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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I am fascinated by attempts “to reproduce the world” by its perception and fine tuning using our brain, but at the same time, I am fascinated by the possibility that consciousness is a physical (and mathematical) product of the same world. Continued...
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Paradoxically, perception cannot figure out true foundations, and you need reason for that. But reason is much more impoverished than perception when it comes to integrating large amounts of data, so you have to use perception for navigation.
End of conversation
New conversation -
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I found this interesting - https://arxiv.org/pdf/1505.00312.pdf …. In any case it looks to me that we see the very real picture...
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