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Have I gone back in time? I feel like I’m reading the exact same sentence that someone posted about if StableDiffusion included images or was just “learning pa

• casey2 3y ago
  It's clearly not a copy stop arguing in bad faith.
• deleted 3y ago
  [deleted]
• stavros 3y ago
  Does this storage argument also go for humans? If I ask a painter to paint paintings they've seen before, what will be their rate of copying the painting exactly?
  • wokwokwok 3y ago
    It doesn’t matter. The process is irrelevant. Black box. Input. Output. Is the output the same as some training input? It’s not rocket science. “…but humans…” argument is not relevant. This is not a human.
    • stavros 3y ago
      But if I put a human in the black box, that somehow now matters to your argument, because you're saying that it only holds for machines.
      • ubercow13 3y ago
        If you transcribe a copyrighted book by hand, that doesn't give you the right to publish it. I don't think being a human currently gives you a legal loophole to copy works so why make the comparison?
      • wokwokwok 3y ago
        I don’t care if there’s a human in the box. If the box spits out training input as output it is copying it. It doesn’t matter if there is a human doing it or not. For your supposition to work, the input to the box would be only an abstract summary of the logical steps, and the output an exact copy of some other thing that was never an input. In that case, yes, it would not be copying. ..but, is that the case? Hm? Is that what we care about? Is it possible to randomly generate the exact sequence of text with no matching training input? Along with the comments? It seems fabulously unlikely, the point of being totally absurd.
      • chmod775 3y ago
        Humans (and their creativity) have special status and privileges in law. Machines don't. It doesn't matter how fancy they are. The law doesn't care. So yes, a human in a black box is different from a machine in a black box until laws change.
      • patates 3y ago
        I'm a proponent of not restricting (well, or trying to restrict) machine learning models and not considering them a lossy database but it must be said here if humans can recreate copyrighted works from memory and publish them, they are in trouble too.
• deleted 3y ago
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• Twirrim 3y ago
  I'll see if I can dig some up, but there have been similar examples to the image reproduction case that have come out from codepilot, all it took was using some more unique method names (i.e. ones that were very specific to a particular code base) and oh look there comes the "totally not copied, honest gov'nor" code. Any company that is using copilot or similar is walking right in to a massive legal minefield. Any engineer that chooses to use Copilot without explicit approval from the company should seriously worry about what target they're putting on their back. You don't want to be putting yourself in a position where your employer can say "They did this without our approval" or worse "Despite explicitly having told them not to", should there end up being legal action. Someone is going to establish precedence one way or another at some point, don't let it be you.
  • hutzlibu 3y ago
    "I'll see if I can dig some up, but there have been similar examples to the image reproduction case that have come out from codepilot, all it took was using some more unique method names " You mean, like the example the article used? https://web.archive.org/web/20221017081115/https://nitter.net/docsparse/status/1581461734665367554 https://web.archive.org/web/20221017081115/https://nitter.ne... "sparse matrix transpose, cs_" Generated the authors matrixes code.
• robocat 3y ago
  Here’s the example of copilot regurgitating GPL code verbatim: https://codeium.com/blog/copilot-trains-on-gpl-codeium-does-not#github-copilot-trains-on-non-permissive-licenses https://codeium.com/blog/copilot-trains-on-gpl-codeium-does-... It produces an almost exact copy of some training data.
• andyjohnson0 3y ago
  > That’s copying. > These models copy code. These assertions have very little weight - what matters is what the law says. And for now, in the jurisdictions that matter, the law is still silent. Maybe it will catch up via either legislation or case law, or maybe it won't. But for now there is no legal consensus on what these new things are doing. Of course there is a moral/ethical component to this, and individuals are obviously free to hold personal views. But unless some global working consensus forms (unlikely) then I don't see how change will come from that. I suspect that it's going to be difficult for politicians to find the will to do something about this issue, and then to get their heads around it enough to make good laws.
  • nassimm 3y ago
    The subject of the thread is "Will my code be regurgitated if I put it on Github ? Should I avoid putting my code on Github if I don't want it copied?" The legality aspect that you are injecting into the discussion is irrelevant
    • andyjohnson0 3y ago
      I was replying to the comment by @wokwokwok.
  • wokwokwok 3y ago
    If y = f(x, T) when y is a member of T, prove f() doesn’t copy a value from T. This is possible. For example, many functions f(0) return 0; if we can derive a function g(x) that generates y without access to T (ie. the training data) then we can plausibly assume that f(x, T) might indeed not be copying from T. …but can we do so? If so, we must admit that it is possible that f(x, T) = g(x) and no copying is taking place. So, in the past 50 years of prior work can we come up with an example of a function g(x) that generates the exact code we see coming out of these LLMs? I’ll grant, it’s not impossible. For example, if stable diffusion generated sin wave patterns or fractals that exhibited “deep complex structure” and it happens that some artist had written code to do that exact thing, there would (I believe) be a fair case that stable diffusion was not copying the artist, it was simply a parallel implementation of the same generative code. However, now my scepticism kicks in. For code written by hand, that was not generated, we are suggesting that a LLM is a parallel equivalent implementation of a human mind, and it can, with purely “learnt patterns” replicate not only the intent and structure of known code, but the exact code itself, repeatedly. I’ll grant. It’s not impossible, and it’s very difficult to prove, but it seems fabulously, unbelievably, extraordinarily unlikely that a clean room reimplementation would be identical, repeatedly. We’re entering into the domain of assigning probability and then doing a zero knowledge proof here, but the solution is easy. Just prove by counter example. Train a model that generates such code without the code as training data. You have now won the argument. …on the bright side, you’ve also solved the 10 million dollar question of “how do I train my LLM when I don’t have enough training data” (because that’s what you just did; train it to do something without training data), so you’re now rich and give zero ducks what I think. Congrats.
