No, it’s not hard. By default open source drivers will run, but you can install the nvidia ones through driver manager and everything should just work.

No, it should work out of the box through the open source driver. But, for most people the Nvidia driver (closed) works without issues, you need to install it through driver manager app.

What folder did you run it in?

As @Strit wrote, use sudo, as docker keeps its container, image and volume files under /var/lib/docker, and that folder is not readable without sudo (or root).

You know that you can change license of software that you own copyright to? You can take GPL code and change it to something else, but you can’t un-GPL existing released code. It’s the same thing with MIT.

The only people bound by the license are people who use it because it is licensed to them.

The difference is that organisation may develop MIT software without publishing their code.

No, it has not „always been fine” - I’ve worked with people who disabled auto updates on their dev machines just to keep a specific kernel & driver version working together. Circa 2016 :)

Stolen? It was forked as is allowed by the MIT license. With GPL as well there is no „you cannot fork” rule, you can do exactly the same thing. The author misunderstood that „you have to push the changes to upstream”, which is not in any of those licenses.

Counter-counter point: people don’t get a Mac or windows laptop to learn about osx or windows. They generally want to run software or at least browser to do what they need to do.

Uh, memory metrics in Linux are a pain. The only tool that reports most cached as available is htop. free, top and a lot of other software (like node_exporter) will report that a lot of cached memory is not available.

To OP: don’t worry, a lot of Linux tools are smart enough to give back memory if memory pressure rises.

Not sure what is hard in it - you need consistent tagging, and that by itself gives you a lot of mileage in cost explorer.