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Comment by NitpickLawyer

6 days ago

> I don't see this getting better.

We went from 2 + 7 = 11 to "solved a frontier math problem" in 3 years, yet people don't think this will improve?

I’ve seen this style of take so much that I’m dying for someone to name a logical fallacy for it, like “appeal to progress” or something.

Step away from LLMs for a second and recognize that “Yesterday it was X, so today it must be X+1” is such a naive take and obviously something that humans so easily fall into a trap of believing (see: flying cars).

  • In finance we say "past performance does not guarantee future returns." Not because we don't believe that, statistically, returns will continue to grow at x rate, but because there is a chance that they won't. The reality bias is actually in favour of these getting better faster, but there is a chance they do not.

    • this is true because markets are generally efficient. It's very hard to find predictive signals. That is a completely different space than what we're talking about here. Performance is incredibly predictable through scaling laws that continue to hold even at the largest scales we've built

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  • Even more insane than assuming the trend will continue is assuming it will not continue. We don't know for sure (especially not by pure reason), but the weight of probability sure seems to lean one direction.

  • Logical fallacies are vastly overrated. Unless the conversation is formal logic in the first place, "logical fallacies" are just a way to apply quick pattern matching to dismiss people without spending time on more substantive responses. In this case, both you and the other are speculating about the near future of a thing, neither of you knows.

    • Hard to make a more substantive response when the OP’s entire comment was a one-sentence logical fallacy. I’m not cherry-picking here.

      > In this case, both you and the other are speculating about the near future of a thing, neither of you knows.

      One of us is making a much grander claim than the other:

        - LLMs have limitless potential for growth; because they are not capable of something today does not mean they won’t be capable of it tomorrow
        - LLMs have fundamental limitations due to their underlying architecture and therefore are not limitless in capability

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    • OK, its not a logical fallacy, its a false assumption.

      The belief in the inevitability of progress is a bad assumption. Especially if you assume a particular technology will keep advancing.

      3 replies →

  • Hmm...the sun comes up today is a pretty good bet that the sun comes up tomorrow.

    We have robust scaling laws that continue to hold at the largest scales. It is absolutely a very safe bet that more compute + more training + algorithmic improvements will certainly improve performance it's not like we're rolling a 1 trillion dollar die.

  • Well if people give the exact same 'reasons' why it could not do x task in the past that it did manage to do then it is tiring seeing the same nonsense again. The reason here does not even make much sense. This result is not easily verifiable math.

  • Yeah, and even if we accept that models are improving in every possible way, going from this to 'AI is exponential, singularity etc.' is just as large a leap.

  • The comment doesn't say it must be X+1. It implies it will improve which I would say is a pretty safe bet.

Scaling law is a power law , requiring orders of magnitude more compute and data for better accuracy from pre-training. Most companies have maxed it out.

For RL, we are arriving at a similar point https://www.tobyord.com/writing/how-well-does-rl-scale

Next stop is inference scaling with longer context window and longer reasoning. But instead of it being a one-off training cost, it becomes a running cost.

In essence we are chasing ever smaller gains in exchange for exponentially increasing costs. This energy will run out. There needs to be something completely different than LLMs for meaningful further progress.

I tend to disagree that improvement is inherent. Really I'm just expressing an aesthetic preference when I say this, because I don't disagree that a lot of things improve. But it's not a guarantee, and it does take people doing the work and thinking about the same thing every day for years. In many cases there's only one person uniquely positioned to make a discovery, and it's by no means guaranteed to happen. Of course, in many cases there are a whole bunch of people who seem almost equally capable of solving something first, but I think if you say things like "I'm sure they're going to make it better" you're leaving to chance something you yourself could have an impact on. You can participate in pushing the boundaries or even making a small push on something that accelerates someone else's work. You can also donate money to research you are interested in to help pay people who might come up with breakthroughs. Don't assume other people will build the future, you should do it too! (Not saying you DON'T)

The problem class is rather very structured which makes it "easier", yet the results are undeniably impressive

But can it count the R's in strawberry?

LLMs in some form will likely be a key component in the first AGI system we (help) build. We might still lack something essential. However, people who keep doubting AGI is even possible should learn more about The Church-Turing Thesis.

https://plato.stanford.edu/entries/church-turing/

  • AGI is definitely possible - there is nothing fundamentally different in the human brain that would surpass a Turing machine's computational power (unless you believe in some higher powers, etc).

    We are just meat-computers.

    But at the same time, there is absolutely no indication or reason to believe that this wave of AI hype is the AGI one and that LLMs can be scaled further. We absolutely don't know almost anything about the nature of human intelligence, so we can't even really claim whether we are close or far.

  • This is a long read on things most people here know at least in some form. Could you pint to a particular fragment or a quote?

> We went from 2 + 7 = 11 to "solved a frontier math problem" in 3 years, yet people don't think this will improve?

This is disingenuous... I don't think people were impressed by GPT 3.5 because it was bad at math.

It's like saying: "We went from being unable to take off and the crew dying in a fire to a moon landing in 2 years, imagine how soon we'll have people on Mars"