Whether to do constant npm upgrades to keep the high-priority security issues count at zero (for what seems like about 15 minutes), or whether to hang back a bit to avoid catching the big one that everyone knows is coming real soon now.

Not enjoying npm at all.

But given a choice between a 20 year old spy thriller involving a Prime Minister who retired 25 years ago, and a dead man, versus a revealing exposure of the dystopia we are all going to be living in imminently (whether Chinese or American), I think the balance tips toward the current winners.

A good choice though. Maybe next year.

The AI techno-luddite crowd is an example that comes to mind.

For the meantime, I use forbearance. But it is a shame that one cannot steer conversations in interesting directions because of the tyranny (such as it is) of the few . I rather like the idea of a sacrificial account, to be honest.

And one would hope that professional software engineers who are writing actual production code are doing more than relying on what was covered in their undergraduate algorithmics course. As a professional, I, personally, think that you have a duty to keep your education up to date by keeping up with academic advances (or at least being savvy enough to go to the literature when dealing like problems like this one). This particular academic paper provides a highly specific implementation of a specific algorithm. But it also provides about five techniques that I'm going to add to my profession arsenal of code-optimization techniques.

I do understand that general criticism that academic researchers do often seem to have curious underdeveloped coding skills. But that's not a criticism one can lay against the this particular academic (member of a research group at ETH Zurich, in case you missed that). He's providing code that concretely provides dramatic optimizations for AVX512 specifically, on a machine architecture that has 512-bit cache lines; but that doesn't detract from the generality of the techniques he's putting forward.

And probably worth mentioning that this is not an isolated instance. There are a number of papers I have used to write production code that provide similar levels of concrete detail for machine architectures that are no longer concretely relevant. A paper that documents a clever SIMD optimization for some IBM mainframe or another (not actually sure which) that provides performance improvements for DFTs that turned out to be usable on ARM NEON comes to mind.

These sorts of skills are what makes the difference between excellent software developers and merely mediocre ones over the arc of a career where one often has to go beyond merely what one was taught as an undergraduate.

The obvious exception in the western system would be the blues scale, which arguably has 9 tones (7 equal tempered notes, plus a just tempered 3rd and 7th).

And Indian ragas break all of these rules. They have scales that don't have 8 notes, scales that don't use equal temperament, and even a few scales that don't repeat on octaves.

Digital sound production, however. Yes. There's all kinds of thoroughly unpleasant mathematics, none of which you actually need to know unless you're writing computer music software.

(I write computer music software, and I am also a jazz musician).