• cmnybo@discuss.tchncs.de
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    5 months ago

    It’s rather hard to open source the model when you trained it off a bunch of copyrighted content that you didn’t have permission to use.

    • chebra@mstdn.io
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      5 months ago

      @cmnybo @marvelous_coyote That’s… not how it works. You wouldn’t see any copyrighted works in the model. We are already pretty sure even the closed models were trained on copyrighted works, based on what they sometimes produce. But even then, the AI companies aren’t denying it. They are just saying it was all “fair use”, they are using a legal loophole, and they might win this. Basically the only way they could be punished on copyright is if the models produce some copyrighted content verbatim.

        • chebra@mstdn.io
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          5 months ago

          @ReakDuck Yup, and that’s a much better avenue to fight against the AI companies. Because fundamentally, this is almost impossible to avoid in the ML models. We should stop complaining about how they scraped copyrighted content, this complaint won’t succeed until that legal loophole is removed. But when they reproduce copyrighted content, that could be fatal. And this applies also to reproducing GPL code samples by copilot for example.

          • ReakDuck@lemmy.ml
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            5 months ago

            Yeah, you just summarize my thoughts I had before chatGPT came to light.

            Ok, not really. My thoughts were: could I store a Picture made illegaly into an LLM and later on ask it to show it again? Because I never stored it as a file and LLMs seem to not count as a storage.

            I could store Pictures I would not be allowed to.

    • flamingmongoose@lemmy.blahaj.zone
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      5 months ago

      BERT and early versions of GPT were trained on copyright free datasets like Wikipedia and out of copyright books. Unsure if those would be big enough for the modern ChatGPT types

  • astro_ray@lemdro.id
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    5 months ago

    I feel like one of thr problem is LLMs hijacked the definition of AI. Like another comment said, the way they trained on copyrighted material, it’s probably not possible. But imagine there was another model (not necessarily LLM) and it was trained with completely public domain material. For example maybe something trained to find genetic diseases from genetic samples of a person, or detecting asteroids from telescope images. Those could become open source. Now, I am not an expert, but do we consider those AI?

    • chebra@mstdn.io
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      5 months ago

      @astro_ray @marvelous_coyote It seems you have the incorrect idea about what open-source means, which is quite sad here in the open-source lemmy community. Being trained on public domain material does NOT make the model open-source. It’s about the license - what the recipients of the model are allowed to do with it - open-source must allow derivative works and commercial use, on top of seeing the code, but for LLM models the “code” is just a bunch of float numbers, nothing interesting to see.

  • 1984
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    5 months ago

    Looking at my open source model downloaded from the internet…

    Yes?

            • sunstoned@lemmus.org
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              5 months ago

              My point precisely :)

              A pre-trained model alone can’t really be open source. Without the source code and full data set used to generate it, a model alone is analogous to a binary.

              • chebra@mstdn.io
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                5 months ago

                @sunstoned @Ephera That’s nonsense. You could write the scripts, collect the data, publish all, but without the months of GPU training you wouldn’t have the trained model, so it would all be worthless. The code used to train all the proprietary models is already open-source, it’s things like PyTorch, Tensorflow etc. For a model to be open-source means you can download the weights and you are allowed to use it as you please, including modifying it and publishing again. It’s not about the dataset.

                • sunstoned@lemmus.org
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                  5 months ago

                  Quite aggressive there friend. No need for that.

                  You have a point that intensive and costly training process plays a factor in the usefulness of a truly open source gigantic model. I’ll assume here that you’re referring to the likes of Llama3.1’s heavy variant or a similarly large LLM. Note that I wasn’t referring to gigantic LLMs specifically when referring to “models”. It is a very broad category.

                  However, that doesn’t change the definition of open source.

                  If I have an SDK to interact with a binary and “use it as [I] please” does that mean the binary is then open source because I can interact with it and integrate it into other systems and publish those if I wish? :)

                • dandi8@fedia.io
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                  5 months ago

                  Just because open source AI is not feasible at the moment is no reason to change the definition of open source.

