oneearedrabbit

Cold turkey. More than seven years ago, on my way home, I stopped at T-Mobile and bought a random flip phone. I still own that same phone. https://news.ycombinator.com/item?id=21929194

Just a few minor updates to my original post:

  - Low-res photos are perfectly fine for my purposes
  - I don't need Google Maps when I'm on the go
  - Quick fact checking is not important
  - One day, I ripped off the band aid and migrated all auth keys to Yubikey
  - Tethering is occasionally useful

Edit: some things never change--I still haven't learned how to format a bulleted list here.

You are not a slow thinker. You are a deliberate thinker. "Slow" suggests laziness; while "deliberate" implies careful consideration.

Decades ago, a closure in Forth was especially innovative with DOES>:

  : COUNTER
    CREATE ,
    DOES> DUP 1 SWAP +! @ ;
  0 COUNTER PK
  PK .  \ => 1
  PK .  \ => 2

A semi-equivalent in Javascript is:

  const counter = init => {
    let x = init;
    return () => { x += 1; return x; };
  };
  const pk = counter(0);
  console.log(pk());  // => 1
  console.log(pk());  // => 2

This is curious. It took approximately 19 hours to turn a HN thread into an article. What does this tell about the speed of information?

Tangentially related, since you are exploring hexagonal and triangular grids; I once caught a space-filling curve bug and decided to port ideas from https://tixy.land to fractional dimensions: https://oneearedrabbit.github.io/l-sys-playground/curves/ind.... After all, why not?

While both MJ and Turnstyle are Turing-complete, Turnstyle shares more similarities with Piet (mentioned by the author), Wireworld, and, of course, Conway's Game of Life.

Neat trick. I found that I had to wrestle with Notes more than necessary, but if I were to pick up the project again, I would approach it differently this time:

- Notes function similarly to tweets, and, by definition, cannot by customized much. They are like cute little memos or a river of news where less is more.

- I thought it would also be cool, if within Notes I could subscribe to memos from my friends. Whoa, Apple Notes as a social network! As you are already familiar with Apple Notes structure, it won't be a surprise that it is not difficult to add content to special folders automatically (I built a prototype, which sadly never published.) However, this topic raises a bunch of important questions, and I don't remember whether I found all the answers. It's been a while.

Two years ago I got carried away and built a tool with a code name "notespub". It is the very same idea, albeit less polished. I documented my journey of extracting content out of Apple Notes, which naturally has been published with Notes as well [1].

I thought this was a cute idea; however, as I started using it more, I inevitably learned that there are features that are hard to mingle in Notes alone, i.e. custom themes, metadata, automatically generated home page, top/side navigation, cross-references, etc. These features could be implemented with an external system that helps you to manage a blog, yet that ruined the idea that I wanted a tool that puts local & privacy above everything else, a tool that has as little dependencies as possible.

Long story short, I started working on the second iteration that I thought wouldn't sacrifice privacy, but eventually shelved and haven't completed it. I guess it is time to open-source it.

[1] https://devlog.notespub.com/2022/08/site-generator-for-apple...

Fascinating. These rules are identical, but I don't have xfractint locally to reproduce/troubleshoot the issue. I think I was using https://dmitrykandalov.com/lsystem/ as a playground, and it appears to be fine there.

Can you try generating 1/8 or 1/4 curves to check the partial generation? Or these rules--should produce the triangular shape:

  A=AFFFB-F-FB+F+A
  B=B+F+AF-F-AFFFB

That sounds super interesting. I would like to learn more if you're willing to share.

Not long ago, I went down the rabbit hole of space-filling curves, and learned about an obscure paper by Rolf Niedermeier, Klaus Reinhardt, and Peter Sanders that introduced a rather peculiar curve with an unfortunate name: H-curve [1]. The paper mentions that it preserves better locality properties compared to the Hilbert-curve. It fills the space with H-like shapes, hence the name. Also, like the Moore curve, it generates a loop.

Space-filling curves are ridiculously easy to implemented with L-system rules, and I spent a few days developing a set of axioms to express it in a rewrite system. This was a fun puzzle [2].

  A => BF-F-BFFFC-F-FC+F+BF-F-BFFFC-F-FC
  B => BFFFC-F-FC+F+B
  C => C+F+BF-F-BFFFC

[1] https://www.sciencedirect.com/science/article/pii/S0166218X0...

[2] https://kruzenshtern.org/25-h-curve.html

Not directly related to the post, but still feels somewhat relevant.

Back in March I used a bit more elaborate multi-step prompts for GPT3.5 to generate amusing pictures and published a gallery [1]. However, I eventually reached a point where changing prompts did not consistently improve the final results. At the end of the day, the quality of images are only as good as the training dataset, and GPT is a black box.

For something different, to test whether it is possible to "compress" visual content specifically for GPT, I ran another experiment. SVG, being a verbose format, takes time to generate a detailed image, and it also becomes expensive over time. I translated a subset of SVG elements into Forth words [2], which has a nice synergy with GPT tokens--this allowed me to progressively render pictures and produce smaller outputs without sacrificing much in quality.

Finally, I training my own GPT2-like model on the QuickDraw dataset [3]. It's not surprising that a sequence transformer can be trained to produce coherent brush strokes and recognizable images as long as there is a way to translate a graphical content into a sequence of tokens. That said, I found myself with more questions than I started, and trying other ideas now.

