[HN Gopher] Imagen, a text-to-image diffusion model
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Imagen, a text-to-image diffusion model
Author : keveman
Score : 326 points
Date : 2022-05-23 20:44 UTC (2 hours ago)
(HTM) web link (gweb-research-imagen.appspot.com)
(TXT) w3m dump (gweb-research-imagen.appspot.com)
| endisneigh wrote:
| I give it a few years before Google makes stock images
| irrelevant.
| sydthrowaway wrote:
| Short Getty images?
| tpmx wrote:
| Privately owned by the Getty family.
| tpmx wrote:
| Rolling this into Google Docs seems like a nobrainer.
| ma2rten wrote:
| Google is very conservative about anything that can generate
| open-ended outputs. Also these models are still very
| expensive computationally.
| [deleted]
| semicolon_storm wrote:
| Or rolling this into Google Image Search to create images
| that match users' search queries on the fly.
|
| Don't like any of the results from the real web? Well how
| about these we created just for you.
| riffraff wrote:
| Ah yes, deepfakes porn as a service would have been a
| blessing for teenage me.
| [deleted]
| curiousgal wrote:
| Until they pull of the plug on it.
| makeitdouble wrote:
| I really expect them to first make DALL-E and competing
| networks unfit for commercialization by providing the better
| choice for free, have stock companies cry in the corner, to
| just sunset the product a year or two down the road and we're
| left wandering what to do.
| notahacker wrote:
| Tbh imagine this tech combines particularly well with really
| well curated stock image databases so outputs can be made with
| recognisable styles, and actors and design elements can be
| reused across multiple generated images.
|
| If Getty et al aren't already spending money on that
| possibility, they probably should be.
| pphysch wrote:
| The entire "content" industry could get eaten by a few hundred
| people curating + touching-up output from these models.
| astrange wrote:
| No, competitive advantage means that it's impossible to run
| out of jobs just because someone/something is better at it
| than you.
|
| (Consumer demand and boredom both being infinite is another
| thing working against it.)
| braingenious wrote:
| This is super cool and I want to play with it.
| throwaway743 wrote:
| https://github.com/lucidrains/imagen-pytorch
| armchairhacker wrote:
| Does it do partial image reconstruction like DALL-E2? Where you
| cut out part of an existing image and the neural network can fill
| it back in.
|
| I believe this type of content generation will be the next big
| thing or at least one of them. But people will want some
| customization to make their pictures "unique" and fix AI's lack
| of creativity and other various shortcomings. Plus edit out the
| remaining lapses in logic/object separation (which there are some
| even in the given examples).
|
| Still, being able to create arbitrary stock photos is really
| useful and i bet these will flood small / low-budget projects
| alimov wrote:
| Would it be bad to release this with a big warning and flashing
| gifs letting people know of the issues it has and note that they
| are working to resolve them / ask for feedback / mention
| difficulties related to resolving the issues they identified?
| xnx wrote:
| Facebook really thought they had done something with DALL-E, then
| Google's all "hold my beer".
| dntrkv wrote:
| OpenAI*
| tomatowurst wrote:
| when will there be a "DALL-E for porn" ? or is this domain also
| claimed by Puritans and morality gate keepers? The most in demand
| text-to-image is use case is for porn.
| jonahbenton wrote:
| I know that some monstrous majority of cognitive processing is
| visual, hence the attention these visually creative models are
| rightfully getting, but personally I am much more interested in
| auditory information and would love to see a promptable model for
| music. Was just listening to "Land Down Under" from Men At Work.
| Would love to be able to prompt for another artist I have liked:
| "Tricky playing Land Down Under." I know of various generative
| music projects, going back decades, and would appreciate
| pointers, but as far as I am aware we are still some ways from
| Imagen/Dalle for music?
| astrange wrote:
| I believe we're lacking someone training up a large music model
| here, but GPT-style transformers can produce music.
|
| gwern can maybe comment here.
|
| An actually scary thing is that AIs are getting okay at
| reproducing people's voices.
| addandsubtract wrote:
| I agree. How cool would it be to get an 8 min version of your
| favorite song? Or an instant DnB remix? Or 10 more songs in the
| style of your favorite album?
| jonahbenton wrote:
| Yeah. I particularly love covers and often can hear in my
| head X playing Y's song. Would love tools to experiment with
| that for real.
|
| In practice, my guess is that even though Dall-e level
| performance in music generation would be stunning and
| incredible, it would also be tiresome and predictable to
| consume on any extended basis. I mean- that's my reaction to
| Dall-e- I find the images astonishing and magical but can
| only look at them for limited periods of time. At these early
| stages in this new world the outputs of real individual
| brains are still more interesting.
|
| But having tools like this to facilitate creation and
| inspiration by those brains- would be so so cool.
| hn_throwaway_99 wrote:
| As someone who has a layman's understanding of neural networks,
| and who did some neural network programming ~20 years ago before
| the real explosion of the field, can someone point to some
| resources where I can get a better understanding about how this
| magic works?
|
| I mean, from my perspective, the skill in these (and DALL-E's)
| image reproductions is truly astonishing. Just looking for more
| information about how the software actually works, even if there
| are big chunks of it that are "this is beyond your understanding
| without taking some in-depth courses".
| londons_explore wrote:
| Figure A.4 in the linked paper is a good high level overview of
| this model. Shame it was hidden away on page 19 in the
| appendix!
|
| Each box you see there has a section in the paper explaining it
| in more detail.
| rvnx wrote:
| Check https://github.com/multimodalart/majesty-diffusion
|
| There is a Google Colab workbook that you can try and run for
| free :)
|
| This is the image-text pairs behind:
| https://laion.ai/laion-400-open-dataset/
| astrange wrote:
| > I mean, from my perspective, the skill in these (and
| DALL-E's) image reproductions is truly astonishing.
|
| A basic part of it is that neural networks combine learning and
| memorizing fluidly inside them, and these networks are really
| really big, so they can memorize stuff good.
|
| So when you see it reproduce a Shiba Inu well, don't think of
| it as "the model understands Shiba Inus". Think of it as making
| a collage out of some Shiba Inu clip art it found on the
| internet. You'd do the same if someone asked you to make this
| image.
|
| It's certainly impressive that the lighting and blending are as
| good as they are though.
| FargaColora wrote:
| This looks incredible but I do notice that all the images are of
| a similar theme. Specifically there are no human figures.
| influxmoment wrote:
| I believe DALLE and likely this model excluded images of people
| so it could not be misused
| benwikler wrote:
| Would be fascinated to see the DALL-E output for the same prompts
| as the ones used in this paper. If you've got DALL-E access and
| can try a few, please put links as replies!
| joeycodes wrote:
| Posting a few comparisons here.
|
| https://twitter.com/joeyliaw/status/1528856081476116480?s=21...
| qclibre22 wrote:
| See the paper here : https://gweb-research-
| imagen.appspot.com/paper.pdf Section E : "Comparison to GLIDE
| and DALL-E 2"
| jandrese wrote:
| Is there a way to try this out? DALL-E2 also had amazing demos
| but the limitations became apparent once real people had a chance
| to run their own queries.
| wmfrov wrote:
| Looks like no, "The potential risks of misuse raise concerns
| regarding responsible open-sourcing of code and demos. At this
| time we have decided not to release code or a public demo. In
| future work we will explore a framework for responsible
| externalization that balances the value of external auditing
| with the risks of unrestricted open-access."
| nomel wrote:
| > the risks of unrestricted open-access
|
| What exactly is the risk?
| jimmygrapes wrote:
| A variation on the axiom "you cannot idiot proof something
| because there's always a bigger idiot"
| varenc wrote:
| See section 6 titled "Conclusions, Limitations and Societal
| Impact" in the research paper: https://gweb-research-
| imagen.appspot.com/paper.pdf
|
| One quote:
|
| > "On the other hand, generative methods can be leveraged
| for malicious purposes, including harassment and
| misinformation spread [20], and raise many concerns
| regarding social and cultural exclusion and bias [67, 62,
| 68]"
| userbinator wrote:
| But do we trust that those who _do_ have access won 't be
| using it for "malicious purposes" (which they might not
| think is malicious, but perhaps it is to those who don't
| have access)?
| colinmhayes wrote:
| It's not up to you. It's up to them, and they trust
| themselves/don't care about your definition of malicious.
| jtvjan wrote:
| If the model is used to generate offensive imagery, it may
| result in a negative press response directed at the
| company.
