Crystal detector Updated 2025-07-16
The first diodes. These were apparently incredibly unreliable, especially for portable radios, as you had to randomly search for the best contact point you could find in a random polycrystalline material!!
And also quality was highly dependant on where the material was sourced from as that affected the impurities present in the material. Later this was understood to be an issue of doping.
It was so unreliable that vacuum tube diodes overtook them in many applications, even though crystal detectors are actually semiconductor diodes, which eventually won over!
For a long time, before artificial semiconductors kicked in, people just didn't know the underlying physical working principle of these detectors. What I cannot create, I do not understand basically.
MuJoCo getting started Updated 2025-07-16
Tested on Ubuntu 23.10;
git clone https://github.com/google-deepmind/mujoco
cd mujoco
git checkout 5d46c39529819d1b31249e249ca399f306a108ac
mkdir -p build
cd build
cmake ..
make -j
Now let's play. Minimal interactive UI simulation of a simple MJCF scene with one falling cube:
bin/basic ../doc/_static/hello.xml
Test soure code: github.com/google-deepmind/mujoco/blob/5d46c39529819d1b31249e249ca399f306a108ac/sample/basic.cc. The only thing you can do is rotate the scene with the computer mouse it seems. Mentioned at: mujoco.readthedocs.io/en/2.2.2/programming.html#sabasic
Some more interesting models can be found under the model/ directory: github.com/google-deepmind/mujoco/tree/5d46c39529819d1b31249e249ca399f306a108ac/model E.g. the imaginary humanoid robot DeepMind used in many demos can be seen with:
bin/basic ../model/humanoid/humanoid.xml
A very cool thing about that UI is that you can manually control joints. There are no joints in the hello.xml, but e.g. with the humanoid model:
bin/simulate ../model/humanoid/humanoid.xml
under "Control" you move each joint of the robot separately which is quite cool.
Video 1.
Demo of MuJoCo's built-in simulate viewer by Yuval Tassa (2019)
Source.
There's also a bin/record test executable that presumably renders the simulation directly to a file:
bin/record ../doc/_static/hello.xml 5 60 rgb.out
ffmpeg -f rawvideo -pixel_format rgb24 -video_size 800x800 -framerate 60 -i rgb.out -vf "vflip" video.mp4
Mentioned at: mujoco.readthedocs.io/en/2.2.2/programming.html#sarecord but TODO that produced a broken video, related issues:
Daisy chain Bitcoin inscription Updated 2025-07-16
This is a term invented by Ciro Santilli, and refers to a loose set of uncommon Bitcoin inscription methods that involve inscribing one or a small number of payloads per Bitcoin transaction.
These methods are both inefficient and hard to detect and decode, partly because Bitcoin Core does not index spending transactions: bitcoin.stackexchange.com/questions/61794/bitcoin-rpc-how-to-find-the-transaction-that-spends-a-txo. This makes finding them all that more rewarding however.
On the other hand, they do have the advantage of not depending on any block size limits, as their individual transactions are very small.
Inscribing anything large would however take a very long time, as you'd have to wait until the previous payload chunk is confirmed before going to the next one. This alone makes the format impractical perhaps.
Dan Abramson Updated 2025-07-16
Dan, if you ever Google yourself here, please contact Ciro Santilli: Section "How to contact Ciro Santilli" to do something with OurBigBook.com. Cheers.
DigitalDreamDoor Updated 2025-07-16
Ahh, this brings good memories of Ciro Santilli's musical formative teenage years scouring the web for the best art humanity had ever produced in certain generes. And it still is a valuable resource as of the 2020's!
Next.js example Updated 2025-07-16
Our examples are located under nodejs/next:
Solved ones:
EMBII Updated 2025-07-16
One of the dudes from the AtomSea & EMBII Bitcoin-based file upload system.
Figure 1.
EMBII's usual profile image
. Source.
Obsidian (software) Updated 2025-07-16
Good:
Bad:
Figure 1.
Obsidian demo
. Source.
Ollama Updated 2025-07-16
Ollama is a highly automated open source wrapper that makes it very easy to run multiple Open weight LLM models either on CPU or GPU.
Its README alone is of great value, serving as a fantastic list of the most popular Open weight LLM models in existence.
Install with:
curl https://ollama.ai/install.sh | sh
The below was tested on Ollama 0.1.14 from December 2013.
Download llama2 7B and open a prompt:
ollama run llama2
On P14s it runs on CPU and generates a few tokens per second, which is quite usable for a quick interactive play.
As mentioned at github.com/jmorganca/ollama/blob/0174665d0e7dcdd8c60390ab2dd07155ef84eb3f/docs/faq.md the downloads to under /usr/share/ollama/.ollama/models/ and ncdu tells me:
--- /usr/share/ollama ----------------------------------
    3.6 GiB [###########################] /.ollama
    4.0 KiB [                           ]  .bashrc
    4.0 KiB [                           ]  .profile
    4.0 KiB [                           ]  .bash_logout
The file:
/usr/share/ollama/.ollama/models/manifests/hf.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF/Q2_K
gives a the exact model name and parameters.
We can also do it non-interactively with:
/bin/time ollama run llama2 'What is quantum field theory?'
which gave me:
0.13user 0.17system 2:06.32elapsed 0%CPU (0avgtext+0avgdata 17280maxresident)k
0inputs+0outputs (0major+2203minor)pagefaults 0swaps
but note that there is a random seed that affects each run by default. ollama-expect is an attempt to make the output deterministic.
Some other quick benchmarks from Amazon EC2 GPU on a g4nd.xlarge instance which had an Nvidia Tesla T4:
0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swaps
and on Nvidia A10G in an g5.xlarge instance:
0.03user 0.05system 0:09.59elapsed 0%CPU (0avgtext+0avgdata 17312maxresident)k
8inputs+0outputs (1major+1934minor)pagefaults 0swaps
So it's not too bad, a small article in 10s.
It tends to babble quite a lot by default, but eventually decides to stop.
react/ref-click-counter.html Updated 2025-07-16
Dummy example of using a React ref This example is useless and to the end user seems functionally equivalent to react/hello.html.
It does however serve as a good example of what react does that is useful: it provides a "clear" separation between state and render code (which becomes once again much less clear in React function components.
Notably, this example is insane because at:
<button onClick={() => {
  elem.innerHTML = (parseInt(elem.innerHTML) + 1).toString()
we are extracing state from some random HTML string rather than having a clean JavaScript variable containing that value.
In this case we managed to get away with it, but this is in general not easy/possible.
riscv/timer.S Updated 2025-07-16
Tested on Ubuntu 23.10:
sudo apt install binutils-riscv64-unknown-elf qemu-system-misc gdb-multiarch
cd riscv
make
Then on shell 1:
qemu-system-riscv64 -machine virt -cpu rv64 -smp 1 -s -S -nographic -bios none -kernel timer.elf
and on shell 2:
gdb-multiarch timer.elf -nh -ex "target remote :1234" -ex 'display /i $pc' -ex 'break *mtrap' -ex 'display *0x2004000' -ex 'display *0x200BFF8'
GDB should break infinitel many times on mtrap as interrupts happen.
Formal proof is useless Updated 2025-07-16
The only cases where formal proof of theorems seem to have had actual mathematical value is for theorems that require checking a very large number of case, so much so that no human can be fully certain that no mistakes were made. Some examples:

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