There was a good example somewhere I can’t find, but of a really complex prompt that Dalle could understand, but SD couldn’t. Maybe some of the GPT-3 is being leveraged for parsing. Anyways I think it’s way too early to start taking sides. I enjoy using all these system.
One of SDs big limitations (understanding from what I had read about it) is positional prompts. dall-e seems to understand x on top of Y, but simple diffusion does not.
Doesnt seem to get IN examples either. E.g. a prompt like 'an eagle holding a snake in its beak' ends up generating eagle snake hybrid creatures.
That’s not what a race to the bottom is. It’s just competition, which is usually good.
It often feels like words are losing their meaning, with everyone misusing terms they don't fully understand. I don't want to be a doomer and have have surely unknowingly misused terms as well, but its definitely noticable how these originally clearly defined terms are getting used in entirely new ways. And it's not just with technical terms like this, it also applies to originally obvious terms such as racism, sexis…
Also, the use of "unironically". What is going on there.
Do you know the best Google Colab tutorial / repo?
Hi, there are a couple of good UIs. https://github.com/cmdr2/stable-diffusion-ui is an easy-to-install and use tool, written by me (with contributions by many). Version 2 is in beta, which is a 1-click installer for Windows, no dependencies or command line needed. v2 beta: https://github.com/cmdr2/stable-diffusion-ui/tree/v2 https://github.com/hlky/stable-diffusion is another popular and good tool.
I'm impressed how fast this is getting adopted. Dozens of repos have popped up.
sama is very active in YC and makes the call on OpenAI product roadmap. Furthermore YC encourages good CEO-community relations. The fact that OpenAI is so far behind Stable Diffusion and has reduced pricing shows that sama wants OpenAI to be a highly profitable enterprise company. I.e. not “Open.” You can do both (e.g. Cloudera) but clearly sama is not strong enough at AI to make this happen.
> sama is very active in YC and makes the call on OpenAI product roadmap. Furthermore YC encourages good CEO-community relations Sam hasn't been at YC in years and (based on anything I've seen) isn't active in YC at all. As for "YC encourages good CEO-community relations", I have no idea what that means* but it has nothing to do with HN. We encourage good content -community relations and that's it. You have a long hi…
While I think the fear might be overexaggerated, being able to make realistic fake content with such ease means it's harder to know what's true and what's not. Plus this has been the claim of OpenAI from the beginning. It's possible the true objective is to keep it private to leverage for money and this is just their excuse.
> means it's harder to know what's true and what's not The danger for society is in not already knowing that is the case, since it's relatively trivial, without AI, to make fake content.
Indeed, this talk OpenAI does is basically security through obscurity, and it's holding us back. Look at how often people make noise with screenshots of tweets or emails that never happened. You don't need photorealism or fancy machine learning for that, and it creates a lot of problems! If they weren't pretending that all we need is to put some yellow tape around machine learning, maybe there would be some interest in solving this type of stuff properly. But you don't need "AI" for that. You just need public awareness and some basic, pre-existing cryptography knowledge.
> I can only guess either safety from misuse I still don't understand what this would mean. Where are all of the terrible things that were supposed to happen, now that Stable Diffusion is available? We've been able to create completely photorealistic fiction for decades now. See any movie with CGI for an example of whole worlds, and people, that don't exist. The bar has gradually been lowering (see the amazing CGI th…
While I think the fear might be overexaggerated, being able to make realistic fake content with such ease means it's harder to know what's true and what's not. Plus this has been the claim of OpenAI from the beginning. It's possible the true objective is to keep it private to leverage for money and this is just their excuse.
Meanwhile someone has already built a photoshop plugin for Stable Diffusion that you can use today to do basically the _exact_ same thing: https://old.reddit.com/r/StableDiffusion/comments/wyduk1/sho...
Doesn't make sense to me why OpenAI has kept DALL-E closed source for so long. I can only guess either safety from misuse or leveraging it for money. At this rate though, Stable Diffusion is going to dwarf it
I don't follow this stuff very closely - is there any open-source model for text generation that outclasses GPT-3? Stable Diffusion has been released for barely a week and already seems like the clear winner. It doesn't seem like any of the open (actually open) text models have made as much of a splash.
Of course maybe it's just because text is less visually impressive than images.
A few weeks ago I was skeptical that this technology would get past the emotional response we get from procedurally generated game environments, but I've been convinced otherwise. The emotional response I get from some of the best of these images are novel and thought provoking. Makes me wonder what percent of what makes us human is now algorithmically solved....
We still know basically nothing about our Brain/Consciousness. I would say we have a lot more to explore/research
Our brain is apparently just a 4 gb large arrangement of electrical weights.
Doesn't make sense to me why OpenAI has kept DALL-E closed source for so long. I can only guess either safety from misuse or leveraging it for money. At this rate though, Stable Diffusion is going to dwarf it
I don't follow this stuff very closely - is there any open-source model for text generation that outclasses GPT-3? Stable Diffusion has been released for barely a week and already seems like the clear winner. It doesn't seem like any of the open (actually open) text models have made as much of a splash. Of course maybe it's just because text is less visually impressive than images.
They’re just harder to run on your own resources, since large language models are very large. BLOOM was released a month ago, is likely better than GPT-3 in quality, and requires 8 A100s for inference, which pretty much no one has on their desk.