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Dall-E 2

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Re: Dall-E 2

#361

Post by refulgentis »

learndeeply wrote: post #346
refulgentis wrote: post #301

Earlier quoted context omitted.

Katherine Crawson is @ Eletheur & IMHO is indisputably most responsible for the advances in text=>image generation. Dall-E 2 is Dall-E and her insight to use diffusion, the intermediate proof of concept of diffusion + Dall-E is GLIDE. https://twitter.com/RiversHaveWings & https://github.com/crowsonkb

Diffusion models existed long before this announcement. I have no idea who this person is, but they did not invent this idea. Edit: Diffusion models guided by CLIP*

They did invent the idea of applying it to image generation, leading to OpenAI citing her _tweets_ (how cool is that?) in a paper for GLIDE, which as other comments note, looks just like a proof of concept of DallE-2.

Re: Dall-E 2

#362

Post by YeGoblynQueenne »

minimaxir wrote: post #122

A few comments by someone who's spent way too much time in the AI-generated space: * I recommend reading the Risks and Limitations section that came with it because it's very through: https://github.com/openai/dalle-2-preview/blob/main/system-c... * Unlike GPT-3, my read of this announcement is that OpenAI does not intend to commercialize it, and that access to the waitlist is indeed more for testing its limits (and…

Regarding cherry-picking, the images of astronauts on horses look stunning, except for their hands. There's something seriously wrong with their hands.

Maybe give it another five years, a few more $billion and a few more petabytes/flops and it will be good. Then finally everyone can generate art for their own Magic: the Gathering cards.

(That's the end goal, right?)

Re: Dall-E 2

#363

Post by astrange »

Imnimo wrote: post #337
krick wrote: post #316

Earlier quoted context omitted.

While the whole narrative of your comment totally makes sense, I don't really see the difference between the two approaches, not on a conceptual level. You still needed to train this so called "prior" at some point (so, I'm also not sure if it's fair to call it a "prior"). I mean, the difference between your two descriptions seems to be the difference between descriptions (i.e., how you chose to name individual parts…

Yeah, my comment didn't really do a good job of making clear that distinction. Obviously the details are pretty technical, but maybe I can give a high-level explanation. The previous systems I was talking about work something like this: "Try to find me the image the looks like it most matches 'a picture of a sunset'. Do this by repeatedly updating your image to make it look more and more like a sunset." Well, what lo…

A bit more detail is that CLIP isn't designed to directly solve "is this a bear" aka "does this image match 'bear'". It's designed to do comparisons, like "which of images A and B is more like 'bear'". So it doesn't have a concept of absolute bear-ness.

OpenAI had no idea it could be used to generate images itself, which is why they left in issues like how it thinks an apple and the word "apple" written on a piece of paper are the same thing. Probably wouldn't have released it if they did know.

Re: Dall-E 2

#364

Post by gwillen »

recuter wrote: post #342
ricardobeat wrote: post #336

Earlier quoted context omitted.

That's not how this works. There is no 'search' step, there is no 'superimposing' step. It's not really possible to explain what the AI is doing using these concepts. If you pay attention to all the corgi examples, the sofa texture changes in each of them, and it synthesizes shadows in the right orientation - that's what it's trained to do. The first one actually does give you the impression of weight. And if you loo…

How do you propose we talk about what it is doing if not by using the terminology from the human editing process it is replacing? I'm struggling to express things. My issue is that it appears to not be possible to explain what the AI is doing at all. If you could, you'd be able to actually control the output. And talking about how the model is trained is interesting but not an answer. Of course there is a superimposi…

> Of course there is a superimposing step, that just means it adds its layer on top of the photo you provide. That's all it means and that's literally what it is doing, that's all I tried to say, heh.

It is not doing this. You are wrong. You are mistaken. You are confused. You do not understand what is happening.

(People have tried to tell you this several times, but you're not listening. shrug One more can't hurt.)

Re: Dall-E 2

#365

Post by gitfan86 »

falcor84 wrote: post #246

>We’ve limited the ability for DALL·E 2 to generate ... adult images. I think that using something like this for porn could potentially offer the biggest benefit to society. So much has been said about how this industry exploits young and vulnerable models. Cheap autogenerated images (and in the future videos) would pretty much remove the demand for human models and eliminate the related suffering, no? EDIT: typo

When you combine advanced versions of this with advanced versions of GTP-3 you will not be able to tell the difference between AI and only fans.

I'm not saying that AI will pass all Turing tests. But as far as having a virtual girlfriend/prostitute.

