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Could modern computers decipher hieroglyphics if we never found the Rosetta Stone? (lemmy.world)

submitted 10 months ago by [email protected] to c/[email protected]

19 comments fedilink hide all child comments

What if we never found the Rosetta Stone and could not read ancient Egyptian hieroglyphics. Could computers or AI decipher them today?

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[–] [email protected] 33 points 10 months ago (2 children)

Given that the AI we have is prone to making things up because it “fits” according to the models it trains on, how much faith would you have in a translation done by an AI on writings made by people who lived millennia before said language models were developed?

[–] [email protected] 41 points 10 months ago* (last edited 10 months ago) (2 children)

Don't confuse modern LLM models (like ChatGPT) with AI. As the saying goes:

All Buicks are Cars, but not all Cars are Buicks

LLMs are a form of AI, but there is a lot more going on in the world of AI than just LLMs.

[–] [email protected] 13 points 10 months ago (1 children)

That’s a good point, and you’re right that I’m conflating them.

What other elements of AI would you imagine would be useful here?

[–] [email protected] 4 points 10 months ago

You'd have to ask people who work in the AI field, and, alas, I'm not one of those people.

There has been a lot of language work on attempting to reconstruct the original Indo-European Language, using combinations of pattern recognition and statistical analysis of child languages. Those sorts of tools could aid in deciphering a dead written language.
https://en.wikipedia.org/wiki/Proto-Indo-European_language

However, another written language called Linear-A (of the ancient Minoans) has yet to be deciphered, despite lots of attempts at trying.
https://www.thoughtco.com/linear-writing-system-of-the-minoans-171553

So:
¯\(ツ)/¯

[–] [email protected] 6 points 10 months ago

to expand your point, the sole job of an LLM is to, when given a sequence of words (e.g. half a sentence), predict what the next several words should be. the model has no concept of what English words mean, so instead it makes this prediction based on statistics that were derived from basically reading through hundreds of thousands of English sentences

TL;DR LLMs don’t understand languages, they’ve just memorized statistics about them

[–] [email protected] 2 points 10 months ago* (last edited 10 months ago)

I'll have more faith once it can reliably switch back and forth between Unicode symbols and their underlying HTML entities. It understands the concept of emojis and can use them appropriately, but I can tell there's still some underlying issues in the token/object model for non-ASCII symbols.