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The problem is that language doesn't produce itself. Re-checking, correcting error is not relevant. Error minimization is not the fount of survival, remaining v
by Mallowram 1y ago
The problem is that language doesn't produce itself. Re-checking, correcting error is not relevant. Error minimization is not the fount of survival, remaining variable for tasks is. The lossy encyclopedia is neither here nor there, it's a mistaken path:
"Language, Halliday argues, "cannot be equated with 'the set of all grammatical sentences', whether that set is conceived of as finite or infinite". He rejects the use of formal logic in linguistic theories as "irrelevant to the understanding of language" and the use of such approaches as "disastrous for linguistics"."
- ACCount37 1y agoSorry, what? This is borderline incoherent.
- mallowdram 1y agoThe units themselves are meaningless without context. The point of existence, action, tasks is to solve the arbitrariness in language. Tasks refute language, not the other way around. This may be incoherent as the explanation is scientific, based in the latest conceptualization of linguistics. CS never solved the incoherence of language, conduit metaphor paradox. It's stuck behind language's bottleneck, and it do so willingly blind-eyed.
- ACCount37 1y agoWhat? This is even less coherent. You weren't talking to GPT-4o about philosophy recently, were you?
- mallowdram 1y agoI'd know cutting-edge linguistics and signaling theory well beyond Shannon to parse this, not NLP or engineering reduction. What I've stated is extremely coherent to Systemic Functional Linguists. Beyond this point engineers actually have to know what signaling is, rather than 'information.' https://www.sciencedirect.com/science/article/abs/pii/S0003347209002589 https://www.sciencedirect.com/science/article/abs/pii/S00033... Ultimately, engineering chose the wrong approach to automating language, and it sinks the field. It's irreversible.
- ACCount37 1y agoOne of the main takeaways from The Bitter Lesson was that you should fire your linguists. GPT-2 knows more about human language than any linguist could ever hope to be able to convey. If you're hitching your wagon to human linguists, you'll always find yourself in a ditch in the end.
- mallowdram 1y agoSorry, 2 billion years of neurobiology beats 60 years of NLP/LLMs which knows less to nothing about language since "arbitrary points can never be refined or defined to specifics" check your corners and know your inputs. The bill is due on NLP.
- morpheos137 1y agoIf not language what training substrate do you suggest? Also not strong ideas are expressible coherently. You have an ironic pattern in your comments of getting lost in the very language morass you propose to deprecate. If we don't train models on language what do we train them on? I have some ideas of my own but I am interested if you can clearly express yours.
- mallowdram 1y agoNeural/spatial syntax. Analoga of differentials. The code to operate this gets built before the component. If language doesn't really mean anything, then automating it in geometry is worse than problematic. The solution is starting over at 1947: measurement not counting.