bbeonx

i was talking to opus the other night about the polio vaccine related stuff (i had been arguing with one of those people who claims the polio vaccine didn't work so i figured i'd use it as an excuse to brush up on some bio/history). i asked it to explain how polio virus was isolated pre PCR and claude hard killed my session citing security reasons (it was talking about stool samples ffs LOL)

i think there are a few reasons.

- lean proofs are hard, and a lot of the time there is so much mathematical machinery that folks are working on that you would need to not only prove your result, but also all of the machinery that your subfield it is built on. it would be infeasible for many authors to do all of this work (this might be a major part of multiple careers, and when there are 5 folks in your entire subfield, the payoff is not really worth it)

- human proofs are readable, and can illustrate concepts better than lean proofs. human proofs give insights into how to think about a type of problem, and this is often the most valuable part of a proof/result.

- lean proofs are often very difficult to read; while they give you a "verified" check mark, they do not necessarily improve the bounds of human understanding if that makes sense.

lol yeah we're doomed

i can kinda get how a glp-1 can be a miracle drug for weight: if we assume that simple molecular fixes to problems will eventually be found by evolution, then when we change our environment rapidly (e.g., with cheap bountiful calories) then this presents an opportunity for a miracle drug, since evolution will take some time to find the fix.

but for something like reducing disease infection, i find it a lot harder to understand why we don't create this naturally unless there is some equal-but-opposite cost that we'd incur, or if there is not actually as big of a benefit as we believe (or if this is all just colinear with the weight loss stuff).

note: i have no background in any of this and have no idea what i'm talking about

these might not be 100% complete, but i think this does a reaaalllly good job at capturing the vast majority of mathematics.

i'm sure you could come up with another breakdown, but these also have the benefit of tracking roughly with history. numbers and geometry (euclid), then eventually algebra. probability was a fundamentally new way of looking at the world. analysis comes via newton/leibniz and then dynamics tries to tackle complex systems (kinda where newton left off, e.g., 3-body problem type stuff).

also: dimension reduction is not a bad thing. this is like a decomposition: we can decompose so much of what research mathematics is doing into 6 different basis elements. that's pretty darn neat.

(edit: liebnitz -> leibniz)

agreed! it's funny, i'm returning to some of the maths i studied in undergrad with a bit more "worldly" knowledge (if you can call comp sci academia knowledge "worldly"), and i'm seeing that so so much of the stuff that was confusing was actually just trying to frame really intuitive properties. of course, the language to do so rigorously can be very dense and terse and difficult to get through, but at the end of the day, mathematicians are often trying to do some very simple things.

for example, intuitively, i and j are _basically_ the same "shape" as one another, and f and c and s and v are _basically_ the same "shape" as each other, but the two sets of shapes are definitely _not_ the same as one another...to quantify this and actually capture it in math you gotta do topology, and once you get past the point set stuff it gets real abstract real fast. but they really just wanna say "hey, my donut kinda looks like my coffee mug".

It seems like you might be inventing a form of non-monotonic logic. Check out answer set programming, it actually does exactly what you want of "unlearning" facts that you've learned. Not sure if it helps in your particular instance, but it's very cool stuff and IIRC there is an implementation that extends datalog. https://en.wikipedia.org/wiki/Answer_set_programming

yeah, i've studied a lot of math and a lot of cs, and stats is tough. part of the problem is the terminology, and just giving a ton of complex machinery without telling you what it's actually doing. i've never learned that way, and it is very easy to feel like you're doing some sort of dark magic.

also, probability theory vs statistics is an important distinction: prob theory is a nice clean mathematical subject, while statistics is almost the philosophy of applying probability theory to the world.

i mean, the headline statistic can be misleading, but you gotta dig in and wrestle with the details. just like anything, we cannot boil down complex things to single numbers and expect any sort of meaningful signal. we gotta roll up our sleeves, look at definitions, think about what our actual questions are, how we might answer those questions through measurements and observations, and what the confounders are. i think a common issue folks have with stats is that they expect a tidy answer, and it just doesn't do that: it's more of a way to prove the world...the results still need some interpretation.

> At the time, my professor closed the final lecture with dramatic words (I'm paraphrasing slightly):

>>> And now you've learned that almost all interesting problems are undecidable and of the remaining ones, almost all are NP-hard. For the project of computer science, that puts the final nail in the coffin.

> Sheesh. Not sure if everyone got such a dire framing but that would explain.

Honestly, this is what makes computer science fun.

is it?