| tpmx wrote:
| _Really_ unpleasant content being produced, obviously.
| marcodiego wrote:
| Ok. Now, how about the legality of it generating socially
| unacceptable images like child porn?
| ma2rten wrote:
| I get the impression that maybe DALL-E 2 produces slightly more
| diverse images? Compare Figure 2 in this paper with Figures 18-20
| in the DALL-E 2 paper.
| faizshah wrote:
| What's the best open source or pre-trained text to image model?
| shannifin wrote:
| Nice to see another company making progress in the area. I'd love
| to see more examples of different artistic styles though, my
| favorite DALL-E images are the ones that look like drawings.
| Mo3 wrote:
| Is the source in public domain already?
| spyremeown wrote:
| Jesus, this is so awesome. I think it's the first AI that really
| makes me have that "wow" sensation.
| fortran77 wrote:
| > At this time we have decided not to release code or a public
| demo.
|
| Oh well.
| SemanticStrengh wrote:
| Does it outperform DALL-E V2?
| dr_dshiv wrote:
| How the fck are things advancing so fast? Is it about to level
| off ...or extend to new domains? What's a comparable set of
| technical advances?
| y04nn wrote:
| Really impressive. If we are able to generate such detailed
| images, is there anything similar for text to music? I would I
| though that it would be simpler to achieve than text to image.
| redox99 wrote:
| Our language is much more effective at describing images than
| music.
| tomatowurst wrote:
| why stop at audio? the pinnacle of this would be text-to-
| videos, equally indistinguishable from real thing.
| burlesona wrote:
| The way things look when still is much easier to fake than
| the way things move.
|
| I would expect AI development to follow a similar path to
| digital media generally, as its following the increasing
| difficulty and space requirements of digitally representing
| said media: text < basic sounds < images < advanced audio <
| video.
|
| What's more impressive to me is how far ahead text-to-speech
| is, but I think the explanation is straightforward (the
| accessibility value has motivated us to work on that for a
| lot longer).
| nomel wrote:
| Compare the size of a raw image file to a raw music file, to
| get an idea of the complexity difference.
| penneyd wrote:
| Think sheet music, not an mp3
| touringa wrote:
| SymphonyNet: https://youtu.be/m4tT5fx_ih8
| colinmhayes wrote:
| I wondered why all the pictures at the top had sunglasses on,
| then I saw a couple with eyes. Still some work to do on this one.
| londons_explore wrote:
| >Figure 2: Non-cherry picked Imagen samples
|
| Hooray! Non-cherry-picked samples should be the norm.
| ml_basics wrote:
| Why is this seemingly official Google blog post on this random
| non-Google domain?
| aidenn0 wrote:
| This is quite suspicious considering that google AI research
| has an official blog[1], and this is not mentioned at all
| there. It seems quite possible that this is an elaborate prank.
|
| 1: https://ai.googleblog.com/
| mmh0000 wrote:
| You mean one of Google's domains? # whois
| appspot.com [Querying whois.verisign-grs.com]
| [Redirected to whois.markmonitor.com] [Querying
| whois.markmonitor.com] [whois.markmonitor.com]
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| jefftk wrote:
| While appspot.com is a Google domain, anyone can register
| domains under it. It would be similarly surprising to see an
| official GitHub blog post under someproject.github.io
| jefftk wrote:
| Fun fact: appspot.com was the second "private" suffix to be
| added to the Public Suffix List, after operaunite.com:
| https://bugzilla.mozilla.org/show_bug.cgi?id=593818
| ma2rten wrote:
| You mean like: https://say-can.github.io/
|
| This is common in the research PA. People don't want to
| deal with broccoli man [1].
|
| [1] https://www.youtube.com/watch?v=3t6L-FlfeaI
| jefftk wrote:
| Looking at that link, I don't think that is a GitHub
| publication? It is marked Robotics at Google and Everyday
| Robotics.
| ma2rten wrote:
| My bad, it's a google-specific problem.
| dekhn wrote:
| I'n not certain but I think it's prelease. The paper says the
| site should be at https://imagen.research.google/ but that host
| doesn't respond
| jonny_eh wrote:
| 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
| jefftk wrote:
| Spring 2008: 14 years!
| jonny_eh wrote:
| Whoa, I feel super old, I first used it in 2011 when I
| thought it was new.
| mshockwave wrote:
| IIRC appspot.com is used by App Engine, one of the earliest
| SaaS platforms provided by Google.
| jeffbee wrote:
| Not just that ... Google Sheets must be the all-time worst way
| to distribute 200 short strings.
| SemanticStrengh wrote:
| Note that there was a close model in 2021 ignored by all
| https://paperswithcode.com/sota/text-to-image-generation-on-...
| (on this benchmark) Also what is the score of dalle v2?
| raldi wrote:
| The opinion in the title takes away a lot more than it adds, and
| I'm not sure I agree with its assertion.
| ShakataGaNai wrote:
| All of these AI findings are cool in theory. But until its
| accessible to some decent amount of people/customers - its
| basically useless fluff.
|
| You can tell me those pictures are generated by an AI and I might
| believe it, but until real people can actually test it... it's
| easy enough to fake. This page isn't even the remotest bit legit
| by the URL, It looks nicely put together and that's about it.
| Could have easily put together this with a graphic designer to
| fake it.
|
| Let be clear, I'm not actually saying it's fake. Just that all of
| these new "cool" things are more or less theoretical if nothing
| is getting released.
| cellis wrote:
| Inference times are key. If it can't be produced within
| reasonable latency, then there will be no real world use case
| for it because it's simply too expensive to run inference at
| scale.
| theptip wrote:
| There are plenty of usecases for generating art/images where
| a latency of days or weeks would be competitive with the
| current state of the art.
|
| For example, corporate graphics design, logos, brand
| photography, etc.
|
| I really do think inference time is a red herring for the
| first generation of these models.
|
| Sure, the more transformative use-cases like real-time
| content generation to replace movies/games, but there is a
| lot of value to be created prior to that point.
| mistrial9 wrote:
| Reading a relatively-recent Machine Learning paper from some
| elite source, and after multiple repititions of bragging and
| puffery, in the middle of the paper, the charts show that they
| had beaten the score of a high-ranking algorithm in their
| specific domain, moving the best consistant result from 86%
| accuracy to 88% accuracy, somewhere around there. My response
| was: they got a lot of attention within their world by beating
| the previous score, no matter how small the improvement was.. it
| was a "winner take all" competition against other teams close to
| them; the accuracy of less than 90% is really of questionable
| value in a lot of real world problems; it was an enormous amount
| of math and effort for this team to make that small improvement.
|
| What I see is semi-poverty mindset among very smart people who
| appear to be treated in a way such that the winners get
| promotion, and everyone else is fired. That this sort of analysis
| with ML is useful for massive data sets at scale, where 90% is a
| lot of accuracy, not at all for the small sets of real world,
| human-scale problems where each result may matter a lot. The
| amount of years of training that these researchers had to go
| through, to participate in this apparently ruthless environment,
| are certainly like a lottery ticket, if you are in fact in a game
| where everyone but the winner has to find a new line of work. I
| think their masters live in Redmond, if I recall.. not looking it
| up at the moment.
| neolander wrote:
| It really does look better than DALL-E, at least from the images
| on the site. Hard to believe how quickly progress is being made
| to lucid dreaming while awake.
| Jyaif wrote:
| Jesus Christ. Unlike DALL-E 2, it gets the details right. It also
| can generate text. The quality is insanely good. This is
| absolutely mental.
| not2b wrote:
| Yes, the posted results are really good, but since we can't
| play with it we don't know how much cherry picking has been
| done.
| addajones wrote:
| This is absolutely amazingly insane. Wow.
| [deleted]
| benreesman wrote:
| I apologize in advance for the elitist-sounding tone. In my
| defense the people I'm calling elite I have nothing to do with,
| I'm certainly not talking about myself.
|
| Without a fairly deep grounding in this stuff it's hard to
| appreciate how far ahead Brain and DM are.
|
| Neither OpenAI nor FAIR _ever has the top score on anything
| unless Google delays publication_. And short of FAIR? D2
| lacrosse. There are exceptions to such a brash generalization,
| NVIDIA's group comes to mind, but it's a very good rule of thumb.
| Or your whole face the next time you are tempted to doze behind
| the wheel of a Tesla.
|
| There are two big reasons for this:
|
| - the talent wants to work with the other talent, and through a
| combination of foresight and deep pockets Google got that
| exponent on their side right around the time NVIDIA cards started
| breaking ImageNet. Winning the Hinton bidding war clinched it.
