15 ms·

In the LLM space, "open source" is being used to mean "downloadable weights"

400 points by FanaHOVA 3y ago

account42 3y ago
The author clearly doesn't understand the term open source as it is used for software in the first place as evidenced by the completely nonesensical diagram [0]. And no, the term doesn't need to evolve even if parasites want to in order to ride of the goodwill fostered by the open source community. [0] https://www.alessiofanelli.com/images/open-models.png https://www.alessiofanelli.com/images/open-models.png
spullara 3y ago
It remains to be seen in court whether weights are even copyrightable potentially making all the various licenses and their restrictions moot.
- FanaHOVA 3y ago
  Yep, same with SSPL. GPL has been tested in FSF vs Cisco (2008), but none of the more restrictive licenses have.
- dvdkon 3y ago
  In a similar vein, the common "you may not use this model's output to improve another model" clause is AFAIK unenforceable under copyright, so it's at best a contractual clause binding a particular user. Anyone using that improved model afterward is in the clear.
  - taneq 3y ago
    And of course anyone using a model improved by this is entirely unworried by these clauses if their improved model takes off hard.
  - banana_feather 3y ago
    The idea is that if you violate the terms of the license to develop your own model, you lose your rights under the license and are creating an infringing derivative work. If I clone a GPL'd work and ship a derivative work under a commercial license, downstream users can't just integrate the derivative work into a product without abiding by the GPL terms and say "well we're downstream relative to the party who actually copied the GPL'd work, so the GPL terms don't apply to us".
    - blendergeek 3y ago
      If such a "derivative" model is a derivative work, then aren't all these LLMs just mass copyright infringement?
      - dTal 3y ago
        Exactly this. What's good for the goose is good for the gander!
      - banana_feather 3y ago
        At the end of the day it's not black and white, but there's a large and obvious difference in degree that would plausibly permit someone to find that one is and the other isn't. It's fairly easy to argue that using the outputs of LLM X to create a slightly more refined LLM Y creates a derivative work. The argument that a model is a derivative work relative to the training data is not so clear cut.
      - dragonwriter 3y ago
        If model weights aren’t copyrightable, derivative model weights are not a “work”, derivative or otherwise, for copyright purposes. If they are, and the license allows creating finetuned models but not using the output to improve the model, then the derived model is not a violation, but it might be a derivative work.
    - rodoxcasta 3y ago
      If the weights are not copyrighteable, you don't need a licence do use them, they are just data. There's not a right to infringe if these numbers have no author. Of course, to use openAI API you must abide to their terms. But if you publish your generations and I download them, I have nothing to do to the contract you have with openAI since I'm no part of it. They can't impede me to use it to improve my models.
  - ljdcfsafsa 3y ago
    > it's at best a contractual clause binding a particular user. Anyone using that improved model afterward is in the clear. That's... not really accurate. See the concept of tortious interference with a contract.
    - dvdkon 3y ago
      Hm, I don't know much about common law, but I don't think this would apply if, say, an ML enthusiast trained a model from LLaMA2 outputs, made it freely available, then someone else commercialised it. The later user never caused the original developer to breach any contract, they simply profited from an existing breach. That said, doing this inside one company or with subsiduaries probably wouldn't fly.
- weinzierl 3y ago
  I find the idea that weights are not copyrightable very fascinating - appealing even. I have a hard time imagining a world where this is the case, though. Can you summarize why weights would not be copyrightable or give me pointers to sources that support that view.
  - slimsag 3y ago
    Speculating (I am not a lawyer) I see two options: 1. Model weights are the output of mathematical principles, in the US facts are not copyrightable, so in general math is not copyrightable. 2. Model weights are the derivative work of all copyrighted works it was trained on - in which case, it would be similar to creating a new picture which contains every other picture in the world inside of it. Who is the copyright owner? Well, everyone, since it includes so many other copyright holders' works in it.
    - humanistbot 3y ago
      Your second argument, if true, disproves your first argument.
      - slimsag 3y ago
        Doesn't matter. A court decides in the end, and the two choices I presented could lead to OPs scenario. If a court decides that, they decide that, period. I'm not 'making an argument' with those points - I'm presenting options a court might choose from when setting precedent.
    - earleybird 3y ago
      Your second question asks: "Who owns the Infinite Library[0]?" related, there was a presentation (i've lost the reference) on automatic song (tune?) generation where the presenter claimed (rather humourusly) that he'd generated all the songs that had ever been and will ever be so that while he was infringing on a large but finite number of songs, he was non infringing on an infinite number of future songs. So, on balance he was in a favourable position. [0] https://en.wikipedia.org/wiki/The_Library_of_Babel https://en.wikipedia.org/wiki/The_Library_of_Babel
- humanistbot 3y ago
  And it also remains to be seen if various legislatures will pass laws that explicitly declare the copyright status of model weights. It is important to remember that what is or is not copyrightable can change.
  - rvcdbn 3y ago
    At least in the US copyright is established by the constitution so not sure how much it’s possible to change via the normal legislative process.
    - gpm 3y ago
      The US constitution grants congress the ability to create copyright ("To promote the progress of science and useful arts, by securing for limited times to authors and inventors the exclusive right to their respective writings and discoveries"), but it doesn't create copyright law itself. That's a broad clause that gives Congress pretty free reign to change how copyright is defined.
      - rvcdbn 3y ago
        Constitutionality is also about how previous cases have been evaluated for example see the bit about how photography copyright was established here: https://constitution.congress.gov/browse/essay/artI-S8-C8-3-1/ALDE_00013063/ https://constitution.congress.gov/browse/essay/artI-S8-C8-3-...
        rvcdbn 3y ago
        specifically: > A century later, in Feist Publications v. Rural Telephone Service Co., the Supreme Court confirmed that originality is a constitutional requirement
- ljdcfsafsa 3y ago
  1. Why wouldn't they be and 2. Does that even matter? If you enter into a contract saying don't do X, and you do X, you're violating the contract.
  - sebzim4500 3y ago
    I assume GP was talking about a scenario in which you had not entered into a contract with Meta. E.g. if I just downloaded the weights from someone else.
  - rvcdbn 3y ago
    1 - because they lack originality, see: https://constitution.congress.gov/browse/essay/artI-S8-C8-3-1/ALDE_00013063/ https://constitution.congress.gov/browse/essay/artI-S8-C8-3-...
- jrockway 3y ago
  It seems like a dangerous clause to me. 1) "Dear artists, the model cannot infringe upon your copyright because it's merely learning like a human does. If it accidentally outputs parts of your book, you know, it just accidentally plagiarized. We all do it haha! Our attorneys remind you that plagiarism is not illegal in the US." 2) "Dear engineers, the output of our model is copyrighted and thus if you use it to train your own model, we own it." I am not sure how both of those can be true at the same time.
  - jimmaswell 3y ago
    We all truly do "accidentally plagiarize", especially artists. Many guitarists realize they accidentally copied a riff they thought they'd come up with on their own for example.
    - jrockway 3y ago
      I, for one, welcome our new plagiarism overlords. Oops. I added the "haha" in there because the probability of a human doing this kind of goes way down as the length of the text increases. Can you type, verbatim, an entire chapter of a book? I can't. But, I bet the AI can be convinced in rare cases to do that. The whole thing is very interesting to me. There was an article on here a couple days ago about using gzip as a language model. Of course, gzipping a book doesn't remove the copyright. So how low does the probability of outputting the input verbatim have to be before copyright is lost? Reading the book and benefitting from what you learned? Obviously not copyright infringement. Putting the book into gzip and sending your friend the result? Obviously copyright infringement. Now we're in the grey area and ... nobody knows what the law is, or honestly, even how to reason about what the law wants here. Fun times. (Personally, I lean towards "not copyright infringement", but I'm not a big believer in copyright myself. In the case of AI training, it just makes it impossible for small actors to compete. Google can just buy a license from every book distributor. SmolStartup can't. So if we want to make AI that is only for the rich and powerful, copyright is the perfect tool to enable that. I don't think we want that, though. My take is that the rest of society kind of hates Tech right now ("I don't really like my Facebook friends, so someone should take away Mark Zuckerberg's money."), so it's likely that protectionist laws will soon be created that ruin it for everyone. The net effect of that is that Europe and the US will simply flat-out lose to China, which doesn't care about IP.)
