The Nonlinear Library LW - ... Wait, our models of semantics should inform fluid mechanics?!? by johnswentworth
Aug 26, 2024
07:14
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: ... Wait, our models of semantics should inform fluid mechanics?!?, published by johnswentworth on August 26, 2024 on LessWrong.
This post is styled after conversations we've had in the course of our research, put together in a way that hopefully highlights a bunch of relatively recent and (ironically) hard-to-articulate ideas around natural abstractions.
John: So we've been working a bit on semantics, and also separately on fluid mechanics. Our main goal for both of them is to figure out more of the higher-level natural abstract data structures. But I'm concerned that the two threads haven't been informing each other as much as they should.
David: Okay…what do you mean by "as much as they should"? I mean, there's the foundational natural latent framework, and that's been useful for our thinking on both semantics and fluid mechanics. But beyond that, concretely, in what ways do (should?) semantics and fluid mechanics inform each other?
John: We should see the same types of higher-level data structures across both - e.g. the "geometry + trajectory" natural latents we used in the
semantics post should, insofar as the post correctly captures the relevant concepts, generalize to recognizable "objects" in a fluid flow, like eddies (modulo adjustments for nonrigid objects).
David: Sure, I did think it was intuitive to think along those lines as a model for eddies in fluid flow. But in general, why expect to see the same types of data structures for semantics and fluid flow? Why not expect various phenomena in fluid flow to be more suited to representation in some data structures which aren't the exact same type as those used for the referrents of human words?
John: Specifically, I claim that the types of high-level data structures which are natural for fluid flow should be a subset of the types needed for semantics.
If there's a type of high-level data structure which is natural for fluid flow, but doesn't match any of the semantic types (noun, verb, adjective, short phrases constructed from those, etc), then that pretty directly disproves at least one version of the natural abstraction hypothesis (and it's a version which I currently think is probably true).
David: Woah, hold up, that sounds like a very different form of the natural abstraction hypothesis than our audience has heard before! It almost sounds like you're saying that there are no "non-linguistic concepts". But I know you actually think that much/most of human cognition routes through "non-linguistic concepts".
John: Ok, there's a couple different subtleties here.
First: there's the distinction between a word or phrase or sentence vs the concept(s) to which it points. Like, the word "dog" evokes this whole concept in your head, this whole "data structure" so to speak, and that data structure is not itself linguistic. It involves visual concepts, probably some unnamed concepts, things which your "inner simulator" can use, etc. Usually when I say that "most human concepts/cognition are not linguistic", that's the main thing I'm pointing to.
Second: there's concepts for which we don't yet have names, but could assign names to. One easy way to find examples is to look for words in other languages which don't have any equivalent in our language. The key point about those concepts is that they're still the same "types of concepts" which we normally assign words to, i.e. they're still nouns or adjectives or verbs or…, we just don't happen to have given them names.
Now with both of those subtleties highlighted, I'll once again try to state the claim: roughly speaking, all of the concepts used internally by humans fall into one of a few different "types", and we have standard ways of describing each of those types of concept with words (again, think nouns, verbs, etc, but also think of the referents of short phrases y...
This post is styled after conversations we've had in the course of our research, put together in a way that hopefully highlights a bunch of relatively recent and (ironically) hard-to-articulate ideas around natural abstractions.
John: So we've been working a bit on semantics, and also separately on fluid mechanics. Our main goal for both of them is to figure out more of the higher-level natural abstract data structures. But I'm concerned that the two threads haven't been informing each other as much as they should.
David: Okay…what do you mean by "as much as they should"? I mean, there's the foundational natural latent framework, and that's been useful for our thinking on both semantics and fluid mechanics. But beyond that, concretely, in what ways do (should?) semantics and fluid mechanics inform each other?
John: We should see the same types of higher-level data structures across both - e.g. the "geometry + trajectory" natural latents we used in the
semantics post should, insofar as the post correctly captures the relevant concepts, generalize to recognizable "objects" in a fluid flow, like eddies (modulo adjustments for nonrigid objects).
David: Sure, I did think it was intuitive to think along those lines as a model for eddies in fluid flow. But in general, why expect to see the same types of data structures for semantics and fluid flow? Why not expect various phenomena in fluid flow to be more suited to representation in some data structures which aren't the exact same type as those used for the referrents of human words?
John: Specifically, I claim that the types of high-level data structures which are natural for fluid flow should be a subset of the types needed for semantics.
If there's a type of high-level data structure which is natural for fluid flow, but doesn't match any of the semantic types (noun, verb, adjective, short phrases constructed from those, etc), then that pretty directly disproves at least one version of the natural abstraction hypothesis (and it's a version which I currently think is probably true).
David: Woah, hold up, that sounds like a very different form of the natural abstraction hypothesis than our audience has heard before! It almost sounds like you're saying that there are no "non-linguistic concepts". But I know you actually think that much/most of human cognition routes through "non-linguistic concepts".
John: Ok, there's a couple different subtleties here.
First: there's the distinction between a word or phrase or sentence vs the concept(s) to which it points. Like, the word "dog" evokes this whole concept in your head, this whole "data structure" so to speak, and that data structure is not itself linguistic. It involves visual concepts, probably some unnamed concepts, things which your "inner simulator" can use, etc. Usually when I say that "most human concepts/cognition are not linguistic", that's the main thing I'm pointing to.
Second: there's concepts for which we don't yet have names, but could assign names to. One easy way to find examples is to look for words in other languages which don't have any equivalent in our language. The key point about those concepts is that they're still the same "types of concepts" which we normally assign words to, i.e. they're still nouns or adjectives or verbs or…, we just don't happen to have given them names.
Now with both of those subtleties highlighted, I'll once again try to state the claim: roughly speaking, all of the concepts used internally by humans fall into one of a few different "types", and we have standard ways of describing each of those types of concept with words (again, think nouns, verbs, etc, but also think of the referents of short phrases y...