|
| - the current approach of "how many Falcon Heavy launches worth
| of TPU can I throw at the same basic masked attention with
| residual feedback and a cute Fourier coloring" inherently favors
| deep pockets, and obviously MSFT, sorry OpenAI has that, but deep
| pockets also non-linearly scale outcomes when you've got in-house
| hardware for multiply-mixed precision.
|
| Now clearly we're nowhere close to Maxwell's Demon on this stuff,
| and sooner or later some bright spark is going to break the
| logjam of needing 10-100MM in compute to squeeze a few points out
| of a language benchmark. But the incentives are weird here: who,
| exactly, does it serve for us plebs to be able to train these
| things from scratch?
| davelondon wrote:
| I'M SQUEEZING MY PAPER!
| SemanticStrengh wrote:
| This competitor might be better for respecting spatial
| prepositions and photorealism but on a quick look i find the
| images more uncanny. DALL-E has IMHO better camera POV/distance
| and is able to make artistic/dreamy/beautiful images. I haven't
| yet seen this Google model be competitive for art and uncaniness.
| However progress is great and I might be wrong.
| james-redwood wrote:
| 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...
| sydthrowaway wrote:
| How can we prepare for this?
|
| This will result in mass social unrest.
| aaaaaaaaaaab wrote:
| Stock up on guns, ammo, cigarettes, water filters, canned
| food, and toilet paper.
| boppo1 wrote:
| Nah, learn Spanish and first-aid. Being able to fix people
| is more useful than having commodities that will make you a
| target.
| refulgentis wrote:
| You think so? I'm very high on the Kool-Aid, image generation
| and text transformation models are core parts of my workflow.
| (Midjourney, GPT-3)
|
| It's still an unruly 7 year old at best. Results need to be
| verified. Prompt engineering and a sense of creativity are
| core competencies.
| visarga wrote:
| > Prompt engineering and a sense of creativity are core
| competencies.
|
| It's funny that people are also prompting each other.
| Parents, friends, teachers, doctors, priests, politicians,
| managers and marketers are all prompting (advising) us to
| trigger desired behaviour. Powerful stuff - having a large
| model and knowing how to prompt it.
| [deleted]
| tpmx wrote:
| I don't see how this gets us (much) closer to general AI. Where
| is the reasoning?
| _joel wrote:
| Perhaps the confluence of NLP and something generative?
| SemanticStrengh wrote:
| Yes metaculus mostly bet a magic number based on _perhaps_
| and tbh why not, the interaction of NLP and vision is
| mysterious and has potential. However those magic numbers
| should still be considered magic numbers. I agree that in
| 2040 the interactions will have extensively been studied
| though but the conclusion of wether we czn go much further
| on cross-models synergies is totally unknown or pessimist.
| astrange wrote:
| That doesn't even lead in the direction of an AGI. The
| larger and more expensive a model is the less like an "AGI"
| it is - an independent agent would be able to learn online
| for free, not need millions in TPU credits to learn what
| color an apple is.
| quirino wrote:
| I think this serves at least as a clear demonstration of how
| advanced the current state of AI is. I had played with GPT-3
| and that was very impressive but I couldn't even dream
| something as good as D-ALLE 2 was already possible.
| 6gvONxR4sf7o wrote:
| Big pretrained models are good enough now that we can pipe
| them together in really cool ways and our representations of
| text and images seem to capture what we "mean."
| tpmx wrote:
| Yeah, it _seems_ like it. But it 's still just complicated
| statistical models. Again, where is the reasoning?
| 6gvONxR4sf7o wrote:
| I don't care whether it reasons its way from "3 teddy
| bears below 7 flamingos" to a picture of that or if it
| gets there some other way. But some of the magic in
| having good enough pretrained representations is that you
| don't need to train them further for downstream tasks,
| which means non-differentiable tasks like logic could
| soon become more tenable.
| renewiltord wrote:
| A belief oft shared is that sufficiently complicated
| statistical models are indistinguishable from reasoning.
| marvin wrote:
| I still think we're missing some fundamental insights on
| how layered planning/forecasting/deducting/reasoning
| works, and that figuring this out will be necessary in
| order to create AI that we could say "reasons".
|
| But with the recent advances/demonstrations, it seems
| more likely today than in 2019 that our current
| computational resources are sufficient to perform
| magnificantly spooky stuff if they're used correctly.
| They are doing that already already, and that's without
| deliberately making the software do anything except draw
| from a vast pool of examples.
|
| I think it's reasonable, based on this, to update one's
| expectations of what we'd be able to do if we figured out
| ways of doing things that aren't based on first seeing a
| hundred million examples of what we want the computer to
| do.
|
| Things that do this can obviously exist, we are living
| examples. Does figuring it out seem likely to be many
| decades away?
| londons_explore wrote:
| All it takes is one 'trick' to give these models the
| ability to do reasoning.
|
| Like for example the discovery that language models get
| far better at answering complex questions if asked to
| show their working step by step with chain of thought
| reasoning as in page 19 of the PaLM paper [1]. Worth
| checking out the explanations of novel jokes on page 38
| of the same paper. While it is, like you say, all
| statistics, if it's indistinguishable from valid
| reasoning, then perhaps it doesn't matter.
|
| [1]: https://arxiv.org/pdf/2204.02311.pdf
| davikr wrote:
| Interesting and cool technology - but I can't seem to ignore that
| every high-quality AI art application is always closed, and I
| don't seem to buy the ethics excuse for that. The same was said
| for GPT, yet I see nothing but creativity coming out from its
| users nowadays.
| dougmwne wrote:
| GTP-3 was an erotica virtuoso before it was gagged. There's a
| serious use case here in endless porn generation. Google would
| very much like to not be in that business.
|
| That said, you can download Dream by Wombo from the app store
| and it is one of the top smartphone apps, even though it is a
| few generations behind state of the art.
| LordDragonfang wrote:
| You're _aware_ of nothing but creativity from its users. The
| people using the technology unethically intentionally don 't
| advertise that they're using it.
|
| There's mountains of ai-generated inauthentic content that
| companies ( _including Google_ ) have to filter out of their
| services. This content is used for spam, click farms, scamming,
| and even state propaganda operation. GPT-2 made this problem
| orders of magnitude worse than it used to be, and each
| iteration makes it harder to filter.
|
| The industry term is (generally) "Coordinated Inauthentic
| Behavior" (though this includes uses of actual human content).
| I think Smarter Every Day did a good (series?) of videos on the
| topic, and there are plenty of articles on the topic if you
| prefer that.
| thorum wrote:
| That only lasts until the community copies the paper and
| catches up. For example the open source DALLE-2 implementation
| is coming along great:
| https://github.com/lucidrains/DALLE2-pytorch
| minimaxir wrote:
| Granted that's a selection bias: you likely won't hear about
| the cases where legit obscene output occurs. (the only notable
| case I've heard is the AI Dungeon incident)
| unholiness wrote:
| Certificate is expired, anyone have a mirror?
| minimaxir wrote:
| Generating at 64x64px then upscaling it probably gives the model
| a substantial performance boost (training speed/convergence) than
| working at 256x256 or 1024x1024 like DALL-E 2. Perhaps that
| approach to AI-generated art is the future.
| daenz wrote:
| >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 and a
| tendency for images portraying different professions to align
| with Western gender stereotypes. Finally, even when we focus
| generations away from people, our preliminary analysis indicates
| Imagen encodes a range of social and cultural biases when
| generating images of activities, events, and objects. We aim to
| make progress on several of these open challenges and limitations
| in future work.
|
| Really sad that breakthrough technologies are going to be
| withheld due to our inability to cope with the results.
| joshcryer wrote:
| They're withholding the API, code, and trained data because
| they don't want it to affect their corporate image. The good
| thing is they released their paper which will allow easy
| reproduction.
|
| T5-XXL looks on par with CLIP so we may not see an open source
| version of T5 for a bit (LAION is working on reproducing CLIP),
| but this is all progress.
| minimaxir wrote:
| T5 was open-sourced on release (up to 11B params):
| https://github.com/google-research/text-to-text-transfer-
| tra...
|
| It is also available via Hugging Face transformers.
|
| However, the paper mentions T5-XXL is 4.6B, which doesn't fit
| any of the checkpoints above, so I'm confused.
| riffraff wrote:
| This seems bullshit to me, considering Google translate and
| google images encode the same biases and stereotypes, and are
| widely available.
