But when I do, it usually because of some deeply nerdy, cutting snark. Like this:
As someone who has read thousands of academic papers, I’ll answer those questions as calmly as possible.
NO.
~ “dynomight“, from https://dynomight.net/digits/
…and then it goes on, CAPSLOCKed, for several paragraphs. The only thing better than math-nerds, is when a math-nerd who is also a reason-nerd stomps on the vanilla-variety math-nerds. This stuff? This stuff makes the world a better place.
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What’s a system for fairly dividing— actually… What does “fair” even mean? If we’re dividing up cake, is fair equal size shares? …or shares proportional to each person’s daily caloric requirements? …or their average recent caloric deficit (so starving people get the cake)? And that’s just cake. What if you want to divide up something important, like say, geographically divide a State into voting districts?
In the first step, one party draws districts on the map. However, unlike regular redistricting, in which they draw the exact number of districts needed, our process requires the first party to draw twice that number of half- or sub-districts. Like full electoral districts, these half-districts must have equal populations and be physically contiguous. Many states also have requirements for district compactness, which would apply to this first stage of map drawing too. We also don’t allow “doughnut” districts – where one district is entirely surrounded by another district.
In the second step, the other party chooses how to pair neighboring half-districts into full-size districts.
Even if each party acts entirely in its own interest, attempting to maximize its own chances of winning the most districts, the fact that the process is split into these two stages holds each party’s ambitions somewhat in check.
~ Benjamin Schneer, Kevin DeLuca and Maxwell Palmer from, https://theconversation.com/how-politicians-can-draw-fairer-election-districts-the-same-way-parents-make-kids-fairly-split-a-piece-of-cake-222859
slip:4uteho2.
Like my examples for possible meanings of “fair” for dividing cake, there are many possibilities for what would be “fair” for voting district maps. To date, every solution has been to have some third party (a commission whose composition itself is contentious) draw the maps and then have judicial review (with the judges themselves also being contentious). The system laid out above is brilliant. One side draws up a map, and the other side chooses how to assemble the map into voting districts.
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I love metaphors about hills and valleys. If it’s an uphill struggle, imagine the view. Hills and valleys is a great metaphor for the concept of a local maximum: It’s visually clear (standing atop a hill) and mathematically clear (at a local maximum) that it is “down” in every direction. But only a special sort of hilltop is actually interesting. A hilltop that is really large becomes a flat tabletop. And a hilltop socked in with fog is easily mistaken for not a hilltop. Only hilltops which are pointy enough, and from which we can see other things, are interesting.
[…] our economy—resource allocation based on employment […]—is a local maximum and we cannot expect to arrive at a good outcome without activism.
[…]
But, unless we automate a lot more, we the species will never have enough wealth to offer a decent basic income, and everyone will continue to waste half their lives at work.
~ Gavin Leech from, https://www.gleech.org/automatic/
slip:4ugeau1.
Is it clear that every direction is “down”? Can we see anything else; if we can’t see anything else we can’t be sure this is a local maximum. How can we explore “down” in some of the directions… when we’re talking about global scale culture and human lives?
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In high school I had a class where your final grade was based on a total number of points earned through the semester. The final exam was worth a large portion of the total semester points—let’s say it was 500 of your semester’s possible points. Your percent-score on the exam determined how many of those points you received. (Ace the exam, and you get all 500 points.)
The exam was many hundreds of multiple-choice questions; The exam was so long that no one could ever finish it. The questions had to be shuffled to mix the material taught in the course. Every year the questions were identical, but each year the teacher made a copy of the master list, cut up (yes, with a scissors) the questions, shuffled the strips, and then taped the questions onto a sheet with question numbering, to create a unique Frankenstein-exam every year. This Franken-xam was then photocopied (via a Volkswagen Beetle sized behemoth in the main office) to produce the actual exams.
In the days before the exam, we were told to work at our own pace, to answer each question (skips counted as wrong answers) and to simply stop when time was called. Afterwards, the teacher would calculate the average number of questions attempted by the class. That average was then used as the possible number of questions for calculating our exam scores. (Thus the shuffling to create an exam that is however-long we made it as we took it!) If you went farther than the class’s average attempted number, then you could score some extra points (if you get the answers right, of course) to offset any wrong answers you had along the way. A lot of work to shuffle it every year, but it was a neat idea.