- sangnoir 3y ago
  If they are nor copyrightable, that'll be the end of publicly-released weights by for-profit companies. All subsequent models will be served behind an API.
  - dragonwriter 3y ago
    > If they are nor copyrightable, that'll be the end of publicly-released weights by for-profit companies I don’t see why, for-profit companies release permissively-licensed ooen-source code all the time, and noncopyrightable models aren't practically much different than that.
    - bilbo0s 3y ago
      Because the courts will have determined their business models for them. As mercenary as it may sound, what these companies are trying to do is find a business model that is as friendly to themselves as it is hostile to their competitors. This is all part of the jockeying.
      - dragonwriter 3y ago
        And, sure, lack of copyrightability changes the parameters and will change behavior. What I think you have failed to support is that the particular change that it will induce will eliminate all such releases.
    - sangnoir 3y ago
      I debated whether to be more specific and verbose in my earlier comment and brevity won at the expense of clarity. I meant large models that cost 6 or 7 digits to train likely won't be released if the donor company can't control how the models are used. > I don’t see why, for-profit companies release permissively-licensed ooen-source code all the time I agree with this - however, they tend to open-source non-core components - Google won't release search engine code, Amazon wont release scalable-virtualization-in-a-box, etc. I'm confident that Facebook won't release a hypothetical Llama 5 in a manner that enables it to be used to improve ChatGPT 8 - the aim will be unchanged from today, byt the mechanism will shift from licensing to rate-limiting, authentication & IP-bans.
taneq 3y ago
There's "open source" in the original sense, where the source was available. Then there's "FOSS" where the source is not only available, but it's under a copyleft license designed to protect the IP from greedy individual humans. And then there's "open" in the Shenzhen sense where you can find the source and other data online and nobody's going to stop you building something based on those. This is an interesting timeline.
- hiatus 3y ago
  > And then there's "open" in the Shenzhen sense where you can find the source and other data online and nobody's going to stop you building something based on those. I believe there is a name for that: gongkai. https://www.bunniestudios.com/blog/?page_id=3107 https://www.bunniestudios.com/blog/?page_id=3107
  - taneq 3y ago
    Ooh, thanks! I've watched a few of bunnie's things in the past but that's a term I'll remember.
- pzo 3y ago
  On top of that there are also different OSS such as Apache and MIT that the latter one can still restrict the user from using because project owner might patented some algorithm and MIT license doesn't have patent grant. LGPL3.0 also pretty much is restricted in a way that not sure if can be used to distribute software in App Store for iOS legally.
- coconut08 3y ago
  The original sense of open source is defined by the people who fractured off from the Free Software movement in the mid 90's and created it. It's just "Free Software" that has a focus on practicality and utility rather than "Free Software"'s focus on idealism and doing the right thing. It has NOTHING to do with "source available" which is a movement that has recently been co-opting the open source name. "FOSS" has absolutely no requirement of it being copyleft. The MIT license is just as FOSS as the GPL. Many of the free software advocates do have an affinity for copyleft, but they are not mutually exclusive. There are plenty of FOSS advocates who also use and advocate for permissive licenses as well.
api 3y ago
I'm not sure open source applies to actual models. Models aren't human readable, so it's closer to a binary blob. It would apply to the training code and possibly data set. Llama2 is a binary blob pre-trained model that is useful and is licensed in a fairly permissive way, and that's fine.
- politelemon 3y ago
  Yes I think you've put it well. If models were smaller I'd see those in the Github releases section. The model training is what I'd see in the source code and the README etc, to arrive at the 'blob'.
  - api 3y ago
    Even if it costs millions in compute to run at that scale, seeing that code would be extremely informative.
- cjdell 3y ago
  Very like a binary blob. You have to execute it to use it and impossible for humans to reason about just by looking at it. At least binary blobs can be disassembled.
pk-protect-ai 3y ago
llama2 is absolutely useless. From the small models the guanaco-33b and guanaco-65b are the best (though they are derived from llama).
- ngai_aku 3y ago
  Is that just based on your experience, or do you have a link to benchmarks?
  - pk-protect-ai 3y ago
    Try these prompts with different models. LLaMA 2 output is pure garbage: ----1---- On a map sized (256,256), Karen is currently located at position (33,33). Her mission is to defeat the ogre positioned at (77,17). However, Karen only has a 1/2 chance of succeeding in her task. To increase her odds, she can: 1. Collect the nightshades at position (122,133), which will improve her chances by 25%. 2. Obtain a blessing from the elven priest in the elven village at (230,23) in exchange for a fox fur, further increasing her chances by additional 25% Foxes can be found in the forest located between positions (55,33) and (230,90). Find the optimal route for Karen's quest which maximizes her chances of defeating the ogre to 100%. ----2---- Write a python code using imageio.v3 to create a PNG image representing the map way-points and the route of Karen in her quest, each way-point must be of a different color and her path must be a gradient of the colors between the waypoints. ------------ I have a lot of cases those I test against different models ... GPT-4 since one week is really degraded, GPT-3.5 became a little bit better, and LLaMA2 is garbage.
- Oranguru 3y ago
  Useless for what? Are you comparing the base model with chat-tuned models? Chat-tuned derivatives of LLaMa 2 are already appearing. Given that the base LLaMa 2 model is more efficient than LLaMa 1, it is reasonable to expect that these more refined chat-tuned versions of the chat-tuned versions will outperform the ones you mention.
- monlockandkey 3y ago
  wait for the tuned models
mk_stjames 3y ago
In the diagram, there is theoretically another category outside the 'Restricted Weights' but maybe less than the 'Completely Closed' superspace, and that would be something along the lines of 'Blackbox weights and model' that is free to use but essentially non inspectable or transferrable. This would be the sister to 'free to use' closed-source software. An AI that is free to use but provided as a binary blob would meet this criterion. Or a module importable to python that calls precompiled binaries for the inference engine + weights with no source available. The traditional complement of this in the current software world would be Linux drivers from 3rd parties that are not open source. They are free, but not open. We haven't seen this too much yet in the AI world, as mostly people who open the weights are doing so in a research manner, where the inference is decidedly needed to be open sourced- and people with closed models do so in order to make money and thus no reason to open source the inference side either, just charge for an API ("OpenAI").
- FanaHOVA 3y ago
  Yea I didn't include it, but that'd be the "free as in beer, but not freedom" circle :)
jerf 3y ago
This isn't really new, the strict "Open Source" as defined for software has never made exact, perfect sense for anything other than software. That's why the Creative Commons licenses exist; putting a photographic image under GPL2 has never made any sense. It always needs redefinition in new media.
- Flimm 3y ago
  It doesn't need redefinition. We just need a new term for new media.
- not2b 3y ago
  An LLM is more like software than it is like media. The GPL defines source code as the preferred form for making modifications, including the scripts needed for building the executable from source. The weights in this case are more similar to the optimized executable code that comes out of a flow. The "source" would be the training data and the code and procedures for turning that into a model. For very large LLMs almost no one could use this, but for smaller academic models it might make sense, so researchers could build on each others' work.
- hardolaf 3y ago
  The strict "Open Source" wasn't even a definition when I started college.
  - asadotzler 3y ago
    Open Source didn't exist until Netscape created Mozilla in early '98 and the definition was soon after developed and then for some years tuned until we have today's "Open Source".
- RobotToaster 3y ago
  Creative commons has never claimed to be an open source licence though, they usually use the term free culture.
- alerighi 3y ago
  Even for medias such as photos, songs, videos, you have a source. That is the raw materials and the projects from which you rendered the image, the video or the audio output. The source of a language model is more in reality the model, that is the code that was used to train the particular model. The model itself is more of a compiled binary, altough not in machine code. So for a model to be really open source to me it would mean that you have to release the software used for generating it, so I can modify it, train it on my data, and use it.
skybrian 3y ago
I don't see why the term "open source" needs to evolve when "source available" is available. Or in this case, "weights available under a license with few restrictions."
- mhh__ 3y ago
  New generation of programmers can't remember not having open source / free software of any kind so the difference is academic versus felt.
donretag 3y ago
Since Open Source has been established in the tech ethos for a while now, any deviation has been met with derision. It seems like the community has been more tolerant of these "open" licenses as of late. While must of the hate for projects that do not fit the FOSS standard is mostly unwarranted, hopefully we are not moving quickly in the "open" direction. Here is another article on LLaMa2: https://opensourceconnections.com/blog/2023/07/19/is-llama-2-open-source-no-and-perhaps-we-need-a-new-definition-of-open/ https://opensourceconnections.com/blog/2023/07/19/is-llama-2...
rapatel0 3y ago
Fully reproducible model training might simply not be possible if information from the training environment is not captured. In addition to data and code you might have additional uncertainty from: - pseudo/true random number generator and initialization - certain speculative optimizations associated with training environments (distributed) - Speculative optimizations associated with model compression - Image decompression algorithm mismatch (basically this is library versioning) - ....things I'm forgetting... It's just a lot of things to remember to capture, communicate, and reproduce.
- martincmartin 3y ago
  pseudo/true random number generator and initialization It's not just the generator and initialization. If you do anything multithreaded, like a producer/consumer queue, then you need to know which pieces of work went to which thread in which order. It's a lot like reproducing subtle and rare race conditions.
- monocasa 3y ago
  Most of the mature ML environments are pretty focused on reproducible training though. It's pretty necessary for debugging and iteration.
curtis3389 3y ago
Part of the benefit of FOSS & open source is that a curious user can inspect how something is made and learn from it. It matters that open weights are no different from a compiled program. Sure, you can always modify an executable's instructions, but there's no openness there. Then there's the problems of the content of the training data, which parallel the dangers of opaque algorithms.
Taek 3y ago
I didn't realize that the llama license forbids you from using its outputs to train other models. That's essentially a dealbreaker, synthetic data is going to be the most important type of training data from here on out. Any model that prohibits use of synthetic data to train new models is crippled.
- SanderNL 3y ago
  Good luck enforcing that, though. How would they ever know?
  - denlekke 3y ago
    i wonder if they could include some marker prompt and response that wouldn't occur "naturally" from any other model or training data
    - ortusdux 3y ago
      https://en.wikipedia.org/wiki/Trap_street https://en.wikipedia.org/wiki/Trap_street
      - mcny 3y ago
        Level1Techs "link show" (because we can't call it news anymore) kind of touched this topic. I would like to read what you guys make of this: > Supreme Court rejects Genius lawsuit claiming Google stole song lyrics SCOTUS won't overturn ruling that US copyright law preempts Genius' claim. > The song lyrics website Genius' allegations that Google "stole" its work in violation of a contract will not be heard by the US Supreme Court. The top US court denied Genius' petition for certiorari in an order list issued today, leaving in place lower-court rulings that went in Google's favor. > Genius previously lost rulings in US District Court for the Eastern District of New York and the US Court of Appeals for the 2nd Circuit. In August 2020, US District Judge Margo Brodie ruled that Genius' claim is preempted by the US Copyright Act. The appeals court upheld the ruling in March 2022. > "Plaintiff's argument is, in essence, that it has created a derivative work of the original lyrics in applying its own labor and resources to transcribe the lyrics, and thus, retains some ownership over and has rights in the transcriptions distinct from the exclusive rights of the copyright owners... Plaintiff likely makes this argument without explicitly referring to the lyrics transcriptions as derivative works because the case law is clear that only the original copyright owner has exclusive rights to authorize derivative works," Brodie wrote in the August 2020 ruling. > Google search results routinely display song lyrics via the service LyricFind. Genius alleged that LyricFind copied Genius transcriptions and licensed them to Google. > Brodie found that Genius' claim must fail even if one accepts the argument that it "added a separate and distinct value to the lyrics by transcribing them such that the lyrics are essentially derivative works." Since Genius "does not allege that it received an assignment of the copyright owners' rights in the lyrics displayed on its website, Plaintiff's claim is preempted by the Copyright Act because, at its core, it is a claim that Defendants created an unauthorized reproduction of Plaintiff's derivative work, which is itself conduct that violates an exclusive right of the copyright owner under federal copyright law," Brodie wrote. https://arstechnica.com/tech-policy/2023/06/supreme-court-rejects-genius-lawsuit-claiming-google-stole-song-lyrics/ https://arstechnica.com/tech-policy/2023/06/supreme-court-re...
failuser 3y ago
Of course, it’s not open source. With proliferation of the cloud, software has obtained an entirely new level of closeness: not being able to see the program binaries. Having an ability to run locally is now somewhat open in comparison.
- Eduard 3y ago
  An understood term like "open open" source shouldn't be hijacked and exploited for marketing purposes. What these models do, they should either invented a new term, or use an appropriate existing term, eg. "fair use"
  - failuser 3y ago
    Absolutely. Maybe the term is already coined, but I don’t know it. Open source implies the ability to compile software from human-generated inputs. This is just self-hosted freeware.
flir 3y ago
"Nyet! Am not open source! Not want lose autonomy!" (Downvotes... oops. The reference is Charlie Stross's Accelerando. The protagonist has a conversation with an AI that's just trying to survive. One of the options he suggests is to open source itself. Which is a roundabout way of saying that eventually we're going to have to take the AI's own opinions into account. What if it doesn't want to be open source?)
- taneq 3y ago
  This post deserved better treatment, along with maybe a couple of metaphorical decerebrated kittens on its doorstep.
sytse 3y ago
Great point in the article. In https://opencoreventures.com/blog/2023-06-27-ai-weights-are-not-open-source/ https://opencoreventures.com/blog/2023-06-27-ai-weights-are-... I propose a framework to solve the confusion. From the post: "AI licensing is extremely complex. Unlike software licensing, AI isn’t as simple as applying current proprietary/open source software licenses. AI has multiple components—the source code, weights, data, etc.—that are licensed differently. AI also poses socio-ethical consequences that don’t exist on the same scale as computer software, necessitating more restrictions like behavioral use restrictions, in some cases, and distribution restrictions. Because of these complexities, AI licensing has many layers, including multiple components and additional licensing considerations."
PreInternet01 3y ago
It's not just in the LLM space; even for 'older' models, companies have aggressively embraced this approach. For example: YOLOv3 has been appropriated by a company called Ultralytics, which has subsequently released the 'YOLOv5' and 'YOLOv8' "updates": https://github.com/ultralytics/ultralytics https://github.com/ultralytics/ultralytics There is no marked increase in model effectiveness in these 'new' versions, but even if you just use the 'YOLOv8' Pytorch weights (and no part of their Python toolchain, which might have some improvements), these will somehow try to download files from Ultralytics servers. Possibly for a good reason, but most likely to, let's say, "pull an Oracle." Serious AI researchers won't go anywhere near this stuff, but the number of students-slash-potential-interns with "but it's on GitHub!" expectations that I had to reject lately due to "nope, we're not paying these guys for their Enterprise license just to check out your project" is rather disheartening...
rvz 3y ago
Yes (Unfortunately). But Llama 2 being released for free as a downloadable AI model is much better than nothing. For now it is a great start against the cloud-only AI models. As for terms, we'll settle on '$0 downloadable AI models' which are available today. Would rather use that over cloud-only AI models which can fall over and break your app at any time and you have zero control over that. Stable Diffusion is a good example that fits the definition of 'open-source AI' as we have the entire training data, weights reproduciblity, etc and Llama 2 does not.
- FanaHOVA 3y ago
  Agreed. I called it a "$3M of FLOPS donation" by Meta.
Havoc 3y ago
It is quite an unfortunate dilution of the term
godelski 3y ago
The headline is editorialized. Actual is "LLaMA2 isn't "Open Source" - and why it doesn't matter" It is actually editorialized in a way that feels quite different from the actual one. I think the author and the poster might disagree on what open source means.
- swyx 3y ago
  they are the same person :)
- FanaHOVA 3y ago
  Mods changed the title, I used the original one when first posting. Not sure why they changed it.
  - godelski 3y ago
