this post was submitted on 02 Feb 2024
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submitted 10 months ago* (last edited 10 months ago) by [email protected] to c/[email protected]
 

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[–] [email protected] 3 points 10 months ago* (last edited 10 months ago) (1 children)

Well… it’s a correct phone number. So that kind of undercuts your message.

edit: I’m actually a bit baffled by people downvoting this. That is the correct number given by both of those organizations. It isn’t some LLM hallucination.

[–] [email protected] 0 points 10 months ago (1 children)

thats like saying theyre wrong because words are spelled correctly yes the number is correct but the machine doesnt know what the hell it is, or what it's for, or in any sense "understand" what it's regurgitating to the user as evidenced by the fact that it listed it twice. "AI" doesn't know anything, it just copy-pastes shit.

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

First, it just copy pastes much in the same way animals do; a neural network with outputs weighted by experience. Secondly it posted it twice because both of those organizations are real and are references for the topic it mistakenly meant to reply about. The same way of asking what to do when a house burns one might reply:

  • Contact x city fire department. 911
  • Contact y county fire and rescue. 911

Third, and most importantly, I’m not saying it invalidates the message completely… but it does undercut it. As in, there would have been a much stronger case for just randomly outputting garbage information that it hopes sounds correct if the information had not been, you know… correct.

[–] [email protected] 0 points 10 months ago (1 children)

meanwhile i asked it to write a short simple hello world in a scripting language designed for children, and it spat out nothing but garbage. one of us is leaning on confirmation bias.

[–] [email protected] 1 points 10 months ago

I’m curious which language and which model, because I have had several of the models write programs like the sieve of Eratosthenes quite successfully. You can find this report in my GitHub of the same name.

I don’t know what bias you’re on about. I was just reporting that those phone numbers are in fact the correct numbers given by those organizations. Are you implying they aren’t? Because, you might want to go to the primary source and check for yourself.