Beyond pattern recognition, intelligence is about building models of the world. But what's a "model"? I think the best analogy is a *map*: an artifact that you can observe and manipulate, that emulates important properties of the original object. Cognition is like cartography.
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An example of such a system:https://twitter.com/neomechanica/status/1035812832091275264?s=21 …
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Words are the equivalent of discrete desire paths on the landscape ?
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Sometimes the path less traveled..
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You mean machine learning is like "cartography" on the space of models Intelligence, information, knowledge,… are something else Related: https://arxiv.org/abs/0706.3639 https://arxiv.org/abs/0712.3329
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Really have trouble seeing 'my own' model of the world as a manifold. So discontinuous and full of singularities... Picturing it as a graph makes a lot more sense to me. Can graphs (and graph algorithms) be modeled/replaced with manifolds and linear algebra?
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Giving it more thought, a map is pretty much exactly a graph drawn on a manifold. The graph carries semantics and enables reasoning (shortest way from A to B?). Do we human first learn what reality is supposed to look like (=the manifold) and then what it means (=the graph)?
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This is rather interesting. I would love to see an example algorithm applying this idea of traversing an information map in order to achieve intelligence.
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Also curious about how one would update this map as new information becomes available. Seems like there would be distinct differences between updating the map from new sensor input and updating it from discovering connections from traversing the map offline.
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