Artificial Intelligence - Memory Management Example

So, let’s image that its time to bring the Ai Online. We’ve built all the components and we’re ready to go.

Here’s how the first 1,000 interactions with if the Ai was only attached to a “Textbox” sensor.

Definitely take a look at the picture as it conveys a lot more but briefly:

“Hi” comes through the textbox sensor, the Ai stumbles through Evaluators till it hits the Language one, which say “I understand this data”, the Ai says ok and lets the evaluator do its thing.

The next time the textbox sensor fires off, the Ai gives it to the only Evaluator it knows Language, language handles things smoothly. This takes place 999 times.

However on interaction 1,000 along comes a math request “3+9”. The language evaluator says…Ummm, no I can’t do anything with this. Again the Ai stumbles around until it hits the Math evaluator, who says, yeah…I can do something with it.

Now when textbox fires off, the brain will randomly ask Math…Do you understand this stuff…If Math says yes, the Brain lets it handle the text. If the Math says “no”, brain turns to Language and passes stuff off.

Summary
This is not the most efficient way and if you notice it never actually pattern matches against what comes in on the textbox sensor.

However, if a different sensor is setup for math functions this approach would lead to an efficient Ai. Math coming across a speech/text sensor would be like being asked does this spell BLUE. Humans can do it, its just…odd, thus we are more likely to answer incorrectly.