• Todd Bonzalez@lemm.ee
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    6 days ago

    “Open Source” is mostly the right term. AI isn’t code, so there’s no source code to open up. If you provide the dataset you trained off of, and open up the code used to train the model, that’s pretty close.

    Otherwise, we need to consider “open weights” and “free use” to be more accurate terms.

    For example, ChatGPT 3+ in undeniably closed/proprietary. You can’t download the model and run it on your own hardware. The dataset used to train it is a trade secret. You have to agree to all of OpenAI’s terms to use it.

    LLaMa is way more open. The dataset is largely known (though no public master copy exists). The code used to train is open source. You can download the model for local use, and train new models based off of the weights of the base model. The license allows all of this.

    It’s just not a 1:1 equivalent to open source software. It’s basically the equivalent of royalty free media, but with big collections of conceptual weights.

    • wewbull@feddit.uk
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      6 days ago

      AI isn’t code

      Yes it is. It defines a function from input to output. It’s not x86 or Arm code. It’s code that runs on a different type of machine. It’s a type of code that you may not be able to read, but it’s still code.

      • Sneezycat@sopuli.xyz
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        6 days ago

        Just by opening wikipedia “In computing, source code, or simply code or source, is a plain text computer program written in a programming language.” So what programming language is it?

        • wewbull@feddit.uk
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          5 days ago

          Is Maxine code “code”? And I don’t mean assembler, I mean the binary stream read by the processor.

          I’d say yes. People have programmed it. It’s where the verb “to code” comes from.

          These models are no different. They are binary streams that encode a function, a program, into a form that can be interpreted by a machine. Yes, a computer generated the code, but that’s nothing new.

        • model_tar_gz@lemmy.world
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          6 days ago

          Neural nets are typically written in C; then frameworks abstract on top of that (like Torch, or Tensorflow) providing higher-level APIs to languages like (most commonly) Python, or JavaScript.

          There are some other nn implementations in Rust, C++, etc.

          • General_Effort@lemmy.world
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            6 days ago

            Other way around. The NNs are written in, mostly, Python. The frameworks, mainly Pytorch now, handle the heavy-duty math.