this post was submitted on 28 Oct 2024
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The stretching is just so blatant. People who train neural networks do not write a bunch of tokens and weights. They take a corpus of training data and run a training program to generate the weights. That's why it is the training program and the corpus that should be considered the source form of the program. If either of these can't be made available in a way that allows redistribution of verbatim and modified versions, it can't be open source. Even if I have a powerful server farm and a list of data sources for Llama 3, I can't replicate the model myself without committing copyright infringement (neither could Facebook for that matter, and that's not an entirely separate issue).
There are large collections of freely licensed and public domain media that could theoretically be used to train a model, but that model surely wouldn't be as big as the proprietary ones. In some sense truly open source AI does exist and has for a long time, but that's not the exciting thing OSI is lusting after, is it?
I've already talked about the indirect damage AI's causing to open source in this thread, but this hyper-stretched definition's probably doing some direct damage as well.
Considering that this "Open Source AI" definition is (almost certainly by design) going to openwash the shit out of blatant large-scale theft, I expect it'll heavily tar the public image of open-source, especially when these "Open Source AIs" start getting sued for copyright infringement.