__mbm__

Kevin wrote a blog post on this topic here: https://www.quantamagazine.org/the-tricky-translation-of-mat...

You're correct: Wired has hyped the original title of the article in Quanta Magazine: "A Path Less Taken to the Peak of the Math World". Any time you see the words "Math Genius" you should assume hyperbole.

If you like this kind of story, I highly recommend putting Quanta (https://www.quantamagazine.org/) on your radar and avoiding most of the tabloid-science articles in Wired.

"A Wavelet Tour of Signal Processing" by Stephan Mallat is pretty good if you've got a background in signal processing at the undergrad EE level. Math heavy CS may require some recollection of linear algebra and numerical algorithms.

Keep it up.

I had a similar experience. Even through my PhD at a top-tier school in applied math, I didn't do "all-nighters" or cram sessions. In fact, after my first 2 years of PhD (where I regularly put in 80 hours a week because of the course load), I toned it down to 40-50 hours. I also didn't use performance enhancing drugs meant to treat things like ADHD.

I did (and still do) use a lot of coffee in the mornings. I also recommend going out to bars to have those petty discussions, so that socializing is reliably separated study.

> Failing at a startup sucks

This. I have a PhD and a failed startup. It felt real bad, and I didn't get that far with it (9 months before calling it quits). Creating a successful startup requires significantly more energy and stress than most science jobs, even for pre-tenure professors.

It requires different skills than science. Few introverts will succeed at founding a company, for example. Moreover, you have to produce actionable results quickly, and you have very different success metrics.

I'm one degree of separation from a PhD startup founder that literally killed himself as his startup imploded, when the company was 5(?) years old. Severe depression, loss of all semblance of a life... these are standard in the world of startup founders. The risk that you destroy your life is real.

Interesting. How does arbital see itself in relation to Wikipedia's math pages? It seems like you are trying to make it more accessible, like the Wikipedia simplified English descriptions

> and there is a risk of Elsevier buying it to shut it down

Yup. I'm still stung by Mendeley's sale to Elsevier.

Anyone have any details? I'm curious how much acqui-hires go for these days.

This confirms Elsevier's status as the most avaricious publisher, accounting for more than one-third of Finland's overall subscription costs. Wiley comes in a distance second at 10%. Many academics, particularly in mathematics, have come to boycott Elsevier's journals due to it's extraordinarily high prices and "all-or-nothing" subscription model. However, due to NDAs that Elsevier forces libraries to sign, confirmed numbers were previously very rare.

Some more information on the boycott appears in [1] and at Tim Gower's blog [2].

[1] http://thecostofknowledge.com/ [2] https://gowers.wordpress.com/2014/04/24/elsevier-journals-so...

Open access repos are available for a number of schools. For Harvard, go to https://dash.harvard.edu/ . For Caltech, you can find all author's work here: http://authors.library.caltech.edu/ . Try googling "<University> open access repository" to see if you can find it.

However, I couldn't get online access for the UC system, even though they have a policy and "plan". I suspect that things just take longer at public universities due to bureaucracy.

Moreover, none of the university repositories I've found do anything close to a good job of making the articles searchable. For example, even though all of my papers are available through Caltech, google only provides links to arXiv or the actual journal. This is actually the problem: if you can't google it, it may as well not be on the open internet at all.

I may be misunderstanding, but the author asserts that Sydney and San Francisco are real (or rather, they have referents), and I'm confused because, in particular, Sydney and San Francisco are real in essentially the same way that numbers are real. Your weight example is more concrete, but I was trying to make the point that it suffers (at a less apparent level) the same problem.

So... the assertion is that physical things are real and numbers are not? It's alluring to accept this axiom, but when challenging a platonic view of mathematics, I don't think that we should accept that without discussion.

In other words, I'm supposed to entertain that math is a fictional tale with fanciful characters called "numbers" that don't exist outside of the story, but the boundaries of so-called physical objects are so apparent that they shouldn't be questioned?

Most physical boundaries are arbitrary, part of the stories that we tell ourselves, and not meaningful in a deep sense. I'd like to know how mathematics, and numbers in particular, are different.

[As an aside: Is it possible to convincingly argue that "this is larger than that" without using numbers?]

> if you want to say something is true, you always need to know what difference it makes.

Absolutely. It seems that fictionalism avoids both the "in some sense" qualifications and worrying about what difference it makes by asserting that statements out of context are simply false. While consistent, I'm similarly not convinced that its useful.

It is interesting to interpret the body of mathematics as you would a collection of fictional tales. However, the philosophy begins to unravel (to me) when it asserts that "8 is larger than 5" is false while "Sydney is larger than San Francisco" is true because the latter statement "has referents".

What is it that makes Sydney and San Francisco real objects with meaningful sizes while 8 and 5 are not real and do not have meaningful sizes? Sydney and San Francisco are defined by political and legal "stories" in the same way that 8 and 5 are defined in mathematical "stories". The theory only seems to be consistent if all out-of-context falsifiable statements are taken to be false.

