For agi the capability of a agi to take in new experiences, learn from them and use that experience in the future without retraining reminds me of quantum phase kickback.In quantum phase kickback data can enter the control qubit despite it not being the target of some controlled operation and this happens for some reasons but that is not the point.What I im interested is this: a)it has no classical information analog b)The important idea is that interaction with something causes useful information about that interaction to become encoded in the state of another subsystem, where it can influence later computation.Then the past experience has effectively left information in the system's state, and that information modifies how future inputs are processed.So it acts as a 'memory'.Now you may argue that this is exactly what weights do but weights havent produced us AGI so I was wondering maybe if this would be the step forward and how it would alter behavior of a AI system built in like how I have described.

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