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Comment by nozzlegear

8 hours ago

Every S-curve looks like an exponential until you hit the bend.

We've been hearing this for 3 years now. And especially 25 was full of "they've hit a wall, no more data, running out of data, plateau this, saturated that". And yet, here we are. Models keep on getting better, at more broad tasks, and more useful by the month.

  • Model improvement is very much slowing down, if we actually use fair metrics. Most improvements in the last year or so comes down to external improvements, like better tooling, or the highly sophisticated practice of throwing way more tokens at the same problem (reasoning and agents).

    Don't get me wrong, LLMs are useful. They just aren't the kind of useful that Sam et al. sold investors. No AGI, no full human worker replacement, no massive reduction in cost for SOTA.

  • Yes, and Moore's law took decades to start to fail to be true. Three years of history isn't even close to enough to predict whether or not we'll see exponential improvement, or an unsurmountable plateau. We could hit it in 6 months or 10 years, who knows.

    And at least with Moore's law, we had some understanding of the physical realities as transistors would get smaller and smaller, and reasonably predict when we'd start to hit limitations. With LLMs, we just have no idea. And that could be go either way.

  • > We've been hearing this for 3 years now

    Not from me you haven't!

    > "they've hit a wall, no more data, running out of data, plateau this, saturated that"

    Everyone thought Moore's Law was infallible too, right until they hit that bend. What hubris to think these AI models are different!

    But you've probably been hearing that for 3 years too (though not from me).

    > Models keep on getting better, at more broad tasks, and more useful by the month.

    If you say so, I'll take your word for it.

    • Except for Moore's law, everyone knew decades ahead of what the limits of Dennard scaling are (shrinking geometry through smaller optical feature sizes), and roughly when we would get to the limit.

      Since then, all improvements came at a tradeoff, and there was a definite flattening of progress.

      2 replies →

  • > And yet, here we are.

    I dunno. To me it doesn’t even look exponential any more. We are at most on the straight part of the incline.

    • Personally my usage has fell off a cliff the past few months. Im not a SWE.

      SWE's may be seeing benefit. But in other areas? Doesnt seem to be the case. Consumers may use it as a more preferred interface for search - but this is a different discussion.

This quote would be more impactful if people haven't been repeating it since gpt-4 time.

  • People have also been saying we'd be seeing the results of 100x quality improvements in software with corresponding decease in cost since gpt-4 time.

    So where is that?

  • I agree, I have been informed that people have been repeating it for three years. Sadly I'm not involved in the AI hype bubble so I wasn't aware. What an embarrassing faux pas.

Cool I guess. Kind of a meaningless statement yeah? Let's hit the bend, then we'll talk. Until then repeating, 'It's an S Curve guys and what's more, we're near the bend! trust me" ad infinitum is pointless. It's not some wise revelation lol.

  • Maybe the best thing to say is we can only really forecast about 3 months out accurately, and the rest is wild speculation :)

    History has a way of being surprisingly boring, so personally I'm not betting on the world order being transformed in five years, but I also have to take my own advice and take things a day at a time.

  • > Kind of a meaningless statement yeah?

    If you say so. It's clear you think these marketing announcements are still "exponential improvements" for some reason, but hey, I'm not an AI hype beast so by all means keep exponentialing lol