this post was submitted on 12 Jun 2024
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[–] [email protected] 46 points 5 months ago (16 children)

As others are saying it's 100% not possible because LLMs are (as Google optimistically describes) "creative writing aids", or more accurately, predictive word engines. They run on mathematical probability models. They have zero concept of what the words actually mean, what humans are, or even what they themselves are. There's no "intelligence" present except for filters that have been hand-coded in (which of course is human intelligence, not AI).

"Hallucinations" is a total misnomer because the text generation isn't tied to reality in the first place, it's just mathematically "what next word is most likely".

https://arstechnica.com/science/2023/07/a-jargon-free-explanation-of-how-ai-large-language-models-work/

[–] [email protected] 3 points 5 months ago (3 children)

I was wondering, are people working on networks that train to create a modular model of the world, in order to understand it / predict events in the world?

I imagine that that is basically what our brains do.

[–] [email protected] 5 points 5 months ago (1 children)

Many attempts, some well-funded.

They have been successful in very limited domains. For example, the F-35 integrated sensor suite.

[–] [email protected] 2 points 5 months ago

For example, the F-35 integrated sensor suite.

Now I know why they crash so often

[–] [email protected] 3 points 5 months ago

Not really anything properly universal, but a lot of task specific models exists with integration with logic engines and similar stuff. Performance varies a lot.

You might want to take a look at wolfram alpha's plugin for chatgpt for something that's public

[–] [email protected] 2 points 5 months ago

Yeah I'm sure folks are working on it, but I'm not knowledgeable or qualified on the details.

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