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Yeah, that's a fair critique, I think the short answer is depends who you ask. See this FAQ here: https://www.licenses.ai/faq-2 https://www.licenses.ai/faq-2

Yeah, that's a fair critique, I think the short answer is depends who you ask. See this FAQ here: https://www.licenses.ai/faq-2 https://www.licenses.ai/faq-2 Specifically: Q: "Are OpenRAILs considered open source licenses according to the Open Source Definition? NO." A: "THESE ARE NOT OPEN SOURCE LICENSES, based on the definition used by Open Source Initiative, because it has some restrictions on the use of the licensed AI artifact. That said, we consider OpenRAIL licenses to be “open”. OpenRAIL enables reuse, distribution, commercialization, and adaptation as long as the artifact is not being applied for use-cases that have been restricted. Our main aim is not to evangelize what is open and what is not but rather to focus on the intersection between open and responsible licensing." FWIW, there's a lot of active discussion in this space, and it could be the case that e.g. communities settle on releasing code under OSI-approved licenses and models/artifacts under lowercase "open" but use-restricted licenses.

skybrian 4y ago
Fair enough. "Source available" would be better than "open source" in this case, to avoid misleading people. (You do want them to read the terms.)
- JoshTriplett 4y ago
  Yeah, this should not have a headline of "open source". Really disappointing that this isn't actually open, or even particularly close to being open.
- daveloyall 4y ago
  I'm not familiar with machine learning. But, I'm familiar with poking around in source code repos! I found this https://huggingface.co/openjourney/openjourney/blob/main/text_encoder/pytorch_model.bin https://huggingface.co/openjourney/openjourney/blob/main/tex... . It's a giant binary file. A big binary blob. (The format of the blob is python's "pickle" format: a binary serialization of an in-memory object, used to store an in-memory object and later load it, perhaps on a different machine.) But, I did not find any source code for generating that file. Am I missing something? Shouldn't there at least be a list of input images, etc and some script that uses them to train the model?
  - kmeisthax 4y ago
    Hahahahaha you sweet summer child. Training code? For an art generator?! Yeah, no. Nobody in the AI community actually provides training code. If you want to train from scratch you'll need to understand what their model architecture is, collect your own dataset, and write your own training loop. The closest I've come across is code for training an unconditional U-Net; those just take an image and denoise/draw it. CLIP also has its own training code - though everyone just seems to use OpenAI CLIP[0]. You'll need to figure out how to write a Diffusers pipeline that lets you combine CLIP and a U-Net together, and then alter the U-Net training code to feed CLIP vectors into the model, etc. Stable Diffusion also uses a Variational Autoencoder in front of the U-Net to get higher resolution and training performance, which I've yet to figure out how to train. The blob you are looking at is the actual model weights. For you see, AI is proprietary software's final form. Software so proprietary that not even the creators are allowed to see the source code. Because there is no source code. Just piles and piles of linear algebra, nonlinear activation functions, and calculus. For the record, I am trying to train-from-scratch an image generator using public domain data sources[1]. It is not going well: after adding more images it seems to have gotten significantly dumber, with or without a from-scratch trained CLIP. [0] I think Google Imagen is using BERT actually [1] Specifically, the PD-Art-old-100 category on Wikimedia Commons.
    - kelipso 4y ago
      Have you looked at LAION-400M? And the OpenCLIP [1] people have replicated CLIP performance using LAION-400M. [1] https://github.com/mlfoundations/open_clip https://github.com/mlfoundations/open_clip
    - walterbell 4y ago
      Thanks for educating the masses of machine-unwashed newbies!
    - nl 4y ago
      This isn't entirely accurate. The SD training set is available and the exact settings are described in reasonable details: > The model is trained from scratch 550k steps at resolution 256x256 on a subset of LAION-5B filtered for explicit pornographic material, using the LAION-NSFW classifier with punsafe=0.1 and an aesthetic score >= 4.5. Then it is further trained for 850k steps at resolution 512x512 on the same dataset on images with resolution >= 512x512. LAION-5B is available as a list of urls.
EamonnMR 4y ago
Seems like 'the lawyers who made the license' and the OSI might be good authorities on what's open source. I'd love to hear a good FSF rant about RAIL though.
- deleted 4y ago
  [deleted]
dmm 4y ago
Are ML models even eligible for copyright protection? The code certainly but what about the trained weights?
- charcircuit 4y ago
  My thought is that it is a derivative work from the training data. The creativity comes from what you choose to or not to include.
kmeisthax 4y ago
My biggest critique of OpenRAIL is that it's not entirely clear that AI is copyrightable[0] to begin with. Specifically the model weights are just a mechanical derivation of training set data. Putting aside the "does it infringe[1]" question, there is zero creativity in the training process. All the creativity is either in the source images or the training code. AI companies scrape source images off the Internet without permission, so they cannot use the source images to enforce OpenRAIL. And while they would own the training code, nobody is releasing training code[2], so OpenRAIL wouldn't apply there. So I do not understand how the resulting model weights are a subject of copyright at all, given that the US has firmly rejected the concept of "sweat of the brow" as a copyrightability standard. Maybe in the EU you could claim database rights over the training set you collected. But the US refuses to enforce those either. [0] I'm not talking about "is AI art copyrightable" - my personal argument would be that the user feeding it prompts or specifying inpainting masks is enough human involvement to make it copyrightable. The Copyright Office's refusal to register AI-generated works has been, so far, purely limited to people trying to claim Midjourney as a coauthor. They are not looking over your work with a fine-toothed comb and rejecting any submissions that have badly-painted hands. [1] I personally think AI training is fair use, but a court will need to decide that. Furthermore, fair use training would not include fair use for selling access to the AI or its output. [2] The few bits of training code I can find are all licensed under OSI/FSF approved licenses or using libraries under such licenses.
- taneq 4y ago
  “Mechanical derivation” is doing a lot of heavy lifting here. What qualifies something as “mechanical”? Any algorithm? Or just digital algorithms? Any process entirely governed by the laws of physics?
  - kmeisthax 4y ago
    So, in the US, the bedrock of copyrightability is creativity. The opposite would be what SCOTUS derided as the "sweat of the brow" doctrine, where merely "working hard" would give you copyright over the result. No court in the US will actually accept a sweat of the brow argument, of course, because there's Supreme Court precedent against it. This is why you can't copyright maps[0], and why scans of public domain artwork are automatically public domain[1][2]. Because there's no creativity in them. The courts do not oppose the use of algorithms or mechanical tools in art. If I draw something in Photoshop, I still own it. Using, say, a blur or contrast filter does not reduce the creativity of the underlying art, because there's still an artist deciding what filters to use, how to control them, et cetera. That doesn't apply for AI training. The controls that we do have for AI are hyperparameters and training set data. Hyperparameters are not themselves creative inputs; they are selected by trial and error to get the best result. And training set data can be creative, but the specific AI we are talking about was trained purely on scraped images from the Internet, which the creator does not own. So you have a machine that is being fed no creativity, and thus will produce no creativity, so the courts will reject claims to ownership over it. [0] Trap streets ARE copyrightable, though. This is why you'll find fake streets that don't exist on your maps sometimes. [1] https://en.wikipedia.org/wiki/Bridgeman_Art_Library_v._Corel_Corp https://en.wikipedia.org/wiki/Bridgeman_Art_Library_v._Corel.... [2] Several museums continue to argue the opposite - i.e. that scanning a public domain work creates a new copyright on the scan. They even tried to harass the Wikimedia Foundation over it: https://en.wikipedia.org/wiki/National_Portrait_Gallery_and_Wikimedia_Foundation_copyright_dispute https://en.wikipedia.org/wiki/National_Portrait_Gallery_and_...

