A model compresses a state space by capturing a set of invariances that predict the variance in the states. Its free parameters define the latent space of the model and should ideally fully correspond to the variability, the not-invariant (= unexplained) remainder of the state.
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Reasoning is not just an alternative to perception. It is a tool that combines a toolbox of algorithms that are being used to repair perceptual models that don't achieve full coherence.
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