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How Imagen Works

assemblyai.com

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Re: How Imagen Works

#61

Post by futureshock »

mortenjorck wrote: post #46
dougmwne wrote: post #33

Earlier quoted context omitted.

I think I can explain this that for most people the whole world is basically magic anyway. They don’t understand any of the details about how any digital tech works so to them they have no framework for which things are impressive and which things are not. The just know that computers can do a great many things that they know nothing about. “Oh I can bank online? Ok.” “Oh, I can have the computer write my book report…

This is the other side of the classic XKCD "Tasks" ( https://xkcd.com/1425/ ). A non-technical person in 2014 (when the above was originally published) would likely have the same conception of the difficulty of recognizing a bird from an image as they would in 2022, even though the task itself has gone from near-insurmountable to off-the-shelf-library in eight years. Even as Imagen and Dall-E 2 amaze us today, these…

Exactly and I was thinking of that XKCD. Very much case in point, I have the Merlin Bird ID app which can determine species from ridiculously blurry photos and can also identify hundreds of birds from their calls alone in noisy environments. In 2014 I would have sworn this would be impossible.

Re: How Imagen Works

#62

Post by tsol »

Uehreka wrote: post #25
joshcryer wrote: post #23

Earlier quoted context omitted.

I've made perhaps overly absolutist statements like "don't you see! this kills artists jobs!" and it was shrugged off as if I was insane. I probably could've phrased it differently, but to me this is game changing in several fields. Granted, it will open up a new field of "generative artists" but, having played with these things, this is a pretty trivial job, and their training nets are only going to get better .

I’ve had a lot of fun playing with Disco Diffusion prompts, but I agree that the people excited about “a generation of prompt artists” are a bit misguided. Soon an AI will emerge that can come up with “better” prompts than you, and the “art” of creating prompts will have a lower skill ceiling.

Like a neutral network just for making prompts that result in aesthetically pleasing Imagen images? And then maybe we can come up with a neutral net that can decide which pictures are good and which aren't. Then we can just have robots making art for the sake of consumption solely by robots.

Re: How Imagen Works

#63

Post by [deleted] »

GrabbinD33ze69 wrote: post #47
dougmwne wrote: post #33

Earlier quoted context omitted.

I think I can explain this that for most people the whole world is basically magic anyway. They don’t understand any of the details about how any digital tech works so to them they have no framework for which things are impressive and which things are not. The just know that computers can do a great many things that they know nothing about. “Oh I can bank online? Ok.” “Oh, I can have the computer write my book report…

A pretty common generalization I've witnessed is many non technical people (even people who are tech savvy but have no CS background do this) is people assuming the feature that is in reality quite difficult to implement won't take much effort, and vice versa.

[deleted]

Re: How Imagen Works

#65

Post by [deleted] »

GrabbinD33ze69 wrote: post #47
dougmwne wrote: post #33

Earlier quoted context omitted.

I think I can explain this that for most people the whole world is basically magic anyway. They don’t understand any of the details about how any digital tech works so to them they have no framework for which things are impressive and which things are not. The just know that computers can do a great many things that they know nothing about. “Oh I can bank online? Ok.” “Oh, I can have the computer write my book report…

A pretty common generalization I've witnessed is many non technical people (even people who are tech savvy but have no CS background do this) is people assuming the feature that is in reality quite difficult to implement won't take much effort, and vice versa.

[deleted]

Re: How Imagen Works

#66

Post by bpiche »

natch wrote: post #53
spullara wrote: post #19

Earlier quoted context omitted.

It is a suitable replica of it. Just isn't trained.

But the training is the thing that would make it suitable.

I mean, you try training this thing without a warehouse full of GPUs… to me, the algorithm is just as interesting as the model. Perhaps more so.

Re: How Imagen Works

#67

Post by [deleted] »

skinner_ wrote: post #29

> The central intuition in using T5 is that extremely large language models, by virtue of their sheer size alone, may still learn useful representations despite the fact that they are not explicitly trained with any text/image task in mind. [...] Therefore, the central question being addressed by this choice is whether or not a massive language model trained on a massive dataset independent of the task of image gener…

[deleted]

Re: How Imagen Works

#68

Post by russdill »

SleekEagle wrote: post #38
russdill wrote: post #28

Earlier quoted context omitted.

The GPT algorithms are actually pretty good at making detailed image generation prompts if you ask it to describe in detail the general idea you want.

Do you have a link to any papers about this? Would love to check them out

No, just playing around with dall-e mini (no access yet to anything else) and beta.openai.com's text-davinci-002 model. For instance, if I ask dall-e mini for "painting with dancers":

https://i.imgur.com/flXoTgZ.png

I can ask davinci-002 "Vivid description of a painting with dancers:" and get:

The painting is of two dancers in a passionate embrace, their bodies entwined as they move together in a sensual dance. The woman's dress is flowing and reveals her curves, while the man's shirt is open, revealing his muscular chest. They are surrounded by a crowd of people who are watching them with looks of admiration and desire. The painting is full of color and movement, and the dancers seem to be in a world of their own, lost in their passion for each other.

And then pass that to dall-e mini:

https://i.imgur.com/eOIQuPF.png

dall-e mini is sadly not quite up to the challenge, but it gives the generation a lot more detail. Some other examples:

"The painting is of two dancers in the middle of a dance. They are both wearing white, and their hair is flowing around them as they move. The background is a blur of color, and the light is shining on the dancers, making them look like they are in the spotlight."

https://i.imgur.com/ldktMHO.png

"The painting is full of energy and movement, with the dancers leaping and spinning around the stage. They are all wearing brightly coloured costumes, which stand out against the dark background. The light from the stage spotlight is shining on them, making them look even more vibrant. The whole scene is full of life and excitement."

https://i.imgur.com/1KFJbzJ.png

Re: How Imagen Works

#69

Post by natch »

bpiche wrote: post #66
natch wrote: post #53

Earlier quoted context omitted.

But the training is the thing that would make it suitable.

I mean, you try training this thing without a warehouse full of GPUs… to me, the algorithm is just as interesting as the model. Perhaps more so.

"This thing" has already been trained. Nobody is saying the algorithm is not interesting. Just that "this thing" has not been released.

Re: How Imagen Works

#70

Post by mapt »

spullara wrote: post #19
refulgentis wrote: post #16

Earlier quoted context omitted.

No, something that's been causing a lotta confusion in AI art is people stand up quick implementations generally matching the general description in the paper, but, they're not really investing in training them. Then people see "imagen-pytorch" on GitHub and get confused, either think it's Imagen itself or a suitable replica of it. There's like 3 projects named DallE, and then the 2 real DallEs...frustrating.

It is a suitable replica of it. Just isn't trained.

"I gave you an open implementation of NAND and NOR gates. That's the core of this groundbreaking CPU. Just finish the job!"
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