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Bold of you to assume that you wouldn’t be the one being beat up.

Sure. If you are using an nvidia optimus laptop, you should also add __NV_PRIME_RENDER_OFFLOAD=1 __GLX_VENDOR_LIBRARY_NAME=nvidia at the start of the last line when running in hybrid mode to run mpv on the dgpu. You should have a file at ~/.wallpaperrc that contains wallpaper_playlist: /path/to/mpv/playlist. You may want to add this script to your startup sequence via your wm/de.

#!/bin/sh

WALLPAPER_PLAYLIST=$(cat ~/.wallpaperrc | grep -v '^\w*#' | grep 'wallpaper_playlist' | sed "s/wallpaper_playlist: //")


xwinwrap -g 1920x1080 -ov -- mpv -wid WID --no-osc --no-audio --loop-playlist --shuffle --playlist=$WALLPAPER_PLAYLIST

Hope this helps!

I set mpv as the root window which worked well. I stopped using it a while back, but if you are interested, I could dig up the simple script for you (literally one or two lines iirc).

I would never do that?

Wow, CUPS is way better than I previously thought and I thought it was amazing!

There is actually a smallest number, typically denoted by a lower case epsilon, which is infintesimally small, typically used in calculus proofs.

0.1111… is equal to 1/9. 0.0000… is trivially equal to 0.

This is not a proof as you start with the answer, albeit disguised as a known truth. Here is a real proof. Start by assigning the recurring decimal a variable.

x = 0.9999...

Now calculate 10 times this by shifting the decimal place.

10x = 9.9999...

You can then subtract the second equation from the first. Note that all the digits after the decimal cancel out, leaving us with the following.

9x = 9
x = 1

Therefore, 0.9999… = 1. Infinity does weird things!

Who’s next?

You already have a plethora of great suggestions for improvements to make, so I won’t leave any more, but rather offer some advice. It can be daunting to go all in and sacrifice the conveniences you currently enjoy. This is why I recommend you change your behaviour and software in a piecemeal fashion. Change only a few (or even one) things at a time and get used to it. Once you are comfortable with where you are at, then introduce more improvements. This approach will help prevent you from getting overloaded or burnt out, resulting in you going back and compromising your privacy. Good luck!

If I’m being honest, it is fairly slow. It takes a good few seconds to respond on a 6800XT using the medium vram option. But that is the price to pay to running ai locally. Of course, a cluster should drastically improve the speed of the model.

You can run llms on text-generation-ui such as open llama and gpt2. It is very similar to the stable diffusion web ui.

Pffsh, that’s baby mode, I use butterflies by releasing them at just the right time to cause the air currents to change just right to cause a solar ray to pass through the atmosphere and flip the bit I want to flip. It is a bit trickier with error correcting memory…

It is just how I prefer to do my computing. I tend to live on the command line and pipe programs together to get complex behavior. If you don’t like that, then my approach is not for you and that’s fine. As for your analogy, I see it more as “instead of driving down the road in a car, I like to put my own car together using prefabs”.

Option 4: levy existing tools such as gpg and git using something like pass. That way, you are keeping things simple but it requires more technical knowledge. Depending on your threat model, you may want to invest in a hardware security key such as a yubikey which works well with both gpg and ssh.

It can’t double the dBs. It will only add 3 as dBs are a log scale and +/-3dBs is double/half.

mCaptcha is an open source proof of work tool to tackle bots.

Why did you mention it?! Now we can never unsee it!

TempleOS