Yeah, that latter bit was my original point. It's easy to hide a derivative work generated by the model, but the model itself MUST comply with the licenses it is trying to launder.
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Antwort an @NoraDotCodes @hipsterelectron und
my apologies, i noticed it earlier but ran out of characters to fully word it; yes you had mentioned it, and word it better than i did ;)
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Antwort an @luisbruno @NoraDotCodes und
oh wow. now that you mention it, it's a very interesting question whether it's even possible for an ML model to comply with the GPL.
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Antwort an @ireneista @luisbruno und
the GPL goes into considerable detail on what it means to provide the "source" of something.
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Antwort an @ireneista @luisbruno und
Yeah. They would have to provide the scripts they used to train the model, and all the training material...
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Antwort an @NoraDotCodes @ireneista und
sorry, i don't see it: that's the AGPL territory, no? for GPL, providing the original training data without modification should meet section #1 of the GPL
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Antwort an @luisbruno @NoraDotCodes und
yeah, you're correct. we went back and re-read the GPL just now to look for the relevant wording and that's when we were reminded of the AGPL.
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Antwort an @ireneista @luisbruno und
Are we sure the training set didn't include AGPL code, though?
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Antwort an @NoraDotCodes @luisbruno und
it would be pretty difficult for GitHub to filter things out that way, given that a single repo may combine code under different licenses. but we shouldn't have to speculate - it's a reasonable question that GitHub should address.
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Antwort an @ireneista @NoraDotCodes und
if they're not willing to address it, that's damning in its own right.
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Antwort an @ireneista @luisbruno und
I sent in a support ticket asking if any of my GPL code was used, so we'll see.
17:44 - 30. Juni 2021
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