7 ms·

okay that’s just because you’re not good at using the models. Obviously you have to play around with them and figure out how to prompt & tune them. Once you d

okay that’s just because you’re not good at using the models. Obviously you have to play around with them and figure out how to prompt & tune them. Once you do that, you can get pretty amazing results. I make do a bunch of social media graphics and stable diffusion + midjourney has been insanely useful.

AshamedCaptain 3y ago
> okay that’s just because you’re not good at using the models. You literally cannot respond with "you are holding it wrong" specially when I'm claiming that even for the popular _example prompts_ SD authors used they had to hand-pick the best random result over a sea of extremely shitty images. And even in the original paper they disclaim it by saying "oh, our model is just bad at limbs". No, it's not just bad at limbs. They just happened to try examples where it could particularly show how terrible it is at limbs (i.e. spider legged horses and the like). But in truth, it's just bad at everything.
- kyleyeats 3y ago
  This is like throwing your hammer down in frustration over each nail taking more than one swing.
  - ChatGTP 3y ago
    I guess the difference is hammers are logical, simple tools to use with a known use case. They’re fairly hard to use incorrectly, although it does take some practice to use one, I’ll admit.
- LewisVerstappen 3y ago
  Nope. You literally just tried out one prompt and saw one good image and several bad ones and just shook your fist at the computer and gave up. I'll repeat myself. You have to play around with the models and learn how to use it (just like you have to do for everything) . > But in truth, it's just bad at everything Thousands of people (including myself) have had the complete opposite result and have gotten amazing pictures. You can play around with the finetuning with different models from civitai and get completely different art styles too. Like, this is so dumb I don't even know how to respond lol. You're like some guy who got a computer for the first time and couldn't figure out how to open the web browser, so he just dismissed it as useless.
  - AshamedCaptain 3y ago
    I don't think you understand the point. Your claims that "all of this needs extensive tuning and hand-holding and picking results" do not help your argument, they help _mine_. Most egregious if you are even doing more tuning and cherry picking that the authors of the models are doing, which you definitely are.
    - SanderNL 3y ago
      It sounds magic to you because you are unskilled. Like people using the mouse for the first time. The things he talks about are very basic, very easy.
  - whateveracct 3y ago
    I would rather just learn to draw than constantly write different text until it looks good Drawing isn't hard, you know
    - sebzim4500 3y ago
      I could spend 20,000 hours trying to learn to draw and I would still be far worse than what I could generate with Stable Diffusion + Control Net + etc.
      - whateveracct 3y ago
        I'm fairly sure if you can best stable diffusion after 7 years of daily 8h investment into drawing :)
        johnnyyyy 3y ago
        I doubt you would be better than someone who would use Stable Diffusion for 7 years. and I don’t even include the technological advancements in the next 7 years.
        3y ago
- cubefox 3y ago
  "It's bad at everything" ... bad by what standards? Just a few years ago it would have been regarded as unbelievable science fiction that a model with such capabilities would soon be available. As soon as they are here, people stop being impressed. But the objective impressiveness of a technology is determined by how unlikely it was regarded in the past, not by how impressed people are now. People get used to things pretty quickly. Besides, there are models that are much more capable than Stable Diffusion. The best one currently seems to be Midjourney V5.
  - wizzwizz4 3y ago
