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Sometimes it's useful, imo, to pick apart the differences in intellectual temperament, intuition, foundational beliefs, etc., that drive disagreements. But I ag

by pxc 1y ago

Sometimes it's useful, imo, to pick apart the differences in intellectual temperament, intuition, foundational beliefs, etc., that drive disagreements. But I agree, sometimes it's a lot of clumsy fumbling. I'll say this against your perspective (or perhaps just use of language), though: it seems to leave little room for skepticism of the greatest general (not product-specific) claims made today in the AI industry. You either buy into the notion that the path we're on is contiguous with "AGI", or you're dismissive of AI! This is nearly as deflationary as your view of consciousness. ;) I would expect "dismissive" to describe more categorically dismissive views, and not to extend, e.g., to views which admit that AI is in principle possible, non-eliminativist materialism (e.g., functionalists who say we just don't have good reason to say LLMs or other neural networks have the requisite structure for consciousness), etc. Since you brought him up, Gödel himself seemed to have a much more "miraculous" notion of human cognition that came out in (IIRC) letters in which he explains why he doesn't think human mathematicians' work is hindered by his second incompleteness theorem. That, I would say is dismissive of AI. But if any view not grounded in illusionism is dismissive of AI, what can a non-dismissive person possibly identify as AI hype? Just particular marketing claims about the concrete capabilities of particular models? If that's true, than rather than characterizing extreme or marginal views, a view is "dismissive" just for refusing to buy into the highest degree of contemporary AI hype.

perching_aix 1y ago
> I'll say this against your perspective (or perhaps just use of language), though: it seems to leave little room for skepticism of the greatest general (not product-specific) claims made today in the AI industry. Maybe I can alleviate this to an extent by expanding on my views, since I believe that's not the case. I tried alluding to this by saying that, in my view, models have an understanding [of things], but to put it in more explicit terms, for me "understanding" on its own is a fairly weak term. Like I personally consider the semantic diffing tool I use to diff YAMLs to have an understanding of YAML. Not in a metaphorical sense, but in a literal sense. The understanding is hardwired, sure, but to me that makes no difference. It may also not even be completely YAML standard-compliant, which is what would be the "equivalent" of an AI model understanding something to an extent but not fully or not right. This leaves a lot of room for criticism and skepticism, as that means models can have elementary understandings of things, that while are understandings, are nevertheless not e.g. meaningfully useful in practice, or fail to live up to the claims and hype vendors spout. Which is sometimes exactly how I view a lot of the models available today. They are not capable of fully understanding what I write, and to the extent they are, they do not necessarily understand it the way I'd expect them to (i.e. as a human). But instead of me classifying this as them not understanding, I still decidedly consider these tools to be just often on the immature, beginning side of a longer spectrum that to me is understanding. I hope this makes sense, even if you still do not find this view agreeable or relatable. You may argue that my definition is too wide, and that then everything can "understand", but that's not necessarily how I think of this either. A "more rigorous" way of putting my thoughts would be that I think things can understand to the extent they can hold representations of some specific thing and manipulate them while keeping to that representation (pretty much what happens when you traverse a model's latent space in a specific axis). But I'm not sure I spent enough time thinking about this thoroughly to be able to confidently tell you that this is a complete and consistent description, fully reflective of my understanding of understanding (pun intended). Like when in an image model you can quite literally manipulate the gender, hairstyle, clothing of characters depicted by moving along specific directions, to me that is a clear evidence of that model having an understanding of these concepts, and in the literal sense.

by pxc 1y ago

perching_aix 1y ago

> I'll say this against your perspective (or perhaps just use of language), though: it seems to leave little room for skepticism of the greatest general (not product-specific) claims made today in the AI industry. Maybe I can alleviate this to an extent by expanding on my views, since I believe that's not the case. I tried alluding to this by saying that, in my view, models have an understanding [of things], but to put it in more explicit terms, for me "understanding" on its own is a fairly weak term. Like I personally consider the semantic diffing tool I use to diff YAMLs to have an understanding of YAML. Not in a metaphorical sense, but in a literal sense. The understanding is hardwired, sure, but to me that makes no difference. It may also not even be completely YAML standard-compliant, which is what would be the "equivalent" of an AI model understanding something to an extent but not fully or not right. This leaves a lot of room for criticism and skepticism, as that means models can have elementary understandings of things, that while are understandings, are nevertheless not e.g. meaningfully useful in practice, or fail to live up to the claims and hype vendors spout. Which is sometimes exactly how I view a lot of the models available today. They are not capable of fully understanding what I write, and to the extent they are, they do not necessarily understand it the way I'd expect them to (i.e. as a human). But instead of me classifying this as them not understanding, I still decidedly consider these tools to be just often on the immature, beginning side of a longer spectrum that to me is understanding. I hope this makes sense, even if you still do not find this view agreeable or relatable. You may argue that my definition is too wide, and that then everything can "understand", but that's not necessarily how I think of this either. A "more rigorous" way of putting my thoughts would be that I think things can understand to the extent they can hold representations of some specific thing and manipulate them while keeping to that representation (pretty much what happens when you traverse a model's latent space in a specific axis). But I'm not sure I spent enough time thinking about this thoroughly to be able to confidently tell you that this is a complete and consistent description, fully reflective of my understanding of understanding (pun intended). Like when in an image model you can quite literally manipulate the gender, hairstyle, clothing of characters depicted by moving along specific directions, to me that is a clear evidence of that model having an understanding of these concepts, and in the literal sense.