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This one doesn't seem to exciting to be honest, but it might be useful. Sample question:
If I deposit $50,000 at 5% APR, compounded weekly, what will my balance be after 18 months?
and it expects the correct answer down to the cents:
53892.27
It should be noted that Project Euler has such "precision matters" problems.
Even more than in other areas of benchmarking, in maths where you only have a right or wrong answer, and it is costly to come up with good sample problems, some benchmarks have adopted private test data sets.
The situation is kind of sad, in that ideally we should have open data sets and only test them on models that were trained on data exclusively published before the problem publish date.
However this is not practical for the following reasons:
  • some of the best models are closed source and don't have a reproducible training with specified cutoff
  • having a private test set allows you to automatically check answers from untrusted sources. If they get answers right, they are onto something, you don't even need to check their methodology
Perhaps the ideal scenario therefore is what ARC-AGI has done: give a sizeable public dataset, which you feel is highly representative of the difficulty level of the private test data, while at the same time holding out some private test data.
This way, reproducible models can actually self test themselves reliably on the open data, while the closed data can then be used for the cases where the open data can't be used.
Video 1.
3D Printed Guns Are Easy To Make And Impossible To Stop by VICE News (2018)
Source.
Here's an execution for 2, 3. When a != 1 we use a as the extra numbers instead of b:
 1 | 2 2(1) ...
 2 | 2 2(0) 2(1) ...
 3 | 3 2(1) 2(0) 2(1) ...
 4 | 3 2(0) 2(0) 2(1) ...
 5 | 2 3(2) 2(1) 2(0) 2(0) ...
 6 | 2 3(1) 2(1) 2(0) 2(1) ...
 7 | 2 3(0) 2(1) 2(0) 2(1) ...
 8 | 3 3(2) 2(0) 2(0) 2(1) ...
 9 | 3 3(1) 2(0) 2(0) 2(1) ...
10 | 3 3(0) 2(0) 2(0) 2(1) ...
11 | 2 2(1) 3(2) 2(1) 2(0) 2(1) ...
12 | 2 2(0) 3(2) 2(1) 2(0) 2(1) ...
13 | 3 2(1) 3(1) 2(1) 2(0) 2(1) ...
14 | 3 2(0) 3(1) 2(1) 2(0) 2(1) ...
15 | 2 2(1) 3(0) 2(1) 2(0) 2(1) ...
16 | 2 2(0) 3(0) 2(1) 2(0) 2(1) ...
17 | 3 3(2) 3(2) 2(0) 2(0) 2(1) ...
Furthermore, note that if a = 1, then the a, b sequence is a subset of the b, a sequence e.g.:
1, 2 = [1, 2, 2, 1, 1, 2, 1, ...]
2, 1 = [   2, 2, 1, 1, 2, 1, ...]
therefore we can always make a not be 1 by switching the pair and then using the generalized algorithm with a != 1.
This algorithm is more efficient in space, using only , as it recursively compresses the state required to keep track of what to do next.
Time is still .
The table at maths-people.anu.edu.au/~brent/pd/Kolakoski-UNSW.pdf page 20 has a summary image, but it is hard to understand.
Let's do a step by step version now.
The notation we use is as follows:
1 2 (1) 1 (1)
means that:
  • this is number 2
  • there is 1 occurrence count left
Note that column 1 does not need to keep a count so we use notation such as:
1 2(0) 1(1)
The starting state is:
2 | 2 2(1) 2(1) 2(1) 2(1) ...
which means that it implicitly contains infinitely many 2(1) at the end which we abbreviate just as:
2 | 2 2(1) ...
The actual algorithm will of course omit as many trailing 2(1) as it can.
The update rules are:
  • go left to right:
    • flip:
      x(0)       y(0)
      !x((!x)-1) unchanged
      continue going left to right.
    • repeat:
      x(0)   y(n > 0)
      x(x-1) y(n - 1)
      and then stop further updates.
Note that both rules don't overlap so that each update is always determined by only one of them at a time.
Also the first column is always implicitly (0).
Use column 2 up once to repeat column 1:
2 | 2 2(1) ...
3 | 2 2(0) 2(1) ...
Here we:
  • switch column 1 because column 2 reached 0 on previous step
  • use column 3 up once to repeat column 2
2 | 2 2(1) ...
3 | 2 2(0) 2(1) ...
4 | 1 2(1) 2(0) 2(1) ...
  • use column 2 up once to repeat 1
2 | 2 2(1) ...
3 | 2 2(0) 2(1) ...
4 | 1 2(1) 2(0) 2(1) ...
5 | 1 2(0) 2(1) 2(0) 2(1) ...
 2 | 2 2(1) ...
 3 | 2 2(0) 2(1) ...
 4 | 1 2(1) 2(0) 2(1) ...
 5 | 1 2(0) 2(0) 2(1) ...
 6 | 2 1(0) 2(1) 2(0) 2(1) ...
 7 | 1 1(0) 2(0) 2(0) 2(1) ...
 8 | 2 2(1) 1(0) 2(1) 2(0) 2(1) ...
 9 | 2 2(0) 1(0) 2(1) 2(0) 2(1) ...
10 | 1 1(0) 1(0) 2(0) 2(0) 2(1) ...
11 | 2 2(1) 2(1) 1(0) 2(1) 2(0) 2(1) ...
12 | 2 2(0) 2(1) 1(0) 2(1) 2(0) 2(1) ...
13 | 1 2(1) 2(0) 1(0) 2(1) 2(0) 2(1) ...
14 | 1 2(0) 2(0) 1(0) 2(1) 2(0) 2(1) ...
15 | 2 1(0) 1(0) 1(0) 2(0) 2(0) 2(1) ...
16 | 1 2(1) 2(1) 2(1) 1(0) 2(1) 2(0) 2(1) ...
The generalized Kolakoski sequence is the generalization of the Kolakoski sequence where you don't need to restrict yourself to 1,2 but can instead use any a,b pair.
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Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact