It's funny, I considered quoting this other part as well:
> The big prize is to discover a new fractal bud. You notice a crack in the surface of knowledge, pry it open, and there's a whole world inside.
The nature of fractals is that everything is a new fractal bud. There's really endless complexity everywhere. So I don't think that alone is the "big prize". There's some other dimension, like utility or interest. Because I get that discovering a new subfield of topology is different from discovering the new sounds you can make banging on your stove. But it's not just that one has more to it than the other.
Real world problems with disparate fields involved are a rich of source of "medium sized" fractal buds by this unnamed measure. No one is dedicating their life to your application of measure theory to data dashboards, but it's meatier than searching in the absurd and easier to find than breaking ground in pure theory.
Here's another dimension: try convincing others of this while they're discussing a specific object level problem and see how that goes.
Is it that it would be hard to convince people there's endless complexity in this domain while they're deciding what to get for lunch? Yeah, probably. They're too hungry.
If you haven't read this (not LLM related), I highly recommend it: https://statweb.stanford.edu/~cgates/PERSI/papers/thinking.p...
With the very present danger that many feel that a couple youtube videos is as deep as they ever need to go.
Being able to gauge how deep and broad you have to go for each difficulty you encounter has become an important skill. But polymath seems very possible.
I really believe that this is the best time to be a polymath, or at least have a broad spectrum of knowledge and references to look into and pull information from; and that being a true generalist that can dive as deep as needed enables you to build great stuff. But maybe that’s just my experience.