09-18-202408:36 PM - last edited on 09-18-202408:44 PM by LordArceus
the ability to use ai on cats but not specific cats might be solved by this method.
first recode neural network artificial intelligence so its easy to see.
how to do this. first see that there is a dictionary. and the dictionary creates global variables.
a global dictionary that holds the values of variables.
now use this dictionary to create a cat using a bunch of true conditions.
To find a cat, there are 50 conditions and the goal of the conditions are not to make a false condition but to make a true condition.
the values of the dictionary are used in the condition.
this way a true condition for a cat makes a cat in the neural network but its a global dictionary so there is no scope to create unique cats only generic cats and that is why artificial intelligence neural networks do not work with specific cats only generic cats.
then you have a problem of scope, because the dictionary is for all the neural network for the conditions to identify its a cat.
- you create an array the array element holds a specific cat,
- loop through the array so each loop creates a scope, the scope has its own dictionary and then 50 conditions to find a specific kind of cat.
- the dictionary is pasted in the scope but the values for cat are made specific to the type of cat your looking for.
