[This is not a very charitable post, but that’s why I’m putting it in shortform because it doesn’t reply directly to any single person.]
I feel like recently there’s been a bit of goalpost shifting with regards to emergent abilities in large language models. My understanding is that the original definition of emergent abilities made it clear that the central claim was that emergent abilities cannot be predicted ahead of time. From their abstract,
We consider an ability to be emergent if it is not present in smaller models but is present in larger models. Thus, emergent abilities cannot be predicted simply by extrapolating the performance of smaller models.
That’s why they are interesting: if you can’t predict some important pivotal ability in AI, we might unexpectedly get AIs that can do some crazy thing after scaling our models one OOM further.
A recent paper apparently showed emergent abilities are mostly a result of the choice of how you measure the ability. This arguably showed that most abilities in LLMs probably are quite predictable, so at the very least, we might not sleepwalk into disaster after scaling one more OOM as you might have otherwise thought.
A bunch of people responded to this (in my uncharitable interpretation) by denying that emergent abilities were ever about predictability, and it was always merely about non-linearity. They responded to this paper by saying that the result was trivial, because you can always reparametrize some metric to make it look linear, but what we really care about is whether the ability is non-linear in the regime we care about.
But that’s not what the original definition of emergence was about! Nor is non-linearity the most important potential feature of emergence. I agree that non-linearity is important, and is itself an interesting phenomenon. But I am quite frustrated by people who seem not to have simply changed their definition about emergent abilities once it was shown that the central claim about them might be false.
A bunch of people responded to this (in my uncharitable interpretation) by denying that emergent abilities were ever about predictability, and it was always merely about non-linearity. They responded to this paper by saying that the result was trivial, because you can always reparametrize some metric to make it look linear, but what we really care about is whether the ability is non-linear in the regime we care about.
I was one of those people. Can you point to where they predict anything, as opposed to retrodict it?
I’m confused. You say that you were “one of those people” but I was talking about people who “responded… by denying that emergent abilities were ever about predictability, and it was always merely about non-linearity”. By asking me for examples of the original authors predicting anything, it sounds like you aren’t one of the people I’m talking about.
Rather, it sounds like you’re one of the people who hasn’t moved the goalposts, and agrees with me that predictability is the important part. If that’s true, then I’m not replying to you. And perhaps we disagree about less than you think, since the comment you replied to did not make any strong claims that the paper showed that abilities are predictable (though I did make a rather weak claim about that).
Regardless, I still think we do disagree about the significance of this paper. I don’t think the authors made any concrete predictions about the future, but it’s not clear they tried to make any. I suspect, however, that most important, general abilities in LLMs will be quite predictable with scale, for pretty much the reasons given in the paper, although I fully admit that I do not have much hard data yet to support this presumption.
[This is not a very charitable post, but that’s why I’m putting it in shortform because it doesn’t reply directly to any single person.]
I feel like recently there’s been a bit of goalpost shifting with regards to emergent abilities in large language models. My understanding is that the original definition of emergent abilities made it clear that the central claim was that emergent abilities cannot be predicted ahead of time. From their abstract,
That’s why they are interesting: if you can’t predict some important pivotal ability in AI, we might unexpectedly get AIs that can do some crazy thing after scaling our models one OOM further.
A recent paper apparently showed emergent abilities are mostly a result of the choice of how you measure the ability. This arguably showed that most abilities in LLMs probably are quite predictable, so at the very least, we might not sleepwalk into disaster after scaling one more OOM as you might have otherwise thought.
A bunch of people responded to this (in my uncharitable interpretation) by denying that emergent abilities were ever about predictability, and it was always merely about non-linearity. They responded to this paper by saying that the result was trivial, because you can always reparametrize some metric to make it look linear, but what we really care about is whether the ability is non-linear in the regime we care about.
But that’s not what the original definition of emergence was about! Nor is non-linearity the most important potential feature of emergence. I agree that non-linearity is important, and is itself an interesting phenomenon. But I am quite frustrated by people who seem not to have simply changed their definition about emergent abilities once it was shown that the central claim about them might be false.
I was one of those people. Can you point to where they predict anything, as opposed to retrodict it?
I’m confused. You say that you were “one of those people” but I was talking about people who “responded… by denying that emergent abilities were ever about predictability, and it was always merely about non-linearity”. By asking me for examples of the original authors predicting anything, it sounds like you aren’t one of the people I’m talking about.
Rather, it sounds like you’re one of the people who hasn’t moved the goalposts, and agrees with me that predictability is the important part. If that’s true, then I’m not replying to you. And perhaps we disagree about less than you think, since the comment you replied to did not make any strong claims that the paper showed that abilities are predictable (though I did make a rather weak claim about that).
Regardless, I still think we do disagree about the significance of this paper. I don’t think the authors made any concrete predictions about the future, but it’s not clear they tried to make any. I suspect, however, that most important, general abilities in LLMs will be quite predictable with scale, for pretty much the reasons given in the paper, although I fully admit that I do not have much hard data yet to support this presumption.