Re: Dall-E 2

#366

Post by stubish »

bufferoverflow wrote: post #145
fbanon wrote: post #10

A friend of mine was studying graphic design, but became disillusioned and decided to switch to frontend programming after he graduated. His thesis advisor said he should be cautious, because automation/AI will soon take the jobs of programmers, implying that graphic design is a safer bet in this regard. Looks like his advisor is a few years from being proven horribly wrong.

If this paper presents this neural net fairly, it pretty much destroys the market of illustrators. Most of the time when an illustration needed, it's described like "an astronaut on a horse in the style xyz".

I'd argue that the market has already been destroyed at this point, at least in some areas. Book covers seem to have been stock image overlaid with text for a long time now, and a race to the bottom for both the people producing the stock images and the intern adding typography. By cutting costs and quality, the bar has been lowered to the point the task can be completely automated. Our AI overlords already have an advantage in that they have time to actually read the book, a potentially useful input. Maybe they won't even need the prompt - just generate an image for what is happening in the story for interesting looking paragraphs and let the author or editor pick. Given the cost cutting in publishing generally, editors will be next followed by the publishing houses themselves as the value they add gets lowered while the automation at Amazon gets better.

Re: Dall-E 2

#367

Post by Fernicia »

aliakhtar wrote: post #349
kromem wrote: post #338

Earlier quoted context omitted.

I don't think it's necessarily certain villainy for those who fight that fight as long as they are fighting it correctly. There's a huge case to be made that flooding the darknet with AI generated CP reduces the revictimization of those in authentic CP images, and would cut down on the motivating factors to produce authentic CP (for which original production is often a requirement to join CP distribution rings). As w…

How do you suppose your CP generator will be trained without using authentic CP images? Not only will that require revictimization but you’ll also be downloading CP to train the model.

Did they need to put possums in space suits to tell Dell-E 2 how to render them?

Re: Dall-E 2

#368

Post by astrange »

Imnimo wrote: post #99
duxup wrote: post #82

Earlier quoted context omitted.

This isn't something I'm knowledgeable on so forgive my simplification but is this like a sort of micro services for AI. Each AI takes their turn handing some aspect, another sort of mediates among them?

I'd say Dall-E 2 is a little more unified - they do have multiple networks, but they're trained to work together. The previous approaches I was talking about are a lot more like the microservices analogy. Someone published a model (called CLIP) that can say "how much does this image look like a sunset". Someone else published a totally different model (e.g. VQGAN) that can generate images (but with no way to provide…

VQGAN (being a "GAN") is already two networks - one Generates things, and the other is Adversarial and judges if the other network is good enough, then you train them both at once and they fight.

CLIP+VQGAN generation IIRC works by replacing the adversarial network with CLIP, so it understands text prompts, then retraining it for a while towards the prompted target, then generating whatever it's learned from that.

GANs are a silly idea that shouldn't work but somehow do. There's some attempts to replace the idea: https://www.microsoft.com/en-us/research/blog/unlocking-new-...

Re: Dall-E 2

#369

Post by uoaei »

sneak wrote: post #360
uoaei wrote: post #353

Earlier quoted context omitted.

No. If people are exposed to stimuli, they will pursue increasingly stimulating versions of it. I.e., if they see artificial CP, they will often begin to become desensitized (habituated) and pursue real CP or even live children thereafter. Conversely, if people are not exposed to certain stimuli, they will never be able to conceptualize them, and thus will be unable to think about them. Obviously you cannot eliminate…

> If people are exposed to stimuli, they will pursue increasingly stimulating versions of it. I.e., if they see artificial CP, they will often begin to become desensitized (habituated) and pursue real CP or even live children thereafter. I have accumulated tens of thousands of headshots in video games but have yet to ever shoot a single real person in the face. More importantly, I have never had the urge to seek out…

The point is more "can you conceive of a headshot before you've ever witnessed one?" And the assertion is, no.

I should be explicit -- I am saying the exposure which makes one seek stimulus is merely a catalyst for deeper urges, not a generator of them as such. A certain level of inhibition (e.g. sociopathy) is required but IMO so is a prior conception of the deed.

In your example, if someone is predisposed to wanting to shoot actual people in the head, exposing them to video game headshots may distract in the short term but desensitizes and entrenches the image in the long term, possibly making it easier to decide to pull the trigger later on if they are sufficiently inhibited of social concerns. This does not happen for people with high inhibitions, or at least sufficient self-control.

Re: Dall-E 2

#370

Post by aya96 »

Do you think some of these techniques could be slightly modified, and applied to DNA sequences?
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