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  • Hacker News
  • The entire company is based on stealing everyone else’s creative content and then passing it off as their own. So this isn’t a surprise.
  • Engineering manager at my company put a comic at the end of our sprint demo that was signed bloper. Except it wasn’t funny at all, and kind of weird. I asked him, sure enough it was ChatGPT and he didn’t notice the signature.
  • Nice. This demolishes the "LLMs can reason" (but not enough to avoid this sort of basic error) and "humans make mistakes too" (not like this) talking points from the LLM promoters.
  • The copyright washing machine strikes again.
  • Of course it does this. The training data is full of examples that associate e.g. "New Yorker-style cartoon" with Loper's signature in the corner, because Loper's signature is in the corner of a lot of them. There's nothing to make it treat the signature as anything special by default; that would have to be trained in explicitly.

    One would hope that the person prompting ChatGPT would notice this sort of thing and do something about it before sharing it publicly, out of a genuine desire not to cause confusion etc. But I guess that's way more personal responsibility than we can expect average people to take on nowadays.

  • This has been a perennial problem with my own generated comics with both Nano Banana Pro and ChatGPT (all generations). I often have to put in an extra edit to erase the false signature. It is annoying and I'm unsurprised most users don't bother.
  • I'm certain if I drew a cartoon and used the signature that looks just like a real cartoonists', I would get sued and liable for the damage.

    The same should apply to LLM vendors.

  • The part of the AI generating the mashup doesn’t really understand what the signature means, or how it may be interpreted, it’s just a visual part of a New Yorker cartoon. Elsewhere in ChatGPT there is plenty of information about signatures and what they mean, and what plagiarism is.

    It’s not organized like a human brain, it shouldn’t be surprising that unusual results occur. They are approximating human intelligence from a different angle. It’s interesting to see the improvements in areas like this that require introspection that isn’t fully wired up yet.

    [edit] I should add that a human making a New Yorker cartoon is extremely iterative and introspective. Current generative AI is meant to push it out, and you can do the iteration and introspection yourself.

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