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> I find it absurd that if I create a model architecture, publish my source code, and slap an open source license on it, I can call that open source…but the mom

> I find it absurd that if I create a model architecture, publish my source code, and slap an open source license on it, I can call that open source…but the moment I publish some weights that are the result of running the program on some proprietary dataset, all of a sudden I can’t call it open source anymore. Then you don't understand open source. You would be distributing something that could not be reproduced because its source was not provided. The source to the product would not be open. It's that simple. The same principle has always applied to images, audio and video. There's no reason for you to be granted a free pass just becauase it's a new medium.

Manuel_D 2y ago
I'm not sure how that relates to AI models. Freely distributing compiled binaries, but not the source code, means modification is extremely difficult. Effectively impossible without reverse-engineering expertise. But I've definitely seen modifications to Llama3.1 floating around. Correctly me if I'm wrong, but open-weight models can be modified fairly easily.
darksaints 2y ago
Let me spell it out for you: 1. I publish the source code to a program that inputs a list of numbers and outputs the sum into a text file. License is open source. Result according to you: this is an open source program. 2. Now, using that open source program, I also publish an output result text file after feeding it a long list of input numbers generated from a proprietary dataset. I even decide to publish this result and give it an open source license. Result according to you: this is NO LONGER AN OPEN SOURCE PROGRAM!!?!! How does that make any fucking sense? You have the model and can use it any way you want. The model can be trained any way you want. You can plug in random weights and random text input if you want to. That is an open source model. The act of additionally publishing a bunch of weights that you can choose to use if you want to should not make that model closed source.
- guerrilla 2y ago
  Hey, tone down the agression. Programs aren't the only things that can be open-source. LLMs are made of more than just programs. Some of those things that are not programs are not open source. If any part of something is not open source, the whole of that thing is not open source, per definition. Therefor any LLM that has any parts that are not open source is not open source, even if some parts of it are open source.
  - darksaints 2y ago
    That simply isn't true. LLM weights are an output of a model training process. They are also an input of a model inference process. Providing weights for people to use does not change the source code in any way, shape, or form. While a model does require weights in order to function, there is nothing about the model that requires you to use any weights provided by anybody, regardless of how they were trained. The model is open source. You can train a Llama 3.1 model from scratch on your proprietary collection of alien tentacle erotica, and you can do so precisely because the model is open source. You can claim that the weights themselves are not open source, but that says absolutely nothing about the model being open source. The weights distributed are simply not required. But more importantly, under your definition, there will never exist in any form a useful open source set of weights. Because almost all data is proprietary. Anybody can train on large quantities of proprietary data without permission using fair use protections, but no matter what you can't redistribute it without permission. Any weights derived from training a model on data that can be redistributed by a single entity would inherently be so tiny that it would be almost useless. You could create a model with a few billion parameters that could memorize it all verbatim. Open weights can be useful, and they can be a huge boon to users that don't have the resources to train large models, but they aren't required for any meaningful definition of open source.
    - guerrilla 2y ago
      > But more importantly, under your definition, there will never exist in any form a useful open source set of weights. Because almost all data is proprietary. Anybody can train on large quantities of proprietary data without permission using fair use protections, but no matter what you can't redistribute it without permission. Any weights derived from training a model on data that can be redistributed by a single entity would inherently be so tiny that it would be almost useless. You could create a model with a few billion parameters that could memorize it all verbatim. That may very well be so. We'll see what the future holds for us.
jncfhnb 2y ago
I have a properietary algorithm that produced the following code: print(“hello world”) Are you going to tell me I cannot open source this hello world program because it was produced by an algorithm that I have not open sourced?

Manuel_D 2y ago

I'm not sure how that relates to AI models. Freely distributing compiled binaries, but not the source code, means modification is extremely difficult. Effectively impossible without reverse-engineering expertise. But I've definitely seen modifications to Llama3.1 floating around. Correctly me if I'm wrong, but open-weight models can be modified fairly easily.

darksaints 2y ago

Let me spell it out for you: 1. I publish the source code to a program that inputs a list of numbers and outputs the sum into a text file. License is open source. Result according to you: this is an open source program. 2. Now, using that open source program, I also publish an output result text file after feeding it a long list of input numbers generated from a proprietary dataset. I even decide to publish this result and give it an open source license. Result according to you: this is NO LONGER AN OPEN SOURCE PROGRAM!!?!! How does that make any fucking sense? You have the model and can use it any way you want. The model can be trained any way you want. You can plug in random weights and random text input if you want to. That is an open source model. The act of additionally publishing a bunch of weights that you can choose to use if you want to should not make that model closed source.

guerrilla 2y ago
Hey, tone down the agression. Programs aren't the only things that can be open-source. LLMs are made of more than just programs. Some of those things that are not programs are not open source. If any part of something is not open source, the whole of that thing is not open source, per definition. Therefor any LLM that has any parts that are not open source is not open source, even if some parts of it are open source.
- darksaints 2y ago
  That simply isn't true. LLM weights are an output of a model training process. They are also an input of a model inference process. Providing weights for people to use does not change the source code in any way, shape, or form. While a model does require weights in order to function, there is nothing about the model that requires you to use any weights provided by anybody, regardless of how they were trained. The model is open source. You can train a Llama 3.1 model from scratch on your proprietary collection of alien tentacle erotica, and you can do so precisely because the model is open source. You can claim that the weights themselves are not open source, but that says absolutely nothing about the model being open source. The weights distributed are simply not required. But more importantly, under your definition, there will never exist in any form a useful open source set of weights. Because almost all data is proprietary. Anybody can train on large quantities of proprietary data without permission using fair use protections, but no matter what you can't redistribute it without permission. Any weights derived from training a model on data that can be redistributed by a single entity would inherently be so tiny that it would be almost useless. You could create a model with a few billion parameters that could memorize it all verbatim. Open weights can be useful, and they can be a huge boon to users that don't have the resources to train large models, but they aren't required for any meaningful definition of open source.
  - guerrilla 2y ago
    > But more importantly, under your definition, there will never exist in any form a useful open source set of weights. Because almost all data is proprietary. Anybody can train on large quantities of proprietary data without permission using fair use protections, but no matter what you can't redistribute it without permission. Any weights derived from training a model on data that can be redistributed by a single entity would inherently be so tiny that it would be almost useless. You could create a model with a few billion parameters that could memorize it all verbatim. That may very well be so. We'll see what the future holds for us.

jncfhnb 2y ago

I have a properietary algorithm that produced the following code: print(“hello world”) Are you going to tell me I cannot open source this hello world program because it was produced by an algorithm that I have not open sourced?