This theory placates me, since it leaves the truth value of mathematical statements (in the context of the mathematical story) to mathematicians. However, it renders any conclusions meaningless to mathematics, even if it is meaningful for a philosophy dealing with human stories.

This article appears to be bent on buttressing an anti-scientific religious viewpoint rather than improving science. (Read the last few paragraphs.) The conclusion strikes the same themes that I've seen many times in the religious anti-science movement: science is a religion, a cult, etc.

Sure, statistics are difficult and can lead to incorrect conclusions, but that's why we make sure that a scientific claim is falsifiable. The fact that we can test the claims are where much of the power lies. Let's not forget that a few centuries of the scientific method have made human lives so much better than millennia of religion.

This relates closely to the [Darpa Spectrum Challenge](http://archive.darpa.mil/spectrumchallenge/) that I participated in a couple years ago. The goal was to transmit information in a congested and contested RF environment. I think that they wanted to develop rapid spectrum-aware sensing as well as hard-to-jam signals.

This is the crankiest comment I've seen on HN in a while. You "know Fields medalists"? Right.

You think that Pricipia Mathematica is the source of all truth in mathematics? Wrong. Most mathematicians working on foundational questions start out by learning Zermelo-Fraenkel set theory, which is well-understood, and avoids several difficulties that Russel had. While few people have read PM, it remains important because it goes through the hard task showing that high-level mathematics (calculus, &c.) can have rigorous, first-principle proofs.

"PM is like a compiler before there were compilers." What?

"I asked a math professor about the '=' sign and how things can be equal at all (...)" OMGWTFNO. I've seen comments like this before. Typically, it creates debate around a non-issue by sowing confusion and never nailing down precisely what we are talking about (hence the need for formal methods—it helps us call bullshit on comments like this).

"Two things are equal iff their transformation leads to the origin. [A - B = 0]". Wrong. There are equality relations that do not require the existence of a zero or the concept of addition or subtraction.

I don't really see a compelling case for this method. The empirical convergence rates are clearly polynomial, while subspace iteration (e.g., Krylov) are "in theory" exponential and in practice pretty good. There is a bit of hand-waving about why Kyrlov methods are not as good (the theory is supposedly not robust to noise), but the techniques for robustifying Krylov-type subspace iterations, such as restarts, are pretty mature.

More than that, the method actually appears to be an iterative "prox" method. These things are very well studied in the convex analysis literature. I wouldn't be surprised if this already appears as a special case of an algorithm in the literature somewhere.

For the official announcement, where you'll hear all of the sound bytes you'll be reading later today, you can get to the livestream from Caltech's website here https://www.caltech.edu/

Starts in 2 minutes.

Thanks for the edit. Of course an even number isn't prime ;)

# Run Miller-Rabin on the prime in the blink of an eye:

from gmpy2 import mpz, is_prime

p_list = [0xCC, 0x17, 0xF2, 0xDC, 0x96, 0xDF, 0x59, 0xA4, 0x46, 0xC5, 0x3E, 0x0E, 0xB8, 0x26, 0x55, 0x0C, 0xE3, 0x88, 0xC1, 0xCE, 0xA7, 0xBC, 0xB3, 0xBF, 0x16, 0x94, 0xD8, 0xA9, 0x45, 0xA2, 0xCE, 0xA9, 0x5B, 0x22, 0x25, 0x5F, 0x92, 0x59, 0x94, 0x1C, 0x22, 0xBF, 0xCB, 0xC8, 0xC8, 0x57, 0xCB, 0xBF, 0xBC, 0x0E, 0xE8, 0x40, 0xF9, 0x87, 0x03, 0xBF, 0x60, 0x9B, 0x08, 0xC6, 0x8E, 0x99, 0xC6, 0x05, 0xFC, 0x00, 0xD6, 0x6D, 0x90, 0xA8, 0xF5, 0xF8, 0xD3, 0x8D, 0x43, 0xC8, 0x8F, 0x7A, 0xBD, 0xBB, 0x28, 0xAC, 0x04, 0x69, 0x4A, 0x0B, 0x86, 0x73, 0x37, 0xF0, 0x6D, 0x4F, 0x04, 0xF6, 0xF5, 0xAF, 0xBF, 0xAB, 0x8E, 0xCE, 0x75, 0x53, 0x4D, 0x7F, 0x7D, 0x17, 0x78, 0x0E, 0x12, 0x46, 0x4A, 0xAF, 0x95, 0x99, 0xEF, 0xBC, 0xA6, 0xC5, 0x41, 0x77, 0x43, 0x7A, 0xB9, 0xEC, 0x8E, 0x07, 0x3C, 0x6D]

p = mpz(0) # Edit: should be zero, not 1

for num in p_list: p = (p << 8) + num

print("Q: Is p a prime?\nA: %s" % (is_prime(p) and 'Yes' or 'No'))