    > Just a few years ago it would have been regarded as unbelievable science fiction that a model with such capabilities would soon be available. No, it wouldn't have – not to people in the know. We just didn't have powerful enough computers back in the 90s. Sure, the techniques we've got now are better, but 90s algorithms (with modern supercomputers) can get you most of the way. Transformers are awesome, but they're not that much of a stretch from 90s technology. GANs are… ridiculously obvious, in hindsight, and people have been doing similar things since the dawn of AI; I imagine the people who came up with the idea were pretty confident of its capabilities even before they tested them. Both these kinds of system – and neural-net-based systems in general – are based around mimicry. Their inability to draw limbs, or to tell the truth, or count, are fundamental to how they function, and iterative improvement isn't going to fix them. Iterative improvement would be going faster, if researchers (outside of OpenAI and similar corporations) thought it was worthwhile to focus on improving these systems specifically. ChatGPT is not where transformers shine. StyleGAN3 is not where GANs shine. Midjourney is not where diffusion models shine. They're really useful lenses for visualising the way the architectures work, so they are useful test-beds for iterative algorithmic improvements…¹ but they aren't all that they're made out to be. ¹: See the 3 in StyleGAN3. Unlike the 4 in GPT-4, it actually means something more than "we made it bigger and changed the training data a bit".
    - cubefox 3y ago
      > No, it wouldn't have – not to people in the know. We just didn't have powerful enough computers back in the 90s. I'm not talking about the 90s. I'm talking about April 29, 2020.
- dragonwriter 3y ago
  > You literally cannot respond with "you are holding it wrong" specially when I'm claiming that even for the popular _example prompts_ SD authors used they had to hand-pick the best random result over a sea of extremely shitty images. I do a lot of my SD with a fixed seed and 1-image batches, once you know the specific model you are using getting decent pictures isn't hard, and zeroing in on a specific vision is easier with a fixed seed. Once I am happy with it, I might do multiple images without a fixed seed using the final prompt to see if I get something better If you are using a web interface that only use the base SD models and don’t allow negative prompts, yes, its harder (negative prompts and in particular good, model specific, negative embeddings are an SD superpower.)
smusamashah 3y ago
Agree with GPT but with StableDiffusion you are only partially correct. Visit /r/StableDiffusion to see the stuff people are making. People share prompt, seed, model settings etc and you can reproduce the exact same thing. I do agree that it's bad at following the prompt exactly. It will produce most of the things you mentioned in the prompt but not necessarily in the same fashion you asked for. I don't agree that produced images are mostly shitty, just visit that subreddit.
- LewisVerstappen 3y ago
  Uhh, I think you're replying to the wrong person?
  - smusamashah 3y ago
    My bad, I miss clicked somewhere.
- AshamedCaptain 3y ago
  > Agree with GPT but with StableDiffusion you are only partially correct. Visit /r/StableDiffusion to see the stuff people are making. People share prompt, seed, model settings etc and you can reproduce the exact same thing. This doesn't really say anything, because it's just survivor bias. The entire purpose of that site is to show the successes. Most people get disasters every single day, they just don't upload them to the site. Even if I try the same prompt I will get a disaster image, as long as I don't use e.g., exactly the same random seed they happened to use. This is not even "prompt engineering". It's just outright playing with the dice.
  - Sunhold 3y ago
    Why do you think it matters if five out of six images are failures? If the sixth is a success, you have your image. The tool has worked. Glancing over a few failed generations is certainly far less effort than making the image from scratch.
    - 3y ago