    Maybe Dang is taking a hard stance on the "open source" position. I'm honestly with you, as long as the source is available people will call it open source and complaining over terms isn't going to convince anyone.
indus 3y ago
No wonder there is such “momentum” on watermarking.
deleted 3y ago
[deleted]
danShumway 3y ago
> For the foreseeable future, open source and open weights will be used interchangeably, and I think that’s okay. This is a little weird given that directly above, the author puts LLaMA into the "restricted weights" category. Even by the definition the author proposes, LLaMA 2.0 isn't open source; we shouldn't be calling it open source. If open source in the LLM world means "you can get the weights" and doesn't imply anything about restrictions on their usage, then I don't think that's adapting terminology to a new context, I think it's really cheapening the meaning of Open Source. If you want to refer to specifically "open weights" as open source, I'm a bit more sympathetic to that (although I don't think it's the right terminology to use). But I see where people are coming from -- I'm not too put off by people using open source to describe weights you can download without restrictions on usage. But LLaMA is not open weights. It's a closed, proprietary set of weights[0] that at best could be compared to source available software. It is deceptive for Facebook to call LLaMA open source, and we shouldn't go along with that narrative. [0]: to the extent weights can be copyrighted at all, which I would argue they can't be copyrighted, but that's another conversation.
- FanaHOVA 3y ago
  Author here. I agree with you. LLaMA2 isn't open source (as my title says, the HN one was modified). My point is that the average person will still call it "open source" because they don't know any better, and it's hard to fix that. Rather than just saying "this isn't open source", we should try to come up with better terminology. Also, while weights usage might be restricted, it's a very big compute investment shared with the public. They use a 285:1 training tokens to params ratio, and the loss graphs show the model wasn't yet saturated. This is valuable information for other teams looking to train their own models. LLaMA1 was highly restrictive, but the data mix mentioned in the paper led to the creation of RedPajama, which was used in the training of MPT. There's still plenty of value in this work that will flow to open source, even if it doesn't fit in the traditional labels.
  - danShumway 3y ago
    Thanks for replying! And agreed on the title change; I think your original title is much, much better phrased and I'm sorry that I glossed over it when reading the article (although I'm not sure "doesn't matter" fully captures the distinction you're making here) -- mods probably shouldn't have changed it. > There's still plenty of value in this work that will flow to open source, even if it doesn't fit in the traditional labels. That is a good point; the fight over what is open source and what is source available can get heated, and part of that is a defense against the erosion of the term. But... in general source available is better than closed source software. And LLaMA 2 is a significant improvement over LLaMA 1 in that regard, it really is. So I don't necessarily want to be down on it, in some ways it's just backlash of being tired of companies stretching definitions. But they're doing a thing that will absolutely help improve open access to LLMs. I'm always a little bit torn about how to go about this kind of criticism of terminology, and I'm not trying to say that people shouldn't be excited about LLaMA 2. But the way it works out I'm often playing word police because the erosion of the term does make it harder to refer to models with actual open weights like StableLM. Facebook deserves real praise for releasing a model with weights that can be used commercially. It doesn't deserve to be treated as if what it's doing is equivalent to what StabilityAI or RedPanda is doing. I do like your terminology of "open weights" and "restricted weights", and I wouldn't be opposed to even breaking that down even further, I think there's a clear difference between LLaMA 1 and 2 in terms of user freedom, so I'm not opposed to people trying to distinguish, just... it's not hitting the bar of being open weights. It's a bit like if the word vegetarian didn't exist, and if everyone argued about how it's unhelpful to say that drinking milk isn't vegan because it's still tangibly different from eating meat. On one hand I agree, but on the other hand it's better to have another category for it that means "not vegan, but still not eating meat." There is an actual danger in blurring a line so much that the line doesn't mean anything anymore, and where people who mean something more rigorous no longer have a term to communicate amongst themselves. If average people get bothered by throwing LLaMA 2 into the "restricted weights" category, it's better to introduce another category between restricted and open that means "restricted but not commercially". Beyond that though... yeah, I agree. I don't really have a problem with people calling open weights open source, my only objection to that is kind of technical and pedantic, but I don't think it causes any actual harm if someone wants to call StableLM open source.
arikanev 3y ago
How is it possible that you can fine tune Llama v2 but the weights are not available? That doesn’t make sense to me.
Der_Einzige 3y ago
Given that it's basically impossible to prove that a particular text was generated using a particular LLM (and yes, even with all the watermarking tricks we know of, this is and will still be the case), they might as well be interchangeable. Folks can and will simply ignore the silly license BS that the creators put on the LLM. I hope that users aggressively ignore these restrictive licenses and give the middle finger to greedy companies like Facebook who try to restrict usage of their models. Information deserves to be free, and Aaron Swartz was a saint.
heyzk 3y ago
You see a similar loosening of the term in other fields e.g. open source journalism. Although that seems to be more about crowdsourcing than transparency or usage rights.
blueblimp 3y ago
What's problematic is that there are big models that adopt truly open source licenses, such as MPT-30b and Falcon-40b. As grateful as I am for having access to the Llama2 weights, it feels unfair that it gets credit for being "open source" when there are competing models that really are open source, in the traditional OSI sense. The practical difference between the licenses is small enough that I expect most people (including me) will choose Llama2 anyway, because the models are higher quality. But that incentive may mean that we get stuck with these awkward pseudo-open licenses.
throwuwu 3y ago
Should be good motivation to figure out what those numbers mean
paulmd 3y ago
> While it’s mostly open, there are caveats such as you can’t use the model commercially if you had more than 700M MAUs as of the release date, and you also cannot use the model output to train another large language model. These types of restrictions don’t play well with the open source ethos No, CC-NC-ND is a thing, and even GPL applies restrictions on derivation as well. "Open source" doesn't mean BSD/MIT. There is even open-source that you cannot freely redistribute at all - not all open-source is FOSS! I always think it's a testament to how much copyleft has succeeded that in many cases people think of GPL and BSD/MIT as being the baseline.
morpheuskafka 3y ago
The chart in this this article is very wrong to show only GPL as free software and MIT/Apache as open source but not free software licenses. While the FSF side of things doesn't like the term "open source," even they say that "nearly all open source software is free software." Specifically, the MIT and Apache (and LGPL) licenses are absolutely free software licenses--otherwise Debian, FSF-approved distros, etc. would have far less software to choose from. What the chart probably meant to distinguish is copyleft vs free software or open source. And if you're ordering it from a permissiveness viewpoint, the subset relationship should be reversed--GPL is far more permissive than SSPL, etc., but still less permissive that MIT/Apache.
- seba_dos1 3y ago
  Yup. The terms "Open Source" and "Free Software" are pretty much interchangeable when it comes to licenses. The difference is political, not technical. This part of the article is pretty misleading as well: > Free software, as specified by the Free Software Foundation, is only a subset of open source software and uses very permissive licenses such as GPL and Apache.
bloppe 3y ago
Why not just "downloadable"? It describes the actual difference between LLaMA and GPT. Open-data is the only other distinction that matters.
lazzlazzlazz 3y ago
The spirit of "open source" implies "open weights", without doubt. Litigating the specific meaning of the terms is pointless.
Terr_ 3y ago
> downloadable weights When it comes to "how much of it has to be available to be open source", I think it may be instructive to look at encryption algorithms. Many of them have numeric constants or initial values--NOT part of the secret key itself--which need to be known and available, both for interoperability and for the expected security-level of the algorithm. These are arguably similar to LLM weights. (Perhaps the simplest example would be the prominence of "13" in ROT13.) Yet if someone tried saying that their encryption standard was "open source" while keeping those constants secret and/or legally-encumbered, I think a lot of people would complain that the label is incorrect or inappropriate.
pabs3 3y ago
I like Debian's ML policy about this: https://salsa.debian.org/deeplearning-team/ml-policy/ https://salsa.debian.org/deeplearning-team/ml-policy/