I think I'd put it this way: if I could flip a switch tomorrow and the AI boom was done, I probably would. The negative effects just super duper outweigh the fact that coders are more efficient. But since it exists, I'm going to use it. Hacking on my own small projects isn't using that many resources. But the benefit simply isn't worth the cost, as much as I personally love using LLMs.

there are some things that clearly exist that are really hard to nail down with definitions; once we get into anything social, we are kinda playing with that territory. everything is so fuzzy that our normal way of defining things breaks down. so saying precisely what gender _is_ is going to be almost impossible. but there are definitely roles and traits that are highly correlated with a person's birth sex that are distinct from their birth sex. there can even be genetic reasons why those correlations emerged. but they are still distinct.

as evidence, what it _means_ to be a man, woman, etc, differs from society to society. if you ask me to quantify this precisely, i will struggle. but it's plain for all to see.

sorry, is this in response to my post? in which case, this is exactly the distinction i'm making. the entire argument is whether or not there _is_ a distinction; my point is that this guy just, a priori, decides gender doesn't exist. but there is plenty of evidence that it does. there are plenty of social traits associated with sex that differ across different cultures: pink used to be a manly color, now it's a feminine color; "be a man" doesn't literally mean "make sure your sex is male"; etc. there are traits that are heavily correlated with a person's sex that are culturally reinforced, and this is distinct from their sex.

yeah, the argument is ridiculous; like, formally, it is ridiculous. i also disagree with the sentiment and conclusions of the argument, but the actual form of the argument is garbage: "i introduce an axiom that says there is no gender and therefore the distinction between sex and gender doesn't exist".

the first post was a swipe, i'll grant you. probably shouldn't have said it. it was a knee-jerk reaction to a structurally fallacious argument that leaves no room for discussion: "i reject your stance not based on reason, evidence, or anything that you can interact with, but based on an new presupposition i've just now decided is true". though i'll admit the severity of my knee jerking was probably amplified by some of the other opinions he holds.

the second post is actually about (a) me having understanding for a position of someone i disagree with harshly, and (b) the logical structure of an argument, not the underlying topic itself. it was in reference to the content of the link that was posted.

anyway, mods can take it down, i get why the rules are there. you're also right to ask folks to keep it clean. but i stand by it; dude just seems to have a trifecta of awful traits and i'm so so so tired of super rich tech dudes ruining the world.

wait this is kinda brilliant tho

Thank. Too much word, me try read but no more tokens.

this is true, "black" has been used in racist ways, but it got rehabbed and reclaimed in the 60s and 70s.

but more to the point, it is not currently used in a racist manner by the vast majority of the US, and certainly does not carry the same connotations as "yellow", so not really comparable imo

"yellowsky" sounds racist because calling asians "yellow" is racist.

"whitesky" sounds racist because...well, i don't know if you're a big history buff but in the US white-people-only gatherings were always suuuuper racist.

agreed...i think it's fine to keep up with what the corporate world is doing, but these projects bring me real joy

This isn't really a metric. It's a description to help the reader understand the magnitude of effort that went into this project. SLoC is a bad metric for plenty of things, but I think it's fine for quickly conveying the scope of a project to a blog reader.

Followed closely by "The Breadboard Has Been Drinking"

chill, be nice

You're presuming that every phrase was worded _just so_. This could very well have been from the author refactoring their sentence and not simplifying everything. They probably were thinking in these terms (the author is a PL guy from MSR who's pretty heavy into a lot of the formalism) and this sounds like a not-perfectly-polished formal thought.

It's technical, and sometimes technical writing isn't written perfectly. That doesn't mean it's due to willful obtusity, or trying to sound smart.

Meh, it's usable w/out github but you'll be reading raw markdown files (unless you get your own markdown renderer which isn't that big of a deal). But yeah, it's either an incomplete git-based wiki or a complete github based wiki.

I found In My Room to be an incredibly moving album. Djesse left me feeling far less after a first listen, but when I returned a few days later I started to notice things I had missed and now I really enjoy that album as well.

I am very moved by his music, in large part because of its cleverness. At the same time, I completely understand why many people are left unmoved. Different strokes, I guess.

This is going on all of my homeworks (submitted electronically, of course)

Pizza gate is an extreme. But also, yes, news has changed dramatucally over the last couple of decades and older generations maybe don't consume as defensively as younger generations. Over time this can make ridiculous things sound plausible.

I remember there was a trump meme going around where he supposedly said "if I ever ran for president it would be as a republican, they are all a bunch of morons". The first time I saw that it looked sketchy as hell, but both of my folks (intelligent people, mind you) bought it hook, line, and sinker. In general, it's younger people that I saw citing it as a fake while older people shared it. Totally anecdotal, I'll grant you, but I hardly think my experience is unique

I don't know, I might push back here. While fake news can certainly be interpreted as news that is false, that is not how it is usually used. There is definitely an insinuation, and while the vanilla reading of the definitions of "fake" and "news" don't contain this insinuation, it exists none the less.

That being said, as a writer I might not be able to resist pointing out the irony that the paper on fake news was fake news :). I really can't fault the author.