Audacity has added AI audio editing capabilities thanks to Intel’s free OpenVINO plugins. These plugins add AI-powered noise suppression, speech transcription, music generation and remixing, and music separation to the freeware sound editor and are available for download today.
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.
Tensorflowlite models are tiny, but they're potentially as much an audio revolution as synthetizer were in the 70s.
It's hard to tell if that's what we're looking at here.
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.
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.
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.
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)
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.