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Stable Diffusion 2.0

stability.ai

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Re: Stable Diffusion 2.0

#181

Post by fsloth »

tamersalama wrote: post #107
LASR wrote: post #27

I am a solo dev working on a creative content creation app to leverage the latest developments in AI. Demoing even the v1 of stable diffusion to the non-technical general users blows them away completely. Now that v2 is here, it’s clear we’re not able to keep pace in developing products to take advantage of it. The general public still is blown away by autosuggest in mobile OS keyboards. Very few really know how far…

I agree that this a big wave, but I'm still struggling to find commercial (read: large organizations) applications.

I guess you need to look at the current TAM for visual production in general. That's the baseline (so includes visualization studios, agencies, game studios etc). Generally this potentially can help in many labour intensive parts of a creative visual process.

Is that a "large" organization market or not depends on your metric and what the market positioning of the offering is. I would see applications in both specialist content creation tools as well as "stock photos and merch".

In terms of finding stock photos, if you add a better text api that is easier to control this probably can compete with static stock photos in the sense that people can tune their images as much as they like. For example with their corporate merch (Imagine producing a slideset at Acme co. "Please give me an elephant and walrus wearing acme caps".

Ad agencies already love that they can train a model to quickly iterate product shot ideas extremely rapidly.

Then we have "the usual" effect automation has on market demand - automation increases the productivity of a task requiring labour, hence allowing to reduce the cost of a unit of production, which generally increases the demand. I.e. creative stuff will be cheaper to do, you won't replace artists, but suddenly the dude or dudette who spent hours just tweaking stuff has their own art studio at finger tips to command. They can get so much more done much faster.

The tech is not 100% bullet proof yet but at this pace it will be good enough soon (or probably is for several applications if there was just an UX sugaring targeting specific domain workflow).

Re: Stable Diffusion 2.0

#182

Post by visarga »

wokwokwok wrote: post #175
ftufek wrote: post #81

Earlier quoted context omitted.

To put things in perspective, the dataset it's trained on is ~240TB and Stability has over ~4000 Nvidia A100 (which is much faster than a 1080ti). Without those ingredients, you're highly unlikely to get a model that's worth using (it'll produce mostly useless outputs). That argument also makes little sense when you consider that the model is a couple gigabytes itself, it can't memorize 240TB of data, so it "learned"…

Quite right, but… > That argument also makes little sense when you consider that the model is a couple gigabytes itself, it can't memorize 240TB of data, so it "learned". The matter is really very nuanced and trivialising it that way is unhelpful. If I recompress 240TB as super low quality jpgs and manage to zip them up as single file that is significantly smaller than 240TB (because you can), does the fact they are…

> The matter is really very nuanced and trivialising it that way is unhelpful.

Harping about copyrights in the Age of Diffusion Models is unhelpful (for artists) like protesting against a tsunami. It's time to move up the ladder.

ML engineers have a similar predicament - GPT-3 like models can solve at first try, without specialised training, tasks that took a whole team a few years of work. Who dares still use LSTMs now like it's 2017? Moving up the ladder, learning to prompt and fine-tune ready made models is the only solution for ML eng.

The reckoning is coming for programmers and for writers as well. Even scientific papers can be generated by LLMs now - see the Galactica scandal where some detractors said it will empower people to write fake papers. It also has the best ability to generate appropriate citations.

The conclusion is that we need to give up some of the human-only tasks and hop on the new train.

Re: Stable Diffusion 2.0

#183

Post by PartiallyTyped »

fastball wrote: post #76
kmeisthax wrote: post #45

Earlier quoted context omitted.

The main reason why Stable Diffusion is worried about NSFW is that people will use it to generate disgusting amounts of CSAM. If LAION-5B or OpenAI's CLIP have ever seen CSAM - and given how these datasets are literally just scraped off the Internet, they have - then they're technically distributing it. Imagine the "AI is just copying bits of other people's art" argument, except instead of statutory damages of up to…

Is artificially generated CSAM that doesn't actually involve children in its production not an improvement over the status quo?

Reminds me of flooding a market with fake rhino horn. Idk whether it worked though.

Re: Stable Diffusion 2.0

#184

Post by PartiallyTyped »

sroussey wrote: post #118
braingenious wrote: post #72

Earlier quoted context omitted.

LMFAO What do you propose? The FBI releases a CSAM data set for devs to use for “training”? Would you be the one to create the model? Would you run a business that sells synthetic CSAM?

Well, Microsoft and others have this model for recognizing CSAM, trained on those CSAM images.

Apple, and meta have as well.

Apparently Facebook has a huge problem with distribution through messenger.

Re: Stable Diffusion 2.0

#185

Post by satvikpendem »

GaryPalmer wrote: post #173
satvikpendem wrote: post #12

Earlier quoted context omitted.

They reportedly did so to stop people from generating CSAM [0]. [0] https://old.reddit.com/r/StableDiffusion/comments/y9ga5s/sta...

What is the point of making it "as hard as possible" for people? This not a game release. It doesn't matter if it's cracked tommorow or in a year. On open source no less, it's going to happen sooner rather than later. As disgusting as it is but somebody is going to feed CP to an A.I. Model and that's just the reality of it. It's just going to happen one way or another and it's not any of these A.I. Companies fault.

Plausible deniability for governments. It's like DRM for Netflix-like streaming platforms. If they don't add DRM and their content owners' content gets pirated, they could argued in court that Netflix didn't do everything in their power to stop such piracy. So too here for Stability AI, they've said this is their reasoning before.

Re: Stable Diffusion 2.0

#187

Post by fragmede »

the_shivers wrote: post #169
joshspankit wrote: post #68

Earlier quoted context omitted.

Porn has driven many tech advances. I predict that models trained on specific porn genres will appear as soon as training a good model is doable for under $5000. They’ll get here much quicker if we get video to that mark first.

What tech advances would those be?

print magazine, cinema, VHS, Internet

Re: Stable Diffusion 2.0

#188

Post by josephcsible »

charcircuit wrote: post #87

I dislike how they call their model open source even though there are restrictions on how you can use the model. The ability to use code however you want and not have to worry about if all the code you are using is compatible with your use case is a key part of open source.

I don't know why you're being downvoted. The model's license is unambiguously noncompliant with the Open Source Definition, yet they falsely claim it to be open source anyway. That's just as misleading as calling a product full of HFCS "sugar free" and saying it's okay because by "sugar", you just mean cane sugar.

Re: Stable Diffusion 2.0

#189

Post by Bilal_io »

iosjunkie wrote: post #138
coldblues wrote: post #137

I just thought about this, so bare in mind that I don't know much of the technical implications of this, but: Couldn't we train a very good model by distributing the dataset along with the computing power using something similar to folding@home?

stop trying to build skynet

Can't stop something that's already finished.

- Skynet

Re: Stable Diffusion 2.0

#190

Post by fragmede »

xnyan wrote: post #66
dougmwne wrote: post #62

Earlier quoted context omitted.

Are you kidding? Many times corporate decisions are being made effectively at random. Thinking that the average company operates with a 999 batting average is a total fantasy.

When our c suite decides on an ad campaign and tells our artists to draw normal humans, those people have 3 legs or upside down teeth exactly 0% of the time. Humans have many many limitations, but with every model I’ve tested there’s a set of errors that would virtually never be made by any human.

I agree. Cars break down and crash, they'll never replace horses.
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