I think it had always worked because kids just didn’t care enough to think it through. We weren’t told the total number of questions, nor what previous classes had attempted. But, for discussion here, let’s say the class’s average-attempted is 200. And let’s say I were to answer 227 questions, but I get 24 wrong. That feels like an 89%, right? No, actually I end up with 203 correct answers, which is more than the class’s average-attempted of 200. I actually score 101.5% and I would get all of the exam’s 500 points towards my semester total. Wait, there’s more: As extra credit, my 3 extra correct answers (my 203 against the 200 attempted average) become extra credit points just added right to my semester total. I’d get 503 points towards my semester!
After the exam was announced, two of my friends and I, realized…
For example, if we could get just 60% right—normally a really poor performance on an exam—while attempting twice as many as the class average, we win big. Say, 200 average-attempted, against our 400 attempted, at 60% correct (240 correct answers of 400)… we’d score 120% on the exam, plus 40 extra points (our 240 correct above the 200 needed) That’s 540 points towards the semester. And, if we could get 75% correct, while attempting 3 times as many questions, then our exam score is 225% (that’s our 450 correct answers, while needing only 200) plus an extra 250 points (that’s our 450, minus the 200 to ace the exam) That’s 750 points towards the semester! Now do you see the attack? :)
I never understood why no one else ever tried that.
I know this is a minor thing in the universe of problems with secondary education and grading, but I found the hack interesting.
~ Bruce Schneier from, https://www.schneier.com/blog/archives/2023/10/hacking-the-high-school-grading-system.html
slip:4usebo19.
…and I’m actually not sure if what we tried even worked. You thought I was going to have a clear take-away about my actual scores, or the test never being given again?! No the take-away is: Oh, I’ve been thinking like a hacker for a Long. Long. Time.
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Inside this box is a thing of beauty—and absurdity. It’s a one-of-a-kind puzzle created just for me by one of the greatest puzzle makers in the world. It is, almost surely, the hardest puzzle ever to exist. But before I open the box, let me tell you how the puzzle came to be, and why I think it’s not a trivial pursuit.
~ A. J. Jacobs from, https://www.theatlantic.com/technology/archive/2022/04/puzzle-will-outlast-world/629651/
slip:4utete5.
There was a time… who am I kidding? The time is now. Must. Resist. The urge. To buy…
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But in our Physics Project we’ve developed a fundamentally different view of space—in which space is not just a background, but has its own elaborate composition and structure. And in fact, we posit that space is in a sense everything that exists, and that all “things” are ultimately just features of the structure of space. We imagine that at the lowest level, space consists of large numbers of abstract “atoms of space” connected in a hypergraph that’s continually getting updated according to definite rules and that’s a huge version of something like this…
~ Stephen Wolfram from, https://writings.stephenwolfram.com/2022/03/on-the-concept-of-motion/
slip:4useoe1.
I’m not sure what to say about this. I am certain that Wolfram is not crazy and that he is brilliant, but he’s pretty far beyond what I can understand. (Picture me doing that slightly askew, squinting thing.) On the other hand, if they really are making the progress they seem to be… it’s going to be a neat time to be alive, in another decade when they get things sorted out.
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However—fourth—over the last century there’s a huge relationship between how rich a country is and the variance in growth. The richest countries have low variance: They all stubbornly keep growing at around the same 1 or 2%. However, middle-income countries vary enormously.
~ “Dynomight” from, https://dynomight.net/gdp/
slip:4udyaa1.
There’s several different interesting threads in this article. But this point about variance leapt out at me. I’m reminded of how just the other day, a piece about statistics that I mentioned was talking about variance (if you clicked through and read the article.) Variance feels like a sort of second-order thinking that I probably should be doing more often.
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For five years as a data analyst, I forecasted and analyzed Google’s revenue. For six years as a data visualization specialist, I’ve helped clients and colleagues discover new features of the data they know best. Time and time again, I’ve found that by being more specific about what’s important to us and embracing the complexity in our data, we can discover new features in that data. These features can lead us to ask better data-driven questions that change how we analyze our data, the parameters we choose for our models, our scientific processes, or our business strategies.
~ Zan Armstrong from, https://stackoverflow.blog/2022/03/03/stop-aggregating-away-the-signal-in-your-data/
slip:4usaso3.
This one just has neat graphs in it. And it has some interesting insights about what data analysts do. The phrase “big data” has been tossed around a lot in recent years—the way “quantum mechanics” gets tossed around by people who have no idea about that either. This article isn’t about truly big data sets, but it’s a neat dive into energy usage as an example of some spiffy data analysis.
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It’s broadly agreed these days that consciousness poses a very serious challenge for contemporary science. What I’m trying to work out at the moment is why science has such difficulty with consciousness. We can trace this problem back to its root, at the start of the scientific revolution.
~ Philip Goff from, https://www.edge.org/conversation/philip_goff-a-post-galilean-paradigm
slip:4ueeco6.
