Can we all please stop confusing freeware with Open Source?
If something can not be reproduced from sources which are all distributed under an OSI license it is not Open Source.
Non public sources of unknown license -> Closed source / Proprietary
No training code, no training sources -> Closed source / Proprietary
OSI public source code -> Open Source / Free Software
These terms are very well defined. https://opensource.org/osd
The Open Source Initiative themselves decided a last year to relax their standards for AI models: they don't require the training data to be released. https://opensource.org/ai
They do continue to require the core freedoms, most importantly "Use the system for any purpose and without having to ask for permission". That's why a lot of the custom licenses (Llama etc) don't fit the OSI definition.
> The Open Source Initiative themselves decided a last year to relax their standards for AI models: they don't require the training data to be released.
Poor move IMO. Training data should be required to be released to be considered an open source model. Without it all I can do is set weights, etc. Without training data I can't truly reproduce the model, inspect the data for biases/audit the model for fairness, make improvements & redistribute (a core open source ethos).
Keeping the training data closed means it's not truly open.
Their justification for this was that, for many consequential models, releasing the training data just isn't possible.
Obviously the biggest example here is all of that training data which was scraped from the public web (or worse) and cannot be relicensed because the model producers do not have permission to relicense it.
There are other factors too though. A big one is things like health data - if you train a model that can e.g. visually detect cancer cells you want to be able to release that model without having to release the private health scans that it was trained on.
See their FAQ item: Why do you allow the exclusion of some training data? https://opensource.org/ai/faq#why-do-you-allow-the-exclusion...
Wouldn't it be great though if it was public knowledge exactly on what they were trained on and how, even though the data itself cannot be freely copied?
> Poor move IMO. Training data should be required to be released to be considered an open source model.
The actual poor move is trying to fit the term "open source" onto AI models at all, rather than new terms with names that actually match how models are developed.
This notably marks a schism with the FSF; it's the first time and context in which "open-source" and "free software" have not been synonymous, coextensive terms.
I think it greatly diminishes the value of the concept and label of open-source. And it's honestly a bit tragic.
I don't agree with that definition. For a given model I want to know what I can/cannot expect from it. To have a better understanding of that, I need to know what it was trained on.
For a (somewhat extreme) example, what if I use the model to write children's stories, and suddenly it regurgitates Mein Kampf? That would certainly ruin the day.
Are you going to examine a few petabytes of data for each model you want to run, to check if a random paragraph from Main Kampf is in there? How?
We need better tools to examine the weights (what gets activated to which extent for which topics, for example). Getting full training corpus, while nice, cannot be our only choice.
> Are you going to examine a few petabytes of data for each model (...) How?
I can think of a few ways. Perhaps I'd use an LLM to find objectionable content. But anyway, it is the same argument as you can have against e.g. the Linux kernel. Are you going to read every line of code to see if it is secure? Maybe, or maybe not, but that is not the point.
The point is now a model is a black box. It might as well be a Trojan horse.
Let's pretend for a moment that the entire training corpus for Deepseek-R1 were released.
How would you download it?
Where would you store it?
I mean many people I know have 100tb+ in storage at home now. A large enough team of dedicated community members cooperating and sharing compute resources online should be able to reproduce any model.
You would use an LLM to process a few petabytes of data to find a needle in the haystack?
Cheaper to train your own.
Too bad. The OSI owns "open source".
Big tech has been abusing open source to cheaply capture most of the internet and e-commerce anyway, so perhaps it's time we walked away from the term altogether.
The OSI has abdicated the future of open machine learning. And that's fine. We don't need them.
"Free software" is still a thing and it means a very specific and narrow set of criteria. [1, 2]
There's also "Fair software" [3], which walks the line between CC BY-NC-SA and shareware, but also sticks it to big tech by preventing Redis/Elasticsearch capture by the hyperscalers. There's an open game engine [4] that has a pretty nice "Apache + NC" type license.
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Back on the main topic of "open machine learning": since the OSI fucked up, I came up with a ten point scale here [5] defining open AI models. It's just a draft, but if other people agree with the idea, I'll publish a website about it (so I'd appreciate your feedback!)
There are ten measures by which a model can/should be open:
1. The model code (pytorch, whatever)
2. The pre-training code
3. The fine-tuning code (which might be very different from the pre-training code)
4. The inference code
5. The raw training data (pre-training + fine-tuning)
6. The processed training data (which might vary across various stages of pre-training and fine-tuning: different sizes, features, batches, etc.)
