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Cake day: June 13th, 2023

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  • Of course, but by just saying Linux you’re bound to be wrong somewhere - I’m just highlighting its so broad its an essentially useless definition (42% of all computers run it by the way). Gnome is pretty shit for customisability, so what’s more customisable than having another option?

    By looking at ‘just Linux’ you couldn’t be more wrong for the core argument.

    It also shifts the blame to many smaller devs like matrix which tbh they’re mostly doing work for free so who’s gonna complain they don’t want to add extra complexity, just get in that source code if you really care. And in the age of such easy frontend engines an experienced could probably whip up their own in a week.

    Also ive never had issues with qt/flatpaks, using prism launcher as an example, its seamlessly followed my color scheme (not saying bugs don’t exist somewhere I’m not seeing, but there certainly is 'just works support to some degree).

    I you’re gonna be mad people don’t like something, yikes open source isn’t for you - git as a whole all but is designed to handle disagreements without breaking its stride.


  • Uhh Linux is a kernel and on its own doesn’t even support graphics much less customising them.

    But if you wanna actually blame someone, we’ll need to know which software youre talking about - could be OPPO’s ColorOS for all we know.

    That being said a big name in the Linux world is KDE, and they have one of the best theming engines Ive ever used. Everything QT follows the theme - so much so I didn’t even realise how ugly some apps look on windows (like prism launcher not matching my file explorer?? Eww)

    That being said I couldn’t agree more with the first part, and in linux specifically I wish we had more ‘basic display driver’ like tools to handle emergency situations.






  • To get a bit more technical, they build images in passes; each becoming more coherent than the last. This gives thsm a boost to understanding understand how ‘things’ relate to one another, knowing them by nothing but that relation. Light + light source being an example, and the angle of lighting being another deeper layer of that a - completed on a less noisy pass.

    This is how its able to build images from its training parts, it sorta understands how each of them relate to some things, so its able to sorta organizes an image of random noise each pass, eventually creating a ‘unique’ image inspired by its training data.

    It also gives it that perfect image you mention, cause its specifically trained to look like what looks good to us - its essentially a function optimised on nothing but.