AshamedCaptain 3y ago

> okay that’s just because you’re not good at using the models. You literally cannot respond with "you are holding it wrong" specially when I'm claiming that even for the popular _example prompts_ SD authors used they had to hand-pick the best random result over a sea of extremely shitty images. And even in the original paper they disclaim it by saying "oh, our model is just bad at limbs". No, it's not just bad at limbs. They just happened to try examples where it could particularly show how terrible it is at limbs (i.e. spider legged horses and the like). But in truth, it's just bad at everything.

kyleyeats 3y ago
This is like throwing your hammer down in frustration over each nail taking more than one swing.
- ChatGTP 3y ago
  I guess the difference is hammers are logical, simple tools to use with a known use case. They’re fairly hard to use incorrectly, although it does take some practice to use one, I’ll admit.
LewisVerstappen 3y ago
Nope. You literally just tried out one prompt and saw one good image and several bad ones and just shook your fist at the computer and gave up. I'll repeat myself. You have to play around with the models and learn how to use it (just like you have to do for everything) . > But in truth, it's just bad at everything Thousands of people (including myself) have had the complete opposite result and have gotten amazing pictures. You can play around with the finetuning with different models from civitai and get completely different art styles too. Like, this is so dumb I don't even know how to respond lol. You're like some guy who got a computer for the first time and couldn't figure out how to open the web browser, so he just dismissed it as useless.
- AshamedCaptain 3y ago
  I don't think you understand the point. Your claims that "all of this needs extensive tuning and hand-holding and picking results" do not help your argument, they help _mine_. Most egregious if you are even doing more tuning and cherry picking that the authors of the models are doing, which you definitely are.
  - SanderNL 3y ago
    It sounds magic to you because you are unskilled. Like people using the mouse for the first time. The things he talks about are very basic, very easy.
- whateveracct 3y ago
  I would rather just learn to draw than constantly write different text until it looks good Drawing isn't hard, you know
  - sebzim4500 3y ago
    I could spend 20,000 hours trying to learn to draw and I would still be far worse than what I could generate with Stable Diffusion + Control Net + etc.
    - whateveracct 3y ago
      I'm fairly sure if you can best stable diffusion after 7 years of daily 8h investment into drawing :)
      - johnnyyyy 3y ago
        I doubt you would be better than someone who would use Stable Diffusion for 7 years. and I don’t even include the technological advancements in the next 7 years.
        3y ago
cubefox 3y ago
"It's bad at everything" ... bad by what standards? Just a few years ago it would have been regarded as unbelievable science fiction that a model with such capabilities would soon be available. As soon as they are here, people stop being impressed. But the objective impressiveness of a technology is determined by how unlikely it was regarded in the past, not by how impressed people are now. People get used to things pretty quickly. Besides, there are models that are much more capable than Stable Diffusion. The best one currently seems to be Midjourney V5.
- wizzwizz4 3y ago
  > Just a few years ago it would have been regarded as unbelievable science fiction that a model with such capabilities would soon be available. No, it wouldn't have – not to people in the know. We just didn't have powerful enough computers back in the 90s. Sure, the techniques we've got now are better, but 90s algorithms (with modern supercomputers) can get you most of the way. Transformers are awesome, but they're not that much of a stretch from 90s technology. GANs are… ridiculously obvious, in hindsight, and people have been doing similar things since the dawn of AI; I imagine the people who came up with the idea were pretty confident of its capabilities even before they tested them. Both these kinds of system – and neural-net-based systems in general – are based around mimicry. Their inability to draw limbs, or to tell the truth, or count, are fundamental to how they function, and iterative improvement isn't going to fix them. Iterative improvement would be going faster, if researchers (outside of OpenAI and similar corporations) thought it was worthwhile to focus on improving these systems specifically. ChatGPT is not where transformers shine. StyleGAN3 is not where GANs shine. Midjourney is not where diffusion models shine. They're really useful lenses for visualising the way the architectures work, so they are useful test-beds for iterative algorithmic improvements…¹ but they aren't all that they're made out to be. ¹: See the 3 in StyleGAN3. Unlike the 4 in GPT-4, it actually means something more than "we made it bigger and changed the training data a bit".
  - cubefox 3y ago
    > No, it wouldn't have – not to people in the know. We just didn't have powerful enough computers back in the 90s. I'm not talking about the 90s. I'm talking about April 29, 2020.
dragonwriter 3y ago
> You literally cannot respond with "you are holding it wrong" specially when I'm claiming that even for the popular _example prompts_ SD authors used they had to hand-pick the best random result over a sea of extremely shitty images. I do a lot of my SD with a fixed seed and 1-image batches, once you know the specific model you are using getting decent pictures isn't hard, and zeroing in on a specific vision is easier with a fixed seed. Once I am happy with it, I might do multiple images without a fixed seed using the final prompt to see if I get something better If you are using a web interface that only use the base SD models and don’t allow negative prompts, yes, its harder (negative prompts and in particular good, model specific, negative embeddings are an SD superpower.)

smusamashah 3y ago

Agree with GPT but with StableDiffusion you are only partially correct. Visit /r/StableDiffusion to see the stuff people are making. People share prompt, seed, model settings etc and you can reproduce the exact same thing. I do agree that it's bad at following the prompt exactly. It will produce most of the things you mentioned in the prompt but not necessarily in the same fashion you asked for. I don't agree that produced images are mostly shitty, just visit that subreddit.

LewisVerstappen 3y ago
Uhh, I think you're replying to the wrong person?
- smusamashah 3y ago
  My bad, I miss clicked somewhere.
AshamedCaptain 3y ago
> Agree with GPT but with StableDiffusion you are only partially correct. Visit /r/StableDiffusion to see the stuff people are making. People share prompt, seed, model settings etc and you can reproduce the exact same thing. This doesn't really say anything, because it's just survivor bias. The entire purpose of that site is to show the successes. Most people get disasters every single day, they just don't upload them to the site. Even if I try the same prompt I will get a disaster image, as long as I don't use e.g., exactly the same random seed they happened to use. This is not even "prompt engineering". It's just outright playing with the dice.
- Sunhold 3y ago
  Why do you think it matters if five out of six images are failures? If the sixth is a success, you have your image. The tool has worked. Glancing over a few failed generations is certainly far less effort than making the image from scratch.
  - 3y ago