It's data
Comment on Audacity adds AI audio editing capabilities thanks to free Intel OpenVINO plugins
Neato@ttrpg.network 2 months agoWhy are they that big? Is it more than code? How could you get to gigabytes of code?
Aatube@kbin.social 2 months ago
acockworkorange@mander.xyz 2 months ago
It’s really nothing of the sort.
Aatube@kbin.social 2 months ago
- Specifying weights, biases and shape definitely makes a graph.
- 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 2 months ago
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There are graph neural networks (meaning NNs that work on graphs), but I don’t think that’s what is used here.
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I do not understand what you mean by “routes”. I suspect that you have misunderstood something fundamental.
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9point6@lemmy.world 2 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.
Amir@lemmy.ml 2 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.
General_Effort@lemmy.world 2 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.