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Imagen, a text-to-image diffusion model

gweb-research-imagen.appspot.com

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Re: Imagen, a text-to-image diffusion model

#101

Post by jayd16 »

rvnx wrote: post #62
ceejayoz wrote: post #40

Earlier quoted context omitted.

"Reality" as defined by the available training set isn't necessarily reality. For example, Google's image search results pre-tweaking had some interesting thoughts on what constitutes a professional hairstyle, and that searches for "men" and "women" should only return light-skinned people: https://www.theguardian.com/technology/2016/apr/08/does-goog... Does that reflect reality? No. (I suspect there are also mostly u…

If your query was about hairstyle, why do you even look or care about the skin color ? Nowhere there is any precision for a preferred skin color in the query of th user. So it sorts and gives the most average examples based on the examples that were found on the internet. Essentially answering the query "SELECT * FROM `non-professional hairstyles` ORDER BY score DESC LIMIT 10". It's like if you search on Google "best…

The results are not inherently neutral because the database is from non-neutral input.

It's a simple case of sample bias.

Re: Imagen, a text-to-image diffusion model

#102

Post by swayvil »

daenz wrote: post #7

>While we leave an in-depth empirical analysis of social and cultural biases to future work, our small scale internal assessments reveal several limitations that guide our decision not to release our model at this time. Some of the reasoning: >Preliminary assessment also suggests Imagen encodes several social biases and stereotypes, including an overall bias towards generating images of people with lighter skin tones…

it isn't woke enough. Lol.

Re: Imagen, a text-to-image diffusion model

#103

Post by rvnx »

ceejayoz wrote: post #67
rvnx wrote: post #62

Earlier quoted context omitted.

If your query was about hairstyle, why do you even look or care about the skin color ? Nowhere there is any precision for a preferred skin color in the query of th user. So it sorts and gives the most average examples based on the examples that were found on the internet. Essentially answering the query "SELECT * FROM `non-professional hairstyles` ORDER BY score DESC LIMIT 10". It's like if you search on Google "best…

> The algorithm is just ranking the top "non-professional hairstyle" in the most neutral way in its database You're telling me those are all the most non-professional hairstyles available? That this is a reasonable assessment? That fairly standard, well-kept, work-appropriate curly black hair is roughly equivalent to the pink-haired, three-foot-wide hairstyle that's one of the only white people in the "unprofessional…

I'm saying that the dataset needs to be expanded to cover the most examples possible.

Work a lot on adding even more examples, in order to make the algorithms as close as possible to the "average reality".

At some point we may even ultimately reach the state that the robots even collect intelligence directly in the real world, and not on the internet (even closer to reality).

Censoring results sounds the best recipe for a dystopian world where only one view is right.

Re: Imagen, a text-to-image diffusion model

#104

Post by [deleted] »

ceeplusplus wrote: post #46
ceejayoz wrote: post #40

Earlier quoted context omitted.

"Reality" as defined by the available training set isn't necessarily reality. For example, Google's image search results pre-tweaking had some interesting thoughts on what constitutes a professional hairstyle, and that searches for "men" and "women" should only return light-skinned people: https://www.theguardian.com/technology/2016/apr/08/does-goog... Does that reflect reality? No. (I suspect there are also mostly u…

The reality is that hair styles on the left side of the image in the article are widely considered unprofessional in today's workplaces. That may seem egregiously wrong to you, but it is a truth of American and European society today. Should it be Google's job to rewrite reality?

[deleted]

Re: Imagen, a text-to-image diffusion model

#105

Post by jonny_eh »

ml_basics wrote: post #45

Why is this seemingly official Google blog post on this random non-Google domain?

appspot.com is the domain that hosts all App Engine apps (at least those that don't use a custom domain). It's kind of like Heroku and has been around for at least a decade.

https://cloud.google.com/appengine

Re: Imagen, a text-to-image diffusion model

#108

Post by aaaaaaaaaaab »

sydthrowaway wrote: post #9
james-redwood wrote: post #6

Metacalculus, a mass forecasting site, has steadily brought forward the prediction date for a weakly general AI. Jaw-dropping advances like this, only increase my confidence in this prediction. "The future is now, old man." https://www.metaculus.com/questions/3479/date-weakly-general...

How can we prepare for this? This will result in mass social unrest.

Stock up on guns, ammo, cigarettes, water filters, canned food, and toilet paper.

Re: Imagen, a text-to-image diffusion model

#109

Post by jimmygrapes »

daenz wrote: post #7

>While we leave an in-depth empirical analysis of social and cultural biases to future work, our small scale internal assessments reveal several limitations that guide our decision not to release our model at this time. Some of the reasoning: >Preliminary assessment also suggests Imagen encodes several social biases and stereotypes, including an overall bias towards generating images of people with lighter skin tones…

Are "Western gender stereotypes" significantly different than non-Western gender stereotypes? I can't tell if that means it counts a chubby stubble-covered man with a lip piercing, greasy and dyed long hair, wearing an overly frilly dress as a DnD player/metal-head or as a "woman" or not (yes I know I'm being uncharitable and potentially "bigoted" but if you saw my Tinder/Bumble suggestions and friend groups you'd know I'm not exaggerating for either category). I really can't tell what stereotypes are referred to here.
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