4 ms·

The innovation with generative AI is fundamentally legal: they're copyright laundering systems. You put a few images (books, etc.) in, mix it around, and "poof"

The innovation with generative AI is fundamentally legal: they're copyright laundering systems. You put a few images (books, etc.) in, mix it around, and "poof" there disappears the copyright. I think this largely accounts for when it will be useful. (And why companies will and will not use it).

justrealist 3y ago
> they're copyright laundering systems. You put a few images (books, etc.) in, mix it around, and "poof" there disappears the copyright This also describes the process of going to university.
- visarga 3y ago
  Why not? This would fix the regurgitation issue and possibly be more palatable to copyright holders. The LLM trained on both copyrighted and open works can generate training data for a second LLM that never sees copyrighted works, achieving perfect separation of idea from expression. Copyright is supposed to protect expression but not ideas. Ideas are free, LLMs should be allowed to learn ideas. This can also filter out bad quality data and PII, or expand on parts of the distribution with less samples. It would be "dataset engineering" as opposed to "model engineering". A recent paper (TinyStories) shows you can train a LM entirely with synthetic data and even evaluate it with another LLM. They could make a model 1000x smaller that still has fluent English - child level English more specifically, but well articulated, and even capable of reasoning. https://arxiv.org/abs/2305.07759 https://arxiv.org/abs/2305.07759 I believe in the future LLMs will train on 100% synthetic data from previous generations of LLM. The benefit will be increased quality, more privacy, less copyright infringement and smaller more efficient models, like TinyStories. Only the first few generations of LLM need to scrape the whole internet, the next generations will have better data.
- mjburgess 3y ago
  > This also describes the process of going to university. I do not recall the lesson wherein I sampled from thousands of prior exam papers to generate my answer to the one I sat. Without any prior exam papers at all I could, indeed, sit the exam. The algorithm which animals follow to be able to do such great things is very expensive: acuring actual skill, technique, knowledge and competence with the world. The algorithm statistical AI follows is simple: hoover up all digitised human history and sample from it. This is entirely dependent on humans not doing that. We have people doing that all the time: writing books, blogs, videos, github, etc. 99.5% of anything we want chatgpt for exists -- we just don't have the audacity to steal it. Now we can!
  - justrealist 3y ago
    If you think ChatGPT is dependent on exam training data to answer exam questions, you have a misunderstanding of how LLMs work.
    - mjburgess 3y ago
      You'll have to show me a single case of an LLM being trained on data which excludes exams and continues to answer exam questions. You'll note that ChatGPT performance drops off a cliff on many exams released after 2021. It's a trick.
      - whimsicalism 3y ago
        All of the GPT-4 exams it were evaluated on were not present in its training data. But honestly, if you don't get it now, I can't hope to convince.
        mjburgess 3y ago
        It's always sampling from an existing distribution of relevant data points -- that's necessarily how its working. If you want to claim the sample set is only mildy similar to exam questions -- so be it, that may be true. Or if you want to claim that its sampling method is attentive to structural associations in its sample set, so that its not lifting from "identical distributions" -- so be it. So long as those "structural associations" are givens, and the data "givens", the process is just sampling from a domain of human effort without expending any of a similar kind. If there had been no internet, ChatGPT would be a dumb mute -- because it has no capacity to generate data; it does not develop actual conceptualisations of the world -- it samples from the data shadows created by people. To produce useful data requires expounding a tremendous effort -- growing an animal to cope with the world. It is this which is being laundered, unpaid and unacknowledged, through LLMs. Whilst star-trek-huffing loons claim this stuff is doing the opposite -- a ideological delusion which benefits all those whose bank accounts are increased by the lie that "ChatGPT wrote this". If we were prepared to price the data commons which has been created over the last 20-30 years of the internet, by everyone, its not hard to think training ChatGPT would cost a trillion. How much labour went into creating that digital resource, and by how many, etc.?
- croes 3y ago
  The difference is the ease of use and the mass of output.
- aeturnum 3y ago
  I see this comment all the time in this conversation and it strikes me as being in very bad faith. I would love to understand what you're trying to get at. Because - first, in a legal sense, it seems wrong? You cannot memorize a book and then reproduce it from memory to disappear the copyright. The law on AI & copyright is very young (and I am not an expert), but artistic expression cases that involve copying (i.e. warhol) have rested on the idea that the copying is transformative in some way - but this seems in direct opposition to the idea that machines cannot create works themselves. I.e. the legal understanding that protects AI from needing to respect copyright also suggests it should not be understood to be traditionally transformative. On a less legal level, an AI ingesting a huge amount of content and adjusting a neural network is very different from a student going to university in most ways. There are also similarities! But in a general way the direct comparison does not line up particularly well. So many complaints about Transformer-based AI exist on levels outside of the precise "agent doing the learning" (including this one).