skybrian 4y ago

Fair enough. "Source available" would be better than "open source" in this case, to avoid misleading people. (You do want them to read the terms.)

JoshTriplett 4y ago
Yeah, this should not have a headline of "open source". Really disappointing that this isn't actually open, or even particularly close to being open.
daveloyall 4y ago
I'm not familiar with machine learning. But, I'm familiar with poking around in source code repos! I found this https://huggingface.co/openjourney/openjourney/blob/main/text_encoder/pytorch_model.bin https://huggingface.co/openjourney/openjourney/blob/main/tex... . It's a giant binary file. A big binary blob. (The format of the blob is python's "pickle" format: a binary serialization of an in-memory object, used to store an in-memory object and later load it, perhaps on a different machine.) But, I did not find any source code for generating that file. Am I missing something? Shouldn't there at least be a list of input images, etc and some script that uses them to train the model?
- kmeisthax 4y ago
  Hahahahaha you sweet summer child. Training code? For an art generator?! Yeah, no. Nobody in the AI community actually provides training code. If you want to train from scratch you'll need to understand what their model architecture is, collect your own dataset, and write your own training loop. The closest I've come across is code for training an unconditional U-Net; those just take an image and denoise/draw it. CLIP also has its own training code - though everyone just seems to use OpenAI CLIP[0]. You'll need to figure out how to write a Diffusers pipeline that lets you combine CLIP and a U-Net together, and then alter the U-Net training code to feed CLIP vectors into the model, etc. Stable Diffusion also uses a Variational Autoencoder in front of the U-Net to get higher resolution and training performance, which I've yet to figure out how to train. The blob you are looking at is the actual model weights. For you see, AI is proprietary software's final form. Software so proprietary that not even the creators are allowed to see the source code. Because there is no source code. Just piles and piles of linear algebra, nonlinear activation functions, and calculus. For the record, I am trying to train-from-scratch an image generator using public domain data sources[1]. It is not going well: after adding more images it seems to have gotten significantly dumber, with or without a from-scratch trained CLIP. [0] I think Google Imagen is using BERT actually [1] Specifically, the PD-Art-old-100 category on Wikimedia Commons.
  - kelipso 4y ago
    Have you looked at LAION-400M? And the OpenCLIP [1] people have replicated CLIP performance using LAION-400M. [1] https://github.com/mlfoundations/open_clip https://github.com/mlfoundations/open_clip
  - walterbell 4y ago
    Thanks for educating the masses of machine-unwashed newbies!
  - nl 4y ago
    This isn't entirely accurate. The SD training set is available and the exact settings are described in reasonable details: > The model is trained from scratch 550k steps at resolution 256x256 on a subset of LAION-5B filtered for explicit pornographic material, using the LAION-NSFW classifier with punsafe=0.1 and an aesthetic score >= 4.5. Then it is further trained for 850k steps at resolution 512x512 on the same dataset on images with resolution >= 512x512. LAION-5B is available as a list of urls.