• sdiupIGPWEfh 3y ago
  > “But stable diffusion is GB in size, how can it have embedded full images of a dataset that is so much larger? It’s not possible.” > …but, it turns out it is possible (1) and it does, in fact, have embedded full copies of the source images. The _not possible_ assertion is in response to people arguing that generative image models literally copy and thus "steal" the images in their training set or that such generative models "work" by infringing on said images. The assertion is not that the models cannot possibly contain _any_ copies of training data, the assertion is that the models are generalizing and can not contain a majority of the training data. Now, let's look at some lines from your linked article titled "Paper: Stable Diffusion 'memorizes' some images, sparking privacy concerns", which happens to lead with scare quotes around "memorizes" and already hedges with "some": > Researchers only extracted 94 direct matches and 109 perceptual near-matches out of 350,000 high-probability-of-memorization images they tested . . . resulting in a roughly 0.03 percent memorization rate in this particular scenario. I do not consider a 0.03% rate of full copies particularly damning. Instead, it sounds like a flaw in training which could be addressed, which the article does in fact also mention being as a matter of overfitting to images that are over-represented in the training data. > the 160 million-image training dataset is many orders of magnitude larger than the 2GB Stable Diffusion AI model. That means any memorization that exists in the model is small, rare, and very difficult to accidentally extract. Which side's claims do you feel this line supports? Generative text models should, in theory, also be generalizing and not memorizing. In practice, however, it does appear far easier to get Copilot and the like to spit out exact copies of code, complete with license text. Presumably, there's just not enough code out there to sufficiently generalize from, so we're seeing overfitting as a matter of course.
  • henriquez 3y ago
    If you made 1,000,000 AI-generated MP3s available and 0.03% of them matched Sony’s copyrighted music catalog then you would be liable for $250,000 * 30 in statutory damages. Arguing that infringement doesn’t occur because the incidence rate is low is wallpapering over a serious problem.
    • matthew9219 3y ago
• scotty79 3y ago
  > in fact, have embedded full copies of the source images few images of of millions
• fwlr 3y ago
  If Edison goes over to Tesla’s house and looks at the latest invention on Tesla’s workbench, then goes to his factory and builds the same thing and sells it, then Edison has stolen and copied Tesla’s invention. If Edison breaks into Tesla’s house at night, takes* the invention off his workbench, goes to his factory and uses it as a reference to build and sell the same thing, then Edison has stolen and copied Tesla’s invention. In both cases we can say “stolen and copied”, but actual sequence of events and the legal recourse that Tesla has is different in each case. This difference matters because open source is like Tesla having his workbench in a public place where people are encouraged to watch him work, play around with the inventions, help him build, etc. In the “Tesla’s public workbench” situation, Tesla’s recourse is debatably impacted in the first scenario, but it is definitely unchanged in the second scenario. Arguing as though Copilot is doing “second scenario stealing and copying” rather than “first scenario stealing and copying” sidesteps that debate about whether open sourcing your code made it ‘up for grabs’ for natural and/or artificial intelligences to learn from and/or memorize. Now, it’s not clear what side will win that debate - I personally think “this has infringed intellectual property rights” has a decent chance of being the victor. But sidestepping that debate is setting off peoples’ “you’re trying to pull a fast one” alarm and making them unsympathetic. That’s what I’m getting at here. *: to avoid “steal vs copy depriving of property”-type discussions, postulate that Edison returns the invention to the workbench before Tesla notices As to the linked article, I would quote from the article itself: “[The paper] is dense with nuance that could potentially be molded to fit a particular narrative”. I could say more: both the article and the paper state there were zero byte-identical matches, and 203 direct or perceptual near matches out of 175 million generations (or out 160 million training images) is 0.0001%, which argues against this very strong claim of “factually and provably incorrect”. But I think the argument I will actually make is this: I said Copilot was synthesizing identical code from its knowledge base, which is completely compatible with the claim that it is outputting code from memory (in the human sense of memory). What it is not compatible with is the claim that it is outputting code from memory (in the computer sense of memory).
• circuit10 3y ago
  They do copy code sometimes but most of the code they generate is new, I think some (maybe not many but some) people have the impression that they literally search for similar code and copy it exactly 100% of the time which isn’t true