soulofmischief 3y ago
If the output is fundamentally different from the input, or reasonably derivative, then I agree that copyright should disappear
542458 3y ago
> I think this largely accounts for when it will be useful. I think this is excessively cynical. For example, I just used chatGPT to write a job description last night. I'm not particularly interested in copyright laundering or anything of the sort - nobody really cares about copyright on job descriptions (they're mostly pretty similar) unless you're being egregious about it. I could spend a bit more time and just pattern match of other postings, but the LLM can do it better and faster than me. I just provided appropriate prompts for the job characteristics and benefits, and then provided the final editing and discretion. I think there are lots of similar situations where we (as humans) need text that is essentially boilerplate, but still is expected to be well-enough-written. ChatGPT isn't a copyright evasion tool to me, it's a shortcut for better writing.
- mjburgess 3y ago
  For me, when I use the output I am acutely aware of how difficult it was to create the sources its sampling from. Behind each line I can imagine a person solving a problem, for themselves and writing up their solution, and sharing it. This process is inordinately expensive for each individual: they must be competent with the ideas, techniques, etc. and deploy them in a novel circumstance. LLMs need no competence with the ideas, indeed, need no ideas or techniques at all. The very same work can be obtain via two radically different algorithms: 1) develop conceptualisations and techniques to generate solutions in the face of novel problems; 2) sample from all such prior attempts. (2) requires many cases of (1) to work -- and that's the copyright laundering, or just, theft if you like. Who in all their writing on the internet was consenting to train ChatGPT? No one. This is the innovation. We have google search. We can easily get 99.5% of whatever chatgpt generates if we have the gaul to copy/paste it. Since we don't we launder these efforts through a novel interface. It is an extremely useful tool, but we should be more aware of where it's utility comes from. From the last twenty years of human labour which has placed all our lives and thoughts on a digital commons which is here being replayed back to us as if "ChatGPT wrote it". AI here has written zilch. Absent all those digital efforts, this is a dumb system with nothing to say. And if we had the audacity just to copy/paste from ebooks, github, blogs and the like -- we would barely benefit from it at all.
  - 3y ago
jillesvangurp 3y ago
I think it's the opposite. There are of course companies that are being more conservative than others. And there are companies that are going to be more successful than others using this stuff. Because those companies may end up with an edge over those other companies. It's that simple. You can hope for courts to put a stop to that but you'd be a fool to expect them to lift a finger any time soon. And can you afford them taking a different decision? Probably Apple is right in not being overly worried about losing an edge here short term. But that would be because they are quite comfortably leading way ahead of the pack. They can adjust as needed and cost is not a factor when you ship products with such fat margins as they do. In other words, they can afford to be conservative here and see how things play out and adjust later. A few thousand people in their team being inconvenienced by having to do things manually without AI assistance doesn't really add up to a whole lot of cost for them. That's not true for a lot of companies. Other companies might have to make different choices in order to stay relevant. In the end it's a choice between artificial intelligence or self-imposed stupidity. Not making proper use of resources available as a company can be a fatal mistake. And things like chat gpt are here right now and usable for anyone who cares to use it. And with some clear added value. As for the legalities. I wouldn't get my hopes up for judges to apply interpretations of copyright law that are inconsistent with the past ones. Copyright is not going anywhere. And forget about politicians adding much to the law that is going to matter any time soon. It boils down to concepts like fair use, people actually starting court cases, etc. Lots of people talking about that but not a lot with the deep pockets to follow that through. Not a lot of coherent lobby activity on this front to make politicians move. Lots of companies with deep pockets and a vested interest in this stuff and a lot of lobbying power to ensure the gravy train doesn't grind to a halt. Apple will eventually integrate AI into their business. It might not be the MS/OpenAI flavour. Or the Google one. Why would they want to depend on that? It's going to be a business decision for them.