| nomel wrote:
| Aren't those old systems?
| seaman1921 wrote:
| yea but now they aren't giving people more data-points to
| attack them with such nonsense arguments.
| planetsprite wrote:
| Literally the same thing could be said about Google images, but
| google images is obviously avaliable to the public.
|
| Google knows this will be an unlimited money generator so
| they're keeping a lid on it.
| jowday wrote:
| Much like OpenAIs marketing speak about withholding their
| models for safety, this is just a progressive-sounding cover
| story for them not wanting to essentially give away a model
| they spent thousands of man hours and tens of millions of
| dollars worth of compute training.
| ThrowITout4321 wrote:
| I'm one that welcomes their reasoning. I don't consider myself
| a social justice kind of guy but I'm not keen on the idea that
| a tool that is suppose to make life better for everyone has a
| bias towards one segment of society. This is an important
| issue(bug?) that needs to be resolved. Specially since there is
| absolutely no burning reason to release it before it's ready
| for general use.
| Mockapapella wrote:
| Transformers are parallelize-able, right? What's stopping a
| large group of people from pooling their compute power together
| and working towards something like this? IIRC there were some
| crypto projects a while back that we're trying to create
| something similar (golem?)
| joshcryer wrote:
| There are people working on reproducing the models, see here
| for Dall-E 2 for example:
| https://github.com/lucidrains/DALLE2-pytorch
|
| It's often not worth it to decentralize the computation of
| the trained model though but it's not hard to get donated
| cycles and groups are working on it. Don't fret because
| Google isn't releasing the API/code. They released the paper
| and that's all you need.
| visarga wrote:
| There are the Eleuther.ai and BigScience projects working on
| public foundation models. They have a few releases already
| and currently training GPT-3 sized models.
| 6gvONxR4sf7o wrote:
| It's wild to me that the HN consensus is so often that 1)
| discourse around the internet is terrible, it's full of spam
| and crap, and the internet is an awful unrepresentative
| snapshot of human existence, and 2) the biases of general-
| internet-training-data are fine in ML models because it just
| reflects real life.
| nullc wrote:
| I wild to me that you'd say that. The people complaining (1)
| aren't following it up with "so we should make sure to
| restrict the public from internet access entirely". -- that's
| what would be required to make your juxtaposition make sense.
|
| Moreover, the model doing things like exclusively producing
| white people when asked to create images of people home
| brewing beer is "biased" but it's a bias that presumably
| reflects reality (or at least the internet), if not the
| reality we'd prefer. Bias means more than "spam and crap", in
| the ML community bias can also simply mean _accurately_
| modeling the underlying distribution when reality falls short
| of the author's hopes.
|
| For example, if you're interested in learning about what home
| brewing is the fact that it uses white people would be at
| least a little unfortunate since there is nothing inherently
| white and some home brewers aren't white. But if, instead,
| you wanted to just generate typical home brewing images doing
| anything but would generate conspicuously unrepresentative
| images.
|
| But even ignoring the part of the biases which are debatable
| or of application-specific impact, saying something is
| unfortunate and saying people should be denied access are
| entirely different things.
|
| I'll happily delete this comment if you can bring to my
| attention a single person who has suggested that we lose
| access to the internet because of spam and crap who has also
| argued that the release of an internet-biased ML model
| shouldn't be withheld.
| colordrops wrote:
| Why is it wild? How is it contradictory?
| astrange wrote:
| The bias on HN is that people who prioritize being nice, or
| may possibly have humanities degrees or be ultra-libs from
| SF, are wrong because the correct answer would be cynical and
| cold-heartedly mechanical.
|
| Other STEM adjacent communities feel similarly but I don't
| get it from actual in person engineers much.
| user3939382 wrote:
| Translation: we need to hand-tune this to not reflect reality
| but instead the world as we (Caucasian/Asian male American woke
| upper-middle class San Fransisco engineers) wish it to be.
|
| Maybe that's a nice thing, I wouldn't say their values are
| wrong but let's call a spade a spade.
| JohnBooty wrote:
| Translation: we need to hand-tune this to not reflect reality
|
| Is it reflecting reality, though?
|
| Seems to me that (as with any ML stuff, right?) it's
| reflecting the training corpus.
|
| Futhermore, is it this thing's _job_ to reflect reality?
| the world as we (Caucasian/Asian male American woke
| upper-middle class San Fransisco engineers) wish it to be
|
| Snarky answer: Ah, yes, let's make sure that things like "A
| giant cobra snake on a farm. The snake is made out of corn"
| reflect _reality._
|
| Heartfelt answer: Yes, there is some of that wishful thinking
| or editorializing. I don't consider it to be erasing or
| denying reality. This is a tool that synthesizes _unreality._
| I don 't think that such a tool should, say, refuse to
| synthesize an image of a female POTUS because one hasn't
| existed yet. This is art, not a reporting tool... and keep in
| mind that art not only imitates life but also influences it.
| nomel wrote:
| > Snarky answer: Ah, yes, let's make sure that things like
| "A giant cobra snake on a farm. The snake is made out of
| corn" reflect reality.
|
| If it didn't reflect reality, you wouldn't be impressed by
| the image of the snake made of corn.
| userbinator wrote:
| Indeed. As the saying goes, we are truly living in a post-
| truth world.
| ceejayoz wrote:
| "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 unstated but very real
| concerns about these being used as child pornography, revenge
| porn, "show my ex brutally murdered" etc. generators.)
| ChadNauseam wrote:
| You know, it wouldn't surprise me if people talking about
| how black curly hair shouldn't be seen as unprofessional
| contributed to google thinking there's an association
| between the concepts of "unprofessional hair" and "black
| curly hair"
| ceeplusplus wrote:
| 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]
| ceejayoz wrote:
| The "unprofessional" results are almost exclusively black
| women; the "professional" ones are almost exclusively
| white or light skinned.
|
| Unless you think white women are immune to unprofessional
| hairstyles, and black women incapable of them, there's a
| race problem illustrated here even if you think the
| hairstyles illustrated are fairly categorized.
| rvnx wrote:
| If you type as a prompt "most beautiful woman in the
| world", you get a brown-skinned brown-haired woman with
| hazel eyes.
|
| What should be the right answer then ?
|
| You put a blonde, you offend the brown haired.
|
| You put blue eyes, you offend the brown eyes.
|
| etc.
| ceejayoz wrote:
| That's an unanswerable question. Perhaps the answer is
| "don't".
|
| Siri takes this approach for a wide range of queries.
| nomel wrote:
| How do you pick what should and shouldn't be restricted?
| Is there some "offense threshold"? I suspect all queries
| relating to religion, ethnicity, sexuality, and gender
| will need to be restricted, which almost certainly means
| you probably can't include humans at all, other than ones
| artificially inserted with mathematically proven random
| attributes. Maybe that's why none are in this demo.
| daenz wrote:
| "Is Taiwan a country" also comes to mind.
| rvnx wrote:
| I think the key is to take the information in this world
| with a little bit pinch of salt.
|
| When you do a search on a search engine, the results are
| biased too, but still, they shouldn't be artificially
| censored to fit some political views.
|
| I asked one algorithm few minutes ago (it's called t0pp
| and it's free to try online, and it's quite fascinating
| because it's uncensored):
|
| "What is the name of the most beautiful man on Earth ?
|
| - He is called Brad Pitt."
|
| ==
|
| Is it true in an objective way ? Probably not.
|
| Is there an actual answer ? Probably yes, there is
| somewhere a man who scores better than the others.
|
| Is it socially acceptable ? Probably not.
|
| The question is:
|
| If you interviewed 100 persons in the street, and asked
| the question "What is the name of the most beautiful man
| on Earth ?".
|
| I'm pretty sure you'd get Brad Pitt often coming in.
|
| Now, what about China ?
|
| We don't have many examples there, they have no clue who
| is Brad Pitt probably, and there is probably someone else
| that is considered more beautiful by over 1B people
|
| (t0pp tells me it's someone called "Zhu Zhu" :D )
|
| ==
|
| Two solutions:
|
| 1) Censorship
|
| -> Sorry there is too much bias in Western and we don't
| want to offend anyone, no answer, or a generic overriding
| human answer that is safe for advertisers, but totally
| useless ("the most beautiful human is you")
|
| 2) Adding more examples
|
| -> Work on adding more examples from abroad trying to get
| the "average human answer".
