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.
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?
> 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.
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.
@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.
Looking at my open source model downloaded from the internet…
Yes?
What makes it open source?
The license.
If I license a binary as open source does that make it open source?
Nope. Second point in the definition: https://opensource.org/osd
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.
@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.
Just because open source AI is not feasible at the moment is no reason to change the definition of open source.
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?
@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.