I once had a mathematics professor make a comment that it’s fascinating that mathematics is able to explain reality. I double-clutched at the time. And every single time I think about the point he was making, I still pause and my mind reels. If one is looking at—for example—classical mechanics, and one studies the ballistic equations, one can go along nicely using forces and trigonometry, and understand golf balls and baseballs in flight. Soon you realize your mathematics is only an approximation. So you dive into fluid mechanics, which requires serious calculus, and you then understand why golf balls have dimples and why the stitching on baseballs is strictly specified in the rules. All along the way, mathematics models reality perfectly!
But why? So you keep peeling. The math and physics gets more and more complicated—stochastic processes, randomness, quantum mechanics, wave-particle theory, etc.—as each layer answers another “why”… but it’s … is “cyclical” the right word? No matter how far you go, you can always ask “why” again, for the most complex and most accurate system you model and explain.
Down there at the bottom, that’s where Galileo declared there was a distinction between physical reality, and consciousness and the soul. We’ve had hundreds of years of progress via science on what Galileo divided off as “physical reality.” (And that progress is a Very Good Thing.) But as this article explores, is there actually a distinction? What if making that distinction is a mistake?
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So in a nutshell, Gömböc is cool, Hungarians are proud of it greatly. So naturally, they made a 4.5-ton statue replica of the shape.
~ Atlas Obscura from, https://www.atlasobscura.com/places/gomboc
I could probably write a blog post about other interesting math-related puzzles and shapes that come from Hungary… or about the number of Hungarian mathematicians… but instead, I’ll just point you towards this particularly interesting thing.
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The core idea of Pasteur’s Quadrant is that basic and applied research are not opposed, but orthogonal. Instead of a one-dimensional spectrum, with motion towards “basic” taking you further away from “applied”, and vice versa, he proposes a two-dimensional classification, with one axis being “inspired by the quest for fundamental understanding” and the other being “inspired by considerations of use”
~ Jason Crawford from, https://rootsofprogress.org/pasteurs-quadrant
slip:4uropa1.
I’ve put a bit of thought into research. I’ve certainly considered the two properties of “research for understanding” and “research for application”. But I’ve never thought of them as two dimensions. Click through and check out the simple but illuminating quadrant graph.
And I’m immediately wondering: Can I think of a third dimension upon which to plot research? (Field-of-study comes to mind. Time; The thing being studied, is it something that happens in micro-time like particle physics, or macro-time like geology?) I’m also wondering: what other activities could be plotted in a quadrant? (Writing: insight versus length? Coaching: net change in performance versus time spent training?)
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Our lack of perfect information about the world gives rise to all of probability theory, and its usefulness. We know now that the future is inherently unpredictable because not all variables can be known and even the smallest error imaginable in our data very quickly throws off our predictions. The best we can do is estimate the future by generating realistic, useful probabilities.
~ Shane Parrish from, https://fs.blog/2018/05/probabilistic-thinking/
slip:4ufopo1.
It’s a good article—of course, why would I link you to something I think you should not read?
To be fair, I skimmed it. But all I could think about was this one graduate course I took on Chaos Theory. It sounds like it should be a Star Trek episode. (Star Trek: The Next Generation was in its initial airing at the time.) But it was really an eye-opening class. Here’s this simple idea, called Chaos. And it explains a whole lot of how the universe works. Over-simplified, Chaos is when it is not possible to predict the future state of a system beyond some short timeframe. Somehow, information about the system is lost as time moves forward. (For example, this physical system of a pendulum, hanging from a pendulum… how hard could that be?)
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“You don’t need [machine learning,]” Bryan said. “What you need is inverse Fast Fourier Transform.”
~ “Shift Happens” from, https://www.getrevue.co/profile/shift-happens/issues/moire-no-more-688319
I stumbled over a blog post, containing a pull-quote where someone mentioned inverse Fast Fourier Transform. (A mathematician named Fourier invented a fast way to do a certain sort of transformation that comes up a lot in science; It’s called a Fast Fourier Transform. There’s also a way to undo that transformation, called “the inverse”. Thus, Fast Fourier Transformations (FFT) and inverse FFT. Well, FFT/IFFT is the first thing I can recall that I could not understand. It was shocking. Every other thing I’d ever encountered was easy. But there I was, 20-some-years-old, in graduate school, and I encountered something that was beyond me. I think I had it sorted about 6 times and every time, the next morning, upon waking, it had fallen out of my head. Holy inappropriately long parentheticals, Batman!)
Anyway. Blog post. IFFTs. Time machine to the early 90s. Emotional vertigo.
