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  • Ah thank you, now I see what you mean. And it seems like we’re mostly talking about the same thing here 😅

    To reiterate: unprecedented amounts of money and resources are being sunk into systems that are fundamentally flawed (among others by semantic drift), because their creators double down on their bad decisions (just scale up more) instead of admitting that LLMs can never achieve what they promise. So when you’re saying that LLMs are just fancy autocorrect, there’s absolutely no disagreement from me: it’s the point of this post.

    And yes, for an informed observed of the field, this isn’t news - I just shared the result of an experiment because I was surprised how easy it was to replicate.




  • But these systems work on interrupting the user’s input

    I’m not entirely sure what you mean here, maybe because I’m not a native speaker. Would you mind phrasing that differently for me?

    That’s got nothing to do with “PhD” level thinking, whatever that’s supposed to mean.

    Oh, we’re absolutely in agreement here, and it’s not me that made the claim, but what Sam Altman said about the then-upcoming GPT 5 in summer. He claimed that the model would be able to perform reasoning comparable to a PhD - something that clearly isn’t happening reliably, and that’s what this post bemoans.

    It’s just fancy autocorrect at this point.

    Yes, with an environmental and economic cost that’s unprecedented in the history of … well, ever. And that’s what this post bemoans.