Comment on Audacity adds AI audio editing capabilities thanks to free Intel OpenVINO plugins

BlastboomStrice@mander.xyz ⁨1⁩ ⁨year⁩ ago

• 9point6@lemmy.world ⁨1⁩ ⁨year⁩ 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.

  source

  • interdimensionalmeme@lemmy.ml ⁨1⁩ ⁨year⁩ ago

    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.

    source
  • Neato@ttrpg.network ⁨1⁩ ⁨year⁩ ago

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

    source

    • General_Effort@lemmy.world ⁨1⁩ ⁨year⁩ 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.

      source
    • Aatube@kbin.social ⁨1⁩ ⁨year⁩ ago

      It's data

      source

      • acockworkorange@mander.xyz ⁨1⁩ ⁨year⁩ ago

        It’s really nothing of the sort.

        source

        • -> View More Comments
    • 9point6@lemmy.world ⁨1⁩ ⁨year⁩ 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.

      source
    • Amir@lemmy.ml ⁨1⁩ ⁨year⁩ ago

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

      source
• bamboo@lemm.ee ⁨1⁩ ⁨year⁩ ago

  It seems reasonable given it includes multiple AI models.

  source
• Fisch@lemmy.ml ⁨1⁩ ⁨year⁩ 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.

  source
• Sneptaur@pawb.social ⁨1⁩ ⁨year⁩ ago

  Isn’t tenacity a joke project made by 4channers

  source

  • CaptainBasculin@lemmy.ml ⁨1⁩ ⁨year⁩ ago

    That fork is sneedacity, which is very dead.

    source

    • Sneptaur@pawb.social ⁨1⁩ ⁨year⁩ ago

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

      source
  • RmDebArc_5@lemmy.ml ⁨1⁩ ⁨year⁩ ago

    Tenacity is a Audacity fork without telemetry

    source

    • mp3@lemmy.ca ⁨1⁩ ⁨year⁩ ago

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

      source

      • Fisch@lemmy.ml ⁨1⁩ ⁨year⁩ 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.

        source