We’re renewing our commitment to using Apache 2.0 license for our general purpose models, as we progressively move away from MRL-licensed models
It's a bit like developing a binary application and slapping a FOSS license on the binary while keeping the code proprietary. Not saying that's wrong or anything, but people reading these announcements tend to misunderstand what actually got FOSS licensed when the companies write stuff like this.
I'm not sure how someone would argue (in good faith) that training on copyrighted materials does not cause the weights to be a derivative of those materials and the output of their AI is not protected under copyright but the part in the middle, the weights, does fall under copyright.
Note that this would be about the weights (i.e. the numbers), not their container.
The opinion that AI output isn't copyrightable derives from the opinion of the US Copyright Office, which argues that AI output is more like commissioning an artist than like taking a picture. And since the artist isn't human they can't claim copyright for their work.
It's not at all obvious to me that the same argument would hold for the output of AI training. Never mind that the above argument about AI output is just the opinion of some US agency and hasn't been tested in court anywhere in the world.
https://en.wikipedia.org/wiki/Threshold_of_originality
Areas of dispute include photographs of famous paintings (is it more in the character of a photocopy?), photographs taken by animals (does the human get copyright if they deliberately created the situation where the animal would take a photograph?), and videos taken automatically (can a CCTV video have an author?)
Historically, the results are all over the place.
Similarly, claiming copyright on AI output is like claiming copyright on something like `init_state(42, &s); for (int i=0; i < count; i++) output[i] = next_random(&s);`. While there is a bit of (theoretical) effort involved into choosing 42 as a starting input, ultimately you can't really claim copyright on a bunch of random numbers because you chose the initial seed value.
Of course you can claim copyright in the code, but doing the same on the output makes no sense: even the if the idea of owning random numbers isn't absurd enough, consider what would happen if -say- 10000 people did the same thing (and to make things even more clear, what if `init_state` used only 8bits of the given number, therefore making sure that there would be a lot of people ending up with the same numbers).
AI is essentially `init_state` and `next_random`, just with more involved algorithms than a random number generator.
The only defense these AI companies have is making the weights machine output and thus not copyrightable.
But then again that's the theory, the copyright system follows money and it wouldn't be surprising to have contradicting ideas being allowed.
Like every other open source / source available LLM?
Also, I don't buy the argument that because many in the ecosystem mislabel/mislead people about the licensing, makes it ethically OK for everyone else to do so too.
This kind of purity test mindset doesn't help anyone. They are shipping the most modifiable form of their model.
I guess I'm vary of the messaging because I'm a developer 99% thanks to FOSS, and being able to learn from FOSS projects how to build similar stuff myself. Without FOSS, I probably wouldn't have been able to "escape" the working-class my family was "stuck in" when I grew up.
I want to do whatever I can to make sure others have the same opportunity, and it doesn't matter if the weights themselves are FOSS or not, others cannot learn how to create their own models based on just looking at the weights. You need to be able to learn the model architecture, training and what datasets models are using too, otherwise you won't get very far.
> This kind of purity test mindset doesn't help anyone. They are shipping the most modifiable form of their model.
It does help others who might be stuck in the same situation I was stuck in, that's not nothing nor is it about "purity". They're not shipping the most open model they can, they could have done something like OLMo (https://github.com/allenai/OLMo) which can teach people how to build their own models from scratch.
I'm not sure I'd even call Llama "open weights". For me that would mean I can download the weights freely (you cannot download Llama weights without signing a license agreement) and use them freely, you cannot use them freely + you need to add a notice from Meta/Llama on everything that uses Llama saying:
> prominently display “Built with Llama” on a related website, user interface, blogpost, about page, or product documentation.
https://www.llama.com/llama3_2/license/
Not sure what the correct label is, but it's not open source nor open weights, as far as I can tell.
To consider just the power of fine tuning: all of the press DeepSeek have received is over their R1 model, a relatively tiny fine-tune on their open source V3 model. The vast majority of the compute and data pipeline work to build R1 was complete in V3, while that final fine-tuning step to R1 is possible even by an enthusiastic dedicated individual. (And there are many interesting ways of doing it.)
