Aperiodic Chevron Tessellation, designed by me
Did you hear? Someone discovered an aperiodic monotile! Obviously, these are origami life goals. And, I’m making it out like a joke, but I’m pretty sure I’m not the only origamist who was thinking that.
Oh, but this origami isn’t the aperiodic monotile. Instead, I read their paper, and was inspired to create a different aperiodic tiling. And in the mean time, I learned how an aperiodic tile ticks.
In my time as a puzzle enthusiast, one of the puzzles I encountered was called the ant and the rubber band. It was only later that I realized that this puzzle had some cosmic significance.
Problem Statement
We have an ant that is trying to crawl from one end of a rubber band to the other. But as the ant crawls, the rubber band also stretches out. The ant crawls one centimeter per second. The rubber band starts out one meter long, and stretches out one meter per second. This is one of those magical math rubber bands that can stretch indefinitely. Let’s just say the ant is mathemagical too. Will the ant ever reach the end?
At first glance, it looks bad for the ant. The ant crawls crawls one centimeter closer, but falls a whole meter back. So the ant is losing about 99 cm per second. That doesn’t sound like a path to victory.
While I’m on the subject of bad puzzles from 1995, I want to briefly share one of my favorite good puzzles from the time. Around 1995, I received a book titled 100 Perceptual Puzzles by Pierre Berloquin. It’s apparently a newer edition of an older book titled 100 Geometric Games, copyright 1976.
The book contains a wide variety of puzzles, mostly of the sort that rely on pictures, or require you to draw pictures. Many people are familiar with the puzzle where you have a 3×3 grid of dots, and you’re asked to draw four straight lines through all the points without lifting your pencil. That puzzle is not in this book, and instead it includes multiple harder versions!
Other puzzles include: mazes, spot the difference, match moving puzzles, shape counting puzzles, and knot puzzles. The knot puzzles! I will share one knot puzzle.
Effective Altruism (EA) is a community focused on donating money to create the greatest good in the world. This is mostly (?) unobjectionable–but there’s problems. The EA community has a number of philosophical viewpoints that most external observers would consider absurd, and which materially affect their donating behavior.
In particular, many people in EA believe that the most efficient way to create the greatest good is by preventing extinction caused by AI. EA surveys suggest that about 18% of community members donate to “Long term & AI” causes, compared to 62% that donate for global health & development. Clearly concern about AI is not a unanimous viewpoint in EA, but you have to imagine the kind of community where everyone takes it seriously.
EA has been under the spotlight in current news because Sam Bankman-Fried–recently arrested for massive fraud at his cryptocurrency exchange FTX–was a vocal proponent of EA. More than a vocal proponent, he founded the FTX Future Fund, which committed $160M in charitable grants to various EA causes. At the top of Future Fund’s cause list? AI.
Although I’m critical of EA, I actually think it’s a bit unfair to pretend that they’re directly responsible for SBF’s fraudulent behavior. Instead I wanted to focus on some of SBF’s philosophical views, which are shared by at least some parts of the EA community. Specifically, let’s talk about the idea that charitable causes are risk-neutral.
Among music-likers, it’s often said that your musical tastes are defined by what we enjoyed at age 14, or that our favorite music came out when we were 14. This claim comes from a 2018 article in the New York Times titled “The Songs That Bind” (paywalled). This article contains dubious statistical analysis, and its claims are probably false.
The article uses Spotify data, “on how frequently every song is listened to by men and women of each particular age.” There are two distinct ways of analyzing this data:
So let’s read the article carefully and determine which analysis was used.
[Read more…]
Data science has an increasing impact on our lives, and not always for the better. People speak of “Big Data”, and demand regulation, but they don’t really understand what that would look like. I work in one of the few areas where data science is regulated, so I want to discuss one particular regulation and its consequences.
So, it’s finally time for me to publicly admit… I work in the finance sector.
These regulations apply to many different financial trades, but for illustrative purposes, I’m going to talk about loans. The problem with taking out a loan is that you need to pay it back plus interest. The interest is needed to give lenders a return on their investment, and to offset the losses from other borrowers who don’t pay it off. Lenders can increase profit margins and/or lower interest rates if they can predict who won’t pay off their debt, and decline those people. Data science is used to help make those decline decisions.
The US imposes two major restrictions on the data science. First, there’s anti-discrimination laws (a subject I might discuss at a later time) (ETA: it’s here). Second, an explanation must be provided to people who are declined.
This is the final part of a series introducing xenharmonic music theory. In the first part, I talked about musical perception, especially the perception of microtones. In the second part, I explained roughness theory, which is an empirical theory of dissonance independent of musical tradition. The first two parts overlap with conventional music theory, but in this third part, I finally reach the music theory that is more particular to the xenharmonic tradition.
I’m just going to scratch the surface here, with an eye towards how you would actually use it in practice, if you were a composer. Most readers, I imagine, are not composers. It’s okay if it’s just a hypothetical for you, as long as you learn something.