To me, mastery would be if you can use mathematics to trivialise an implimentation in a counter intuitive way. I understand that this is a different kind of mastery. But does the essay write code that is a sign of mastery, or does it just use the byte code as a talisman? I don't follow the code so I wouldn't know.
I think it counts as mastery, precisely because it does choose a thing so counterintuitive that it's past what most of us would even think of as a possible solution.
I spent many years writing Java, but never took the time to learn how to write the bytecode (that's why we have a compiler ...). I know that Clojure lets you call Java classes, but it's a completely crazy, magical, frightening, and awesome thing to see someone do it by writing their own class loader, and then writing their own class -- in bytecode! -- to load, when the _simplest_ and clearest solution would be far from that.
It's a bit like solving FizzBuzz with Tensorflow: terrifying on at least some level, as it makes it so clear that there's so much more depth I could be learning, yet exciting for almost the same reasons.
> It's a bit like solving FizzBuzz with Tensorflow
I had to wiki that, but it's a good point. The first thing about NN that interested me, rather than images or audio or anything like that, is that a one level NN (IIRC) can approximate any function (by adding more and more nodes to that level).
I guess the point is also that any really deep rabbit hole is in some sense better than a selection of random 1000 rabbit holes.
To me, mastery would be if you can use mathematics to trivialise an implimentation in a counter intuitive way. I understand that this is a different kind of mastery. But does the essay write code that is a sign of mastery, or does it just use the byte code as a talisman? I don't follow the code so I wouldn't know.