I would guess almost none, less than single digit percent. Only a small fraction of undergraduate math majors who happen to be interested in algebraic geometry would be able to understand this. The average HN user knows far less math than an average undergraduate math major. Of course there are also math PhDs and the like on here, but vanishingly few compared to the bulk of the site.
This is not true at all. The parameter space is absolutely MASSIVE. The counterexample is a degree 7 polynomial in 3 variables, which means 360 coefficients. There's no particular way to bound these coefficients or even the degree or number of variables apriori, but assume you somehow did. Also assume you were confident that it would work with integer coefficients bounded from -12 to 12. Now you have to iterate over 360 degrees of freedom, verify that the Jacobian is a nonzero constant, and somehow show uninvertibility of the transformation, which is not a particularly simple task.
If you searched for coefficients from -12 to 12, this would be 25^360 = 2 * 10^503 different possibilities. A common reference point is that there are 10^80 atoms in the observable universe. Sure you could probably reduce this a bit with clever tricks, but the starting point makes the method completely unviable, even with the knowledge: A) a counterexample exists, B) it's in 3 variables, C) it's in degree 7 or less, D) it's in integer coefficients, E) those coefficients are 12 or lower.
Perhaps there was something in the prompt or settings preventing this, but I'm surprised (and slightly disappointed) that none of the models approached this the way I would: download an image of the Mona Lisa, run all of the drawing functions many times to construct a forward model of the drawing implements, and attempt to solve some kind of explicit inverse problem through either ML or a classical algorithm to minimize some difference metric. Were they just restricted from running code or are the models unindustrious without a very specific prompt?
As someone who has met a lot of math majors and a lot of CS majors, I am skeptical of your supposition that CS majors are better at finding and applying novel abstractions than math majors who know how to code.
I didn't watch it myself, but there was a recent Netflix documentary on the subject where Magnus claims he was misled by chess.com into believing that they had more concrete evidence than they did.
Why does its use in production matter? Perhaps the syntax itself is obscure, but we're not discussing syntax but general awareness. Anyway, the most common "real" use of brainfuck is to prove Turing completeness of other things by finding a way to compile them into brainfuck.
What? Brainfuck is the single least obscure esoteric programming language. It's the most famous example of a simple Turing complete language and its provocative name gets it a fair amount of media coverage outside its niche.
This is true, but the crushing response to this scandal is clearly disproportionate. Millions of views on videos making crude sexual jokes about a 19 year old is already an incredibly unfortunate situation, and his career got completely halted for years due to (what are now clearly) false accusations.
I have no idea why this continues to be a popular opinion among laypeople. Even at the time actual cheating experts using computer analysis determined it to be likely fair play. His accuracy was rather pedestrian, Magnus just had on off day and played terribly. There is no proposed mechanism for how he could even HAVE cheated. He has continued to perform at a similar level under much tighter security enforcement. The primary accusation seems to be that he's poor at explaining the reasoning behind his moves, but anyone who's ever watched a Hans stream can tell you that the man simply cannot speak.
Regarding general knowledge, it's a pretty well known phenomena within the community. Here's a video with the three players who spent the longest time at #2 in the world (see [0]) behind Magnus Carlsen answering basic trivia questions[1].
A lot of players actually do go to college, although likely a minority. I know that Maxime Vachier-Lagrave in particular has a math degree. Ding Liren has a law degree. Daniel Naroditsky himself, while not quite a top grandmaster by the typical definition, had a bachelors in history.
Slight mistake in equation (1) (or maybe it's supposed to be a narrative decision?), the inner product of Av_i with itself should end up being s_i^2 and not 1. The vectors u_i are orthonormal, but Av_i = s_i u_i, not just u_i.
> Same transformation. Same map on every actual vector. But now it looks like an arbitrary tangle of scaling, shearing, and sign flips — you’d never guess it was just “stretch x by 3.”
I have a very hard time imagining a human writing this if they weren't intentionally attempting to sound like an LLM.
Exceedingly unlikely. This was one of the more discussed Erdos problems, and multiple experts have attested to the technique's novelty. If you're referring to the lack of comments on the erdosproblems website, that doesn't really mean much. From its own blog[0], the site was only started in 2023 and only really gained momentum as a place to discuss AI solving attempts, you aren't going to see serious mathematicians discussing the problems there even if there have been significant efforts to solve it.