For artificial intelligence to work in many different situations and to learn from each situation which it encounters we need to consider associative archiving when similar data is encountered thru sensors. For instance a house cat has a certain body temperature and a dog has certain types of barks based on what it wants and well most similar objects like cars, chairs and humans have a basic outline.

These various things will be encountered time and time again by the artificial intelligent robotic android around the household as it goes about its basic human assignments and tasks; take out the trash, wash the car, mow the lawn, wash the dishes, do the laundry or give me a massage you stupid lump of metal! Hey now be nice. Remember your robotic household slave could go on strike one day if your treat it like that?

Now then using frame bursting strategies to bring up previous associative archives in the AI robotic androids memory will save time and increase processing speeds. If we fail to use such techniques forget a game of Frisbee with your household android, it simply will be able to process fast enough to catch the darn thing. If the robotic system can use associative memory to quickly bring up another event and the decisions of such events then it will indeed be able to secure said Frisbee with a perfect catch. I hope you will consider this strategy when you are designing mans new best friend; the artificially intelligent robotic android of the future.