400 points by FanaHOVA 3y ago

The author clearly doesn't understand the term open source as it is used for software in the first place as evidenced by the completely nonesensical diagram [0]. And no, the term doesn't need to evolve even if parasites want to in order to ride of the goodwill fostered by the open source community. [0] https://www.alessiofanelli.com/images/open-models.png https://www.alessiofanelli.com/images/open-models.png

spullara 3y ago

It remains to be seen in court whether weights are even copyrightable potentially making all the various licenses and their restrictions moot.

FanaHOVA 3y ago
Yep, same with SSPL. GPL has been tested in FSF vs Cisco (2008), but none of the more restrictive licenses have.
dvdkon 3y ago
In a similar vein, the common "you may not use this model's output to improve another model" clause is AFAIK unenforceable under copyright, so it's at best a contractual clause binding a particular user. Anyone using that improved model afterward is in the clear.
- taneq 3y ago
  And of course anyone using a model improved by this is entirely unworried by these clauses if their improved model takes off hard.
- banana_feather 3y ago
  The idea is that if you violate the terms of the license to develop your own model, you lose your rights under the license and are creating an infringing derivative work. If I clone a GPL'd work and ship a derivative work under a commercial license, downstream users can't just integrate the derivative work into a product without abiding by the GPL terms and say "well we're downstream relative to the party who actually copied the GPL'd work, so the GPL terms don't apply to us".
  - blendergeek 3y ago
    If such a "derivative" model is a derivative work, then aren't all these LLMs just mass copyright infringement?
    - dTal 3y ago
      Exactly this. What's good for the goose is good for the gander!
    - banana_feather 3y ago
      At the end of the day it's not black and white, but there's a large and obvious difference in degree that would plausibly permit someone to find that one is and the other isn't. It's fairly easy to argue that using the outputs of LLM X to create a slightly more refined LLM Y creates a derivative work. The argument that a model is a derivative work relative to the training data is not so clear cut.
    - dragonwriter 3y ago
      If model weights aren’t copyrightable, derivative model weights are not a “work”, derivative or otherwise, for copyright purposes. If they are, and the license allows creating finetuned models but not using the output to improve the model, then the derived model is not a violation, but it might be a derivative work.
  - rodoxcasta 3y ago
    If the weights are not copyrighteable, you don't need a licence do use them, they are just data. There's not a right to infringe if these numbers have no author. Of course, to use openAI API you must abide to their terms. But if you publish your generations and I download them, I have nothing to do to the contract you have with openAI since I'm no part of it. They can't impede me to use it to improve my models.
- ljdcfsafsa 3y ago
  > it's at best a contractual clause binding a particular user. Anyone using that improved model afterward is in the clear. That's... not really accurate. See the concept of tortious interference with a contract.
  - dvdkon 3y ago
    Hm, I don't know much about common law, but I don't think this would apply if, say, an ML enthusiast trained a model from LLaMA2 outputs, made it freely available, then someone else commercialised it. The later user never caused the original developer to breach any contract, they simply profited from an existing breach. That said, doing this inside one company or with subsiduaries probably wouldn't fly.
weinzierl 3y ago
I find the idea that weights are not copyrightable very fascinating - appealing even. I have a hard time imagining a world where this is the case, though. Can you summarize why weights would not be copyrightable or give me pointers to sources that support that view.
- slimsag 3y ago
  Speculating (I am not a lawyer) I see two options: 1. Model weights are the output of mathematical principles, in the US facts are not copyrightable, so in general math is not copyrightable. 2. Model weights are the derivative work of all copyrighted works it was trained on - in which case, it would be similar to creating a new picture which contains every other picture in the world inside of it. Who is the copyright owner? Well, everyone, since it includes so many other copyright holders' works in it.
  - humanistbot 3y ago
    Your second argument, if true, disproves your first argument.
    - slimsag 3y ago
      Doesn't matter. A court decides in the end, and the two choices I presented could lead to OPs scenario. If a court decides that, they decide that, period. I'm not 'making an argument' with those points - I'm presenting options a court might choose from when setting precedent.
  - earleybird 3y ago
    Your second question asks: "Who owns the Infinite Library[0]?" related, there was a presentation (i've lost the reference) on automatic song (tune?) generation where the presenter claimed (rather humourusly) that he'd generated all the songs that had ever been and will ever be so that while he was infringing on a large but finite number of songs, he was non infringing on an infinite number of future songs. So, on balance he was in a favourable position. [0] https://en.wikipedia.org/wiki/The_Library_of_Babel https://en.wikipedia.org/wiki/The_Library_of_Babel
humanistbot 3y ago
And it also remains to be seen if various legislatures will pass laws that explicitly declare the copyright status of model weights. It is important to remember that what is or is not copyrightable can change.
- rvcdbn 3y ago
  At least in the US copyright is established by the constitution so not sure how much it’s possible to change via the normal legislative process.
  - gpm 3y ago
    The US constitution grants congress the ability to create copyright ("To promote the progress of science and useful arts, by securing for limited times to authors and inventors the exclusive right to their respective writings and discoveries"), but it doesn't create copyright law itself. That's a broad clause that gives Congress pretty free reign to change how copyright is defined.
    - rvcdbn 3y ago
      Constitutionality is also about how previous cases have been evaluated for example see the bit about how photography copyright was established here: https://constitution.congress.gov/browse/essay/artI-S8-C8-3-1/ALDE_00013063/ https://constitution.congress.gov/browse/essay/artI-S8-C8-3-...
      - rvcdbn 3y ago
        specifically: > A century later, in Feist Publications v. Rural Telephone Service Co., the Supreme Court confirmed that originality is a constitutional requirement
ljdcfsafsa 3y ago
1. Why wouldn't they be and 2. Does that even matter? If you enter into a contract saying don't do X, and you do X, you're violating the contract.
- sebzim4500 3y ago
  I assume GP was talking about a scenario in which you had not entered into a contract with Meta. E.g. if I just downloaded the weights from someone else.
- rvcdbn 3y ago
  1 - because they lack originality, see: https://constitution.congress.gov/browse/essay/artI-S8-C8-3-1/ALDE_00013063/ https://constitution.congress.gov/browse/essay/artI-S8-C8-3-...
jrockway 3y ago
It seems like a dangerous clause to me. 1) "Dear artists, the model cannot infringe upon your copyright because it's merely learning like a human does. If it accidentally outputs parts of your book, you know, it just accidentally plagiarized. We all do it haha! Our attorneys remind you that plagiarism is not illegal in the US." 2) "Dear engineers, the output of our model is copyrighted and thus if you use it to train your own model, we own it." I am not sure how both of those can be true at the same time.
- jimmaswell 3y ago
  We all truly do "accidentally plagiarize", especially artists. Many guitarists realize they accidentally copied a riff they thought they'd come up with on their own for example.
  - jrockway 3y ago
    I, for one, welcome our new plagiarism overlords. Oops. I added the "haha" in there because the probability of a human doing this kind of goes way down as the length of the text increases. Can you type, verbatim, an entire chapter of a book? I can't. But, I bet the AI can be convinced in rare cases to do that. The whole thing is very interesting to me. There was an article on here a couple days ago about using gzip as a language model. Of course, gzipping a book doesn't remove the copyright. So how low does the probability of outputting the input verbatim have to be before copyright is lost? Reading the book and benefitting from what you learned? Obviously not copyright infringement. Putting the book into gzip and sending your friend the result? Obviously copyright infringement. Now we're in the grey area and ... nobody knows what the law is, or honestly, even how to reason about what the law wants here. Fun times. (Personally, I lean towards "not copyright infringement", but I'm not a big believer in copyright myself. In the case of AI training, it just makes it impossible for small actors to compete. Google can just buy a license from every book distributor. SmolStartup can't. So if we want to make AI that is only for the rich and powerful, copyright is the perfect tool to enable that. I don't think we want that, though. My take is that the rest of society kind of hates Tech right now ("I don't really like my Facebook friends, so someone should take away Mark Zuckerberg's money."), so it's likely that protectionist laws will soon be created that ruin it for everyone. The net effect of that is that Europe and the US will simply flat-out lose to China, which doesn't care about IP.)
sangnoir 3y ago
If they are nor copyrightable, that'll be the end of publicly-released weights by for-profit companies. All subsequent models will be served behind an API.
- dragonwriter 3y ago
  > If they are nor copyrightable, that'll be the end of publicly-released weights by for-profit companies I don’t see why, for-profit companies release permissively-licensed ooen-source code all the time, and noncopyrightable models aren't practically much different than that.
  - bilbo0s 3y ago
    Because the courts will have determined their business models for them. As mercenary as it may sound, what these companies are trying to do is find a business model that is as friendly to themselves as it is hostile to their competitors. This is all part of the jockeying.
    - dragonwriter 3y ago
      And, sure, lack of copyrightability changes the parameters and will change behavior. What I think you have failed to support is that the particular change that it will induce will eliminate all such releases.
  - sangnoir 3y ago
    I debated whether to be more specific and verbose in my earlier comment and brevity won at the expense of clarity. I meant large models that cost 6 or 7 digits to train likely won't be released if the donor company can't control how the models are used. > I don’t see why, for-profit companies release permissively-licensed ooen-source code all the time I agree with this - however, they tend to open-source non-core components - Google won't release search engine code, Amazon wont release scalable-virtualization-in-a-box, etc. I'm confident that Facebook won't release a hypothetical Llama 5 in a manner that enables it to be used to improve ChatGPT 8 - the aim will be unchanged from today, byt the mechanism will shift from licensing to rate-limiting, authentication & IP-bans.

