10 ms·

Notable: they open-sourced the weights under Apache 2.0, unlike OpenAI and DeepMind whose IMO gold models are still proprietary.

SilverElfin 11mo ago
If they open source just weights and not the training code and data, then it’s still proprietary.
- mips_avatar 11mo ago
  Yeah but you can distill
  - amelius 11mo ago
    Is that the equivalent of decompile?
    - c0balt 11mo ago
      No, that is the equivalent of lossy compression.
  - littlestymaar 11mo ago
    You can distill closed weights models as well. (Just not logit-distillation)
    - mips_avatar 11mo ago
      Though it violates their terms of service
- falcor84 11mo ago
  Isn't that a bit like saying that if I open source a tool, but not a full compendium of all the code that I had read, which led me to develop it, then it's not really open source?
  - fragmede 11mo ago
    No. In that case, you're providing two things, a binary version of your tool, and the tool's source. That tool's source is available to inspect and build their own copy. However, given just the weights, we don't have the source, and can't inspect what alignment went into it. In the case of DeepSeek, we know they had to purposefully cause their model to consider Tiananmen Square something it shouldn't discuss. But without the source used to create the model, we don't know what else is lurking around inside the model.
    - NitpickLawyer 11mo ago
      > However, given just the weights, we don't have the source This is incorrect, given the definitions in the license. > (Apache 2.0) "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. (emphasis mine) In LLMs, the weights are the preferred form of making modifications. Weights are not compiled from something else. You start with the weights (randomly initialised) and at every step of training you adjust the weights. That is not akin to compilation, for many reasons (both theoretical and practical). In general licenses do not give you rights over the "know-how" or "processes" in which the licensed parts were created. What you get is the ability to inspect, modify, redistribute the work as you see fit. And most importantly, you modify the work just like the creators modify the work (hence the preferred form). Just not with the same data (i.e. you can modify the source of chrome all you want, just not with the "know-how and knowledge" of a google engineer - the license can not offer that). This is also covered in the EU AI act btw. > General-purpose AI models released under free and open-source licences should be considered to ensure high levels of transparency and openness if their parameters, including the weights, the information on the model architecture, and the information on model usage are made publicly available. The licence should be considered to be free and open-source also when it allows users to run, copy, distribute, study, change and improve software and data, including models under the condition that the original provider of the model is credited, the identical or comparable terms of distribution are respected.
      - fragmede 11mo ago
- amelius 11mo ago
  True. But the headline says open weights.
- very_illiterate 11mo ago
  [flagged]
- ekianjo 11mo ago
  It's just open weights, the source has no place in this expression
- jimmydoe 11mo ago
  you are absolutely right. I'd rather use true closed models, not fake open source ones from China.
PunchyHamster 11mo ago
I think we should treat copyright for the weights the same way the AI companies treat source material ;)
- littlestymaar 11mo ago
  We don't even have to do that: weights being entirely machine generated without human intervention, they are likely not copyrightable in the first place. In fact, we should collectively refuse to abide to these fantasy license before weight copyrightability gets created out of thin air because it's been commonplace for long enough.
  - mitthrowaway2 11mo ago
    There's an argument by which machine-learned neural network weights are a lossy compression of (as well as a smooth interpolator over) the training set. An mp3 file is also a machine-generated lossy compression of a cd-quality .wav file, but it's clearly copyrightable. To that extent, the main difference between a neural network and an .mp3 is that the mp3 compression cannot be used to interpolate between two copyrighted works to output something in the middle. This is, on the other hand, perhaps the most common use case for genAI, and it's actually tricky to get it to not output something "in the middle" (but also not impossible). I think the copyright argument could really go either way here.
    - littlestymaar 11mo ago
      > An mp3 file is also a machine-generated lossy compression of a cd-quality .wav file, but it's clearly copyrightable. Not the .mp3 itself, the creative piece of art that it encode. You can't record Taylor Swift at a concert and claim copyright on that. Nor can you claim copyright on mp3 re-encoded old audio footage that belong to the public domain. Whether LLMs are in the first category (copyright infringement of copyright holders of the training data) or in the second (public domain or fair use) is an open question that jurisprudence is slowly resolving depending on the jurisdiction, but that doesn't address the question of the weight themselves.

