same thing. It is the music of the spheres, so to speak. Now I have a better algorithm to examine the data and a more realistic expectation of observing a meaningful pattern.