ROBBIE LYMAN

In 2020 I was part of the inaugural group of participants in the Women in Groups, Geometry and Dynamics retreat. Since the ball got rolling before COVID hit, the retreat didn't physically happen for more than a year, and we did a lot of meeting on Zoom. Five years later, I think my research group is finally planning to send a draft around to potentially interested experts next week.

One of the things that fascinates me about language is the degree to which the written representation of language does or does not capture the pronunciation. On the one hand you have French, which I don't speak with any skill at all, but do sometimes marvel at comparing text to what I understand to be the correct pronunciation of it. American English of all stripes does this too, of course: easy to imagine somebody tripping over the correct-to-locals pronunciation of placenames like Delhi (NY), Worcester (MA), Wayzata (MN), or Houston St (in Manhattan). On the other you have things like the Hepburn system for romanization of Japanese.

I had some intention of starting a mailing list. I thought maybe I would share musings about songs I like on it. Part of my personal path lately is about finding the right level to aim at. I think a newsletter is higher than I should aim right now; I'm trying to avoid the pride loop. Anyway, here's some songs that were a big part of my January. They're arranged in a reasonable listening order, and I’ll write something about each track, but I'm trying to just press send, since it's almost a week into February now.

I wanted to share a little a-ha moment that I ran into while teaching today.

Over on the lines forum, I snagged the opportunity to be the one who started the yearly goals thread. (Actually, I was hoping that one of the previous posters would have started it, but then suddenly it was almost the new year and the thread had still not started.) I really appreciated these threads over the past couple years. Slightly uncharacteristically, my contribution, which I just wrote today, has very little in the way of specific achievements I'm in pursuit of. Anyway, the purpose of this post is to riff on what I wrote there. (By the way, if you're reading this and would like an invitation to join the conversation, please feel invited to sign up and chime in.)

Seamstress is an "art engine". That's not a term, as far as I'm aware, but I think it describes accurately where I'm hoping to take it. Programmers might be familiar with the concept of a "game engine", like Unreal Engine, Unity, Godot, or Love2D. None of these programs are games, rather, they enable building games by attempting to let a user focus on what is expressive and joyful about making a game rather than what can feel like drudgery.

I started writing Seamstress because I was lonely and a little bored. It grew out of a love letter to the monome norns, a little "sound computer" which orchestrates an inspiring and accessible palette for a truly special community by weaving together SuperCollider, a general-purpose synthesis and musical coding framework, softcut, a powerful audio buffer manipulation library, and Lua scripting for designing sequencers, user interfaces, speaking with external devices, drawing to a screen, and so on.

This is a post inspired by my approach to this year’s Advent of Code, but it does not contain spoilers. Instead I want to talk about how being more “data-oriented” has helped my thinking about coding problems.

I’m doing Advent of Code again this year; so far I’ve been very pleasantly surprised that my facility for solving the problems has improved. (Of course, I’m well aware that the difficulty is likely to ramp up soon, so I may end up eating my words.) Previously, I did the 2023 Advent of Code as it happened in Zig. Pace Loris Cro, who wrote a great blog post on the subject, I think that despite the way Advent of Code problems are at odds with the kinds of software problems that Zig aims itself at solving, doing Advent of Code is a great way to gain familiarity with Zig. Over this past summer I also did the 2022 Advent of Code problems as a way of learning Rust. Today, solving the 5th problem for 2024, it occurred to me that Rust had taught me something surprisingly useful for my Zig solution. The purpose of this post is to talk about what I learned—this post does not contain spoilers for any Advent of Code problems, and indeed is not really “about” Advent of Code at all: as I was writing it, it became clear that part of this blog post actually belongs on the Zig issue tracker.

Today my 15th posting to the arXiv went live! I intend to write about some of the other aspects of that paper elsewhere (possibly another post on this blog), since I think it really clarified something important for me, but I wanted to explain one insight that made a mysterious thing less mysterious to me: “double cosets”.

The purpose of this post is to serve as a reference I can link to. I define topological spaces, sure, but the goal is really to communicate what they feel like, how I think about them, what I think is neat about them.

The purpose of this post is to serve as a reference I can link to. I define groups, sure, but the goal is really to communicate what they feel like, how I think about them, what I think is neat about them.

I’ve heard people observe that although we often think of language as purely a medium for expressing something that exists prior to language, that the words available to us shape who we are as well. I think there’s some truth to this: I took four semesters of Japanese in grad school—not enough to approach fluency without intensive immersion, but plenty to start feeling out the language. I found that at the time my personality as expressed in Japanese was a bit more cautious than I am in English.

It’s interesting to observe that this difference in what I want to express and how is also present for me in programming. Not every language I’ve written a line of has a personality for me yet—mostly this correlates with how seriously I’ve learned what the language has to offer, but interestingly as I’ve improved as a programmer, the personality associations have also started coming faster.

I wrote a little library! The purpose of this post is to advertise its existence.

I’ll go ahead and begin by claiming that generative AI has plateaued, if not already peaked. I might come back to justify that claim later on, but the purpose of this post is to share some musings on generative AI as a tool for accessing expertise.

This summer I spent twelve weeks at The Recurse Center, a self-directed program that describes itself as “like a writer’s retreat, but for programmers”. Many participants write a “return statement” describing and reflecting on their time with the program. The name is a cute little pun: many functions in a computer program finish with a “return statement”, which allows the function to yield a bit of data as a result of the function’s execution. Anyway, this is mine.

In mathematics, if you squint, the word “real” has a kind of eldritch quality. Although calculus students work confidently with them, and they enable all kinds of nice behavior in topology, the definition of a /real number/ is, well, surreal. The title of this blog post is a pun. You might ask why we need the real numbers, and one answer is “for completeness”. For the same reason, I thought a blog post would be useful.