jstrieb

Wow, I'm seriously impressed! Questions for the author:

I haven't had a chance to read the code yet, but how does this actually adjust the text? I get that it uses Knuth-Plass to calculate layout, but what does it do in CSS (or SVG?) to apply the layout to the DOM?

Looks like the first commit was sometime last week, which is pretty tight turnaround for something like this. For my own sanity when reading the code (no judgment either way), did you use LLMs to help write this? Knowing is helpful for me to calibrate what I pay attention to when reading through the code.

I agree with the spirit of what you're saying: that many aspects of this post seem unnecessary. But I do think there are reasonable answers to your (admittedly probably rhetorical) questions.

Zig is a relatively young language with a small community, and Oven/Bun is one of few places that someone could previously have written Zig code professionally. It's therefore Zig's business to make sure that either it's a good place to refer community members for work, or that they don't explicitly encourage people to work there. Likewise, as one of the highest-profile Zig projects, the community's leaders were understandably invested in making sure it represented the language well.

I feel like I am exactly the target audience for this post: someone who uses Zig regularly, but hasn't touched Bun, despite being aware of it. While I would have proceeded differently than Andrew Kelley here in terms of framing and phrasing (and leaving out some parts entirely), I do think reading this gave me new information about Zig's relationship to Bun. The specific dry, professional post you suggest wouldn't have given me any new information at all.

This is awesome!

I do want to point out that the data in that ClickHouse playground only seems to go as far back as April 6, 2024 according to the query below:

  SELECT * FROM hackernews_history ORDER BY update_time ASC LIMIT 10

The best exploration of this that I have seen in media is one of my favorite movies: Nightcrawler (2014), starring Jake Gyllenhaal. The movie doesn't touch on the government/democracy aspect of the article, but it very much captures the notion that desparate people can be pressured to do horrible things when their job is at stake.

In Nightcrawler, some characters are trying to get ahead, and others are desperate not to fall behind, but their opportunism (driven by the necessity to make money in order to survive in our capitalist society) makes all of them vulnerable to exploitation by an ambitious psychopath. In that case, he is profit-motivated, whereas the article here is about dictators retaining power, but the same principles apply. The movie does an amazing job of exploring how these individuals can wield power irresponsibly, poison everyone who gives them an inch, and sound almost reasonable while they do it. It is a masterful portrayal of how much some people can be willing to compromise on their morals for their job.

If you haven't seen it, you should watch it. If you have seen it, but don't remember it being deeply critical of capitalist society, you should re-watch it. (It's easy to get so engrossed by the truly suspenseful and thrilling moment-to-moment action that you miss the big picture.) The deterioration of American news media is a more overt theme in the movie, but in my opinion, that serves as a complementary backdrop to the anticapitalist message, which is the engine that drives the movie inexorably onward. Also the acting, directing, and writing are great.

Don't spoil it by reading the plot summary, just watch it.

https://en.wikipedia.org/wiki/Nightcrawler_(film)

I like currying because it's fun and cool, but found myself nodding along throughout the whole article. I've taken for granted that declaring and using curried functions with nice associativity (i.e., avoiding lots of parentheses) is as ergonomic as partial application syntax gets, but I'm glad to have that assumption challenged.

The "hole" syntax for partial application with dollar signs is a really creative alternative that seems much nicer. Does anyone know of any languages that actually do it that way? I'd love to try it out and see if it's actually nicer in practice.

Thanks! I also told Aga via email in the thread where I submitted my article.

Worth noting that the HTML tag in the title was stripped from the PDF table of contents as well, so the title for that article in the contents is missing a word. No big deal, but good to know for future submissions!

The article I submitted has an HTML tag in the title, and seems to have broken the web viewer :(

Note that you can link to pages in a PDF with a hash like #page=64 (for example) in the URL.

https://pagedout.institute/download/PagedOut_008.pdf#page=64

Wow, this is jam-packed with interesting information. Thanks for writing it! (Also thanks for all of your other great open source work!)

Are there plans to upstream this into the Zig std library? Seems like it could be useful for more than just the cryptography package, since the benchmarks at the end have it often being faster than std pdqsort. I just checked the issue trackers on Codeberg and GitHub, and didn't see anything mentioning djbsort or NTRU Prime, which leads me to believe there aren't (official) plans to upstream this (yet).

If those announcement posts don't take off, how do you end up finding a community of users/players?

I consider Recursion by Blake Crouch to be similar, even though I liked Antimemetics much better. I haven't read Crouch's other books, but have heard that Dark Matter is better than Recursion, though it may be less similar to Antimemetics.

Nice fork! (I am the person who wrote the original.)

My version is still working well for me, so it's been hard to find motivation to update it. Also, I've been using my increasingly limited free time to work on some exciting new projects, rather than maintenance tasks that feel like a continuation of my day job.

All that to say I'm excited about new repos like yours that take the idea further! I also really appreciate your attention to detail calling out the differences with the original, and that you licensed your version under the GPL.

As an aside, you may want to add "Show HN" to the title. It will allow the page to show up on https://news.ycombinator.com/show

https://jstrieb.github.io

Maybe I missed it, but I didn't notice a submission of yours in the jam. Did you end up getting around to doing your solo project?

The rest of the games submitted to this very interesting, somewhat niche game jam (including my own entry) are here:

https://itch.io/jam/langjamgamejam/entries

There were some really impressive submissions in spite of the short time frame!

Hey, I wrote this! There are a couple of reasons that I included the disclosure.