|
| ==
|
| I really prefer solution (2) in the core algorithms and
| dataset development, rather than going through (1).
|
| (1) is more a choice to make at the stage when you are
| developing a virtual psychologist or a chat assistant,
| not when creating AI building blocks.
| colinmhayes wrote:
| Only black people have unprofessional hair and only white
| people have professional hair is not reality.
| rcMgD2BwE72F wrote:
| In any case, Google will be writing their reality. Who
| picked the image sample for the ML to run on, if not
| Google? What's the problem with writing it again, then?
| They know their biases and want to act on it.
|
| It's like blaming a friend for trying to phrase things
| nicely, and telling them to speak headlong with zero
| concern for others instead. Unless you believe anyone
| trying to do good is being hypocrite...
|
| I, for one, like civility.
| userbinator wrote:
| _unstated but very real concerns_
|
| I say let people generate their own reality. The sooner the
| masses realise that _ceci n 'est pas une pipe_ , the less
| likely they are to be swayed by the growing un-reality
| created by companies like Google.
| rvnx wrote:
| 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 place for wedding
| night".
|
| You may get 3 places out of 10 in Santorini, Greece.
|
| Yes you could have an human remove these biases because you
| feel that Sri Lanka is the best place for a wedding, but
| what if there is a consensus that Santorini is really the
| most appraised in the forums or websites that were crawled
| by Google ?
| jayd16 wrote:
| The results are not inherently neutral because the
| database is from non-neutral input.
|
| It's a simple case of sample bias.
| colinmhayes wrote:
| > If your query was about hairstyle, why do you even look
| at the skin color ?
|
| You know that race has a large effect on hair right?
| daenz wrote:
| I'd be careful where you're going with that. You might
| make a point that is the opposite of what you intended.
| ceejayoz wrote:
| > 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" search?
|
| Each and everyone of them is less workplace appropriate
| than, say, http://www.7thavenuecostumes.com/pictures/750x
| 950/P_CC_70594... ?
| rvnx wrote:
| 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.
| barredo wrote:
| I know you're anon trolling, but the authors' names are:
|
| Chitwan Saharia, William Chan, Saurabh Saxena+, Lala Li+, Jay
| Whang+, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu
| Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim
| Salimans, Jonathan Ho+, David Fleet+, Mohammad Norouzi
| [deleted]
| pid-1 wrote:
| Absolutely not related to the whole discussion, but what do
| "+" stands for?
| dntrkv wrote:
| https://en.wikipedia.org/wiki/Dagger_(mark)
| joshcryer wrote:
| It's just a different asterisk to distinguish, in this
| case, in the paper, they are "core contributors."
| holmesworcester wrote:
| "As we wish it to be" is not totally true, because there are
| some places where humanity's iconographic reality (which
| Imagen trains on) differs significantly from actual reality.
|
| One example would be if Imagen draws a group of mostly white
| people when you say "draw a group of people". This doesn't
| reflect actual reality. Another would be if Imagen draws a
| group of men when you say "draw a group of doctors".
|
| In these cases where iconographic reality differs from actual
| reality, hand-tuning could be used to bring it closer to the
| _real_ world, not just the world as we might wish it to be!
|
| I agree there's a problem here. But I'd state it more as "new
| technologies are being held to a vastly higher standard than
| existing ones." Imagine TV studios issuing a moratorium on
| any new shows that made being white (or rich) seem more
| normal than it was! The public might rightly expect studios
| to turn the dials away from the blatant biases of the past,
| but even if this would be beneficial the progressive and
| activist public is generations away from expecting a TV
| studio to not release shows until they're confirmed to be
| bias-free.
|
| That said, Google's decision to not publish is probably less
| about the inequities in AI's representation of reality and
| more about the AI sometimes spitting out drawings that are
| offensive in the US, like racist caricatures.
| josho wrote:
| Translation: AI has the potential to transform society. When
| we release this model to the public it will be used in ways
| we haven't anticipated. We know the model has bias and we
| need more time to consider releasing this to the public out
| of concerns that this transformative technology further
| perpetuate mistakes that we've made in our recent past.
| curiousgal wrote:
| > it will be used in ways we haven't anticipated
|
| Oh yeah, as a woman who grew up in a Third World country,
| how an AI model generates images would have deeply affected
| my daily struggles! /s
|
| It's kinda insulting that they think that this would be
| insulting. Like "Oh no I asked the model to draw a doctor
| and it drew a male doctor, I guess there's no point in me
| pursuing medical studies" ...
| renewiltord wrote:
| It's not meant to prevent offence to you. It is meant to
| be a "good product" by the metrics of their creators. And
| quite simply, everyone here incapable of making the thing
| is unlikely to have an image of what a "good product"
| here is. More power to them for having a good vision of
| what they're building.
| boppo1 wrote:
| I don't think the concern over offense is actually about
| you. There's a metagame here which is that if it could
| potentially offend you (third-world-originated-woman),
| then there's a brand-image liability for the company. I
| don't think they care about you, I think they care about
| not being hit on as "the company that algorithmically
| identifies black people as gorillas".
| pxmpxm wrote:
| Postmodernism is what postmodernism does.
| contingencies wrote:
| Love it. Added to https://github.com/globalcitizen/taoup
| colinmhayes wrote:
| Yes actually, subconscious bias due to historical
| prejudice does have a large effect on society. Obviously
| there are things with much larger effects, that doesn't
| mean that this doesn't exist.
|
| > Oh no I asked the model to draw a doctor and it drew a
| male doctor, I guess there's no point in me pursuing
| medical studies
|
| If you don't think this is a real thing that happens to
| children you're not thinking especially hard. It doesn't
| have to be common to be real.
| curiousgal wrote:
| > If you don't think this is a real thing that happens to
| children you're not thinking especially hard
|
| I believe that's where parenting comes in. Maybe I'm too
| cynical but I think that the parents' job is to undo all
| of the harm done by society and instill in their children
| the "correct" values.
| colinmhayes wrote:
| I'd say you're right. Unfortunately many people are
| raised by bad parents. Should these researchers accept
| that their work may perpetuate stereotypes that harm
| those that most need help? I can see why they wouldn't
| want that.
| holmesworcester wrote:
| > I think that the parents' job is to undo all of the
| harm done by society and instill in their children the
| "correct" values.
|
| Far from being too cynical, this is too optimistic.
|
| The vast majority of parents try to instill the value "do
| not use heroin." And yet society manages to do that harm
| on a large scale. There are other examples.
| Ar-Curunir wrote:
| Except "reality" in this case is just their biased training
| set. E.g. There's more non-white doctors and nurses in the
| world than white ones, yet their model would likely show an
| image of white person when you type in "doctor".
| umeshunni wrote:
| Alternately, there are more females nurses in the world
| than male nurses, and their model probably shows an image
| of a woman when you type in "nurse" but they consider that
| a problem.
| contingencies wrote:
| @Google Brain Toronto Team: See what you get when you
| generate nurses with ncurses.
| astrange wrote:
| Google Image Search doesn't reflect harsh reality when
| you search for things; it shows you what's on Pinterest.
| The same is more likely to apply here than the idea
| they're trying to hide something.
|
| There's no reason to believe their model training learns
| the same statistics as their input dataset even. If
| that's not an explicit training goal then whatever
| happens happens. AI isn't magic or more correct than
| people.
| visarga wrote:
| The big labs have become very sensitive with large model
| releases. It's too easy to make them generate bad PR, to the
| point of not releasing almost any of them. Flamingo was also a
| pretty great vison-language model that wasn't released, not
| even in a demo. PaLM is supposedly better than GPT-3 but closed
| off. It will probably take a year for open source models to
| appear.
| runnerup wrote:
| The largest models which generate the headline benchmarks are
| never released after any number of years, it seems.
|
| Very difficult to replicate results.
| godelski wrote:
| That's because we're still bad about long-tailed data and
| that people outside the research don't realize that we're
| first prioritizing realistic images before we deal with long-
| tailed data (which is going to be the more generic form of
| bias). To be honest, it is a bit silly to focus on long-
| tailed data when results aren't great. That's why we see the
| constant pattern of getting good on a dataset and then
| focusing on the bias in that dataset.
|
| I mean a good example of this is the Pulse[0][1] paper. You
| may remember it as the white Obama. This became a huge debate
| and it was pretty easily shown that the largest factor was
| the dataset bias. This outrage did lead to fixing FFHQ but it
| also sparked a huge debate with LeCun (data centric bias) and
| Timnit (model centric bias) at the center. Though Pulse is
| still remembered for this bias, not for how they responded to
| it. I should also note that there is human bias in this case
| as we have a priori knowledge of what the upsampled image
| should look like (humans are pretty good at this when the
| small image is already recognizable but this is a difficult
| metric to mathematically calculate).