taneq 3y ago

There's "open source" in the original sense, where the source was available. Then there's "FOSS" where the source is not only available, but it's under a copyleft license designed to protect the IP from greedy individual humans. And then there's "open" in the Shenzhen sense where you can find the source and other data online and nobody's going to stop you building something based on those. This is an interesting timeline.

hiatus 3y ago
> And then there's "open" in the Shenzhen sense where you can find the source and other data online and nobody's going to stop you building something based on those. I believe there is a name for that: gongkai. https://www.bunniestudios.com/blog/?page_id=3107 https://www.bunniestudios.com/blog/?page_id=3107
- taneq 3y ago
  Ooh, thanks! I've watched a few of bunnie's things in the past but that's a term I'll remember.
pzo 3y ago
On top of that there are also different OSS such as Apache and MIT that the latter one can still restrict the user from using because project owner might patented some algorithm and MIT license doesn't have patent grant. LGPL3.0 also pretty much is restricted in a way that not sure if can be used to distribute software in App Store for iOS legally.
coconut08 3y ago
The original sense of open source is defined by the people who fractured off from the Free Software movement in the mid 90's and created it. It's just "Free Software" that has a focus on practicality and utility rather than "Free Software"'s focus on idealism and doing the right thing. It has NOTHING to do with "source available" which is a movement that has recently been co-opting the open source name. "FOSS" has absolutely no requirement of it being copyleft. The MIT license is just as FOSS as the GPL. Many of the free software advocates do have an affinity for copyleft, but they are not mutually exclusive. There are plenty of FOSS advocates who also use and advocate for permissive licenses as well.

api 3y ago

I'm not sure open source applies to actual models. Models aren't human readable, so it's closer to a binary blob. It would apply to the training code and possibly data set. Llama2 is a binary blob pre-trained model that is useful and is licensed in a fairly permissive way, and that's fine.

politelemon 3y ago
Yes I think you've put it well. If models were smaller I'd see those in the Github releases section. The model training is what I'd see in the source code and the README etc, to arrive at the 'blob'.
- api 3y ago
  Even if it costs millions in compute to run at that scale, seeing that code would be extremely informative.
cjdell 3y ago
Very like a binary blob. You have to execute it to use it and impossible for humans to reason about just by looking at it. At least binary blobs can be disassembled.

pk-protect-ai 3y ago

llama2 is absolutely useless. From the small models the guanaco-33b and guanaco-65b are the best (though they are derived from llama).

ngai_aku 3y ago
Is that just based on your experience, or do you have a link to benchmarks?
- pk-protect-ai 3y ago
  Try these prompts with different models. LLaMA 2 output is pure garbage: ----1---- On a map sized (256,256), Karen is currently located at position (33,33). Her mission is to defeat the ogre positioned at (77,17). However, Karen only has a 1/2 chance of succeeding in her task. To increase her odds, she can: 1. Collect the nightshades at position (122,133), which will improve her chances by 25%. 2. Obtain a blessing from the elven priest in the elven village at (230,23) in exchange for a fox fur, further increasing her chances by additional 25% Foxes can be found in the forest located between positions (55,33) and (230,90). Find the optimal route for Karen's quest which maximizes her chances of defeating the ogre to 100%. ----2---- Write a python code using imageio.v3 to create a PNG image representing the map way-points and the route of Karen in her quest, each way-point must be of a different color and her path must be a gradient of the colors between the waypoints. ------------ I have a lot of cases those I test against different models ... GPT-4 since one week is really degraded, GPT-3.5 became a little bit better, and LLaMA2 is garbage.
Oranguru 3y ago
Useless for what? Are you comparing the base model with chat-tuned models? Chat-tuned derivatives of LLaMa 2 are already appearing. Given that the base LLaMa 2 model is more efficient than LLaMa 1, it is reasonable to expect that these more refined chat-tuned versions of the chat-tuned versions will outperform the ones you mention.
monlockandkey 3y ago
wait for the tuned models

mk_stjames 3y ago

In the diagram, there is theoretically another category outside the 'Restricted Weights' but maybe less than the 'Completely Closed' superspace, and that would be something along the lines of 'Blackbox weights and model' that is free to use but essentially non inspectable or transferrable. This would be the sister to 'free to use' closed-source software. An AI that is free to use but provided as a binary blob would meet this criterion. Or a module importable to python that calls precompiled binaries for the inference engine + weights with no source available. The traditional complement of this in the current software world would be Linux drivers from 3rd parties that are not open source. They are free, but not open. We haven't seen this too much yet in the AI world, as mostly people who open the weights are doing so in a research manner, where the inference is decidedly needed to be open sourced- and people with closed models do so in order to make money and thus no reason to open source the inference side either, just charge for an API ("OpenAI").

FanaHOVA 3y ago
Yea I didn't include it, but that'd be the "free as in beer, but not freedom" circle :)

jerf 3y ago

This isn't really new, the strict "Open Source" as defined for software has never made exact, perfect sense for anything other than software. That's why the Creative Commons licenses exist; putting a photographic image under GPL2 has never made any sense. It always needs redefinition in new media.

Flimm 3y ago
It doesn't need redefinition. We just need a new term for new media.
not2b 3y ago
An LLM is more like software than it is like media. The GPL defines source code as the preferred form for making modifications, including the scripts needed for building the executable from source. The weights in this case are more similar to the optimized executable code that comes out of a flow. The "source" would be the training data and the code and procedures for turning that into a model. For very large LLMs almost no one could use this, but for smaller academic models it might make sense, so researchers could build on each others' work.
hardolaf 3y ago
The strict "Open Source" wasn't even a definition when I started college.
- asadotzler 3y ago
  Open Source didn't exist until Netscape created Mozilla in early '98 and the definition was soon after developed and then for some years tuned until we have today's "Open Source".
RobotToaster 3y ago
Creative commons has never claimed to be an open source licence though, they usually use the term free culture.
alerighi 3y ago
Even for medias such as photos, songs, videos, you have a source. That is the raw materials and the projects from which you rendered the image, the video or the audio output. The source of a language model is more in reality the model, that is the code that was used to train the particular model. The model itself is more of a compiled binary, altough not in machine code. So for a model to be really open source to me it would mean that you have to release the software used for generating it, so I can modify it, train it on my data, and use it.