The main one is to set reader expectations that any errors are entirely my own, and that I spent time reviewing the details of the work. The disclosure seemed to me a concise way to do that -- my intention was not any form of anti-AI virtue signaling.

The other reason is that I may use AI for some of my future work, and as a reader, I would prefer a disclosure about that. So I figured if I'm going to disclose using it, I might as well disclose not using it.

I linked to other thoughts on AI just in case others are interested in what I have to say. I don't stand to gain anything from what I write, and I don't even have analytics to tell me more people are viewing it.

All in all, I was just trying to be transparent, and share my work.

This project reminds me of Matt Might's work (predating LLMs) on using techniques from Precision Medicine to help his son, who had a rare disease.

https://www.youtube.com/watch?v=Rt3XyeFHvt4 (poorly transcribed here: https://www.janestreet.com/tech-talks/algorithm-for-precisio...)

If I recall correctly, he used miniKanren along with formalized, structured data extracted from medical research. Unfortunately, his son has since passed away.

Note that this article is by the same Greg Egan who wrote Permutation City, a (in my opinion) really good, deeply technical, hard science fiction novel exploring consciousness, computation, and the infinite nature of the universe.

If that sounds interesting, I recommend not reading too much about the book before starting it; there are spoilers in most synopses.

https://en.wikipedia.org/wiki/Permutation_City

You don't necessarily need a background in programming and theoretical computer science to enjoy it. But you'll probably like it better if you already have some familiarity with computational thinking.

Probably worth me revisiting! Web tech has changed a bit since I last investigated this in 2021, and I'm also not sure if I considered options like IndexedDB at the time.

This post recommends the Newsit extension to view Hacker News discussion associated with a page.

In the same vein, a few years ago, I made a Firefox extension for users who want a privacy-preserving way to see if pages have associated HN discussion:

https://addons.mozilla.org/en-US/firefox/addon/hacker-news-d...

Most other extensions probably hit an external API (such as Algolia) to check submission status, which means they send every page you visit to that API. Instead, my extension uses Bloom filters compiled from every link ever submitted (updated daily from the Hacker News BigQuery dataset) to check the current page's submission status. By using Bloom filters, my extension only hits the API when you click the button to view the discussion.

Source code here:

https://github.com/jstrieb/hackernews-button

Feel free to pull the Bloom filters from the "Releases" section of that repo on GitHub to use in other projects if you'd like!

Here is the other video we've released so far if anyone is curious:

https://youtu.be/z09X_ZnAcLs

Happy to take recommendations for other stuff to drop in there and film!

Also if this sounds cool to you, we're hiring US citizens.

https://redballoonsecurity.com/company/careers/

I'll let the right people know, thanks to you and the YouTube commenter!

What a funny, positive way to point out our error.

LLMs are trained on text, only some of which includes facts. It's a coincidence when the output includes new facts not explicitly present in the training data.

The point from the end of the post that AI produces output that sounds correct is exactly what I try to emphasize to friends and family when explaining appropriate uses of LLMs. AI is great at tasks where sounding correct is the essence of the task (for example "change the style of this text"). Not so great when details matter and sounding correct isn't enough, which is what the author here seems to have rediscovered.

The most effective analogy I have found is comparing LLMs to theater and film actors. Everyone understands that, and the analogy offers actual predictive power. I elaborated on the idea if you're curious to read more:

https://jstrieb.github.io/posts/llm-thespians/

This teardown is great!

At my work, we have an X-ray machine for PCB reverse engineering. On Fridays we throw in random stuff from around the office, and sometimes make videos about what we find inside.

A few weeks ago we released an X-ray teardown of several other, older chargers. Very interesting to compare with these fancy new ones!

https://youtu.be/4h4qabPsPfI

Haven't tried it myself, but this official-seeming website suggests that you can schedule a test call ahead of time with your local 911 call center.

https://www.911.gov/calling-911/frequently-asked-questions/#...

I implied that on purpose. I'm generally hesitant to anthropomorphize LLMs, but in this case, I disagree with you that they don't have intention. They were developed to output likely tokens, and tuned such that their big tech developers approve the output. That is their intention. Their one and only intention.

That being said, I completely agree on the agency point. They don't make decisions, and certainly don't "think" like people.

Still, I believe the benefits of the analogy outweigh the potential loss of nuance here.

I have been explaining LLMs to friends and family by comparing them to actors. They deliver a performance in-character, and are only factual if it happens to make the performance better.

I just posted a full write up of the idea to HN: https://news.ycombinator.com/item?id=45103597

Nobody that I'd be using this analogy with is currently using LLMs for tasks that are covered by RLVF. They're asking models for factual information about the real world (Google replacement), or to generate text (write a cover letter), not the type of outputs that are verifiable within formal systems—by definition the type of output that RLVF is intended to improve. The actor analogy is still helpful for providing intuition to non-technical people who don't know how to think about LLMs, but do use them.

Also, unless I am mistaken, RLVF changes the training to make LLMs less likely to hallucinate, but in no way does it make hallucination impossible. Under the hood, the models still work the same way (after training), and the analogy still applies, no?

I have been explaining this to friends and family by comparing LLMs to actors. They deliver a performance in-character, and are only factual if it happens to make the performance better.

https://jstrieb.github.io/posts/llm-thespians/

Even if you don't read the article, and even if (like me) you don't particularly care about coin collecting, you should still scroll to the bottom for the cool photos showing how the designs became more abstract over time.