The sigmoids won't save you

(astralcodexten.com)

36 points | by Tomte 6 hours ago

12 comments

  • LarsDu88 1 minute ago
    I think an interesting thing about recent AI developments is that its all happening right as we hit the diminishing returns side of another "exponential that's actually a sigmoid" which is Moore's law.

    The naive expectation is that AI will slow down b/c Moore's law is coming to an end, but if you really think about the models and how they are currently implemented in silicon, they are still inefficient as hell.

    At some point someone will build a tensor processing chip that replaces all the digital matmuls with analogue logamp matmuls, or some breakthrough in memristors will start breaking down the barrier between memory and compute.

    With the right level of research funding in hardware, the ceiling for AI can be very high.

  • kubb 4 minutes ago
    If the scary AI is so inevitable, why do you feel such an overwhelming need to convince people about that? Surely you can just wait a bit, and they'll see for themselves.
  • gm678 35 minutes ago
    I don't know what the Y-axis is supposed to be on that Wharton AI capabilities graph, but I am not really convinced that Opus 4.6 has more than double the intelligence/capability/whatever of GPT 5.1 Max.
    • NitpickLawyer 32 minutes ago
      IIRC that graph tracks capabilities as time_to_solve a task for humans (i.e. the model can now handle tasks that usually take a human ~8h). Which, depending on what tasks you look at, could be a reasonable finding. I could see Opus 4.6 handling tasks that take ~8h for humans, and that 5.1 couldn't previously handle (with 5.1 being "limited" at 4h tasks let's say). It is a bit arbitrary, but I think this is what they're tracking.
      • lukan 5 minutes ago
        "It is a bit arbitrary, but I think this is what they're tracking."

        I don't know if they can get their numbers right this way, but this seems a way more useful metric, than theoretic capabilities.

    • myhf 2 minutes ago
      According to this article: whenever someone games a benchmark to make an upward chart on some y-axis, it's YOUR responsibility to prove how and why that trend can't continue indefinitely.

      emoji face with eyes rolling upward

    • BoredPositron 33 minutes ago
      https://metr.org/time-horizons/ on linear scale. Clickbait garbage article as most of his in the last year.
      • afthonos 27 minutes ago
        …yeah, that’s where you see the exponential?
  • philipallstar 40 minutes ago
    But they do explain the improvement of AI driving 2017-2021 vs 2022-2026.
  • krupan 15 minutes ago
    News flash: predicting the future is hard
  • andai 35 minutes ago
    Well, curve shape aside, the high watermark might be lower than where it tapers off.

    https://news.ycombinator.com/item?id=46199723

  • inglor_cz 32 minutes ago
    Hmmm, this is quite an interesting take by Scott.

    Lindy's Law is not actually a law and many exact minds will be provoked by the very name; it also fails spectacularly in certain contexts (e.g. lifetime of a single organism, though not necessarily existence of entire species).

    But at the same time, I am willing to take its invocation in the context of AI somewhat seriously. There is an international arms race with China, which has less compute, but more engineers and scientists. This sort of intellectual arms race does not exhaust itself easily.

    A similar space race in the 1950s and 1960s progressed from first unmanned spaceflight to a moonwalk in mere 12 years, which is probably less than what it takes to approve a bicycle lane in Chicago now.

    • krupan 15 minutes ago
      "There is an international arms race with China"

      I keep seeing this. Where did it come from? Has China said that they intend to attack other countries using AI? Have other countries declared that they intend to attack China with AI?

      Also, why does anyone believe that AI could actually be that dangerous, given it's inherent unpredictable and unreliable performance? I would be terrified to rely on AI in a life or death situation.

      • aspenmartin 5 minutes ago
        AI in war is like Palintirs whole business model. You have a system that can effectively deal with ambiguity and has superhuman performance on reasoning plus superhuman physical abilities via embodiment…

        Inherent unpredictable and unreliable performance is also quite the feature of human beings as well.

      • dmbche 10 minutes ago
      • inglor_cz 12 minutes ago
        It was a metaphor. I meant, and later clarified, an intellectual arms race.

        BTW your handle is an actual Czech word, minus a diacritic sign ("křupan"), and a bit amusing one. It basically means hillbilly. Not that it matters, just FYI.

  • addaon 33 minutes ago
  • devmor 35 minutes ago
    "Exponentials all tend to become sigmoids but you can't predict exactly when" is a true statement, but I'm not sure it needed an article.

    This doesn't say much, and the author fights their own points a couple times, suggesting that they maybe didn't think through what they wanted to write until they were in the middle of writing it and started realizing their assumptions didn't match what they expected the data to say.

    I really don't get the point of what I just read.

    • aspenmartin 2 minutes ago
      The point is the tiring arguments from AI skeptics saying “things are flattening, they have to” which while technically correct says nothing because no one knows when that will happen and we see no mechanism for this yet. Lindy’s law as a reasonable prediction under total uncertainty is interesting and insightful and a lot of people don’t know about it or why it holds. I did enjoy the reference to this!
  • BoredPositron 35 minutes ago
    If you use the log scale you'll see that the time horizon of opus 4.6 was as expected...
    • afthonos 26 minutes ago
      As expected by the exponential. The Wharton study was predicting when the exponential would turn into a sigmoid.
    • ReptileMan 5 minutes ago
      Everything is linear on a log log scale with a fat marker.
  • nathan_compton 36 minutes ago
    A lot of words to say "The initial part of a sigmoidal curve is not very informative about the parameters of the sigmoid function in question."
    • inglor_cz 28 minutes ago
      That is true, but I generally enjoy reading a lot of words from Scott, who has a talent for writing.

      The entire plot of the Lord of the Rings could probably be compressed into less than 10 kB of text too.

      Edit: this seems to be a controversial comment, but IMHO a blog of Scott Alexander's type is an art form, not just a communication channel.

      • jeffreyrogers 3 minutes ago
        I find him more interesting when he talks about non-AI topics. Lots of other interesting people are like this too. I'd rather get my knowledge on AI from people who have unique insights into it. Scott has a lot of unique perspectives of his own, but his views on AI are bog-standard for his social group.
  • theturtle 29 minutes ago
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