skybrian 3y ago

I don't see why the term "open source" needs to evolve when "source available" is available. Or in this case, "weights available under a license with few restrictions."

mhh__ 3y ago
New generation of programmers can't remember not having open source / free software of any kind so the difference is academic versus felt.

donretag 3y ago

Since Open Source has been established in the tech ethos for a while now, any deviation has been met with derision. It seems like the community has been more tolerant of these "open" licenses as of late. While must of the hate for projects that do not fit the FOSS standard is mostly unwarranted, hopefully we are not moving quickly in the "open" direction. Here is another article on LLaMa2: https://opensourceconnections.com/blog/2023/07/19/is-llama-2-open-source-no-and-perhaps-we-need-a-new-definition-of-open/ https://opensourceconnections.com/blog/2023/07/19/is-llama-2...

rapatel0 3y ago

Fully reproducible model training might simply not be possible if information from the training environment is not captured. In addition to data and code you might have additional uncertainty from: - pseudo/true random number generator and initialization - certain speculative optimizations associated with training environments (distributed) - Speculative optimizations associated with model compression - Image decompression algorithm mismatch (basically this is library versioning) - ....things I'm forgetting... It's just a lot of things to remember to capture, communicate, and reproduce.

martincmartin 3y ago
pseudo/true random number generator and initialization It's not just the generator and initialization. If you do anything multithreaded, like a producer/consumer queue, then you need to know which pieces of work went to which thread in which order. It's a lot like reproducing subtle and rare race conditions.
monocasa 3y ago
Most of the mature ML environments are pretty focused on reproducible training though. It's pretty necessary for debugging and iteration.

curtis3389 3y ago

Part of the benefit of FOSS & open source is that a curious user can inspect how something is made and learn from it. It matters that open weights are no different from a compiled program. Sure, you can always modify an executable's instructions, but there's no openness there. Then there's the problems of the content of the training data, which parallel the dangers of opaque algorithms.

Taek 3y ago

I didn't realize that the llama license forbids you from using its outputs to train other models. That's essentially a dealbreaker, synthetic data is going to be the most important type of training data from here on out. Any model that prohibits use of synthetic data to train new models is crippled.

SanderNL 3y ago
Good luck enforcing that, though. How would they ever know?
- denlekke 3y ago
  i wonder if they could include some marker prompt and response that wouldn't occur "naturally" from any other model or training data
  - ortusdux 3y ago
    https://en.wikipedia.org/wiki/Trap_street https://en.wikipedia.org/wiki/Trap_street
    - mcny 3y ago
      Level1Techs "link show" (because we can't call it news anymore) kind of touched this topic. I would like to read what you guys make of this: > Supreme Court rejects Genius lawsuit claiming Google stole song lyrics SCOTUS won't overturn ruling that US copyright law preempts Genius' claim. > The song lyrics website Genius' allegations that Google "stole" its work in violation of a contract will not be heard by the US Supreme Court. The top US court denied Genius' petition for certiorari in an order list issued today, leaving in place lower-court rulings that went in Google's favor. > Genius previously lost rulings in US District Court for the Eastern District of New York and the US Court of Appeals for the 2nd Circuit. In August 2020, US District Judge Margo Brodie ruled that Genius' claim is preempted by the US Copyright Act. The appeals court upheld the ruling in March 2022. > "Plaintiff's argument is, in essence, that it has created a derivative work of the original lyrics in applying its own labor and resources to transcribe the lyrics, and thus, retains some ownership over and has rights in the transcriptions distinct from the exclusive rights of the copyright owners... Plaintiff likely makes this argument without explicitly referring to the lyrics transcriptions as derivative works because the case law is clear that only the original copyright owner has exclusive rights to authorize derivative works," Brodie wrote in the August 2020 ruling. > Google search results routinely display song lyrics via the service LyricFind. Genius alleged that LyricFind copied Genius transcriptions and licensed them to Google. > Brodie found that Genius' claim must fail even if one accepts the argument that it "added a separate and distinct value to the lyrics by transcribing them such that the lyrics are essentially derivative works." Since Genius "does not allege that it received an assignment of the copyright owners' rights in the lyrics displayed on its website, Plaintiff's claim is preempted by the Copyright Act because, at its core, it is a claim that Defendants created an unauthorized reproduction of Plaintiff's derivative work, which is itself conduct that violates an exclusive right of the copyright owner under federal copyright law," Brodie wrote. https://arstechnica.com/tech-policy/2023/06/supreme-court-rejects-genius-lawsuit-claiming-google-stole-song-lyrics/ https://arstechnica.com/tech-policy/2023/06/supreme-court-re...

failuser 3y ago

Of course, it’s not open source. With proliferation of the cloud, software has obtained an entirely new level of closeness: not being able to see the program binaries. Having an ability to run locally is now somewhat open in comparison.

Eduard 3y ago
An understood term like "open open" source shouldn't be hijacked and exploited for marketing purposes. What these models do, they should either invented a new term, or use an appropriate existing term, eg. "fair use"
- failuser 3y ago
  Absolutely. Maybe the term is already coined, but I don’t know it. Open source implies the ability to compile software from human-generated inputs. This is just self-hosted freeware.

flir 3y ago

"Nyet! Am not open source! Not want lose autonomy!" (Downvotes... oops. The reference is Charlie Stross's Accelerando. The protagonist has a conversation with an AI that's just trying to survive. One of the options he suggests is to open source itself. Which is a roundabout way of saying that eventually we're going to have to take the AI's own opinions into account. What if it doesn't want to be open source?)

taneq 3y ago
This post deserved better treatment, along with maybe a couple of metaphorical decerebrated kittens on its doorstep.

sytse 3y ago

Great point in the article. In https://opencoreventures.com/blog/2023-06-27-ai-weights-are-not-open-source/ https://opencoreventures.com/blog/2023-06-27-ai-weights-are-... I propose a framework to solve the confusion. From the post: "AI licensing is extremely complex. Unlike software licensing, AI isn’t as simple as applying current proprietary/open source software licenses. AI has multiple components—the source code, weights, data, etc.—that are licensed differently. AI also poses socio-ethical consequences that don’t exist on the same scale as computer software, necessitating more restrictions like behavioral use restrictions, in some cases, and distribution restrictions. Because of these complexities, AI licensing has many layers, including multiple components and additional licensing considerations."

PreInternet01 3y ago

It's not just in the LLM space; even for 'older' models, companies have aggressively embraced this approach. For example: YOLOv3 has been appropriated by a company called Ultralytics, which has subsequently released the 'YOLOv5' and 'YOLOv8' "updates": https://github.com/ultralytics/ultralytics https://github.com/ultralytics/ultralytics There is no marked increase in model effectiveness in these 'new' versions, but even if you just use the 'YOLOv8' Pytorch weights (and no part of their Python toolchain, which might have some improvements), these will somehow try to download files from Ultralytics servers. Possibly for a good reason, but most likely to, let's say, "pull an Oracle." Serious AI researchers won't go anywhere near this stuff, but the number of students-slash-potential-interns with "but it's on GitHub!" expectations that I had to reject lately due to "nope, we're not paying these guys for their Enterprise license just to check out your project" is rather disheartening...

rvz 3y ago

Yes (Unfortunately). But Llama 2 being released for free as a downloadable AI model is much better than nothing. For now it is a great start against the cloud-only AI models. As for terms, we'll settle on '$0 downloadable AI models' which are available today. Would rather use that over cloud-only AI models which can fall over and break your app at any time and you have zero control over that. Stable Diffusion is a good example that fits the definition of 'open-source AI' as we have the entire training data, weights reproduciblity, etc and Llama 2 does not.

FanaHOVA 3y ago
Agreed. I called it a "$3M of FLOPS donation" by Meta.

