I haven't been posting publicly lately. Instead I've been juggling mental and physical health (and seeing some improvement, thankfully)—quietly learning more low level stuff, writing some code, and reading graduate math texts. And making time for jazz music studies. But the last few months have been interesting. A lot of good security research has been making the rounds on twitter lately—like SandboxBear's OpenSSL bug—as well as bugs in authentication protocols (looking at you SPNEGO).
But computer science is a domain extending far before and beyond sillicon. All of nature is math. Everything can be abstracted into component parts. It's machines all the way down—brains, language, computers—even art. But sometimes it seems as though one could pick a niche subdomain in any field, spend an entire lifetime there, and still have only chipped away at the tip of the iceberg.
It's true that all things have finer details. And those details sometimes necessitate specialization. But conversely, the real rub here is quite perverse—the real trick to specialization arises from the ability to generalize.
But yet it's easy to make things hard and hard to make things simple. There is much to learn and seemingly little time. My attention span often feels schizophrenically scattered across all of the domains—taking in all of reality at once, whether I want it or not, rather than watching it frame by frame. On one hand, this has helped me develop as a human being. But on the other hand, it is the very thing that ails me. My methodology for studying is idiosyncratic and irreverent.
I've a sort of disorder where I can't stop seeing patterns wherever I look—and I'm often unable to repress this. I ruminate far more than I should. This is the source of much of my anguish, but also much of my hope. Luckily I've at least learned to (mostly) not autistically say the quiet parts out loud. But there is no doubt a secret world underneath this one. As it is in physics, so it is with the whole of nature—language, ideas, systems, and so on. To quote Dan Kaminsky: "You don't incrementally learn a system. You eventually unlearn its necessary lies."
While I have been lurking for sometime, I've only been taking things seriously since 2020. There's room to grow. Looking forward to publishing new research soon. Onward to a winter of code, among other things.
No comments:
Post a Comment