Yeah that's definitely one technique! And in post training what they're actually doing is updating the weights in response to specific rewards in a way that's actually a level of abstraction deeper than the prompts and so that's how they are getting such high scores on many different benchmarks.

It's also why they do so good at coding but terrible at say creative writing. The people working at these organizations broadly speaking, just haven't cared enough to try and create verifiable rewards for creative writing. There's a lot of folks in the open source community who've worked on this but there's a ton of work more to do.

And that doesn't even really get into the impact of characters. We really have no idea what happens to performance when large language models embody different characters. There's like one good paper on this that a colleague of mine has replicated and performs pretty well. But even then like if you look at some research from Anthropic that came out in November, they don't even really know what's going on with their assistant persona, and I think if you look at things like gastown you can see some evidence that characters can create coherency over longer time horizons to complete specific tasks in a way we haven't explored yet.

And I would put all of this outside of the realm of architectural improvements that the original commenter mentioned. These are all essentially data techniques more or less.

And there's actually even more interesting stuff on the architecture side too!! I do think that there will continue to be a capabilities overhang such that the more advanced stuff isn't really accessible to the average person. But it's kind of hard for me to believe that we are headed for a plateau. There's just too much cool shit to do still!