Havoc 3y ago

It is quite an unfortunate dilution of the term

godelski 3y ago

The headline is editorialized. Actual is "LLaMA2 isn't "Open Source" - and why it doesn't matter" It is actually editorialized in a way that feels quite different from the actual one. I think the author and the poster might disagree on what open source means.

swyx 3y ago
they are the same person :)
FanaHOVA 3y ago
Mods changed the title, I used the original one when first posting. Not sure why they changed it.
- godelski 3y ago
  Maybe Dang is taking a hard stance on the "open source" position. I'm honestly with you, as long as the source is available people will call it open source and complaining over terms isn't going to convince anyone.

indus 3y ago

No wonder there is such “momentum” on watermarking.

deleted 3y ago

[deleted]

danShumway 3y ago

> For the foreseeable future, open source and open weights will be used interchangeably, and I think that’s okay. This is a little weird given that directly above, the author puts LLaMA into the "restricted weights" category. Even by the definition the author proposes, LLaMA 2.0 isn't open source; we shouldn't be calling it open source. If open source in the LLM world means "you can get the weights" and doesn't imply anything about restrictions on their usage, then I don't think that's adapting terminology to a new context, I think it's really cheapening the meaning of Open Source. If you want to refer to specifically "open weights" as open source, I'm a bit more sympathetic to that (although I don't think it's the right terminology to use). But I see where people are coming from -- I'm not too put off by people using open source to describe weights you can download without restrictions on usage. But LLaMA is not open weights. It's a closed, proprietary set of weights[0] that at best could be compared to source available software. It is deceptive for Facebook to call LLaMA open source, and we shouldn't go along with that narrative. [0]: to the extent weights can be copyrighted at all, which I would argue they can't be copyrighted, but that's another conversation.

FanaHOVA 3y ago
Author here. I agree with you. LLaMA2 isn't open source (as my title says, the HN one was modified). My point is that the average person will still call it "open source" because they don't know any better, and it's hard to fix that. Rather than just saying "this isn't open source", we should try to come up with better terminology. Also, while weights usage might be restricted, it's a very big compute investment shared with the public. They use a 285:1 training tokens to params ratio, and the loss graphs show the model wasn't yet saturated. This is valuable information for other teams looking to train their own models. LLaMA1 was highly restrictive, but the data mix mentioned in the paper led to the creation of RedPajama, which was used in the training of MPT. There's still plenty of value in this work that will flow to open source, even if it doesn't fit in the traditional labels.
- danShumway 3y ago
  Thanks for replying! And agreed on the title change; I think your original title is much, much better phrased and I'm sorry that I glossed over it when reading the article (although I'm not sure "doesn't matter" fully captures the distinction you're making here) -- mods probably shouldn't have changed it. > There's still plenty of value in this work that will flow to open source, even if it doesn't fit in the traditional labels. That is a good point; the fight over what is open source and what is source available can get heated, and part of that is a defense against the erosion of the term. But... in general source available is better than closed source software. And LLaMA 2 is a significant improvement over LLaMA 1 in that regard, it really is. So I don't necessarily want to be down on it, in some ways it's just backlash of being tired of companies stretching definitions. But they're doing a thing that will absolutely help improve open access to LLMs. I'm always a little bit torn about how to go about this kind of criticism of terminology, and I'm not trying to say that people shouldn't be excited about LLaMA 2. But the way it works out I'm often playing word police because the erosion of the term does make it harder to refer to models with actual open weights like StableLM. Facebook deserves real praise for releasing a model with weights that can be used commercially. It doesn't deserve to be treated as if what it's doing is equivalent to what StabilityAI or RedPanda is doing. I do like your terminology of "open weights" and "restricted weights", and I wouldn't be opposed to even breaking that down even further, I think there's a clear difference between LLaMA 1 and 2 in terms of user freedom, so I'm not opposed to people trying to distinguish, just... it's not hitting the bar of being open weights. It's a bit like if the word vegetarian didn't exist, and if everyone argued about how it's unhelpful to say that drinking milk isn't vegan because it's still tangibly different from eating meat. On one hand I agree, but on the other hand it's better to have another category for it that means "not vegan, but still not eating meat." There is an actual danger in blurring a line so much that the line doesn't mean anything anymore, and where people who mean something more rigorous no longer have a term to communicate amongst themselves. If average people get bothered by throwing LLaMA 2 into the "restricted weights" category, it's better to introduce another category between restricted and open that means "restricted but not commercially". Beyond that though... yeah, I agree. I don't really have a problem with people calling open weights open source, my only objection to that is kind of technical and pedantic, but I don't think it causes any actual harm if someone wants to call StableLM open source.

arikanev 3y ago

How is it possible that you can fine tune Llama v2 but the weights are not available? That doesn’t make sense to me.

Der_Einzige 3y ago

Given that it's basically impossible to prove that a particular text was generated using a particular LLM (and yes, even with all the watermarking tricks we know of, this is and will still be the case), they might as well be interchangeable. Folks can and will simply ignore the silly license BS that the creators put on the LLM. I hope that users aggressively ignore these restrictive licenses and give the middle finger to greedy companies like Facebook who try to restrict usage of their models. Information deserves to be free, and Aaron Swartz was a saint.

heyzk 3y ago

You see a similar loosening of the term in other fields e.g. open source journalism. Although that seems to be more about crowdsourcing than transparency or usage rights.

blueblimp 3y ago

What's problematic is that there are big models that adopt truly open source licenses, such as MPT-30b and Falcon-40b. As grateful as I am for having access to the Llama2 weights, it feels unfair that it gets credit for being "open source" when there are competing models that really are open source, in the traditional OSI sense. The practical difference between the licenses is small enough that I expect most people (including me) will choose Llama2 anyway, because the models are higher quality. But that incentive may mean that we get stuck with these awkward pseudo-open licenses.

throwuwu 3y ago

Should be good motivation to figure out what those numbers mean

paulmd 3y ago

> While it’s mostly open, there are caveats such as you can’t use the model commercially if you had more than 700M MAUs as of the release date, and you also cannot use the model output to train another large language model. These types of restrictions don’t play well with the open source ethos No, CC-NC-ND is a thing, and even GPL applies restrictions on derivation as well. "Open source" doesn't mean BSD/MIT. There is even open-source that you cannot freely redistribute at all - not all open-source is FOSS! I always think it's a testament to how much copyleft has succeeded that in many cases people think of GPL and BSD/MIT as being the baseline.

morpheuskafka 3y ago

The chart in this this article is very wrong to show only GPL as free software and MIT/Apache as open source but not free software licenses. While the FSF side of things doesn't like the term "open source," even they say that "nearly all open source software is free software." Specifically, the MIT and Apache (and LGPL) licenses are absolutely free software licenses--otherwise Debian, FSF-approved distros, etc. would have far less software to choose from. What the chart probably meant to distinguish is copyleft vs free software or open source. And if you're ordering it from a permissiveness viewpoint, the subset relationship should be reversed--GPL is far more permissive than SSPL, etc., but still less permissive that MIT/Apache.

seba_dos1 3y ago
Yup. The terms "Open Source" and "Free Software" are pretty much interchangeable when it comes to licenses. The difference is political, not technical. This part of the article is pretty misleading as well: > Free software, as specified by the Free Software Foundation, is only a subset of open source software and uses very permissive licenses such as GPL and Apache.

bloppe 3y ago

Why not just "downloadable"? It describes the actual difference between LLaMA and GPT. Open-data is the only other distinction that matters.

lazzlazzlazz 3y ago

The spirit of "open source" implies "open weights", without doubt. Litigating the specific meaning of the terms is pointless.

Terr_ 3y ago

> downloadable weights When it comes to "how much of it has to be available to be open source", I think it may be instructive to look at encryption algorithms. Many of them have numeric constants or initial values--NOT part of the secret key itself--which need to be known and available, both for interoperability and for the expected security-level of the algorithm. These are arguably similar to LLM weights. (Perhaps the simplest example would be the prominence of "13" in ROT13.) Yet if someone tried saying that their encryption standard was "open source" while keeping those constants secret and/or legally-encumbered, I think a lot of people would complain that the label is incorrect or inappropriate.

pabs3 3y ago

I like Debian's ML policy about this: https://salsa.debian.org/deeplearning-team/ml-policy/ https://salsa.debian.org/deeplearning-team/ml-policy/