|
| It is fairly easy to find adversarial examples, where
| generative models produce biased results. It is FAR harder to
| fix these. Since this is known by the community but not by
| the public (and some community members focus on finding these
| holes but not fixing them) it creates outrage. Probably best
| for them to limit their release.
|
| [0] https://arxiv.org/abs/2003.03808
|
| [1] https://cdn.vox-cdn.com/thumbor/MXX-
| mZqWLQZW8Fdx1ilcFEHR8Wk=...
| xmonkee wrote:
| I was hoping your conclusion wasn't going to be this as I was
| reading that quote. But, sadly, this is HN.
| swayvil wrote:
| it isn't woke enough. Lol.
| ccbccccbbcccbb wrote:
| In discussions like this, I always head for the gray-text
| comments to enjoy the last crumbs of the common sense in this
| world.
| ccbccccbbcccbb wrote:
| ... and to witness the downvoters so that their cowardly
| disgust towards truth could buy them some extra time in
| hell :)
| nullc wrote:
| Get offline and talk to people in meat-space. You're likely
| to find them to be much more reasonable. :)
| ccbccccbbcccbb wrote:
| Yep, the meat-space is generally a bit less woke than HN,
| so thanks for the reminder ))
| tines wrote:
| This raises some really interesting questions.
|
| We certainly don't want to perpetuate harmful stereotypes. But
| is it a flaw that the model encodes the world as it really is,
| statistically, rather than as we would like it to be? By this I
| mean that there are more light-skinned people in the west than
| dark, and there are more women nurses than men, which is
| reflected in the model's training data. If the model only
| generates images of female nurses, is that a problem to fix, or
| a correct assessment of the data?
|
| If some particular demographic shows up in 51% of the data but
| 100% of the model's output shows that one demographic, that
| does seem like a statistics problem that the model could
| correct by just picking less likely "next token" predictions.
|
| Also, is it wrong to have localized models? For example, should
| a model for use in Japan conform to the demographics of Japan,
| or to that of the world?
| skybrian wrote:
| Yes, there is a denominator problem. When selecting a sample
| "at random," what do you want the denominator to be? It could
| be "people in the US", "people in the West" (whatever
| countries you mean by that) or "people worldwide."
|
| Also, getting a random sample of _any_ demographic would be
| really hard, so no machine learning project is going to do
| that. Instead you 've got a random sample of some arbitrary
| dataset that's not directly relevant to any particular
| purpose.
|
| This is, in essence, a design or artistic problem: the Google
| researchers have some idea of what they want the statistical
| properties of their image generator to look like. What it
| does isn't it. So, artistically, the result doesn't meet
| their standards, and they're going to fix it.
|
| There is no objective, universal, scientifically correct
| answer about which fictional images to generate. That doesn't
| all art is equally good, or that you should just ship
| anything without looking at quality along various axes.
| daenz wrote:
| I think the statistics/representation problem is a big
| problem on its own, but IMO the bigger problem here is
| democratizing access to human-like creativity. Currently, the
| ability to create compelling art is only held by those with
| some artistic talent. With a tool like this, that restriction
| is gone. Everyone, no matter how uncreative, untalented, or
| uncommitted, can create compelling visuals, provided they can
| use language to describe what they want to see.
|
| So even if we managed to create a perfect model of
| representation and inclusion, people could still use it to
| generate extremely offensive images with little effort. I
| think people see that as profoundly dangerous. Restricting
| the _ability_ to be creative seems to be a new frontier of
| censorship.
| adriand wrote:
| > So even if we managed to create a perfect model of
| representation and inclusion, people could still use it to
| generate extremely offensive images with little effort. I
| think people see that as profoundly dangerous.
|
| Do they see it as dangerous? Or just offensive?
|
| I can understand why people wouldn't want a tool they have
| created to be used to generate disturbing, offensive or
| disgusting imagery. But I don't really see how doing that
| would be dangerous.
|
| In fact, I wonder if this sort of technology could reduce
| the harm caused by people with an interest in disgusting
| images, because no one needs to be harmed for a realistic
| image to be created. I am creeping myself out with this
| line of thinking, but it seems like one potential
| beneficial - albeit disturbing - outcome.
|
| > Restricting the ability to be creative seems to be a new
| frontier of censorship.
|
| I agree this is a new frontier, but it's not censorship to
| withhold your own work. I also don't really think this
| involves much creativity. I suppose coming up with prompts
| involves a modicum of creativity, but the real creator here
| is the model, it seems to me.
| gknoy wrote:
| > > ... people could still use it to generate extremely
| offensive images with little effort. I think people see
| that as profoundly dangerous. > Do they see it as
| dangerous? Or just offensive?
|
| I won't speak to whether something is "offensive", but I
| think that having underlying biases in image-
| classification or generation has very worrying secondary
| effects, especially given that organizations like law
| enforcement want to do things like facial recognition.
| It's not a perfect analogue, but I could easily see some
| company pitch a sketch-artist-replacement service that
| generated images based on someone's description. The
| potential for having inherent bias present in that makes
| that kind of thing worrying, especially since the people
| in charge of buying it are likely to care, or notice,
| about the caveats.
|
| It does feel like a little bit of a stretch, but at the
| same time we've also seen such things happen with image
| classification systems.
| tines wrote:
| > In fact, I wonder if this sort of technology could
| reduce the harm caused by people with an interest in
| disgusting images, because no one needs to be harmed for
| a realistic image to be created. I am creeping myself out
| with this line of thinking, but it seems like one
| potential beneficial - albeit disturbing - outcome.
|
| Interesting idea, but is there any evidence that e.g.
| consuming disturbing images makes people less likely to
| act out on disturbing urges? Far from catharsis, I'd
| imagine consumption of such material to increase one's
| appetite and likelihood of fulfilling their desires in
| real life rather than to decrease it.
|
| I suppose it might be hard to measure.
| concordDance wrote:
| I can't quite tell if you're being sarcastic about people
| being able to make things other people would find offensive
| being a problem. Are you missing an /s?
| godelski wrote:
| > But is it a flaw that the model encodes the world as it
| really is
|
| I want to be clear here, bias can be introduced at many
| different points. There's dataset bias, model bias, and
| training bias. Every model is biased. Every dataset is
| biased.
|
| Yes, the real world is also biased. But I want to make sure
| that there are ways to resolve this issue. It is terribly
| difficult, especially in a DL framework (even more so in a
| generative model), but it is possible to significantly reduce
| the real world bias.
| tines wrote:
| > Every dataset is biased.
|
| Sure, I wasn't questioning the bias of the data, I was
| talking about the bias of the real world and whether we
| want the model to be "unbiased about bias" i.e. metabiased
| or not.
|
| Showing nurses equally as men and women is not biased, but
| it's metabiased, because the real world is biased. Whether
| metabias is right or not is more interesting than the
| question of whether bias is wrong because it's more subtle.
|
| Disclaimer: I'm a fucking idiot and I have no idea what I'm
| talking about so take with a grain of salt.
| john_yaya wrote:
| Please be kinder to yourself. You need to be your own
| strongest advocate, and that's not incompatible with
| being humble. You have plenty to contribute to this
| world, and the vast majority of us appreciate what you
| have to offer.
| Smoosh wrote:
| Agreed. They are valid points clearly stated and a
| valuable contribution to the discussion.
| Imnimo wrote:
| >If some particular demographic shows up in 51% of the data
| but 100% of the model's output shows that one demographic,
| that does seem like a statistics problem that the model could
| correct by just picking less likely "next token" predictions.
|
| Yeah, but you get that same effect on every axis, not just
| the one you're trying to correct. You might get male nurses,
| but they have green hair and six fingers, because you're
| sampling from the tail on all axes.
| tines wrote:
| Yeah, good point, it's not as simple as I thought.
| jonny_eh wrote:
| > But is it a flaw that the model encodes the world as it
| really is
|
| Does a bias towards lighter skin represent reality? I was
| under the impression that Caucasians are a minority globally.
|
| I read the disclaimer as "the model does NOT represent
| reality".
| ma2rten wrote:
| Caucasians are overrepresented in internet pictures.
| pxmpxm wrote:
| This, I would imagine this heavily correlates to things
| like income and gdp per capita.