SilverElfin 11mo ago

If they open source just weights and not the training code and data, then it’s still proprietary.

mips_avatar 11mo ago
Yeah but you can distill
- amelius 11mo ago
  Is that the equivalent of decompile?
  - c0balt 11mo ago
    No, that is the equivalent of lossy compression.
- littlestymaar 11mo ago
  You can distill closed weights models as well. (Just not logit-distillation)
  - mips_avatar 11mo ago
    Though it violates their terms of service
falcor84 11mo ago
Isn't that a bit like saying that if I open source a tool, but not a full compendium of all the code that I had read, which led me to develop it, then it's not really open source?
- fragmede 11mo ago
  No. In that case, you're providing two things, a binary version of your tool, and the tool's source. That tool's source is available to inspect and build their own copy. However, given just the weights, we don't have the source, and can't inspect what alignment went into it. In the case of DeepSeek, we know they had to purposefully cause their model to consider Tiananmen Square something it shouldn't discuss. But without the source used to create the model, we don't know what else is lurking around inside the model.
  - NitpickLawyer 11mo ago
    > However, given just the weights, we don't have the source This is incorrect, given the definitions in the license. > (Apache 2.0) "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. (emphasis mine) In LLMs, the weights are the preferred form of making modifications. Weights are not compiled from something else. You start with the weights (randomly initialised) and at every step of training you adjust the weights. That is not akin to compilation, for many reasons (both theoretical and practical). In general licenses do not give you rights over the "know-how" or "processes" in which the licensed parts were created. What you get is the ability to inspect, modify, redistribute the work as you see fit. And most importantly, you modify the work just like the creators modify the work (hence the preferred form). Just not with the same data (i.e. you can modify the source of chrome all you want, just not with the "know-how and knowledge" of a google engineer - the license can not offer that). This is also covered in the EU AI act btw. > General-purpose AI models released under free and open-source licences should be considered to ensure high levels of transparency and openness if their parameters, including the weights, the information on the model architecture, and the information on model usage are made publicly available. The licence should be considered to be free and open-source also when it allows users to run, copy, distribute, study, change and improve software and data, including models under the condition that the original provider of the model is credited, the identical or comparable terms of distribution are respected.
    - fragmede 11mo ago
amelius 11mo ago
True. But the headline says open weights.
very_illiterate 11mo ago
[flagged]
ekianjo 11mo ago
It's just open weights, the source has no place in this expression
jimmydoe 11mo ago
you are absolutely right. I'd rather use true closed models, not fake open source ones from China.

PunchyHamster 11mo ago

I think we should treat copyright for the weights the same way the AI companies treat source material ;)

littlestymaar 11mo ago
We don't even have to do that: weights being entirely machine generated without human intervention, they are likely not copyrightable in the first place. In fact, we should collectively refuse to abide to these fantasy license before weight copyrightability gets created out of thin air because it's been commonplace for long enough.
- mitthrowaway2 11mo ago
  There's an argument by which machine-learned neural network weights are a lossy compression of (as well as a smooth interpolator over) the training set. An mp3 file is also a machine-generated lossy compression of a cd-quality .wav file, but it's clearly copyrightable. To that extent, the main difference between a neural network and an .mp3 is that the mp3 compression cannot be used to interpolate between two copyrighted works to output something in the middle. This is, on the other hand, perhaps the most common use case for genAI, and it's actually tricky to get it to not output something "in the middle" (but also not impossible). I think the copyright argument could really go either way here.
  - littlestymaar 11mo ago
    > An mp3 file is also a machine-generated lossy compression of a cd-quality .wav file, but it's clearly copyrightable. Not the .mp3 itself, the creative piece of art that it encode. You can't record Taylor Swift at a concert and claim copyright on that. Nor can you claim copyright on mp3 re-encoded old audio footage that belong to the public domain. Whether LLMs are in the first category (copyright infringement of copyright holders of the training data) or in the second (public domain or fair use) is an open question that jurisprudence is slowly resolving depending on the jurisdiction, but that doesn't address the question of the weight themselves.