every program and OS

every nonfree program and OS

I know that, I was just joining in

“Woke liberal commie antifa terrorism”

ICE engines function well but are quite suboptimal, they pollute the air

Developing a good replacement (such as electric cars) is important

Welcome to Lemmy!

Fight me

I will not fight you, I agree with what you said

Face ID has been replaced with Genitals ID

• why? yes
• no? yes
• actually why? training ai to generate csam probably

competition is bad for competition

checks out

translation: having more competitors harms our chance of winning against them

I understand why there are paid features; I just personally intend to wait until federation drops so I can join an instance that offers Plutonium for free.

The GNU operating system is pretty neat and has a strong opposition to evil megacorporations

It usually uses the Linux kernel

The distribution I use is openSUSE Tumbleweed, a simple, full-featured, up-to-date but quite stable distribution

this is an old version

the current iteration is way taller

And if you selfhost you can get the stuff for free

Movim seems less like a Discord alternative and more like a Whatsapp alternative

Paid features? Ew.

I’ll be waiting until federation rolls out. Someone will definitely set up an instance that gives you the paid features for free

edit: replaced fork with instance after finding out that it can be configured

!ihadastroke@lemmy.world

Aseprite?

Oh no they’re poisoning the water supply with nonfree software

You weren’t yet

Soon you will have been

[citation needed]

what?? AI is not conscious, marketing just says that with no understanding of the maths and no legal obligation to tell the truth.

Here’s how LLMs work:

The basic premise is like an autocomplete: It creates a response word by word (not literally using words, but “tokens” which are mostly words but sometimes other things such as “begin/end codeblock” or “end of response”). The program is a guessing engine that guesses the next token repeatedly. The autocomplete on your phone is different in that it merely guesses which word follows the previous word. An LLM guesses what the next word after the entire conversation (not always entire: conversation history may be truncated due to limited processing power) is.

The “training data” is used as a model of what the probabilities are of tokens following other tokens. But you can’t store, for every token, how likely it is to follow every single possible combination of 1 to <big number like 65536, depends on which LLM> previous tokens. So that’s what “neural networks” are for.

Neural networks are networks of mathematical “neurons”. Neurons take one or more inputs from other neurons, apply a mathematical transformation to them, and output the number into one or more further neurons. At the beginning of the network are non-neurons that input the raw data into the neurons, and at the end are non-neurons that take the network’s output and use it. The network is “trained” by making small adjustments to the maths of various neurons and finding the arrangement with the best results. Neural networks are very difficult to see into or debug because the mathematical nature of the system makes it pretty unclear what a given neuron does. The use of these networks in LLMs is as a way to (quite accurately) guess the probabilities on the fly without having to obtain and store training data for every single possibility.

I don’t know much more than this, I just happen to have read a good article about how LLMs work. (Will edit the link into this post soon, as it was texted to me and I’m on PC rn)