7. The resultant weights blob(s)
8. The inference inputs and outputs (which also need a license; see also usage limits like O-RAIL)
9. The research paper(s) (hopefully the model is also described and characterized in the literature!)
10. The patents (or lack thereof)
A good open model will have nearly all of these made available. A fake "open" model might only give you two of ten.
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[1] https://www.fsf.org/
[2] https://en.wikipedia.org/wiki/Free_software
[3] https://fair.io/
[4] https://defold.com/license/
[5] https://news.ycombinator.com/item?id=44438329
> These terms are very well defined. https://opensource.org/osd
Yes. And you're using them wrong.
From the OSD:
< The source code must be the preferred form in which a programmer would modify the program. >
So, what's the preferred way to modify a model? You get the weights and then run fine-tuning with a relatively small amount of data. Which is way cheaper than re-training the entire thing from scratch.
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The issue is that normal software doesn't have a way to modify the binary artifacts without completely recreating them, and that AI models not only do have that but have a large cost difference. The development lifecycle has nodes that don't exist for normal software.
Which means that really, AI models need their own different terminology that matches that difference. Say, open-weights and open-data or something.
Kinda like how Creative Commons is a thing because software development lifecycle concepts don't map very well to literature or artwork either.
The worst part is that they even lack internal consistency, so they (someone at least) know it's wrong, yet they persist regardless.
> https://www.llama.com/ - "Industry Leading, Open-Source AI"
> https://www.llama.com/llama4/license/ - “Llama Materials” means, collectively, Meta’s proprietary Llama 4
Either the team that built the landing page (Marketing dept?) is wrong, or the legal department is wrong. I'm pretty sure I know who I'd bet on to be more correct.
Meta is indeed leading the gaslighting efforts to convince the press and masses that binary blobs provably built from pirated sources are actually Open Source.
The sad part is it is working. It is almost like Meta is especially skilled at mass public manipulation.
To be fair Zuckerberg is not the worst, "OpenAI".
To be honest, they're more or less the same. Zuckerberg frequently talks proudly of his "open source models" constantly, while OpenAI at least doesn't claim to release open source models when they're not. Still, agree that the name should change, but in my eyes they're equally shit at knowing what "Open" is supposed to mean.
No, because "open source" itself was never clear enough to carry that weight.
That's why we keep being annoying about "Free Software."
> OSI public source code -> Open Source / Free Software
Can we all please stop confusing Free/Libre Open Source with Open Source?
https://www.gnu.org/philosophy/open-source-misses-the-point....
Maybe if we'd focused on communicating the ethics the world wouldn't be so unaware of the differences
Are there any instances of OSI licensed code that are not Free Software making my statement here invalid?
I was attempting to direct that when software is called Open Source and actually is based on OSI licensed sources, then they are likely talking about Free Software.
The last time I heard a comment along those lines I was attending a session by an Open Source person and up on screen they had a picture of RMS dressed as Che Guevara.
All those silly ethics, they get in the way of the real work!
Since you didn't get a real answer yet: Absolutely. For example, MIT is an OSI license but it's not Free Software.
Honestly, I think "the framers" got it right here.
Too much communicating of the ethics would have bogged down the useful legal work.
My take is, Free Software actually won and we're in a post-that world.
I'm not sure I fully understand - whilst I agree there's been useful legal work, we now have such a plethora of licenses I ended up having to back what I'd call basic common sense when someone was suggesting using a highly restrictive "community" license that had ridiculous intents such as saying you can't use it in this particular industry because that industry is "bad".
The reason Free/Libre Open Source Software wins - and always will do in the long run - is because the four freedoms are super-simple and they reflect how the natural world works.
Oh, you and I 100% agree.
I meant the useful legal work too. AKA, get the four freedoms and law in line as much as possible and no more.
You're right, most all the other licences range from "hmm interesting experiment" to "well that's just goofy."
Glad someone else said all this so I did not have to. Hats off to you
The older I get the more I fear I am turning into Richard Stallman, but it is absolutely offensive to continually see corporate proprietary freeware binary blobs built from unlicensed sources be confused with Free Open Source Software which is a dramatically higher bar of investment in public good.
> The older I get the more I fear I am turning into Richard Stallman
You and me both. I always preferred and promoted FLOSS where possible but still had a bit of a pragmatic approach, but now the older I get the more I just want to rip out everything not free (as in freedom) from my life, and/or just go become a goat farmer.
Stallman was right from the beginning, and big tech have proven over and over again that they are incapable of being good citizens.
I'm probably a few more years away from "I'd like to interject for a moment..."
Don’t worry, until you’re chewing on your foot mid lecture, you’re good
I mean the article did mention some legitimately open source models.
Which would have been great to distinguish from the ones that certainly are not.