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[-] BlastboomStrice@mander.xyz 58 points 7 months ago* (last edited 7 months ago)

[Edit: indeed, its actually good that it's 2gb]

2gb plugin??!

Btw, does it work with tenacity?

[-] 9point6@lemmy.world 62 points 7 months ago

AI models are often multiple gigabytes, tbh it's a good sign that it's not "AI" marketing bullshit (less of a risk with open source projects anyway). I'm pretty wary of "AI" audio software that's only a few megabytes.

[-] Neato@ttrpg.network 4 points 7 months ago

Why are they that big? Is it more than code? How could you get to gigabytes of code?

[-] General_Effort@lemmy.world 52 points 7 months ago

Currently, AI means Artificial Neural Network (ANN). That's only one specific approach. What ANN boils down to is one huge system of equations.

The file stores the parameters of these equations. It's what's called a matrix in math. A parameter is simply a number by which something is multiplied. Colloquially, such a file of parameters is called an AI model.

2 GB is probably an AI model with 1 billion parameters with 16 bit precision. Precision is how many digits you have. The more digits you have, the more precise you can give a value.

When people talk about training an AI, they mean finding the right parameters, so that the equations compute the right thing. The bigger the model, the smarter it can be.

Does that answer the question? It's probably missing a lot.

[-] Aatube@kbin.social 15 points 7 months ago* (last edited 7 months ago)

It's basically a huge graph/flowchart.

[-] acockworkorange@mander.xyz 6 points 7 months ago

It's really nothing of the sort.

[-] Aatube@kbin.social 14 points 7 months ago
  1. Specifying weights, biases and shape definitely makes a graph.
  2. IMO having a lot of more preferred and more deprecated routes is quite close to a flowchart except there's a lot more routes. The principles of how these work is quite similar.
[-] General_Effort@lemmy.world 3 points 7 months ago
  1. There are graph neural networks (meaning NNs that work on graphs), but I don't think that's what is used here.

  2. I do not understand what you mean by "routes". I suspect that you have misunderstood something fundamental.

[-] Aatube@kbin.social 5 points 7 months ago
  1. I'm not talking about that. What's weights, biases and shape if not a graph?
  2. By routes, I mean that the path of the graph doesn't necessarily converge and that it is often more tree-like.
[-] General_Effort@lemmy.world 4 points 7 months ago* (last edited 7 months ago)

You can see a neural net as a graph in that the neurons are connected nodes. I don't believe that graph theory is very helpful, though. The weights are parameters in a system of linear equations; the numbers in a matrix/tensor. That's not how the term is used in graph theory, AFAIK.

ETA: What you say about "routes" (=paths?) is something that I can only make sense of, if I assume that you misunderstood something. Else, I simply don't know what that is talking about.

[-] Natanael@slrpnk.net 2 points 7 months ago

If you look at the nodes which are most likely to trigger from given inputs then you can draw paths

[-] General_Effort@lemmy.world 2 points 7 months ago

I still don't know what this is supposed to mean for neural nets. I think it reflects a misunderstanding.

[-] 9point6@lemmy.world 8 points 7 months ago* (last edited 7 months ago)

The current wave of AI is around Large Language Models or LLMs. These are basically the result of a metric fuckton of calculation results generated from running a load of input data in, in different ways. Given these are often the result of things like text, pictures or audio that have been distilled down into numbers, you can imagine we're talking a lot of data.

(This is massively simplified, by someone who doesn't entirely understand it themselves)

[-] Amir@lemmy.ml 7 points 7 months ago

They're composed of many big matrices, which scale quadratically in size. A 32x32 matrix is 4x the size of a 16x16 matrix.

[-] bamboo@lemm.ee 31 points 7 months ago

It seems reasonable given it includes multiple AI models.

[-] Fisch@lemmy.ml 7 points 7 months ago

2gb is pretty normal for an AI model. I have some small LLM models on my PC and they're about 7-10gb big. The big ones take up even more space.

[-] Sneptaur@pawb.social 3 points 7 months ago

Isn’t tenacity a joke project made by 4channers

[-] CaptainBasculin@lemmy.ml 15 points 7 months ago

That fork is sneedacity, which is very dead.

[-] Sneptaur@pawb.social 3 points 7 months ago

Gotcha, thank you for the info. Gotta admit their made-up words are pretty funny

[-] RmDebArc_5@lemmy.ml 10 points 7 months ago

Tenacity is a Audacity fork without telemetry

[-] mp3@lemmy.ca 15 points 7 months ago

Isn't the telemetry in Audacity opt-in anyway?

[-] Fisch@lemmy.ml 3 points 7 months ago

The fork was created when Audacity was bought and one of the first things the new developers were about to do was add opt-out telemetry. People didn't like that at all. From what I read in this thread, they ended up adding opt-in telemetry instead.

this post was submitted on 13 Feb 2024
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