Monday, October 9, 2017

“Necklace” unsupervised learning algorithm.

There are some entities which are easily comprehend by almost everybody, yet are very difficult to describe in details or give strict science definition. That is true for almost any term from the field of our intelligence, and term intelligence itself. Thought, feeling, understanding, consciousness, learning, recognition and the interest, the sense of beauty in image, form, melody, and the sense of humor. It is hard for intelligence to formulate these entities, same as it is hard for a snowman to answer “what is snow?” question.

I feel that “Interest” is the one among these entities, that is undeservedly deprived of attention from AI researches. And the one that I am long interested in.

In the 4 pages pdf paper below you can read my thoughts on the interest and how it can help to build unsupervised learning HTM.

https://www.dropbox.com/s/8nnn1w10yw90m2h/%E2%80%9CNecklace%E2%80%9D%20unsupervised%20learning%20algorithm.pdf?dl=0

Sunday, February 19, 2017

Harmony.

Harmony, the musicality - is the simpliest and plane exposition for intelligence interest.

You got sequence of sounds, some of them are predicted by mind, some are unexpected. The right balance of these makes music being loved.
If you got too many unexpected sounds - the music is too complicated and feels like a noise.
If you got too many predicted sounds - the music is too dull and uninteresting to listen.

Also, it seems that here lies some mind delimiter clues.
Some old melodies are interesting, even if we do listen them for the hungred+1 time. But they not interesting if we listen them 3 times in a row.
It means that some part of the melody are great at forgetting it. And some are coming easy to predict. That is how greatest hits are made.
Because some part of the melody is forgetting quick, but looks like periodic and predicted when you hear it or play it.