this post was submitted on 16 Oct 2023
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[–] Veraticus@lib.lgbt 8 points 1 year ago (3 children)

LLMs can't do any of those things though...

If no one teaches them how to speak a dead language, they won't be able to translate it. LLMs require a vast corpus of language data to train on and, for bilingual translations, an actual Rosetta stone (usually the same work appearing in multiple languages).

This problem is obviously exacerbated quite a bit with animals, who, definitionally, speak no human language and have very different cognitive structures to humans. It is entirely unclear if their communications can even be called language at all. LLMs are not magic and cannot render into human speech something that was never speech to begin with.

The whole article is just sensationalism that doesn't begin to understand what LLMs are or what they're capable of.

[–] bouh@lemmy.world 3 points 1 year ago (1 children)

They are making sense of a language without a rosetta stone. The English llm talk is learned from English.

Now the corpus is a big work to do. But still.

[–] Veraticus@lib.lgbt 2 points 1 year ago* (last edited 1 year ago)

No, they learn English (or any other language) from humans. Translation requires a Rosetta Stone and LLMs are still much worse at such tasks than dedicated translation programs.

Edit: I guess if you are suggesting that the LLM could become an LLM of the dead language and communicate only in said dead language, that is indeed possible. Since users would need to speak that dead language to communicate with it though I don’t understand the utility of such a thing (and is certainly not what the author meant anyway).

[–] narwhal@lemmy.ml 2 points 1 year ago (2 children)

What about preserving languages that are close to extinct, but still have language data available? Can LLMs help in this case?

[–] ImpossibilityBox@lemmy.world 5 points 1 year ago (1 children)

Preservation only but not likely any better than a linguistic historian.

But it gets tricky because LLMs only function on HUGE sets of data. LLMs are nothing more than complicated probability engines. Give it the question "What color is the sky?" and the math extracted from the massive databases that it has says the highest probability answer is "Blue". It doesn't actually KNOW the answer it just knows the probabilities of different words.

Without large amounts of data on the dying language current gen LLM's won't be accurate or able to generate reliable answers. Shoot... LLMs can barely generate reliable answers with the massive datasets they currently have.

I strongly recommend anyone even remotely interested in LLMs to read this interactive article:

https://ig.ft.com/generative-ai/

[–] Veraticus@lib.lgbt 1 points 1 year ago

This is a great article, thanks for linking it!

[–] Veraticus@lib.lgbt 1 points 1 year ago

Yeah, that would be a good usage of an LLM!

[–] rawrthundercats@lemmy.ml 1 points 1 year ago (2 children)

Curious your thoughts about this. Not an LLM but likely using transformers in the architecture.

[–] PipedLinkBot@feddit.rocks 1 points 1 year ago

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[–] Veraticus@lib.lgbt 1 points 1 year ago

This is so funny, I know him personally; we went to school together. I'll watch it and comment later.