Smooth model progress can create sudden capability jumps

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 28:41

   As Boris Churny famously said, coding is solved. And many people are just like, holy shit, over, I think, winter break, we're just like, wow, AI is really, really good at this now. So there's been this kind of these moments of big jumps in abilities. And you actually said internally, as you just said, it's actually been this very smooth progression of AI power that happens to cross some threshold where now we can do something.

2. 28:53

   Speak a little bit about that. you know, there's a term for this, which is sort of this idea of emergence, which is it seems like two things are true at once, like there's this predictably smooth trend. And then, you know, before, like Opus 4.5, I really couldn't let Claude, you know, cook too much on my code without a short leash. And then after Opus 4.5, I could. And so that's weird, like, I feel like you would expect a more gradual transition. And the mental model I have for this is, you know, there's kind of two ways of looking at it. So there's the way that I talked about briefly just earlier, where it's like, if you're just doing this kind of next token prediction, you could imagine that, you know, all the text in the world has sort of like easy words and medium words and hard words in terms of

3. 29:37

   how hard they are to predict. And so as you're going down this curve, first, you know, the model is bad at everything. And then at some point, it gets all of the easy words right. And that means, you know, maybe the easy words are like the structure of sentences. And so the model, like, all of a sudden can write coherent sentences, you know, but just one sentence at a time. And so it's kind of cool and impressive, but like, we can't really do anything with that. And then maybe the medium words are sort of, yeah, these sort of basic facts about the world. And as the model smoothly gets better at predicting words, at some points, it predicts most of the medium words, right? And now all of a sudden, it can write coherent sentences and sentences that are true.

4. 30:14

   And so now maybe it's helpful to like write emails, maybe it's helpful to sort of like, help you write drafts of blog posts right even though that was like a smooth improvement it just takes it taking over to be helpful and then i guess the hard words which maybe are like you know your select domain expertise like science or code um and another way to look at it is it's a question of kind of how many of these words do you get right and how many do you get wrong you know um once you get to the point where you're getting like i don't know maybe 90 percent of the medium words right then you're useful as like an email writer but if you're at 50 percent it's it's like you're it's actually wasting my time to to use you because i'm just gonna have to go in and fix it half the time but if i have to go in and fix it you know 10 percent of time

5. 31:03

   it's better or five percent of time it's better what different tasks have a difference or like reliably thresholds. But you smoothly improve, and then at some point, it's just reliable enough to be good. And again, for me, my lived experience is basically exactly that, which is at some point, I was just using the models to help when I was stuck. I would just talk to them, and then they would never write my code. And then at some point, they could write small snippets of code basically all the time. And so now I don't write small snippets. And at some point, they could write large snippets.

6. 31:35

   Like this year, basically, Claude has taken on most of my code writing. And that's because it went from doing that correctly, I don't know, 80% of the time, which was not useful, to 99% of the time, which now is useful. And so this combination of smooth improvement, and then each different task has a different threshold, at which now it becomes solved, I think gives you these big jumps, even though we're just smoothly going down that scale.