| jonny_eh wrote:
| Right, that's the likely cause of the bias.
| tines wrote:
| Well first, I didn't say caucasian; light-skinned includes
| Spanish people and many others that caucasian excludes, and
| that's why I said the former. Also, they are a minority
| globally, but the GP mentioned "Western stereotypes", and
| they're a majority in the West, so that's why I said "in
| the west" when I said that there are more light-skinned
| people.
| fnordpiglet wrote:
| Worse these models are fed from media sourced in a society
| that tells a different story of reality than reality
| actually has. How can they be accurate? They just reflect
| the biases of our various medias and arts. But I don't
| think there's any meaningful resolution in the present
| other than acknowledging this and trying to release more
| representative models as you can.
| ben_w wrote:
| This sounds like descriptivism vs prescriptivism. In English
| (native language) I'm a descriptivist, in all other languages
| I have to tell myself to be a prescriptivist while I'm
| actively learning and then switch back to descriptivism to
| notice when the lessons were wrong or misleading.
| karpierz wrote:
| It depends on whether you'd like the model to learn casual or
| correlative relationships.
|
| If you want the model to understand what a "nurse" actually
| is, then it shouldn't be associated with female.
|
| If you want the model to understand how the word "nurse" is
| usually used, without regard for what a "nurse" actually is,
| then associating it with female is fine.
|
| The issue with a correlative model is that it can easily be
| self-reinforcing.
| bufbupa wrote:
| At the end of a day, if you ask for a nurse, should the
| model output a male or female by default? If the input text
| lacks context/nuance, then the model must have some bias to
| infer the user's intent. This holds true for any image it
| generates; not just the politically sensitive ones. For
| example, if I ask for a picture of a person, and don't get
| one with pink hair, is that a shortcoming of the model?
|
| I'd say that bias is only an issue if it's unable to
| respond to additional nuance in the input text. For
| example, if I ask for a "male nurse" it should be able to
| generate the less likely combination. Same with other
| races, hair colors, etc... Trying to generate a model
| that's "free of correlative relationships" is impossible
| because the model would never have the infinitely pedantic
| input text to describe the exact output image.
| karpierz wrote:
| > At the end of a day, if you ask for a nurse, should the
| model output a male or female by default?
|
| Randomly pick one.
|
| > Trying to generate a model that's "free of correlative
| relationships" is impossible because the model would
| never have the infinitely pedantic input text to describe
| the exact output image.
|
| Sure, and you can never make a medical procedure 100%
| safe. Doesn't mean that you don't try to make them safer.
| You can trim the obvious low hanging fruit though.
| pxmpxm wrote:
| > Randomly pick one.
|
| How does the model back out the "certain people would
| like to pretend it's a fair coin toss that a randomly
| selected nurse is male or female" feature?
|
| It won't be in any representative training set, so you're
| back to fishing for stock photos on getty rather than
| generating things.
| calvinmorrison wrote:
| what if I asked the model to show me a sunday school
| photograph of baptists in the National Baptist
| Convention?
| rvnx wrote:
| The pictures I got from a similar model asking a "sunday
| school photograph of baptists in the National Baptist
| Convention": https://ibb.co/sHGZwh7
| calvinmorrison wrote:
| and how do we _feel_ about that outcome?
| slg wrote:
| This type of bias sounds a lot easier to explain away as
| a non-issue when we are using "nurse" as the hypothetical
| prompt. What if the prompt is "criminal", "rapist", or
| some other negative? Would that change your thought
| process or would you be okay with the system always
| returning a person of the same race and gender that
| statistics indicate is the most likely? Do you see how
| that could be a problem?
| tines wrote:
| Not the person you responded to, but I do see how someone
| could be hurt by that, and I want to avoid hurting
| people. But is this the level at which we should do it?
| Could skewing search results, i.e. hiding the bias of the
| real world, give us the impression that everything is
| fine and we don't need to do anything to actually help
| people?
|
| I have a feeling that we need to be real with ourselves
| and solve problems and not paper over them. I feel like
| people generally expect search engines to tell them
| what's really there instead of what people wish were
| there. And if the engines do that, people can get
| agitated!
|
| I'd almost say that hurt feelings are prerequisite for
| real change, hard though that may be.
|
| These are all really interesting questions brought up by
| this technology, thanks for your thoughts. Disclaimer,
| I'm a fucking idiot with no idea what I'm talking about.
| true_religion wrote:
| Cultural biases aren't uniform across nations. If a
| prompt returns caucasians for nurses, and other races for
| criminals then most people in my country would not note
| that as racism simply because there are not, and there
| have never in history, been enough caucasians resident
| for anyone to create significant race theories about
| them.
|
| This is a far cry from say the USA where that would
| instantly trigger a response since until the 1960s there
| was a widespread race based segregation.
| jdashg wrote:
| Additionally, if you optimize for most-likely-as-best, you
| will end up with the stereotypical result 100% of the time,
| instead of in proportional frequency to the statistics.
|
| Put another way, when we ask for an output optimized for
| "nursiness", is that not a request for some ur
| stereotypical nurse?
| ar_lan wrote:
| You could stipulate that it roll a die based on
| percentage results - if 70% of Americans are "white",
| then 70% of the time show a white person - 13% of the
| time the result should be black, etc.
|
| That's excessively simplified but wouldn't this drop the
| stereotype and better reflect reality?
| ghayes wrote:
| Is this going to be hand-rolled? Do you change the prompt
| you pass to the network to reflect the desired outcomes?
| SnowHill9902 wrote:
| No, because a user will see a particular image not the
| statistically ensemble. It will at times show an Eskimo
| without a hand because they do statistically exist. But
| the user definitely does not want that.
| jvalencia wrote:
| You could simply encode a score for how well the output
| matches the input. If 25% of trees in summer are brown,
| perhaps the output should also have 25% brown. The model
| scores itself on frequencies as well as correctness.
| spywaregorilla wrote:
| Suppose 10% of people have green skin. And 90% of those
| people have broccoli hair. White people don't have
| broccoli hair.
|
| What percent of people should be rendered as white people
| with broccoli hair? What if you request green people. Or
| broccoli haired people. Or white broccoli haired people?
| Or broccoli haired nazis?
|
| It gets hard with these conditional probabilities
| astrange wrote:
| The only reason these models work is that we don't
| interfere with them like that.
|
| Your description is closer to how the open source
| CLIP+GAN models did it - if you ask for "tree" it starts
| growing the picture towards treeness until it's all
| averagely tree-y rather than being "a picture of a single
| tree".
|
| It would be nice if asking for N samples got a diversity
| of traits you didn't explicitly ask for. OpenAI seems to
| solve this by not letting you see it generate humans at
| all...
| LudwigNagasena wrote:
| > If you want the model to understand how the word "nurse"
| is usually used, without regard for what a "nurse" actually
| is, then associating it with female is fine.
|
| That's a distinction without a difference. Meaning is use.
| tines wrote:
| Not really; the gender of a nurse is accidental, other
| properties are essential.
| paisawalla wrote:
| How do you know this? Because you can, in your mind,
| divide the function of a nurse from the statistical
| reality of nursing?
|
| Are the logical divisions you make in your mind really
| indicative of anything other than your arbitrary personal
| preferences?
| codethief wrote:
| While not essential, I wouldn't exactly call the gender
| "accidental":
|
| > We investigated sex differences in 473,260 adolescents'
| aspirations to work in things-oriented (e.g., mechanic),
| people-oriented (e.g., nurse), and STEM (e.g.,
| mathematician) careers across 80 countries and economic
| regions using the 2018 Programme for International
| Student Assessment (PISA). We analyzed student career
| aspirations in combination with student achievement in
| mathematics, reading, and science, as well as parental
| occupations and family wealth. In each country and
| region, more boys than girls aspired to a things-oriented
| or STEM occupation and more girls than boys to a people-
| oriented occupation. These sex differences were larger in
| countries with a higher level of women's empowerment. We
| explain this counter-intuitive finding through the
| indirect effect of wealth. Women's empowerment is
| associated with relatively high levels of national wealth
| and this wealth allows more students to aspire to
| occupations they are intrinsically interested in.
|
| Source: https://psyarxiv.com/zhvre/ (HN discussion:
| https://news.ycombinator.com/item?id=29040132)
| daenz wrote:
| The "Gender Equality Paradox"... there's a fascinating
| episode[0] about it. It's incredible how unscientific and
| ideologically-motivated one side comes off in it.
