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No usage stats, no tracking, no illusions of mass adoption. The only real signal we get is the occasional person who appears in our Matrix chat going "hey, it booted on my watch from 2014 and now it's usable again" — and that's plenty.

Privacy is non-negotiable: zero telemetry, no cloud, full local control. Longevity is the other half: we refuse to let good hardware become e-waste just because support ended. On the learning side, it's been one of the best playgrounds: instant feedback on your wrist makes QML/Qt, JavaScript watchfaces and embedded Linux feel tangible. The community is small and kind — perfect for people who want to learn open-source dev without gatekeeping.

Technically we're still pragmatic: libhybris + older kernels on most devices since it just works, but we've already mainlined rinato (Samsung Gear 2) and sparrow (ASUS ZenWatch 2) — rinato even boots with a usable UI. That's the direction we're pushing toward.

Repo: https://github.com/AsteroidOS Install images & docs: https://asteroidos.org 2.0 demo video : https://www.youtube.com/watch?v=U6FiQz0yACc Announcement post: https://asteroidos.org/news/2-0-release/

Questions, port requests, mentoring offers, criticism, weird ideas — all welcome. We do this because shaping a tiny, open wearable UX and infrastructure is oddly satisfying, and because Linux on the wrist still feels like a playground worth playing in.

Cheers, the AsteroidOS Team

https://www.anthropic.com/claude-sonnet-4-6-system-card [pdf]

https://x.com/claudeai/status/2023817132581208353 [video]

For nearly a year, this community drove so much traffic that we couldn’t list patients fast enough. Then pg saw us on HN, wrote us our first big check, and accepted us as the first YC nonprofit (W13). The next few years were a whirlwind.

I was a young, naive founder with just enough experience to know I wanted Watsi to be more efficient, transparent, and innovative than most nonprofits. We spent 24/7 talking to users and coding. We did things that don’t scale. We tried our best to be walking, talking pg essays.

Over the years we learned that product/market fit is different for nonprofits. Not many people wake up and think, "I'd love to donate to a nonprofit today" with the same oomph that they think, "I'd love a coffee" or "I'd like to make more money."

No matter how much effort we put into fundraising, donations grew linearly, while requests for care grew exponentially. I felt caught in the middle. After investing everything I had, I eventually burned out and transitioned to the board.

I made a classic founder mistake and intertwined my self-worth with Watsi's success. I believed that if I could somehow help every patient, I was a good person, but if I let down some patients, which became inevitable, I was a bad person.

This was exacerbated by seeing our for-profit YC batch mates raise massive rounds. I felt like a failure for not scaling Watsi faster, but eventually we accepted reality and set Watsi on more of a slow, steady, and sustainable trajectory.

Now that I have perspective, I'm incredibly proud of what the org has accomplished and grateful to everyone who has done a tour of duty to support us. Watsi donors have donated over $20M to fund 33,241 surgeries, and we have a good shot of helping patients for a long time to come.

In a world of fast growth and fast crashes, here's a huge thank you to the HN users who have stuck by Watsi, or any other important cause, even when it's not on the front page. I believe it embodies the best of humanity. Thanks HN!

[1] http://news.ycombinator.com/item?id=4424081

What it does

    Design UIs visually with a flexible canvas –like Figma–.
    Define app logic with a visual, instruction-stacked editor inspired by Shortcuts.
    Live preview apps directly on the canvas –no separate preview window–.
    Publish working web apps with one click.

Why we made it

    Modernize the HyperCard idea: combine layout, behavior, and instant sharing in one place.
    Reduce friction between design and a working app.
    Make simple web apps approachable for non-developers while keeping power features for developers.
    Build a foundation for LLM integration so users can design and develop with AI while still understanding what’s happening, even without coding experience –in progress!–.

Try it –no signup required–

Weather forecast app: https://app.breadboards.io/playgrounds/weather

Swiss Public Transit: https://app.breadboards.io/playgrounds/public_transit

info: https://breadboards.io

I would appreciate any feedback :)

111011011111110101111101111

and give this output:

101101110111101111101111111

I.e., it's sorting the array [3,2,7,1,5,4]. The machine has 31 states and requires 1424 steps before it comes to a halt. It also introduces two extra symbols onto the tape, 'A' and 'B'. (You could argue that 0 is also an extra symbol because turinmachine.io uses blank, ' ', as well).

When I started writing the code the LLM (Claude) balked at using unary numbers and so we implemented bubble_sort.yaml which uses the tape symbols '1', '2', '3', '4', '5', '6', '7'. This machine has fewer states, 25, and requires only 63 steps to perform the sort. So it's easier to watch it work, though it's not as generalized as the other TM.

Some comments about how the 31 states of bubbles_sort_unary.yaml operate:

  | Group | Count | Purpose |
  |---|---|---|
  | `seek_delim_{clean,dirty}` | 2 | Pass entry: scan right to the next `0` delimiter between adjacent numbers. |
  | `cmpR_*`, `cmpL_*`, `cmpL_ret_*`, `cmpL_fwd_*` | 8 | Comparison: alternately mark units in the right (`B`) and left (`A`) numbers to compare their sizes. |
  | `chk_excess_*`, `scan_excess_*`, `mark_all_X_*` | 6 | Excess check: right number exhausted — see if unmarked `1`s remain on the left (meaning L > R, swap needed). |
  | `swap_*` | 7 | Swap: bubble each `X`-marked excess unit rightward across the `0` delimiter. |
  | `restore_\*` | 6 | Restore: convert `A`, `B`, `X` marks back to `1`s, then advance to the next pair. |
  | `rewind` / `done` | 2 | Rewind to start after a dirty pass, or halt. |

(The above is in the README.md if it doesn't render on HN.)

I'm curious if anyone can suggest refinements or further ideas. And please send pull requests if you're so inclined. My development path: I started by writing a pretty simple INITIAL_IDEAS.md, which got updated somewhat, then the LLM created a SPECIFICATION.md. For the bubble_sort_unary.yaml TM I had to get the LLMs to build a SPEC_UNARY.md because too much context was confusing them. I made 21 commits throughout the project and worked for about 6 hours (I was able to multi-task, so it wasn't 6 hours of hard effort). I spent about $14 on tokens via Zed and asked some questions via t3.chat ($8/month plan).

A final question: What open source license is good for these types of mini-projects? I took the path of least resistance and used MIT, but I observe that turingmachine.io uses BSD 3-Clause. I've heard of "MIT with Commons Clause;" what's the landscape surrounding these kind of license questions nowadays?