[1] https://drawmeasheep.net/pages/about.html

[2] https://drawmeasheep.net/pages/gpt-forth.html

[3] https://drawmeasheep.net/pages/nn-training.html

This number is tokenized as a list: 43 20 59 83 409 58 340 9 58 340 95 30 95 809 34 850 9 34 850 34 809 58 340 9 58 30 49 850 385 30 49 58 30. If GPT recognizes the context "+ 1 equals" through the attention mechanism, it can predict that the next number in the sequence should be 31: ... 58 30 -> ... 58 31

This may be a bit esoteric -- eee pc 701/901 if you get can get by with Atom N270.

I think in your notation it should have been:

y=Wx_0

y=W(x)x_0

Hi. I built a tool that transforms input prompts to amusing SVG illustrations. It runs on GPT3.5, Janet, HMTX, and a home-grown scheduler.

A couple of months ago I learned that GPT is capable of creating rudimentary drawings, and since then I poured my heart into tinkering and improving GPT and algorithmic steps until I reached a point where images became recognizable.

GPT3.5 doesn't always generate the most artistic illustrations, but once in a while it may draw surprisingly delightful sketches. GPT4 is more creative, but is also more expensive. I selected a few images and prompts to demonstrate what GPT3.5 can do right out of the box: https://kruzenshtern.org/23-draw-me-a-sheep.html

First and foremost, pinpoint the goal. Is it purely for funsies? To acquire new knowledge? Must it be pragmatic? Perhaps a business venture? Are there any users who will interact with the thing?

Next, break it down into steps. Write everything down like a brainstorm meeting.

This is a preliminary plan. Identify any known unknowns and research topics until they become known knowns. In the end, there is a list of steps to be done to achieve the goal. Can't crack it yet? Not a problem, put it in the reserved zone and move on.

Tackle step #1, or perhaps start with the most troubling one, then reassess the remaining parts. Is the goal still stand, or has something changed? No? Excellent--proceed. Yes? Take a half step back and adjust the plan.

Repeat.

Don’t forget to take breaks, drink water, and, please, be forgiving.

Recently, I started a project that draws simple illustrations using GPT. It began as a lighthearted curiosity, but eventually grew into something bigger, something that makes me smile when “a cat” or “a tesla car” turns into a recognizable sketch with a hint of creativity. It is private yet, but I will be releasing soon. I cherry picked a few illustrations and published them here: https://drawmeasheep.net/

I built a similar tool you are describing. A quick demo and a technical post is here: https://notespub.com/. However, truth be told, I migrated off Notes to Emacs Org-mode recently and didn't finish the project for GA. If it helps, I do plan to release it on Github soon-ish.

If you are willing to go the extra mile, it is not that difficult to export Notes with media files from Sqlite and templatize them, and I am happy to help.

I second your sentiment that it is a hack, and here be dragons. At the same time, I had an honest conversation with myself about the dilemma, and whether I am worried about changes to the database or not. I ended up answering that it is a low-risk factor especially for the project of that kind.

I am sure that Apple won’t be making any substation breaking changes to a database structure unless they have to, there is a price to pay. Such changes will always be tied to a major macOS/iPhone release, and it doesn't happen very often.

That said, I had to put this project on the back burner, it was not immediately clear what is the ROI especially considering there is a long tail of databases to parse. It starts with Mountain Lion and then adds up quickly.

I need to release my source code to Github--ORM approach was worth exploring, it is a concise declaration that is relatively easy to update and manage.

I was toying with this idea, and the best (and also the worst) workaround I found it to share a note with yourself; then link a note with ⌘-k. I tried doing this a couple of times--nah, it is a workaround.

Thanks for notesutils, I enjoyed reading your protobuf implementation!

I am excited to see more solutions that work with Apple Notes database directly. This is my go-to application to capture unstructured memos while researching various topics. Last year I got carried away and built a simple site generator for Notes [0]. As a fun exercise I implemented ORM models to query Sqlite database in Ruby:

  User::Account.server(database: "tmp/test.sqlite").first.
    folders_dataset.offset(1).first
    notes.
    map(&:attachments).flatten.
    find { |el| el.is_a?(User::ObjectTypes::EmbeddedPublicJpeg) &&
      el.height > 700 &&
      el.summary[/animal/i] }.
    media_filepath
 => "Accounts/<uuid>/Media/F669B83A-0C47-408E-9645-015737F3B11F/Pasted Graphic.jpg"

Apple Notes' database structure is a fascinating product story. Notes started as a simple note-taking application that stored its content as raw HTML in a few simple tables. However, as the product grew and needed more features like collaboration, they had to make changes and add new columns and tables. They also implemented two flavors of CRDT-like algorithms that evolved over time: one for plaintext chunks and the other one for embedded objects like tables. On top of that, every change that Apple makes must be backward compatible to support legacy devices and systems; but backward-compatibility was not always possible and users had to go through “Migrate your Notes” steps, but it is again a product story.

I wish that one day, someone from the development team would write an article about it.

[0] https://devlog.notespub.com/2022/08/site-generator-for-apple...

I love it! On a somewhat related note, I've been working on a tiny Forth interpreter lately, and I think the e-ink device it could be an interesting choice to explore and test it on as a dedicated computational environment. Inkplate looks very appealing: https://soldered.com/product/inkplate-6plus-e-paper-display-...

You might want to check out Kagi to summarize articles: https://labs.kagi.com/ai/sum. It does the heavy lifting of producing nice outputs for you.

Badger comes with a built-in Qwiic / STEMMA QC connector. I believe it should work out of the box with Adafruit ST25DV16K I2C RFID: https://www.adafruit.com/product/4701