justrealist 3y ago

> they're copyright laundering systems. You put a few images (books, etc.) in, mix it around, and "poof" there disappears the copyright This also describes the process of going to university.

visarga 3y ago
Why not? This would fix the regurgitation issue and possibly be more palatable to copyright holders. The LLM trained on both copyrighted and open works can generate training data for a second LLM that never sees copyrighted works, achieving perfect separation of idea from expression. Copyright is supposed to protect expression but not ideas. Ideas are free, LLMs should be allowed to learn ideas. This can also filter out bad quality data and PII, or expand on parts of the distribution with less samples. It would be "dataset engineering" as opposed to "model engineering". A recent paper (TinyStories) shows you can train a LM entirely with synthetic data and even evaluate it with another LLM. They could make a model 1000x smaller that still has fluent English - child level English more specifically, but well articulated, and even capable of reasoning. https://arxiv.org/abs/2305.07759 https://arxiv.org/abs/2305.07759 I believe in the future LLMs will train on 100% synthetic data from previous generations of LLM. The benefit will be increased quality, more privacy, less copyright infringement and smaller more efficient models, like TinyStories. Only the first few generations of LLM need to scrape the whole internet, the next generations will have better data.
mjburgess 3y ago
> This also describes the process of going to university. I do not recall the lesson wherein I sampled from thousands of prior exam papers to generate my answer to the one I sat. Without any prior exam papers at all I could, indeed, sit the exam. The algorithm which animals follow to be able to do such great things is very expensive: acuring actual skill, technique, knowledge and competence with the world. The algorithm statistical AI follows is simple: hoover up all digitised human history and sample from it. This is entirely dependent on humans not doing that. We have people doing that all the time: writing books, blogs, videos, github, etc. 99.5% of anything we want chatgpt for exists -- we just don't have the audacity to steal it. Now we can!
- justrealist 3y ago
  If you think ChatGPT is dependent on exam training data to answer exam questions, you have a misunderstanding of how LLMs work.
  - mjburgess 3y ago
    You'll have to show me a single case of an LLM being trained on data which excludes exams and continues to answer exam questions. You'll note that ChatGPT performance drops off a cliff on many exams released after 2021. It's a trick.
    - whimsicalism 3y ago
      All of the GPT-4 exams it were evaluated on were not present in its training data. But honestly, if you don't get it now, I can't hope to convince.
      - mjburgess 3y ago
        It's always sampling from an existing distribution of relevant data points -- that's necessarily how its working. If you want to claim the sample set is only mildy similar to exam questions -- so be it, that may be true. Or if you want to claim that its sampling method is attentive to structural associations in its sample set, so that its not lifting from "identical distributions" -- so be it. So long as those "structural associations" are givens, and the data "givens", the process is just sampling from a domain of human effort without expending any of a similar kind. If there had been no internet, ChatGPT would be a dumb mute -- because it has no capacity to generate data; it does not develop actual conceptualisations of the world -- it samples from the data shadows created by people. To produce useful data requires expounding a tremendous effort -- growing an animal to cope with the world. It is this which is being laundered, unpaid and unacknowledged, through LLMs. Whilst star-trek-huffing loons claim this stuff is doing the opposite -- a ideological delusion which benefits all those whose bank accounts are increased by the lie that "ChatGPT wrote this". If we were prepared to price the data commons which has been created over the last 20-30 years of the internet, by everyone, its not hard to think training ChatGPT would cost a trillion. How much labour went into creating that digital resource, and by how many, etc.?
croes 3y ago
The difference is the ease of use and the mass of output.
aeturnum 3y ago
I see this comment all the time in this conversation and it strikes me as being in very bad faith. I would love to understand what you're trying to get at. Because - first, in a legal sense, it seems wrong? You cannot memorize a book and then reproduce it from memory to disappear the copyright. The law on AI & copyright is very young (and I am not an expert), but artistic expression cases that involve copying (i.e. warhol) have rested on the idea that the copying is transformative in some way - but this seems in direct opposition to the idea that machines cannot create works themselves. I.e. the legal understanding that protects AI from needing to respect copyright also suggests it should not be understood to be traditionally transformative. On a less legal level, an AI ingesting a huge amount of content and adjusting a neural network is very different from a student going to university in most ways. There are also similarities! But in a general way the direct comparison does not line up particularly well. So many complaints about Transformer-based AI exist on levels outside of the precise "agent doing the learning" (including this one).

