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The one that constantly grinds my gears is commenters comparing how AI systems are trained to human learning as if they are the same. E.g. "How is *GPT taking i

• rowanG077 4y ago
  I think it's a incredibly important question to be able to explain how an AI creating novel work is different then a Human creating novel work. Why does this grind your gears?
  • sillysaurusx 4y ago
    I suspect it's the same reason it grinds my gears that it's called a "learning rate" instead of "step size" in ML. Not only is it less precise term, but it gives the wrong implications. Personally, I'm on the side of releasing training data. Let everybody train on everything. But it's always felt absurd to say that the ML models are "learning" things. But hey, none of us know how learning works anyway, right? So maybe it's not such a big distinction. As you say, none of us can pinpoint why a model isn't learning vs why we are.
    • godelski 4y ago
      I think the problem with these words is that the vernacular has different meanings with the common lexicon. But this is quite true for any field. "Field" is even a good example of this as mathematicians use it in a drastically different way than I just used it now. This can make people think they understand technicals more than they do. But if you're making the argument that ML needs to learn more math and needs more rigor, then I'd defend that claim. It is a personal pet peeve of min (fuck man, how often I have to explain to my research group what a covariance matrix is and why it is essential to diffusion is absurd).
      • wnkrshm 4y ago
        A lot of what we see is cargo cult engineering and not fundamental research in ML. Most of it is applied research or engineering - there is a little bit of fundamental research that actually expands our own knowledge about how things work and what their limits are, while applied science keeps marching on (maybe towards funamentally impossible goals).
  • bonsaibilly 4y ago
    To me it seems to imply a stunningly nihilistic point of view vis-a-vis human writing (or art, where it also gets repeated a lot here). It seems almost definitionally obvious that what an LLM does is not the same as what a human does – both on the basis that if all human writing were merely done via blending together other writing we had seen in the past, it would appear to be impossible for us to have developed written communication in the first place, and on the basis that when I write something, I mean something I am then attempting to communicate. An LLM never means to communicate anything, there is no there there; it simply reproduces the most likely tokens in response to a prompt. To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory.
    • hprotagonist 4y ago
      see: http://www.jaronlanier.com/zombie.html http://www.jaronlanier.com/zombie.html It’s not said very much, but this style of dehumanization is really corrosive in a way that directly benefits the worst forms of human governments and structures, and this fact goes i think genuinely unrecognized too often in tech-land. if we really are p-zombies, then those people aren’t really suffering, right, so it’s fine …
    • oneoff786 4y ago
      > To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory Let’s assume humans are not just evolved pattern machines for a second. A human can still do a completely non profound work of art following a prompt to draw X in the style of Y. And that’s ok. So why can a machine not do the same? Surely not everything a human does is intrinsically profound.
      • bonsaibilly 4y ago
        This is not just moving but fully inverting the goal posts. Nobody at any point was disputing that a machine can’t ape non-profound or rote or meaningless human output. The original discussion was precisely an objection to the attitude underlying "How is *GPT taking in data and producing an output different than a human learning a skill and making prose/code/art?" and the answer is right in your premise - not everything a human does is not profound. A human can intend to mean something with prose or art, even if not all prose or art means something — but any meaning we see in ChatGPT’s output is essentially pareidolia.
  • kube-system 4y ago
    I'm not the parent commenter, but it grinds my gears because the answer is obvious. Humans value human creativity because of emotion, shared experience, and the value we place on each other as humans.
    • MacsHeadroom 4y ago
      It's just as obvious to me that humans do not actually care where creative works they appreciate come from. Some of my favorite creative works came from some awful people and others came from algorithms. I don't care. It does not effect the works or the way in which the works effect me.
      • kube-system 4y ago
        Awful people are humans, with human experiences. All algorithms are made by humans and/or process human input. And besides, I never said creativity is a requirement for appreciation. I appreciate things in nature regardless of the fact they weren’t the result of creativity.
      • greysphere 4y ago
        The fashion industry and pretty much the concept and existence of luxury brands are counter to this claim.
  • AnimalMuppet 4y ago
    Because the implied answer is "it isn't different". That grinds our gears (for various values of "our") because 1) it assumes an answer to what is, at best, an open question, and 2) we think it assumes the wrong answer. If asked in good faith (not assuming the answer), I can agree that it's an important question.
    • intelVISA 4y ago
      ChatGPT can already replicate the bugs in an average shop, I would say it is becoming post-human if we remove its ability to generate nonsense.
  • discreteevent 4y ago
    > Why does this grind your gears? For the same reason it ground Kurt Cobain's gears. "He knows all our pretty songs, and he likes to sing along. But he don't know what it means" I always thought that was a bit condescending but it applies perfectly to chatgpt.
  • robotresearcher 4y ago
    > I think it's a incredibly important question Why do you think that? If we had an widely accepted answer, how would the world be different?
    • rowanG077 4y ago
      Because we most likely could use that information to both gain greater insight into how humans learn and most importantly innovate. And also we can strive to create better AI based on the principles discovered.
• zzzzzzzza 4y ago
  as a "reductivist" I feel I stand on the side of freedom, and that the other side wants to own our souls as intellectual property, under the guise of extending and protecting their current contractual relationships with media companies (i don't believe intellectual property is a morally legitimate concept, since it comes from a exploration of a pre existing space of ideas (also I am a georgist so I don't believe physical space can be morally owned either)) naturally this strongly held belief can result in sharp words against perceived enemies.
  • jrumbut 4y ago
    I am torn. While I am skeptical of a lot of IP concepts, I am much more skeptical of a law that is enforced against internet users who want to download MP3s but not enforced against technology companies that want to sell AI generated content. So I currently find myself saying "we must get a handle on this copyright infringement" because equal protection is important, while also believing that copyright protections ought to be much weaker than they are.
• krona 4y ago
  Didn't You just state the Chinese room thought experiment? It's an important observation that humans are just as capable of doing tasks without understanding them, and so its no surprise that the computer doesn't understand them either.
• godelski 4y ago
  > How [is an AI artist] taking in data and producing an output different than a human learning a skill and making prose/code/art? There may be a misalignment in intent of the claim and interpretation of the claim. As someone that researches generative modeling I actually think there is an important aspect to this question, but I do not think that this question has anything to do with how the brain or the machine learn art. It has to do with legality and morals. So I'll break it down. We believe that it is morally and legally acceptable for a human to look at copyrighted artwork and even mimic it in the process of learning how to become a better artist (sales are where the morality breaks down and especially with impersonation). The question is "where is the nuanced difference between a machine using that data and a human using that data to learn?" This doesn't depend on the learning techniques just like how no one cares if one person learns differently than another person. Obviously no one thinks AI art should impersonate real artists nor do they think people should sell this work if it contains copyrighted material. That's in line with the human artist values (fine to draw Mickey Mouse, not fine to sell a drawing of Mickey Mouse and worse to sell that drawing and claim it is official Disney art). This is a very important question because we need to create laws about how we can train these systems and how we handle the data that they produce (two very different things!). The line between human and machine is a lot thinner than people think (think digital painting and CGI), and it doesn't matter that stochastic algorithms learn differently than humans learn. The question is about how/if learning material can be used and if machines should be treated differently. And if so, why. But this is way more than one sentence.
  • AmericanChopper 4y ago
    > This is a very important question because we need to create laws about how we can train these systems and how we handle the data that they produce This is a rather prejudiced statement. AI does pose some interesting questions about copyright, but the most obvious question is whether the existing laws are sufficient. You go on to ask that question, but this statement presupposes the answer is that they’re not.
    • mLuby 4y ago
      In that sentence, prejudiced is a pejorative way to say opinionated. I assert that existing legal systems do not suffice. Human governments and courts have shown themselves to be near-sighted, slow, and even corrupt when it comes to rapidly advancing lucrative technology (except perhaps when that tech is a weapon).
• cma 4y ago
  > E.g. "How is *GPT taking in data and producing an output different than a human learning a skill and making prose/code/art?" It can go the other way too, like proof that diffusion models memorize heavily repeated training examples being used as evidence they aren't creating stuff at all and just copy pasting, but artists can memorize whole works too, especially artists that copy style really well. Many English classes will have you verbatim memorize poetry as well, to show how things were done with memorization in oral storytelling traditions.
  • MacsHeadroom 4y ago
    > like proof that diffusion models memorize heavily repeated training examples being used as evidence they aren't creating stuff at all and just copy pasting This proof actually demonstrated the opposite. In that paper it was found that something like only 11 pictures from millions were recoverable. They were only recoverable because those handful of pictures were accidentally duplicated in the training data many multiples more than other pictures. Even pictures which were accidentally duplicated dozens of times were found to be unrecoverable by the trained model.