More than just based on them bro

I hate this so much. What can we even do to protect our freedoms from France?

There are other init system other then sys V and systemD

You don't need to ignore it. She should understand your stance on AI. You don't need to come off strong with pure hatred, but she should understand your dislike of AI. On the topic of her homework, keep it light. You don't need to fixate on it, just say it looks good (if it does). I don't know if you can help her reduce her usage. Maybe someone else here can figure that out.

Ya. This feels like some corporate crap. They really don't like that we can run our own models.

Is there a lawsuit? I'm not in America, but taking a protester's eyes sounds illegal.

As a Debian user and programmer, I also suggest Fedora. As said above, Fedora has everything that Ubuntu does, does not force snap packs on its users, and finally, it offers updated software libraries compared to more stable distros such as Debian.

I found the offical guide here and someone else's guide here. There is also this guide here. I hope this helps!

Hello! First of all, I wrote this myself without AI (but with a stackover post here for the word counter (wc) part and here for the -exec of find part).

How it works

We select a directory called A. If A has a sub-directory at somepoint with the matching string "red" in it, we then ignore it. Otherwise, it is the deepest directory with "red" in its name. That makes sense. So, how do we do this?

First, I wrote a find.sh script

if [[ $(find "$1" -mindepth 1 -type d -name '*red*' | wc -c) -eq 0 ]]; then
  echo "$1"
fi

It will output the name of the directory if it is the deepest match, or nothing if not. Then I do

find . -type d -name '*red*' -exec bash find.sh {} \;

Finally

find . -type d -name '*red*' -exec $SHELL -c 'if [[ $(find "$1" -mindepth 1 -type d -name "*red*" | wc -c) -eq 0 ]]; then echo $1; fi' sh {} \;

Hope this helps 👍

I believe so. They do not mention a change in model architecture which reduce the compute for these byte-level models. So it would be expected that compute costs of token generation increase proportionally with the average increase of tokens with respect to current subword tokenization. I have just read the paper here and they seem to combat the increase compute cost with their efficent self-attention method, I do not see a mention of this here, so I only assume that the internal model architecture remains the same, and thus it is expected that the larger context length and time to generate a token will be the main issues.

It was better when they at least made money with the personal data instead of giving it out for free lol. On a real note, hope tiktok dies. Terrible platform and im so happy I've never had to use it.

These guys are terrible people. Hopefully meta falls under.