soulofmischief 3y ago

If the output is fundamentally different from the input, or reasonably derivative, then I agree that copyright should disappear

542458 3y ago

> I think this largely accounts for when it will be useful. I think this is excessively cynical. For example, I just used chatGPT to write a job description last night. I'm not particularly interested in copyright laundering or anything of the sort - nobody really cares about copyright on job descriptions (they're mostly pretty similar) unless you're being egregious about it. I could spend a bit more time and just pattern match of other postings, but the LLM can do it better and faster than me. I just provided appropriate prompts for the job characteristics and benefits, and then provided the final editing and discretion. I think there are lots of similar situations where we (as humans) need text that is essentially boilerplate, but still is expected to be well-enough-written. ChatGPT isn't a copyright evasion tool to me, it's a shortcut for better writing.

mjburgess 3y ago
For me, when I use the output I am acutely aware of how difficult it was to create the sources its sampling from. Behind each line I can imagine a person solving a problem, for themselves and writing up their solution, and sharing it. This process is inordinately expensive for each individual: they must be competent with the ideas, techniques, etc. and deploy them in a novel circumstance. LLMs need no competence with the ideas, indeed, need no ideas or techniques at all. The very same work can be obtain via two radically different algorithms: 1) develop conceptualisations and techniques to generate solutions in the face of novel problems; 2) sample from all such prior attempts. (2) requires many cases of (1) to work -- and that's the copyright laundering, or just, theft if you like. Who in all their writing on the internet was consenting to train ChatGPT? No one. This is the innovation. We have google search. We can easily get 99.5% of whatever chatgpt generates if we have the gaul to copy/paste it. Since we don't we launder these efforts through a novel interface. It is an extremely useful tool, but we should be more aware of where it's utility comes from. From the last twenty years of human labour which has placed all our lives and thoughts on a digital commons which is here being replayed back to us as if "ChatGPT wrote it". AI here has written zilch. Absent all those digital efforts, this is a dumb system with nothing to say. And if we had the audacity just to copy/paste from ebooks, github, blogs and the like -- we would barely benefit from it at all.
- 3y ago

jillesvangurp 3y ago

I think it's the opposite. There are of course companies that are being more conservative than others. And there are companies that are going to be more successful than others using this stuff. Because those companies may end up with an edge over those other companies. It's that simple. You can hope for courts to put a stop to that but you'd be a fool to expect them to lift a finger any time soon. And can you afford them taking a different decision? Probably Apple is right in not being overly worried about losing an edge here short term. But that would be because they are quite comfortably leading way ahead of the pack. They can adjust as needed and cost is not a factor when you ship products with such fat margins as they do. In other words, they can afford to be conservative here and see how things play out and adjust later. A few thousand people in their team being inconvenienced by having to do things manually without AI assistance doesn't really add up to a whole lot of cost for them. That's not true for a lot of companies. Other companies might have to make different choices in order to stay relevant. In the end it's a choice between artificial intelligence or self-imposed stupidity. Not making proper use of resources available as a company can be a fatal mistake. And things like chat gpt are here right now and usable for anyone who cares to use it. And with some clear added value. As for the legalities. I wouldn't get my hopes up for judges to apply interpretations of copyright law that are inconsistent with the past ones. Copyright is not going anywhere. And forget about politicians adding much to the law that is going to matter any time soon. It boils down to concepts like fair use, people actually starting court cases, etc. Lots of people talking about that but not a lot with the deep pockets to follow that through. Not a lot of coherent lobby activity on this front to make politicians move. Lots of companies with deep pockets and a vested interest in this stuff and a lot of lobbying power to ensure the gravy train doesn't grind to a halt. Apple will eventually integrate AI into their business. It might not be the MS/OpenAI flavour. Or the Google one. Why would they want to depend on that? It's going to be a business decision for them.