@S410@kbin.social
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S410

@S410@kbin.social

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S410,
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To provide features that Xorg can't.
If you don't need features like fractional scaling, VRR, touchscreen gestures, etc. you won't notice a difference.
People who do use those, will. Because for them, those features would be missing or not complete on Xorg.

S410,
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In case of Gnome it was addressed, just by different people. Gnome 2 continues to live on as MATE, so anyone who doesn't like Gnome 3 can use it instead.

S410,
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To be honest, most things in Nobra can be installed/done to regular Fedora. And, unlike Nobra, Fedora has more than 1 maintainer: goof for the bus factor.

recommendations for lightweight window managers for an old netbook

Hi, I’ve got an old netbook from Samsung that has an old Intel Atom CPU (Intel Atom N455 1.66 GHz). I installed Arch on it and am now thinking of a suitable window manager. I tried Hyprland (kinda expecting it to not work really) whick didn’t start at all. Before I had Debian with Gnome, which technically worked, but...

S410,
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Almost everything that's not Gnome can be considered lightweight, to be honest.

New to Linux, have a few questions

I currently use Windows 10 and I’d like to try out Linux. My plan is to set up a dual boot with OpenSUSE tumbleweed and KDE Plasma. I’ve read so many different opinions about choosing a distro, compatibility with gaming and Nvidia drivers, and personal issues with the ethos of different companies like Canonical. I value...

S410,
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OpenSUSE + KDE is a really solid choice, I'd say.

The most important Linux advice I have is this: Linux isn't Windows. Don't expect things to works the same.
Don't try too hard to re-configure things that don't match the way things are on Windows. If there isn't an easy way to get a certain behavior, there's probably a reason for it.

S410,
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It's illegal if you copy-paste someone's work verbatim. It's not illegal to, for example, summarize someone's work and write a short version of it.

As long as overfitting doesn't happen and the machine learning model actually learns general patterns, instead of memorizing training data, it should be perfectly capable of generating data that's not copied verbatim from humans. Whom, exactly, a model is plagiarizing if it generates a summarized version of some work you give it, particularly if that work is novel and was created or published after the model was trained?

S410,
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Learning is, essentially, "algorithmically copy-paste". The vast majority of things you know, you've learned from other people or other people's works. What makes you more than a copy-pasting machine is the ability to extrapolate from that acquired knowledge to create new knowledge.

And currently existing models can often do the same! Sometimes they make pretty stupid mistakes, but they often do, in fact, manage to end up with brand new information derived from old stuff.

I've tortured various LLMs with short stories, questions and riddles, which I've written specifically for the task and which I've asked the models to explain or rewrite. Surprisingly, they often get things either mostly or absolutely right, despite the fact it's novel data they've never seen before. So, there's definitely some actual learning going on. Or, at least, something incredibly close to it, to the point it's nigh impossible to differentiate it from actual learning.

S410, (edited )
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Not once did I claim that LLMs are sapient, sentient or even have any kind of personality. I didn't even use the overused term "AI".

LLMs, for example, are something like... a calculator. But for text.

A calculator for pure numbers is a pretty simple device all the logic of which can be designed by a human directly.

When we want to create a solver for systems that aren't as easily defined, we have to resort to other methods. E.g. "machine learning".

Basically, instead of designing all the logic entirely by hand, we create a system which can end up in a number of finite, yet still near infinite states, each of which defines behavior different from the other. By slowly tuning the model using existing data and checking its performance we (ideally) end up with a solver for something a human mind can't even break up into the building blocks, due to the shear complexity of the given system (such as a natural language).

And like a calculator that can derive that 2 + 3 is 5, despite the fact that number 5 is never mentioned in the input, or that particular formula was not a part of the suit of tests that were used to verify that the calculator works correctly, a machine learning model can figure out that "apple slices + batter = apple pie", assuming it has been tuned (aka trained) right.

S410, (edited )
@S410@kbin.social avatar

Not once did I claim that LLMs are sapient, sentient or even have any kind of personality. I didn't even use the overused term "AI".

LLMs, for example, are something like... a calculator. But for text.

A calculator for pure numbers is a pretty simple device all the logic of which can be designed by a human directly.

When we want to create a solver for systems that aren't as easily defined, we have to resort to other methods. E.g. "machine learning".

Basically, instead of designing all the logic entirely by hand, we create a system which can end up in a number of finite, yet still near infinite states, each of which defines behavior different from the other. By slowly tuning the model using existing data and checking its performance we (ideally) end up with a solver for something a human mind can't even break up into the building blocks, due to the shear complexity of the given system (such as a natural language).

And like a calculator that can derive that 2 + 3 is 5, despite the fact that number 5 is never mentioned in the input, or that particular formula was not a part of the suit of tests that were used to verify that the calculator works correctly, a machine learning model can figure out that "apple slices + batter = apple pie", assuming it has been tuned (aka trained) right.

S410,
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Not OP, but I have the same setup.

I have BTRFS on /, which lives on an SSD and ext4 on an HDD, which is /home. BTRFS can do snapshots, which is very useful in case an update (or my own stupidity) bricks the systems. Meanwhile, /home is filled with junk like cache files, games, etc. which doesn't really make sense to snapshot, but that's, actually, secondary. Spinning rust is slow and BTRFS makes it even worse (at least on my hardware) which, in itself, is enough to avoid using it.

S410,
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You can put your /home on a different BTRFS subvolume and exclude it from being snapshotted.

S410,
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As long as you don't re-format the partition. Not all installers are created equal, so it might be more complicated to re-install the OS without wiping the partition entirely. Or it might be just fine. I don't really install linux often enough to know that. ¯_(ツ)_/¯

S410,
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I have a 120 gig SSD. The system takes up around 60 gigs + BTRFS snapshots and its overhead. A have around 15 gigs of wiggle room, on average. Trying to squeeze some /home stuff in there doesn't really seem that reasonable, to be honest.

S410,
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Virtual desktops are arranged on a one dimensional axis. Whether it's vertical, horizontal or fucking diagonal doesn't really change how they work. It's just fluff and animations, really.

S410,
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Element has been working for me and my friends. At the moment, it just embeds Jitsi within the client to do group calls (which works fine. Jisti isn't bad by any means), but native group calls are being worked on and are currently in beta!

S410,
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Most music I have is from "Pay what you want" albums from Ponies@Dawn, VibePoniez, A State Of Sugar, etc.
When I come across artists I like, I tend to check out their other tracks and grab the ones I like.

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