            • sunstoned@lemmus.org
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              5 months ago

              You would be obligated, if your goal were to be complying with the spirit and description of open source (and sleeping well at night, in my opinion).

              Do you have the source code and full data set used to train the “open source” model you’re referring to?

                • sunstoned@lemmus.org
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                  5 months ago

                  Do you plan to sue the provider of your “open source” model? If so, would the goal be to force the provider to be in full compliance with the license (access to their source code and training set)? Would the goal be to force them to change the license to something they comply with?

  • llothar@lemmy.ml
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    5 months ago

    The architecture can easily be open source - as long as repo is missing just the training data. Just like there are Doom engines that are open source, even though they do not provide WAD files, which are still copyrighted. The code is there, but it is somewhat useless without the data. Analogy is not perfect, but let’s assume it compiles to a single binary containing everything, maps included.

    If ID Software gives you a compiled Doom with maps free to use it is freeware. If they open source the engine (they actually did), but do not release the WAD files as open source, the compiled game is not open source - it is still freeware.

    It is not complicated really.

    • dandi8@fedia.io
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      5 months ago

      But then it’s the tools to make the AI that are open source, not the model itself.

      I think that we can’t have a useful discussion on this if we don’t distinguish between the source code of the training framework and the “source code” of the model itself, which is the training data set. E.g, Mistral Nemo can’t be considered open source, because there is no Mistral Nemo without the training data set.

      It’s like with your Doom example - the Doom engine is open source, but Doom itself isn’t. Unfortunately, here the analogy falls apart a bit, because there is no logic in the art assets of doom, whereas there is plenty of logic in the dataset for Mistral - enough that the devs said they don’t want to disclose it for fear of competition.

      This data set logic - incredibly valuable and important for the behavior of the AI, as confirmed by the devs - is why the model is not open source, even though the training framework might be.

      Edit:

      Another aspect is the spirit of open-source. One of the benefits of OSS is you can study the source code to determine whether the software is in compliance with various regulations - you can audit that software.

      How can we audit Mistral Nemo? How can we confirm that it doesn’t utilize copyrighted material to provide its answers?

      • chebra@mstdn.io
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        5 months ago

        @dandi8 @marvelous_coyote

        > E.g, Mistral Nemo can’t be considered open source, because there is no Mistral Nemo without the training data set.

        Right here - that’s your logical conflict. By downloading the model file, you can run it, thereby you can “have Mistral Nemo” even without having the training data, contradicting your statement -> your statement is invalid.

        • dandi8@fedia.io
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          5 months ago

          You’re, hopefully not on purpose, misunderstanding the argument.

          You can download a binary of Adobe Photoshop and run it. That doesn’t make it open source.

          I cannot make Mistral Nemo from just the open-sourced tools, therefore Mistral Nemo is not open source.

          • chebra@mstdn.io
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            5 months ago

            @dandi8 the license of Adobe Photoshop is not open-source because it specifically restricts reverse-engineering and modifications, and a lot of other things. The license of Mistral Nemo IS open-source, because it’s Apache2.0, you are free to use it, study it, redistribute it, … open-source doesn’t say anything about giving you all the tools to re-create it, because that would mean they would need to give you the GPU time. “Open-source” simply means something else than what you think.

            • dandi8@fedia.io
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              5 months ago

              You seem to think that “open source” is just about the license and that a project is open source if you’re allowed to reverse engineer it.

              You have a gross misunderstanding of what OSS is, which contradicts even the Wikipedia definition, and are unwilling to educate yourself about it.

              You suggest that Mistral would need to lend us their GPUs to fit the widely accepted definition of OSS, which is untrue.

              You’re either not a software engineer, or you have an agenda.

              Because of this, I will not be continuing this conversation with you, as at this point it is just a waste of my time.

  • dandi8@fedia.io
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    5 months ago

    Are the petabytes of training data included in the repo? No? Then how could it ever be called open source?

    At best, some of the current AI can be called freeware.

    If you’re just including the trained AI itself, it’s more like including a binary, rather than source.

    You can’t really modify Llama in a significant way, can you? You can’t fork it and continue improving that fork.