…and then I clicked thru to the magnificent post which is brilliant. And then I realized the by-line was, “Shift Happens.” o_O This entire thing. I’m in nerd heaven.
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PS: Sorry, what? Oh, you read my title, heard the Italian word, “amore,” and wanted a, That’s Amore! pun? Okay, here: When an eel climbs a ramp to eat squid from a clamp… Yes. Really.
Your ideas are worth less than you think—it’s all about how you execute upon them.
~ Chris Bailey from, https://alifeofproductivity.com/your-ideas-arent-that-unique/
slip:4uaiyo2.
The pull-quote says it all. I recently had a pleasant conversation, wherein the idea of the “why” and the “how” came up. Thanks to Simon Sinek, we all know to, “start with why,” (that is to say, start with the idea.) The idea is important, but it’s literally worthless without the execution. Because anything, multiplied by zero, is zero.
To my 20-something-year-old’s surprise, knowing Al Gebra turned out to actually be useful. Take, for example, evaluating some idea and its execution: The total value could be calculated by multiplying the value of the idea by the value of the execution. (Note my use of, “could be.”) Great ideas are represented by a large, positive value, and terrible ideas by a large, negative value; Similarly for the execution. Great idea multiplied by great execution? Huge total value.
This simple model also shows me how I regularly ruin my life: Terrible idea, (represented by a negative value,) with great execution… Or, great idea, with terrible execution, (represented by a negative value,)… either leads to a large negative total. Interestingly, the slightest negativity—in either of those cases—amplifies the magnitude of the other parameter’s greatness.
This leads to an algebra of idea-and-execution. If you’re going to half-ass the execution, (a negative value,) or you’re concerned that you cannot execute well, it’s better to do so with a “small” idea. Only if you’re sure you can do the execution passably well, (“positive”,) should you try a really great idea. If you work through the logic with the roles flipped, the same feels true. This leads to a question that can be used in the fuzzy, real world: Is this pairing of idea and execution in alignment? Am I pairing the risk of negative-execution align with a “small” idea, or pairing the risk of a bad idea with “small” execution. That to me is a very interesting “soft” analysis tool, which falls surprising out of some very simple algebra.
What I’m not sure about though is what to do with the double-negative scenarios. (Which I’ll leave as an exercise for you, Dear Reader.) Perhaps, I should be using a quadratic equation?
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Over on the Astronomy Stack Exchange site, (obviously I follow the “new questions” feed in my RSS reader,) someone asked if it was possible, without knowing the date, to determine one’s latitude only by observing the sun. These are the sorts of random questions that grab me by the lapels and shake me until an idea falls out.
So my first thought was: Well if you’re in the arctic or antarctic polar circles you could get a good idea… when you don’t see the sun for a few days. Also, COLD. But that feels like cheating and doesn’t give a specific value. Which left me with this vague feeling that it would take me several months of observations. I could measure the highest position of the sun over the passing days and months and figure out what season I was in…
…wait, actually, I should be able to use knowledge of the Coriolis Force—our old friend that makes water circle drains different in the northern and southern hemispheres, and is the reason that computers [people who compute] were first tasked with complex trigonometry problems when early artillery missed its targets because ballistics “appear” to curve to do this mysterious force because actually the ground rotates . . . where was I?
Coriolis Force, right. But wait! I don’t need the sun at all! All I need is a Foucault Pendulum and some trigonometry… Here I went to Wikipedia and looked it up—which saved me the I’m-afraid-to-actually-try-it hours of trying to derive it in spherical trig… anyway. A Foucault Pendulum exhibits rotation of the plane of the pendulum’s swing. Museums have these multi-story pendulums where the hanging weight knocks over little dominos as it rotates around. Cut to the chase: You only need to be able to estimate the sine function, and enough hours to measure the rotation rate of the swing-plane and you have it all; northern versus southern hemisphere and latitude.
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Predicting the behaviour of a sigmoid-like process is not fitting the parameters of a logistic curve. Instead, it’s trying to estimate the strength of the dampening term – a term that might be actually invisible in the initial data.
~ Stuart Armstrong from, https://www.lesswrong.com/posts/6tErqpd2tDcpiBrX9/why-sigmoids-are-so-hard-to-predict
slip:4ulepo4.
Wait! Don’t flee!
It’s a great explanation of sigmoids—you know what those are, but you [probably] didn’t know they have a general name. People toss up sigmoid curves as explanations and evidence all. the. time.
