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InitialsDiceBearhttps://github.com/dicebear/dicebearhttps://creativecommons.org/publicdomain/zero/1.0/„Initials” (https://github.com/dicebear/dicebear) by „DiceBear”, licensed under „CC0 1.0” (https://creativecommons.org/publicdomain/zero/1.0/)IL
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2
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Joined
2 yr. ago

  • I think there are definitely a lot of compounding issues that all combine to make admitting you're wrong something that's really hard to do. Some of them related to brain chemistry, some of them entirely societal, like you mentioned. But I do think that it's on the person who was wrong to be the one who does the growing; it shouldn't be society that has to pick up the slack for an arrogant and incorrect person.

  • Honestly a lot of the issues result from null results only existing in the gaps between information (unanswered questions, questions closed as unanswerable, searches that return no results, etc), and thus being nonexistent in training data. Models are therefore predisposed toward giving an answer of any kind, and if one doesn't exist it'll "make one up."

    Which is itself a misnomer, because it can't look for an answer and then decide to make one up when it can't find it. It just gives an answer that sounds plausible, and if the correct answer is most likely in its training data then that'll seem most plausible.

  • "Unintentionally" is the wrong word, because it attributes the intent to the model rather than the people who designed it.

    You misunderstand me. I don't mean that the model has any intent at all. Model designers have no intent to misinform: they designed a machine that produces answers.

    True answers or false answers, a neural network is designed to produce an output. Because a null result ("there is no answer to that question") is very, very rare online, the training data doesn't include it; meaning that a GPT will almost invariably produce any answer; if a true answer does not exist in its training data, it will simply make one up.

    But the designers didn't intend for it to reproduce misinformation. They intended it to give answers. If a model is trained with the intent to misinform, it will be very, very good at it indeed; because the only training data it will need is literally everything except the correct answer.

  • Sure, but unintentionally. I heard about a guy whose small business (which is just him) recently had someone call in, furious because ChatGPT told them that he was having a sale that she couldn't find. The customer didn't believe him when he said that the promotion didn't exist. Once someone decides to leverage that, and make a sufficiently-popular AI model start giving bad information on purpose, things will escalate.

    Even now, I think Elon could put a small company out of business if he wanted to, just by making Grok claim that its owner was a pedophile or something.

  • I keep getting caught off-guard seeing current photos of Torvalds. He's just like...a guy.

    And honestly I'd rather my mission-critical software be written by "just a guy" than by whoever Mr. Battlestation is down there on the bottom.

  • I'm sure there were some forum software packages that offered voting and ranking and such. All of the ones that I was a part of were quiet enough that you didn't need such a thing, though; you could keep up with every post, even if only to decide that you weren't interested in it, if you read it every third day or so.

  • Literally yes. The Pharisees of Jesus' time were the conservative religious hardliners of Israel, having drifted significantly from their original theology because of political expediency, pushing their version of morality under the threat of harm; and Jesus represented a challenge to their power.

    So more than just "would've," they (well, their first century predecessors) did.

  • I don't know about photoshopped. I would imagine that there's a lot of heavy (and misguided) makeup going on, and I don't think the lighting is doing her any favors, but she legitimately looks significantly different from her pre-surgery appearance.