peterkos

Someone did it! https://hachyderm.io/@samhenrigold/115159295473019599

This reminds me of those videos where the bar staff try blind pouring a shot, and it's wild how good some people are. Would love to see a similar competition, re: can the most senior store members be accurate to 1° :)

I'm imagining a spectrum between "has to be slow" and "needlessly slow", with a middle slider for that one razor where things take as much time as you give them.

Intentionality is a big theme in math research (so i've heard), where solving "useful" problems isn't the ideal goal. The goal is to solve interesting problems, which might seem useless, but along the way achieve results with much wider implications that would have been impossible to discover directly. Or, how inventions like toothpaste came from space travel research.

(rhetorically) Does an indirect result "justify" a longer, slower project? Is speed an inherent property of the problem, or is it only knowable once it's complete? Or both, in the cases of misused funds?

"Users experiencing issues connecting to Slack and unable to load threads" - https://slack-status.com/2025-05/7b32241eb41a54aa

After reading this, I am now of the belief that software is, actually, a good thing. And that programming can be enjoyable.

Seriously, this does such a good job of capturing the feeling of MAGIC that code is capable of -- both in its process and in its output. Textbook "craft". It's hard to experience that sometimes when surrounded by dependency hell, environments, build systems, certain dynamic programming languages, and the modern web ecosystem.

What is the benefit of this over something like Pkl[0]? Pkl compiles down to JSON, YAML, etc., but the language itself is user-friendly. This way you get best of both worlds: readable and editable for humans, and parsable for computers.

[0] https://pkl-lang.org

That's a pretty egregious mistake for a designer to make -- and that's not even mentioning the lack of accessibility. WebAIM's contrast checker says it's a 1:1 contrast ratio!

If someone is releasing a model that claims to have a level of reasoning, one would hope that their training dataset was scrutinized and monitored for unintended bias (as any statistical dataset is susceptible to: see overfitting). But if the graph on the announcement page is literally unreadable to seemingly anyone but the creator... that's damning proof that there is little empathy in the process, no?

It may not sound like much, but this was a lot of work. I spent days just thinking about this problem, trying to understand what is happening now and how to improve it.

I find these kinds of problems the most fun and the most educational! I tried building a grid layout system from scratch in SwiftUI, and it was similarly tricky to map out:

- what the "ideal" behavior one expects is,

- what edge cases exist,

- how to handle the edge cases,

- maintaining ideal behavior while handling edge cases.

(It was tricky b/c SwiftUI lays out its children, then its parent -- so the parent needs to ask its children for its view size, and iterate and set rows/columns that way.)

Maybe because the problem seem simple, it is that much more fun to dig into. Some good ol' time with a whiteboard.

Cabinette[0], a macOS app for musicians/producers to manage their music catalog. My WIP folder has about 75 songs, ranging from electronic/orchestral/piano, and I wanted something with dedicated filtering, tracking progress over time, and pretty drag/drop. So... I built it!

Currently in TestFlight, but 1.0 is launching soon :) Feel free to give it a spin, and drop thoughts on the feedback board.

(Another idea I'm starting is an easy-learn, hard-to-master, productivity app: split calendar and todo list, with fluid drag/drop and power user features. Targeting the iPad at first, and will hopefully bring to more platforms. Keep an eye on my website[1] for launch!)

[0] https://cabinette.app

[1] https://peterkos.me

I'm reminded of a time that an intern took down us-east1 on AWS, by modifying a configuration file they shouldn't have had access to. Amazon (somehow) did the correct thing and didn't fire them -- instead, they used the experience to fix the security hole. It was a file they shouldn't have had access to in the first place.

If the intern "had no experience with the AI lab", is it the right thing to do to fire them, instead of admitting that there is a security/access fault internally? Can other employees (intentionally, or unintentionally) cause that same amount of "damage"?

I like thinking of CS theory as "math, with more hand-waving". Or, I can't remember where I read it, but something about CS being the mathematics of asymptotes.

The first image on the marketing page is an AI-generated picture of a person staring back. At best it's unsettling, and at worst it makes me wonder how authentic of a user experience the app can offer. Above-the-fold, first landing page content is valuable real estate. Ethically/copyright-ambiguous, inauthentic marketing is a strange thing to value imo.

This looks a lot like Swift. To me, that's a good thing :)

According to the article/filing, she wasn't given specific reasons for the demotion, treated discriminatorily, and given a PiP that was unattainably difficult.

One would assume that choosing to file litigation against Amazon would be done thoughtfully / with a plausible rate of success; they have an army of lawyers. What informs the opinion that a PIPed employee isn't worth even listening to, esp. from a lawsuit? Amazon is not exactly a shining star for work culture, and this situation doesn't sound unfathomable.

I like the alternative this implies of dreaming in 2D :p

What’s your use case? I’d imagine the macOS display extending is wildly cool.

