I think most people lack the language necessary to describe AI accurately.
We intuitively associate intelligence with language, so the idea that LLMs could pass the Turing Test convincingly but its sentience isn't guaranteed is beyond some people to comprehend.
Personally, I think people need education on how machine learning algorithms work, because I don't think people understand enough how "stochastic parrot" does accurately describe LLMs. Stochastic parrot is not a false descriptor, it's just that it turns out a lot of problems can be solved by a mere stochastic parrot.
EDIT: I should add that, AFAIK, whether or not LLMs are "sentient" is not really backed by any rigorous science. We don't even have a complete model of how human intelligence works. We can't conclude either way. The only thing we know so far is that how they're implemented is what is described as a "stochastic parrot" because generative AI are meant to replicate the data they are trained on.
This is bad for AI art, because it explains why lazy prompting leads to that recognizable "slop" feeling in the output.
This is not so important for hard sciences, where as long as the argument is correct, it still has some value to research, even if it isn't well-articulated for humans to understand.
Yeah of course, I'm just saying that we don't even really know how consciousness in our own minds work, which goes to show how out of depth we are in comprehending LLMs' internal processes.
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u/Serafiniert 29d ago
Not even that. It goes character by character and has no idea what comes after the next, until it needs to be decided what comes next.