Ever make that slightly squinting face? The one where you turn your head slightly to one side and look dubiously, literally askance at someone? …that face that says, “you keep using that word, but I do not think it means what you think it means.” After you read that little article about sigmoids, you’re going to make that face every time some talking-head tosses up a sigmoid as evidence for a prediction.
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In short, stop optimizing for today or tomorrow and start playing the long game. That means being less efficient in the short term but more effective in the long term. [… I]f you play the long game you stop optimizing and start thinking ahead to the second-order consequences of your decisions.
~ Shane Parrish from, https://fs.blog/2014/10/an-antifragile-way-of-life/
slip:4ufoaa4.
Fundamentally, we humans and our lives are not mathematically tidy.
Aside: I had a math course once—I can’t even remember the material—and the professor said, “it’s a very subtle point that mathematics should model and predict reality.” …or something to that effect. It was mind-bending; but math is part of reality so why wouldn’t reality model itself? *smoke-emits-from-my-ears* The scene, the room, the lighting, everything are burned into my brain.
Heuristics are always and in all cases true but sort of false, because they are imperfect. But the purpose of heuristics is to enable us to wrap our meager brains around the vastly complicated universe. Maths, as in compound interest, exponential growth, 1/r^2 forces, and Fourier transformations, provide models of reality. The comment about second order consequences challenges us to dig deeper into our heuristics, (which are otherwise known more generally as “models.”)
I’ve said this before, here on the blog and out loud: Have you intentionally created the models you have of the world?
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In this situation, before committing to a three year PhD, you better make sure you spend three months trying out research in an internship. And before that, it seems a wise use of your time to allocate three days to try out research on your own. And you better spend three minutes beforehand thinking about whether you like research.
~ ‘jsevillamol’ from, https://www.lesswrong.com/posts/eZCrCB3HiDB55Ccqx/spend-twice-as-much-effort-every-time-you-attempt-to-solve-a
slip:4ulepo11.
This one caught my eye because the vague heuristic of spending increasing amounts of effort at each attempt to solve a problem felt true. But I was thinking of it from the point of view of fixing some process— Like a broken software system that occasionally catches fire. Putting the fire out is trivial, but the second time I start trying to prevent that little fire. The third time I find I’m more curious as to why does it catch fire, and why didn’t my first fix make a difference. The fourth time I’m taking off the kid gloves and bringing in industrial lighting, and power tools. The fifth time I’m roping in mathematicians and textbooks and wondering if I’m trying to solve the Halting Problem.
Turns out the context of the problem doesn’t matter. The answer is, “2.” Every time you attempt to solve a problem—any sort of problem, any context, any challenge, any unknown—the most efficient application of your effort is to expend just a bit less than twice the effort of your last attempt.
Not, “it feels like twice would be good,” but rather: Doubling your efforts each time is literally the best course of action.
…and now that I’ve written this. My brain dredges up the Exponential Backoff algorithm. That’s been packed in the back of my brain for 30 years. I’ve always known that was the chosen solution to a very hard problem. (“Hard,” as in proven to be impossible to solve generally, so one needs a heuristic and some hope.) They didn’t just pick that algorithm; Turns out it’s the actual best solution.
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More than 2,000 years ago, Marcus Terentius Varro, a roman citizen, proposed an answer, which ever since has been called “The Honeybee Conjecture.” He thought that if we better understood, there would be an elegant reason for what we see. “The Honeybee Conjecture” is an example of mathematics unlocking a mystery of nature.
~ Shane Parrish from, https://fs.blog/2013/05/what-is-it-about-bees-and-hexagons/
slip:4ufowa4.
Every once in a while, you will have the chance to be alive when a multi-thousand-year old mystery is solved. Humans are awesome. Mathematics for the win. *drops mic*
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[…] recognize that at least in terms of sheer numbers, the current population is easily outweighed by all those who will come after us. In a calculation made by writer Richard Fisher, around 100 billion people have lived and died in the past 50,000 years. But they, together with the 7.7 billion people currently alive, are far outweighed by the estimated 6.75 trillion people who will be born over the next 50,000 years, if this century’s birth rate is maintained (see graphic below). Even in just the next millennium, more than 135 billion people are likely to be born.
~ Roman Krznaric from, https://blog.longnow.org/02020/07/20/six-ways-to-think-long-term-a-cognitive-toolkit-for-good-ancestors/
slip:4ulosi1.
50,000 years is, of course, somewhat arbitrary. But it’s a good estimate of the span so far of recognizably-like-current-us human history. It’s obvious that today, most people are already dead. It’s those trillion yet to come that warp the brain and create perspective.
This article from The Long Now Foundation has 6 good examples of explicit ways to think long-term, rather than short-term.
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