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Stable Diffusion 2.0

stability.ai

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Re: Stable Diffusion 2.0

#211

Post by CamperBob2 »

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…

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 not pixel perfect matches for the original images mean you’re not violating copyright?

If you compress them down to two or three bytes each, which is what the process effectively does, then yes, I would argue that we stand to lose a LOT as a technological society by enforcing existing copyright laws on IP that has undergone such an extreme transformation.

Re: Stable Diffusion 2.0

#212

Post by [deleted] »

kmeisthax wrote: post #74
echelon wrote: post #61

Earlier quoted context omitted.

> train this from scratch If you're talking about training from scratch and not fine tuning, that won't be cheap or easy to do. You need thousands upon thousands of dollars of GPU compute [1] and a gigantic data set. I trained something nowhere near the scale of Stable Diffusion on Lambda Labs, and my bill was $14,000. [1] Assuming you rent GPUs hourly, because buying the hardware outright will be prohibitively expen…

I have... ~11TBs of free disk space and a 1080ti. Obviously nowhere close to being able to crunch all of Wikimedia Commons, but I'm also not trying to beat Stability AI at their own game. I just want to move the arguments people have about art generators beyond "this is unethical copyright laundering" and "the model is taking reference just like a real human".

[deleted]

Re: Stable Diffusion 2.0

#213

Post by sendfoods »

ftufek wrote: post #134
prawn wrote: post #131

Hopefully related: If I'm a photographer wanting to improve resolution of my content for printing, what's my current best bet for upscaling? Is it realistic to make use of this on the command line, feeding it my own images? Or has someone wrapped it in an app or online service?

You're probably better of using Real-ESRGAN: https://github.com/xinntao/Real-ESRGAN . It's pretty solid and fast, even has portable executables you can just use as is. The upscaler that comes with stable diffusion might work for you, but I suspect it'll probably do a better job at upscaling stable diffusion output rather than a natural images (might be wrong though).

Not sure about your last claim. The example given in the blog post looks very very close to a natural image.

Re: Stable Diffusion 2.0

#214

Post by TaylorAlexander »

ftufek wrote: post #134
prawn wrote: post #131

Hopefully related: If I'm a photographer wanting to improve resolution of my content for printing, what's my current best bet for upscaling? Is it realistic to make use of this on the command line, feeding it my own images? Or has someone wrapped it in an app or online service?

You're probably better of using Real-ESRGAN: https://github.com/xinntao/Real-ESRGAN . It's pretty solid and fast, even has portable executables you can just use as is. The upscaler that comes with stable diffusion might work for you, but I suspect it'll probably do a better job at upscaling stable diffusion output rather than a natural images (might be wrong though).

I tried this on one of my home images. I have a nice canon pro 100 printer that can print 13”x19” pictures, and my camera is a 20 megapixel Panasonic GH-5. The printer can print much higher resolution than my camera. So I did take one of my photos and process it with Real-ESRGAN to double the resolution (in each direction, so 4x pixels). The photo is a red barn with redwood trees behind it. It did well increasing the resolution of the barn. It made it look more crisp and bright. But there is an area with some trees in shadow behind the barn, and it lost detail there.

Anyway I think it would be fun to play with, just depends on the content of the image and the artists preferences. I still haven’t printed a full page of the upscaled photo but I do want to try that and see how it looks in comparison!

Re: Stable Diffusion 2.0

#215

Post by [deleted] »

LASR wrote: post #128
hackernewds wrote: post #53

Earlier quoted context omitted.

Strongly believe selection bias among the folks you're getting this impression from. The avg user is not our circle.

This is exactly it. Honestly I was quite surprised at how regular people are impressed by this tech. I was also surprised by how little regular people are aware of this tech even existing. We, on hackernews, on a thread about Stable Diffusion, are of course not too unimpressed. But that’s not the vast majority of people.

[deleted]

Re: Stable Diffusion 2.0

#216

Post by rcoveson »

nbzso wrote: post #204

The crimes against the creative people are getting better and better. What a time to live, when your entire career burns to dust just because. I hope AI gets these programmers jobs soon. Then we all can go to the woods and have a good life, finally.

You hope that AI gets the jobs of AI programmers soon? I urge you to reconsider the implications of that.

Re: Stable Diffusion 2.0

#217

Post by wmwragg »

ftufek wrote: post #81
kmeisthax wrote: post #74

Earlier quoted context omitted.

I have... ~11TBs of free disk space and a 1080ti. Obviously nowhere close to being able to crunch all of Wikimedia Commons, but I'm also not trying to beat Stability AI at their own game. I just want to move the arguments people have about art generators beyond "this is unethical copyright laundering" and "the model is taking reference just like a real human".

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"…

Well that would be ~4000 people each with an Nvidia A100 equivalent, or more with less, this would be an open effort after all. Something similar to folding@home could be used. Obviously the software for that would need to be written, but I don't think the idea is unlikely. The power of the commons shouldn't be underestimated.

Re: Stable Diffusion 2.0

#218

Post by s1k3s »

this_is_not_you wrote: post #210
s1k3s wrote: post #203

Is there any place where we can learn more about all these AI tools that keep popping up, that is not marketing speak? Also, I see the words 'open' and 'open source' and yet they all require me to sign up to some service, join some beta program, buy credits etc. Are they open source?

Did you miss the first part of the article? > It is our pleasure to announce the open-source release of Stable Diffusion Version 2.[0] > The original Stable Diffusion V1 led by CompVis changed the nature of open source AI models and spawned hundreds of other models and innovations all over the world. It had one of the fastest climbs to 10K Github stars of any software, rocketing through 33K stars in less than two mon…

I did. Thank you!

Re: Stable Diffusion 2.0

#219

Post by FPGAhacker »

SkyPuncher wrote: post #49
mberning wrote: post #43

Earlier quoted context omitted.

I don’t know anybody that is blown away by keyboard auto suggest. It’s wrong as often as it is right. Not saying it isn’t useful, but let’s not oversell it.

Lol. Especially the AI version of keyboard auto suggest. Let's take a deterministic algorithm that predictably corrects your typos and build it on AI. It will offer you no benefits, but it will completely destroy the utility since it will never work predictably or accurately.

Auto correct and auto suggest are related but different things.

Suggest puts up options for the next word.

Re: Stable Diffusion 2.0

#220

Post by foobazgt »

fragmede wrote: post #190
xnyan wrote: post #66

Earlier quoted context omitted.

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.

I think this analogy doesn't hold water - horses aren't exactly a beacon of reliability (having owned one).

I've already seen tools that support workflows where you compose art by iteratively generating a piece of it, performing some correction, and repeating. So, I think there's room in the art world for less than perfectly generated art. That said, let's not kid ourselves that the typical failure modality of ML today (99% correct enough, 1% disastrously incorrect) doesn't either cause it to be entirely useless in many applications or end up wreaking havoc on end users in others.

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