Speaker unverified: belief

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…Well does that imply that the abstractions are real? Right? So you know, like, I see you as an agent, and I see you as factorized quite neatly into organs and brains and eyes and whatnot. But if we want to build an artificial intelligence, 1 approach is we we handcraft the abstraction hierarchy. Another 1 is that we adaptively learn it. Yeah. And and adaptively learning it is definitely the way to go because we we have learned the abstractions we have in order to because these things are useful to us. So a chair, for example, is useful to me. It is something that that is a cause of valence to me, or is a step on the way to causing some positive or negative valence. It has utility. Table, same thing. I don't have the concept of half a chair that I think about. Like, it's just not useful to me to think. I have to combine this other concept of half to even describe it. And the world is in every aspect divided into these simplifications, these classifiers. And these are, if we want to go back to talking about an intelligence that builds programs, I'm building all these classifier programs for television, light, chair, you, table. Like, this is all stuff that matters to me. I don't build classifiers for things that don't matter. And so you can even tie this in with things like the Fermi Paradox of like, why we don't even notice something that might be classified as intelligent. It's behavior is just not relevant to anything that causes us valence. Which would tie in with Mike Levin's work on mind blindness. Very good, very good. And you spoke about the need for actually learning causal relationships between things as well. Tell me about that.…

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