On Mon Apr 28, 2025 at 9:24 PM CEST, Aigars Mahinovs wrote:
In fact, for adjusting a LLM for use in a particular domain or a particular company it actually *is* the "binary" that is the *preferred* form to be modified - you take a model that "knows" a lot in general and "knows" how your language works and you train the model further by doing specialisation training for your, specific data set. And a result you get from one "generic" binary another - "specialized" binary.
While this may be the case for extremely big LLMs, I wouldn't call the trained model the preferred form of modification. You just want to do fine tuning? Sure, go ahead, but you aren't modifying the model in the real sense, and cannot study how it was implemented.
Moreover, this proposal is about "AI", and not LLMs in particular. Yes, "AI" is too broad, but I'd say that deep learning models should be in. And, speaking of deep learning, I recently had to play a bit with a computer vision model for object recognition, and fine-tuning wasn't enough --- I had to re-train the model from scratch. If the model were not free, I couldn't have completed my project.
That *could* be the technical difference in definitions between what is "DFSG-free AI" and what is "Debian-main-grade-free AI".
What? Isn't main supposed to represent DFSG-free stuff? Bye :)
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