I'm not an expert so correct me if I'm wrong but neural networks are bound by the actual weighting implementation and the fitness evaluation function which are determined a-priori by the programmer. A call this mimicking, not learning.
There is no system to simulate: self-awareness, concepts, meaning, input senses, intentions, self-reflexivity, etc.
The main things that neural nets simulate are fixed needs and a feedback system.
Although I think that neural nets will greatly participate in AI (and they actually do at this very moment), I mostly consider that AI should be a collection of sub-systems.
If this is the case, what sub-system would neural-nets be good at?
and do you think we should focus more on good-old symbolic systems?
JohnLeTigre1 karma
I'm not an expert so correct me if I'm wrong but neural networks are bound by the actual weighting implementation and the fitness evaluation function which are determined a-priori by the programmer. A call this mimicking, not learning.
There is no system to simulate: self-awareness, concepts, meaning, input senses, intentions, self-reflexivity, etc.
The main things that neural nets simulate are fixed needs and a feedback system.
Although I think that neural nets will greatly participate in AI (and they actually do at this very moment), I mostly consider that AI should be a collection of sub-systems.
If this is the case, what sub-system would neural-nets be good at? and do you think we should focus more on good-old symbolic systems?
thanks
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