Concept AI (part 2)

This is the latest addition to the brainstorming file. Please not that the information not sited is just my concepts, they might not always be realistic or accurate.

http://www.phy.syr.edu/courses/modules/MM/brain/organizations/organizations.html#work
And sub/super site
"A simple explanation of the processing step is that the cell sums up the incoming signals and produces an output signal only if this sum exceeds some threshold; i.e. only if the total input signal is big enough will the cell `fire' an output signal to its neighbors.""new memories are stored not on individual neurons but by adjusting the strengths of connections between neurons.""the connection between two neurons will strengthen if more often than not the two neurons fire together. This is often called the Hebb rule.""The nodes in the network are vast simplifications of real neurons - they can only exist in one of two possible "states" - firing or not firing.""Certain nodes will be always "on" and others "off"."

Emotions affect the threshold. Causing "speechlessness" when too happy, lower threshold value for certain categories (associated with anger) when angry ect.

The connections between the neurons are also important. The higher the current that passes through the connection, the more it's strength.

A, B, C are neurons.
A is connected to b and c.
B is connected to a and c.
C is connected to a and b.
During sleep time, this system can be reworked to:
A is connected to b.
B is connected to c.
C is connected to b.

Once a neuron receives a signal, it waits to see if the signal will add up to the threshold. If not, it returns false, otherwise true. This feedback will help improve the heuristic algorithm that direct the connections.

Techior2
"cannot be limited to words, but must also extend to the concepts those words communicate"

Research "Hopfield Networks" for memory.

The input gates should use pattern recognition to simplify the complex input and direct the general flow of input to the right nodes.