EamonnMR 4y ago

Seems like 'the lawyers who made the license' and the OSI might be good authorities on what's open source. I'd love to hear a good FSF rant about RAIL though.

deleted 4y ago
[deleted]

dmm 4y ago

Are ML models even eligible for copyright protection? The code certainly but what about the trained weights?

charcircuit 4y ago
My thought is that it is a derivative work from the training data. The creativity comes from what you choose to or not to include.

kmeisthax 4y ago

My biggest critique of OpenRAIL is that it's not entirely clear that AI is copyrightable[0] to begin with. Specifically the model weights are just a mechanical derivation of training set data. Putting aside the "does it infringe[1]" question, there is zero creativity in the training process. All the creativity is either in the source images or the training code. AI companies scrape source images off the Internet without permission, so they cannot use the source images to enforce OpenRAIL. And while they would own the training code, nobody is releasing training code[2], so OpenRAIL wouldn't apply there. So I do not understand how the resulting model weights are a subject of copyright at all, given that the US has firmly rejected the concept of "sweat of the brow" as a copyrightability standard. Maybe in the EU you could claim database rights over the training set you collected. But the US refuses to enforce those either. [0] I'm not talking about "is AI art copyrightable" - my personal argument would be that the user feeding it prompts or specifying inpainting masks is enough human involvement to make it copyrightable. The Copyright Office's refusal to register AI-generated works has been, so far, purely limited to people trying to claim Midjourney as a coauthor. They are not looking over your work with a fine-toothed comb and rejecting any submissions that have badly-painted hands. [1] I personally think AI training is fair use, but a court will need to decide that. Furthermore, fair use training would not include fair use for selling access to the AI or its output. [2] The few bits of training code I can find are all licensed under OSI/FSF approved licenses or using libraries under such licenses.

taneq 4y ago
“Mechanical derivation” is doing a lot of heavy lifting here. What qualifies something as “mechanical”? Any algorithm? Or just digital algorithms? Any process entirely governed by the laws of physics?
- kmeisthax 4y ago
  So, in the US, the bedrock of copyrightability is creativity. The opposite would be what SCOTUS derided as the "sweat of the brow" doctrine, where merely "working hard" would give you copyright over the result. No court in the US will actually accept a sweat of the brow argument, of course, because there's Supreme Court precedent against it. This is why you can't copyright maps[0], and why scans of public domain artwork are automatically public domain[1][2]. Because there's no creativity in them. The courts do not oppose the use of algorithms or mechanical tools in art. If I draw something in Photoshop, I still own it. Using, say, a blur or contrast filter does not reduce the creativity of the underlying art, because there's still an artist deciding what filters to use, how to control them, et cetera. That doesn't apply for AI training. The controls that we do have for AI are hyperparameters and training set data. Hyperparameters are not themselves creative inputs; they are selected by trial and error to get the best result. And training set data can be creative, but the specific AI we are talking about was trained purely on scraped images from the Internet, which the creator does not own. So you have a machine that is being fed no creativity, and thus will produce no creativity, so the courts will reject claims to ownership over it. [0] Trap streets ARE copyrightable, though. This is why you'll find fake streets that don't exist on your maps sometimes. [1] https://en.wikipedia.org/wiki/Bridgeman_Art_Library_v._Corel_Corp https://en.wikipedia.org/wiki/Bridgeman_Art_Library_v._Corel.... [2] Several museums continue to argue the opposite - i.e. that scanning a public domain work creates a new copyright on the scan. They even tried to harass the Wikimedia Foundation over it: https://en.wikipedia.org/wiki/National_Portrait_Gallery_and_Wikimedia_Foundation_copyright_dispute https://en.wikipedia.org/wiki/National_Portrait_Gallery_and_...