Say we have a detector network that detects for a “c”. How this detector comes into existence will be in different discussion. Cause the SDR selects what detector come
into being and where they will wire in as a self organizing map, SOM.
All activation of detectors NN are wired to a SDR bit.
All images are compressed before they a presented to a detector or moved to other
detector withing the brain.
A detector is not memory it is ring the bell when it is seen or a bit that goes high.
Or “I know it when i see it”.
To store the detection in memory the detector is forced to look a internal sketch
board that re generates compressed input. When the detector re activates it mean
mission complete the compress data, on the sketch board, can now be stored away.
So when you close your eye and view letter “C” the compressed data in the neural
software is un compress it to make it look real.
When a person set back and thinks of paths they will take the detects the detectors
will activate on everything as if they were really there.
This way a a complete record temporal loop or a temporal length of data can be
inputted into a NN detector all at once and then mapped to a SDR bit.
The compression and un compression of data is done by something like this:
All the other plumbing is being done by a GAN: