4 ms·

Oh dear lord .... sub heading states - Storm - Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models Good luck with this storm,

• tossandthrow 2y ago
  there is this sentiment of Ai induced deterioration and pollution. what if that is not the case? what if the quality of this type of content actually increases?
  • CamperBob2 2y ago
    It will for a while, I imagine. But the long-term is a concern. Where will new information come from, exactly?
    • tossandthrow 2y ago
      why not Ai? And even if we accept the premise (as flawed as it might be) that Ai is not able to create original knowledge, most of what's online is dessimination and dies not represent new information but just old information rewritten to be understandable by a certain segment. something LLMs excel at.
      • poyu 2y ago
        > Ai is not able to create original knowledge The current state of LLMs do hallucinate though. It's just not a very trustworthy source of facts.
        • tossandthrow 2y ago
          just like my first teachers said I should absolutely not use Wikipedia. LLMs was popularized less than 2 years ago. I think it is safe to assume that it will be as trustworthy as you see Wikipedia today, and probably even more as you can embed reasoning techniques into the LLMs to correct misunderstandings. Wikipedia cannot self correct.
          • howenterprisey 2y ago
            Wikipedia absolutely self-corrects, that's the whole point!
            • tossandthrow 2y ago
              it does not. it's authors corrects it. unless you see Wikipedia as the organisation and not the encyklopedia? in that case: sigh, then everything self corrects
              • howenterprisey 2y ago
                It is incoherent to discuss Wikipedia as some text divorced from the community and process that made it, so I'm done here.
          • pksebben 2y ago
            There's an important difference between wikipedia and the LLMs that are actually useful today. Wikipedia is open, like completely open. GPT is not. Unless we manage to crack the distributed training / incremental improvement barriers, LLMs are a lot more likely to follow the Google path (that is, start awesome and gradually enshittify as capitalist concerns pollute the decision matrix) than they are the Wikipedia path (gradual improvement as more eyes and minds work to improve them).
            • tossandthrow 2y ago
              this is super interesting! it also carves I to the question what constituted model openness? most people agree that just releasing weights are not enough. but I don't think it will ever be feasible to say that reproducing model training is feasible. especially when factoring in branching and merging of models. for me this is an open and super interesting question.
              • pksebben 2y ago
                Here's what I envision (note: impossible with current state of the art) A model that can be incrementally trained (this is the bit we're missing) hosted by a nonprofit, belonging to "we the people" (like wikipedia). The training process could be done a little like wikipedia talk pages are now - datasets are proposed and discussed out in the open and once generally approved, trained into the model. Because training currently involves backpropagation, this isn't possible. Hinton was working on a structure called "forward-forward" that would have overcome this (if it worked) before he decided humanity couldn't be trusted [1]. It is my hope that someone smarter than me picks up this thread of research - although in the spirit of personal responsibility I've started picking up my old math books to try and get to a point where I grok the implementation enough to experiment myself (I'm not super confident I'm gonna get there but you can't win if you don't play, right?) It's hard to tell when (if?) we're ever going to have this - if it does happen, it'll be because a lot of people do a lot of really smart unpaid work (after seeing OpenAI do what it did, I don't have a ton of faith that even non-profit orgs have the will or the structure to pull it off. Please prove me wrong.) 1 - https://arxiv.org/abs/2212.13345 https://arxiv.org/abs/2212.13345
  • prionassembly 2y ago
    I mean, putting a bullet to someone's head can extirpate a brain tumor they hadn't been alerted to before, while leaving a grateful person owing you kudos. What if?
    • tossandthrow 2y ago
      you can always find some radical regressionist argument that is completely out of contact with anything. congrats on that!
  • pksebben 2y ago
    On the one hand, a tool is as good or bad as the person wielding it. Smart folks with the right intentions will certainly be able to use this stuff to increase the rate and quality of their output (because they're smart, so they'll verify rather than trust. Hopefully.) On the other, moderation is an unsolved problem. The general mess of the internet is probably not quite ready to be handed a footgun of this caliber. As with many things tech, some of the outcome falls to us, the techies. We can build systems to help steer this.
    • tossandthrow 2y ago
      > On the one hand, a tool is as good or bad as the person wielding it. I think the real reason is one line dogmas like this.
      • pksebben 2y ago
        I'm not sure I follow you - reason for what? To be clear - I'm with you that these systems can absolutely be a force for vast good (at least, I think that was what you were getting at unless there was a missing '/s'). I use them daily to pretty astounding effect. I'll admit to being a little put off by being labeled dogmatic - it's not something I consider myself to be.
        • tossandthrow 2y ago
          it was a half sentence, for that I apologize. and I don't remember entirely what I meant. However, I do see a lot of one-sentence "truthms" being thrown around. like "garbage in; garbage out" and the likest. these are not correct. we can just look at the current state of the art with LLMs that has vast amounts of garbage going in - it seems like the value is in the vastness of the data over the quality. > On the one hand, a tool is as good or bad as the person wielding it. I see this as being a dogme. smart people make good LLMs dumb people do not. but this is an open question. it seems like the biggest wallet will be the winner of the LLM game. please correct me if I misunderstood something.
          • 2y ago
  • jerf 2y ago
    The concern is not just a vaguely cynical hand-wringing about how bad AI is. Feeding AIs their own output as training material is a bad thing for mathematical reasons, and feeding AIs the output of other very similar AIs is close enough for it to also be bad. The reasons are subtle and hard to describe in plain English, and I'm not enough of an expert to even try, so pardon if I don't. But given that it is hard to determine if output is from an AI, AI really does face a crisis of having a hard time coming across good training material in the future.
    • tossandthrow 2y ago
      can you show me a mathematical reason that cannot philosophically be applied to people also? people only being fed other people output.
      • jerf 2y ago
        I'd go with "no", because people just consuming the output of other people is a big ongoing problem. Input from the universe needs to be added in order to maintain alignment with the universe, for whichever "universe" you are considering. Without frequent reference to reality, people feeding too much on people will inevitably depart from reality. In another context, you may know this as an "echo chamber". Not quite exactly the same concept, but very, very similar. I do like to remind people that the AI of today and LLMs are not the whole of reality. Perhaps someday there will be AIs that are also capable of directly consulting the universe, through some sort of body they can use. But the current LLMs, which are trained on some sort of human output, need to exclude AI-generated input or they too will converge on some sort of degenerate attractor.
        • tossandthrow 2y ago
          yep, then we are back a "vaguely cynical hand-wringing about how bad AI is." currently we have mostly LLMs in the mix. but there are no reason that the Ai mix will not contain embodied agents thst also publish stuff in the internet. (think search and rescue bots that automatically write a report). Now Ai is connected to reality without people in the mix.
  • skywhopper 2y ago
    How could it? LLMs hallucinate false information. Even if hallucinations are improved, the false information they've generated is now part of the body of text they will be trained on.
• deleted 2y ago
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• achrono 2y ago
  LLM mediocrity is just a reflection of human mediocrity, and my bet is on the average LLM to get way better much faster than the average human doing the same.
  • _akhe 2y ago
    Agree with you, but on mediocrity: Mistral barely passes as usable, GPT-4 is barely better than Googling, and nothing else I've tried is even ready for production. So there's some element of the model's design, weights/embeddings, and training data that matters a lot. Only fine-tuned models are producing impressive work, because when we say something is impressive it by definition means not like the status quo - the model must be tuned toward some bias or other, whether it's aesthetic or otherwise, in order to stand out from the rest. And generic models like GPT or Stable Diffusion will always be generic, they won't have a bias toward certain truths - they'll be mostly unbiased which we want for general research or internet search. So it's interesting, in order to get incredible quality of work out of AI, you have to make it specific, but in order to that, you have to train it on the work of humans. I think for this reason AI will always be ultimately behind humans, though it of course will displace a lot of work we do, which is significant.
  • singleshot_ 2y ago
    Humans are limited in the volume of garbage they can produce.