I think it more targets the “apple enthusiast”, or at least the “tech enthusiast”, who is used to paying a $$$ premium (at the cost of polish) to be the First at a new thing. Every company does it but Apple has a strong pattern of “v1 is setting up for v2” — e.g., the original iPhone being expensive af with no apps, but getting 3G and apps the next year.

Also, I’d wager the people buying this can mostly Certainly afford it, given how expensive it is. For those people the money is meh, or justified (business expense, app platform). For others who are Maybe affording it, returns seem like an easy failsafe if it doesn’t meet expectations.

These models aren't actually doing any musical comparison -- they are trained on audio, and from audio, piece apart with a "note" and a "melody" and an "instrument" are from the labelled training data. No intentional theory is being done!

Algorithmic music composition has usually been split into two:

1. Generate notes (re: theory, genre)

2. Generate sound

(i.e., EMI[0], Kulitta[1], MusicNet[2])

Now we are doing both at the same time, and backwards. The model isn't (necessarily) going "write melody, then generate the sound", but rather, "here are 500 songs that are described with X, 500 with Y, and you want XY, so we'll combine these two" :)

(This is my best understanding, so feel free to correct)

[0] http://artsites.ucsc.edu/faculty/cope/experiments.htm

[1] https://hackage.haskell.org/package/Kulitta

[2] https://zenodo.org/record/5120004

also, common capitalization mixups: "ID vs. Id", "snapshot vs. snapShot", "username vs. userName"

A little manual, but music21[0] can do the analysis!

[0] http://web.mit.edu/music21/

They used to have this in Seattle (Car2Go (Merc), and ShareNow (BMW)) but they had a messy back-and-forth acquisition, shutdown, then apparent resurgence?

I recognize that it could be a helpful and rigorous experience in sales, but most car people I've gone to across dealerships have tried to guilt trip and lie to me to get me to spend more money than I have. As a student paying full in cash, I was pushed ruthlessly despite firmly saying no, and ultimately I got my car somewhere else.

It reminds me how Best Buy used to have horrible customer experience, it was all commission-based, and you would be hounded when first walking in the store. Then Apple came along with the model of "don't force someone to do anything, and the right product for them might not be in the store, and that's fine". (Notably, Best Buy seems to have gotten better since.)

No source control? There's "it works" and then there's "they got lucky enough to not implode yet".

From course homepage:

Most course material is covered in video lectures recorded in 2010 (already watched by over 350,000 people), which you can conveniently play at faster speed than real time. There may also be some new material presented by the professor and/or guest lecturers, which will be recorded for asynchronous viewing.

They may have meant "2010s"?

I use CleanShot X, which gives me a ton of easier options for this stuff (and the nostalgia from Skitch) -- highly recommend, included with Setapp too.

I was really desperate to contribute to an open-source project in high school, specifically an iOS or frontend web one, and it was hard to find projects that I could make a substantial contribution to. Many with `good first issue` tags were not very active, and the ones that were active were hard to get my foot in the door.

I was able to do a variety of "good first" things: readme updates, typo fixes, adding small features -- but it was hard to feel really _validated_ that my work was valuable, or that contributing to open-source was an impressive thing to do, because I (felt like I was) was surrounded by engineers, and nobody ever told me that OSS was "cool", until I met a company 3 years into college who valued OSS (more than just "wow, great job, you fixed a typo!")

I really liked the story of Celeste, not super deep but the gameplay is super smooth, and the art is gorgeous. It has the perfect balance of being difficult but not difficult enough to get mad at (except a few levels...).

I used to go there a ton and I wanted to see if there were any good deals, see if my go-to was in stock, accumulate rewards, and check hours if I went to a new store. The app theoretically provides the "best" experience as well -- I've yet to see a mobile website recently for something I use day-to-day that isn't trying to push me towards the mobile app, or was clearly never tested on a real device. (Obviously, that's the ideal, but such is the state of things.)

The website didn't really suffice because the UX was bad, and wrestling with it got tiring. Apple+Google's hours were never quite correct.

In high school my favorite resource was the Calculus (9E?) textbook by Larson. Super thorough in the explanations, there were tons of practice problems and step by step solutions on their website (no subscription needed iirc) for odd # problems.

My biggest struggle was skipping some of the basics and having to go back and re-learn after really struggling. But struggling helped in a way because then I really understood why X or Y solution didn’t work. If there’s anything i’d suggest, it’s that once you get some confidence in solving problems, try to approach new ones without looking through the entire lesson first, and that will help the actual way to solve the problem really stick. (And it’ll help you ask more focused questions!)

The reposts are what made me the most frustrated. I got really tired of seeing the same stuff keep cropping up literally every two or three days

My philosophy is to never browse reddit as a "whole" but instead just go to specific subreddits for what I need. It's been 10x more "normal" and each subreddit has a better balance between full of snarky replies (r/programmerhumor) or more helpful (r/rust) rather than the more popular ones (r/funny, etc.)