this post was submitted on 26 Jun 2023
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I guess the important thing to understand about spurious output (what gets called "hallucinations") is that it's neither a bug nor a feature, it's just the nature of the program. Deep learning language models are just probabilities of co-occurrence of words; there's no meaning in that. Deep learning can't be said to generate "true" or "false" information, or rather, it can't be meaningfully said to generate information at all.
So then people say that deep learning is helping out in this or that industry. I can tell you that it's pretty useless in my industry, though people are trying. Knowing a lot about the algorithms behind deep learning, and also knowing how fucking gullible people are, I assume that—if someone tells me deep learning has ended up being useful in some field, they're either buying the hype or witnessing an odd series of coincidences.
I mean AI is already generating lots of bullshit 'reports'. Like you know, stuff that reports 'news' with zero skill. It's glorified copy-pasting really.
If you think about how much language is rote, in like law and etc. Makes a lot of sense to use AI to auto generate it. But it's not intelligence. It's just creating a linguistic assembly line. And just like in a factory, it will require human review to for quality control.
It drives me nuts about how often I see the comments section of an article have one smartass pasting the GPT summary of that article. The quality of that content is comparable to the "reply girl" shit from 10 years ago.