this post was submitted on 21 Oct 2024
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[–] apotheotic@beehaw.org 7 points 3 weeks ago (9 children)

The person you're replying to is correct though. They do not understand, they do not analyse. They generate (roughly) the most statistically likely answer to your prompt, which may very well end up being text representing an accurate analysis. They might even be incredibly reliable at doing so. But this person is just pushing back against the idea of these models actually understanding or analysing. Its slightly pedantic, sure, but its important to distinguish in the world of machine intelligence.

[–] GetOffMyLan@programming.dev 3 points 3 weeks ago (8 children)

I literally quoted the word for that exact reason. It just gets really tiring when you talk about AIs and someone always has to make this point. We all know they don't think or understand in the same way we do. No one gains anything by it being pointed out constantly.

[–] apotheotic@beehaw.org 4 points 3 weeks ago (7 children)

You said "they literally do analyze text" when that is not, literally, what they do.

And no, we don't "all know" that. Lay persons have no way of knowing whether AI products currently in use have any capacity for genuine understanding and reasoning, other than the fact that the promotional material uses words like "understanding", "reasoning", "thought process", and people talking about it use the same words. The language we choose to use is important!

[–] Rivalarrival@lemmy.today 2 points 3 weeks ago (1 children)

The human capacity for reason is greatly overrated. The overwhelming majority of conversation is regurgitated thought, which is exactly what LLMs are designed to do.

[–] apotheotic@beehaw.org 2 points 3 weeks ago

I don't really dispute that but at least we are able to apply formal analytical methods with repeatable outcomes. LLMs might (and do) achieve a similar result but they do so without any formal approach that can be reviewed, which has its drawbacks.

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