The insistence every time open sourced model weights come up that it is not "truly" open source is tiring. There is enormous value in open source weights compared to closed APIs. Let us call them open source weights. What you want can be "open source data" or somesuch.
Agree that there is more value in open source weights than closed APIs, but what I really want to enable, is people learning how to create their own models from scratch. FOSS to me means being able to learn from other projects, how to build the thing yourself, and I wrote about why this is important to me here: https://news.ycombinator.com/item?id=42878817
It's not a puritan view but purely practical. Many companies started using FOSS as a marketing label (like what Meta does) and as someone who probably wouldn't be a software developer without being able to learn from FOSS, it fucking sucks that the ML/AI ecosystem is seemingly OK with the term being hijacked.
The thing you want, open source model data pipelines, is a different thing. It's existence in no way invalidates the concept of an open source model. Nothing has been hijacked.
Meta/Llama probably started the trend, and they still today say "The open-source AI models" and "Llama is the leading open source model family" which is grossly misleading.
You cannot download the Llama models or weights without signing a license agreement, you're not allowed to use it for anything you want, you need to add a disclaimer on anything that uses Llama (which almost the entire ecosystem breaks as they seemingly missed this when they signed the agreement) and so on, which to me goes directly against what FOSS means.
If you cannot reproduce the artifact yourself (again, granted you have the resources), you'd have a really hard time convincing me that that is FOSS.
If it would not be hijacked, then such articles would not exist.
META is falsely and deceptively, but also carefully, pretending to be Open Source.
The Open Source Definition – Open Source Initiative https://opensource.org/osd
What is Free Software? - GNU Project - Free Software Foundation https://www.gnu.org/philosophy/free-sw.html
Word "Open" as in "Open Source" - Words to Avoid (or Use with Care) Because They Are Loaded or Confusing https://www.gnu.org/philosophy/words-to-avoid.html#Open
Please refrain from using "open" or "open source" as a synonym for "free software." These terms originate from different perspectives and values. The free software movement advocates for your freedom in computing, grounded in principles of justice. The open source approach, on the other hand, does not promote a set of values in the same way. When discussing open source views, it's appropriate to use that term. However, when referring to our views, our software, or our movement, please use "free software" or "free (libre) software" instead. Using "open source" in this context can lead to misunderstandings, as it implies our views are similar to those of the open source movement.
My concern in this thread is people rejecting the concept of open source model weights as not "true" open source, because there is more that could be open sourced. It discounts a huge amount of value model developers provide when they open source weights. You are doing a variant of that here by trying to claim a narrow definition of "free software". I don't have any interest in the FSF definition.
It seems to me that open source weights enable everything the FOSS community is practically capable of doing.
You can still learn web development even though you don't have 10,000s of users with a large fleet of servers and distributed servers. Thanks to FOSS, it's trivial to go through GitHub and find projects you can learn a bunch from, which is exactly what I did when I started out.
With LLMs, you don't have a lot of options. Sure, you can download and fine-tune the weights, but what if you're interested in how the weights are created in the first place? Some companies are doing a good job (like the folks building OLMo) to create those resources, but the others seems to just want to use FOSS because it's good marketing VS OpenAI et al.
Finetuning weights and building infrastructure around that involves almost all the same things as building a model, except it's actually possible. That's where I've seen most small-scale FOSS development take place over the last few years.
Learning how to make a small website is useful, and so is the website.
Learning how to finetune a large GPT is useful, and so is the finetuned model.
Learning how to train a 124M GPT is useful, but the resulting model is useless.
Those are two completely different roles? One is mostly around infrastructure and the other is actual ML. There are people who know both, I'll give you that, but I don't think that's the default or even common. Fine-tuning is trivial compared to building your own model and deployments/infrastructure is something else entirely.
For someone who basically couldn't become a developer with FOSS, this way of thinking is so backwards, especially on Hacker News. I thought we were pro-FOSS in general, but somehow LLMs get a pass because "they're too complicated and no one would build one from scratch".
Yes, it'd be nice if it was open and reproducible from start to finish. But let's not let perfect be the enemy of good.
"Let's not let companies exploit well-known definitions for their own gain" is what I'm going for, regardless if we personally gain from it or not.
No one's going to pay for an inferior closed model...