Ackermann function by Ciro Santilli 40 Updated 2025-07-16
To get an intuition for it, see the sample computation at: en.wikipedia.org/w/index.php?title=Ackermann_function&oldid=1170238965#TRS,_based_on_2-ary_function where in this context. From this, we immediately get the intuition that these functions are recursive somehow.
Now let's try and use the trained ONNX file for inference on some manually drawn images on GIMP:
Note that:
  • the images must be drawn with white on black. If you use black on white, it the accuracy becomes terrible. This is a good very example of brittleness in AI systems!
  • images must be converted to 32x32 for lenet.onnx, as that is what training was done on. The training step converted the 28x28 images to 32x32 as the first thing it does before training even starts
We can try the code adapted from thenewstack.io/tutorial-using-a-pre-trained-onnx-model-for-inferencing/ at lenet/infer.py:
cd lenet
cp ~/git/LeNet-5/lenet.onnx .
wget -O 9.png https://raw.githubusercontent.com/cirosantilli/media/master/Digit_9_hand_drawn_by_Ciro_Santilli_on_GIMP_with_mouse_white_on_black.png
./infer.py 9.png
and it works pretty well! The program outputs:
9
as desired.
We can also try with images directly from Extract MNIST images.
infer_mnist.py lenet.onnx mnist_png/out/testing/1/*.png
and the accuracy is great as expected.
Adam Curtis by Ciro Santilli 40 Updated 2025-07-16
Ciro Santilli really loved his documentary called Can't get you out of my head by Adam Curtis (2021), and then proceeded to basically watch all of this films.
Adenosine triphosphate by Ciro Santilli 40 Updated 2025-07-16
The fact that ATP is the universal energy storage mollecule of all life on Earth is such an incredible unifying principle of biology!
It is the direct output of all the major forms of "energy generation" in cells: ATP synthesis mechanism.
It is just as fundamental as the genetic code for example.
No wonder dozens of Nobel Prizes were related to its discovery, given its complexity.
Length contraction by Ciro Santilli 40 Updated 2025-07-16
Suppose that a rod has is length measured on a rest frame (or maybe even better: two identical rulers were manufactured, and one is taken on a spaceship, a bit like the twin paradox).
Question: what is the length than an observer in frame moving relative to as speed observe the rod to be?
The key idea is that there are two events to consider in each frame, which we call 1 and 2:
  • the left end of the rod is an observation event at a given position at a given time: and for or and for
  • the right end of the rod is an observation event at a given position at a given time : and for or and for
Note that what you visually observe on a photograph is a different measurement to the more precise/easy to calculate two event measurement. On a photograph, it seems you might not even see the contraction in some cases as mentioned at en.wikipedia.org/wiki/Terrell_rotation
Measuring a length means to measure the difference for a single point in time in your frame ().
So what we want to obtain is for any given time .
In summary, we have:
By plugging those values into the Lorentz transformation, we can eliminate , and conclude that for any , the length contraction relation holds:
The key question that needs intuitive clarification then is: but how can this be symmetric? How can both observers see each other's rulers shrink?
And the key answer is: because to the second observer, the measurements made by the first observer are not simultaneous. Notably, the two measurement events are obviously spacelike-separated events by looking at the light cone, and therefore can be measured even in different orders by different observers.
Adjoint operator by Ciro Santilli 40 Updated 2025-07-16
Given a linear operator over a space that has a inner product defined, we define the adjoint operator (the symbol is called "dagger") as the unique operator that satisfies:
ALSA can be thought as analogous to physical wires linking up machines.
Except that instead of machines, you have separate programs. One such typical link is:
The advantage of this setup is that separate programs can collaborate to make complex sounds.
The disadvantage of this setup is that it makes it very hard to reproduce results, you basically need a Docker image with the exact same version of everything. And some script to launch and connect all programs correctly.
Some composition systems like LMMS reduce that problem by having synthesizers as plugins, so that you don't have to setup any connections yourself.

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