Hot take: I think the em-dash is just lazy punctuation that can be replaced by the more nuanced pauses, i.e. the comma, semicolon, and colon. I think its popularity stems from people being confused on how to use a semicolon.
I never use them to replace a comma, certainly, and only rarely a colon.
I find parenthesis often awkward or too heavy, so may use the m-dash to replace those. Especially if what might have been a parenthetical is going to terminate a sentence, an m-dash is much cleaner, as it doesn't need a closing mark, and a terminating paren right before a period looks awful. For long potential-parentheticals that do terminate before the end of the sentence, the m-dash takes up more visual space and marks the beginning and end more-visibly, making for easier scanning. One ought probably re-write to avoid parenthetical statements most of the time in the first place, when there's time, but sometimes they're desirable for stylistic reasons, or just because one lacks the time to improve a draft.
I also use it as a "classier" version of the ellipsis. It doesn't replace every use, but it replaces very-casual, colloquial use of that mark as a kind of harder-comma. Looks much better, I think, and serves the same purpose.
As for the semicolon, I'd never shy away from the semicolon when I can get away with it, but use them rarely nonetheless. I don't think I ever replace them with the m-dash, though. As inline list separators they're great and an m-dash would be an awful replacement, while as soft-periods, they're fine, though most of the time I just use a full period—but not an m-dash, not if a semicolon could have worked.
I do think they're more at-home in, say, fiction than technical writing, but I like having them in my toolbox in any case.
Yeah. My problem with the em-dash is that it has too many uses (parenthetical statements, independent clause, verbal pauses) and as a reader you don't always know which one is intended until after you've read a bit past the em-dash, and might need to go back and reread the sentence once you figure out how it is supposed to be parsed. Use of semicolon and parenthesis are much clearer in contrast. The comma has the same problem to some extent. I would be happy if we could settle on consistently replacing some specific uses of comma with em-dash to make writing less ambiguous, but in the real world I find it clearer to just avoid the em-dash all around.
I find that I never have a reason to use a semicolon. Every time I typed one, it looked off, and I reformulated into 2 sentences to express things more clearly. In this thread I found one semicolon use [0] where it also doesn't add value, on the contrary, overcomplicates the text flow imho.
My Nintendo Switch 2 Pro Controller didn't work with my Mac, so I had Claude write me a driver. Amazing times we live in. (As long as I still have a job so I can buy controllers in ten years.)
I'm tired of this pseudointellectual reductionist response. It's not "literally by accident" when they're trained to do something, as if we are not also machines that generate next actions based on learned neural weights and abstract (embedded) representations. Your issue is with semantics rather than content.
Obviously "hallucinate" and "lie" are metaphors. Get over it. These are still emergent structures that we have a lot to learn from by studying. But I suppose any attempt by researchers to do so should be disregarded because Person On The Internet has watched the 3blue1brown series on Neural Nets and knows better. We know the basic laws of physics, but spend lifetimes studying their emergent behaviors. This is really no different.
I just kind of wish the behavior for "hallucinations" just didn't have such confident language in the context... actual people will generally be relatively forthcoming at the edge of their knowledge or at least not show as much confidence. I know LLMs are a bit different, but that's about the best comparison I can come up with.
Of course they hallucinate because we are training on random mode. +Since you mentioned 3blue1brown there is an excellent video on ANN interpretation based on the works of famous researchers who attempt to provide plausible explanations about how these (transformers based) archs store and retrieve information. Randomness and stochasticity is literally the most basic components which allow all these billions of parameters to represent better embedding spaces almost hilbertian in nature and barely orthogonal as training progresses.
The "emergent structures" you are mentioning are just the outcome of randomness guided by "gradiently" descending to data landscapes. There is nothing to learn by studying these frankemonsters. All these experiments have been conducted in the past (decades past) multiple times but not at this scale.
We are still missing basic theorems, not stupid papers about which tech bro payed the highest electricity bill to "train" on extremely inefficient gaming hardware.
If someone is nominally trying to convince you of a point, but they shroud this point within a thicket of postmodern verbiage* that is so dense that most people could never even identify any kind of meaning, you should reasonably begin to question whether imparting any point at all is actually the goal here.
*Zizek would resist being cleanly described as a postmodernist - but when it comes to his communication style, his works are pretty much indistinguishable from Sokal affair-grade bullshit. He's usually just pandering to a slightly different crowd. (Or his own navel.)
I usually scroll a page to see how many headings it has, but I'm looking for the opposite. Too many headings is one of the quickest aesthetic clues that I'm looking at slop, as it doesn't require me to read any of the text. (Emojis and over-usage of bullet point lists are the others I can think of in this category.)
I noticed something similar when working with (unlike the post's author, non-marxist, as far as I know) Russian developers who had made the jump abroad (EU).
When debating directions, some of them focused on just never stopping talking. Instead of an interactive discussion (5-15 seconds per statement), they consistently went with monotone 5-10 minute slop. Combined with kind of crappy English it is incredibly efficient at shutting down discourse. I caught on after the second guy used the exact same technique.
This was a long time ago. I have since worked with some really smart and nice russian developers escaping that insane regime. And some that I wish would have stayed there after they made their political thoughts on Russia known.
When you have a 30 minutes meeting with busy people, a single 15 minute monologue might buy you another week to solve your problem.
Indeed, very efficient, usually it requires somebody to put his foot down AND a consensus to deescalate immediately. If you have an antidote, please let me know.
Some ask: "Isn't backpropagation just the chain rule of Leibniz (1676) [LEI07-10] & L'Hopital (1696)?" No, it is the efficient way of applying the chain rule to big networks with differentiable nodes—see Sec. XII of [T22][DLH]). (There are also many inefficient ways of doing this.) It was not published until 1970 [BP1].
The article says that but it's overcomplicating to the point of being actually wrong. You could, I suppose, argue that the big innovation is the application of vectorization to the chain rule (by virtue of the matmul-based architecture of your usual feedforward network) which is a true combination of two mathematical technologies. But it feels like this and indeed most "innovations" in ML is only considered as such due to brainrot derived from trying to take maximal credit for minimal work (i.e., IP).
This misses the point of isospin. Isospin is an approximate SU(2) symmetry due to the fact that the up and down quarks (the "light" quarks) have very similar masses compared to the rest of the quarks, so they can be approximated as two different eigenstates of the same particle. It's mathematically identical to the SU(2) symmetry of a spin-half particle. The reason it doesn't include the other quarks is because they are so much more massive.
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