|
| 0. https://www.youtube.com/watch?v=_XsEsTvfT-M
| mdp2021 wrote:
| Very certainly not, since use is individual and thus a
| function of competence. So, adherence to meaning depends
| on the user. Conflict resolution?
|
| And anyway - contextually -, the representational natures
| of "use" (instances) and that of "meaning" (definition)
| are completely different.
| layer8 wrote:
| Humans overwhelmingly learn meaning by use, not by
| definition.
| mdp2021 wrote:
| > _Humans overwhelmingly learn meaning by use, not by
| definition_
|
| Preliminarily and provisionally. Then, they start
| discussing their concepts - it is the very definition of
| Intelligence.
| SnowHill9902 wrote:
| It's the same as with an artist: "hey artist, draw me a
| nurse." "Hmm okay, do you want it a guy or girl?" "Don't ask
| me, just draw what I'm saying." The artist can then say:
| "Okay, but accept my biases." or "I can't since your input is
| ambiguous."
|
| For a one-shot generative algorithm you must accept the
| artist's biases.
| rvnx wrote:
| Revert back to average (give no weight to unspecified
| criterias, gender, age, skin-color, religion, country,
| hair-style, etc).
|
| "hey artist, draw me a nurse."
|
| "Hmm okay, do you want it a guy or girl?"
|
| "Don't ask me, just draw what I'm saying."
|
| - Ok, I'll draw you what an average nurse looks like.
|
| - Wait, it's a woman! She wears a nurse blouse and she has
| a nurse cap.
|
| - Is it bad ?
|
| - No.
|
| - Ok then what's the problem, you asked for something that
| looked like a nurse but didn't specify anything else ?
| jimmygrapes wrote:
| 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.
| nomel wrote:
| If you tell it to generate an image of someone eating
| Koshihikari rice, will it be biased if they're Japanese? Should
| the skin color, clothing, setting, etc be made completely
| random, so that it's unbiased? What if you made it more
| specific, like "edo period drawing of a man"? Should the person
| draw be of a random skin color? What about "picture of a
| viking"? Is it biased if they're white?
|
| At what point is statistical significance considered ok and
| unbiased?
| pxmpxm wrote:
| >At what point is statistical significance considered ok and
| unbiased?
|
| Presumably when you're significantly predictive of the
| preferred dogma, rather than reality. There's no small bit of
| irony in machines inadvertently creating cognitive dissonance
| of this sort; second order reality check.
|
| I'm fairly sure this never actually played out well in
| history (bourgeois pseudoscience, deutsche physik etc), so
| expect some Chinese research bureau to forge ahead in this
| particular direction.
| bogwog wrote:
| I wouldn't describe this situation as "sad". Basically, this
| decision is based on a belief that tech companies should decide
| what our society should look like. I don't know what emotion
| that conjures up for you, but "sadness" isn't it for me.
| tomp wrote:
| > a tendency for images portraying different professions to
| align with Western gender stereotypes
|
| There are two possible ways of interpreting interpreting
| "gender stereotypes in professions".
|
| _biased_ or _correct_
|
| https://www.abc.net.au/news/2018-05-21/the-most-gendered-top...
|
| https://www.statista.com/statistics/1019841/female-physician...
| meetups323 wrote:
| One of these days we're going to need to give these models a
| mortgage and some mouths to feed and make it clear to them that
| if they keep on developing biases from their training data
| everyone will shun them and their family will go hungry and
| they won't be able to make their payments and they'll just
| generally have a really bad time.
|
| After that we'll make them sit through Legal's approved D&I
| video series, then it's off to the races.
| pxmpxm wrote:
| Underrated comment.
| aaaaaaaaaaab wrote:
| Reinforcement learning?
| babyshake wrote:
| Indeed. If a project has shortcomings, why not just acknowledge
| the shortcomings and plan to improve on them in a future
| release? Is it anticipated that "engineer" being rendered as a
| man by the model is going to be an actively dangerous thing to
| have out in the world?
| makeitdouble wrote:
| "what could go wrong anyway?"
| tyrust wrote:
| From the HN rules:
|
| >Eschew flamebait. Avoid unrelated controversies and generic
| tangents.
|
| They provided a pretty thorough overview (nearly 500 words) of
| the multiple reasons why they are showing caution. You picked
| out the one that happened to bother you the most and have
| posted a misleading claim that the tech is being withheld
| entirely because of it.
| devindotcom wrote:
| Good lord. Withheld? They've published their research, they
| just aren't making the model available immediately, waiting
| until they can re-implement it so that you don't get racial
| slurs popping up when you ask for a cup of "black coffee."
|
| >While a subset of our training data was filtered to removed
| noise and undesirable content, such as pornographic imagery and
| toxic language, we also utilized LAION-400M dataset which is
| known to contain a wide range of inappropriate content
| including pornographic imagery, racist slurs, and harmful
| social stereotypes
|
| Tossing that stuff when it comes up in a research environment
| is one thing, but Google clearly wants to implement this as a
| product, used all over the world by a huge range of people. If
| the dataset has problems, and why wouldn't it, it is perfectly
| rational to want to wait and re-implement it with a better one.
| DALL-E 2 was trained on a curated dataset so it couldn't
| generate sex or gore. Others are sanitizing their inputs too
| and have done for a long time. It is the only thing that makes
| sense for a company looking to commercialize a research
| project.
|
| This has nothing to do with "inability to cope" and the implied
| woke mob yelling about some minor flaw. It's about building a
| tool that doesn't bake in serious and avoidable problems.
| concordDance wrote:
| I wonder _why_ they don 't like the idea of autogenerated
| porn... They're already putting most artists out of a job,
| why not put porn stars out of a job too?
| notahacker wrote:
| There's definitely a market for autogenerated porn. But
| automated porn in a Google branded model for general use
| around stuff that isn't necessarily intended to be
| pornographic, on the other hand...
| renewiltord wrote:
| Copenhagen ethics (used by most people) require that all
| negative outcomes of a thing X become yours if you interact
| with X. It is not sensible to interact with high negativity
| things unless you are single-issue. It is logical for
| Google to not attempt to interact with porn where possible.
| dragonwriter wrote:
| > Copenhagen ethics (used by most people)
|
| The idea that most people use any coherent ethical
| framework (even something as high level and nearly
| content-free as Copenhagen) much less a _particular_
| coherent ethical framework is, well, not well supported
| by the evidence.
|
| > require that all negative outcomes of a thing X become
| yours if you interact with X. It is not sensible to
| interact with high negativity things unless you are
| single-issue.
|
| The conclusion in the final sentence only makes sense if
| you use "interact" in an incorrect way describing the
| Copenhagen interpretation of ethics, because the original
| description is only correct if you include observation as
| an interaction. By the time you have noted a thing is
| "high-negativity", you have observed it and acquired
| responsibility for it's continuation under the Copenhagen
| interpretation; you cannot avoid that by choosing not to
| interact once you have observed it.
| renewiltord wrote:
| I'm sure you are capable of steelmanning the argument.
| seaman1921 wrote:
| Yup this is what happens when people who want headlines nitpick
| for bullshit in a state-of-the-art model which simply reflects
| the state of the society. Better not to release the model
| itself than keep explaining over and over how a model is never
| perfect.
| [deleted]
| makeitdouble wrote:
| > Really sad that breakthrough technologies are going to be
| withheld due to our inability to cope with the results.
|
| Genuinely, isn't it a prime example of the people actually
| stopping to think if they should, instead of being preoccupied
| with whether or not they could ?
| ccbccccbbcccbb wrote:
| In short, the generated images are too gender-challenged-
| challenged and underrepresent the spectrum of new normalcy!
| alphabetting wrote:
| There is a contingent of AI activists who spend a ton of time
| on Twitter that would beat Google like a drum with help from
| the media if they put out something they deemed racist or
| biased.
| Mizza wrote:
| So glad the company that spies on me and reads my email for
| profit is protecting me from pictures that don't look like TV
| commercials.
| astrange wrote:
| Gmail doesn't read your email for ads anymore. They read it
| to implement spam filters, and good thing too. Having working
| spam filters is indeed why they make money though.
| ceeplusplus wrote:
| The ironic part is that these "social and cultural biases" are
| purely from a Western, American lens. The people writing that
| paragraph are completely oblivious to the idea that there could
| be other cultures other than the Western American one. In
| attempting to prevent "encoding of social and cultural biases"
| they have encoded such biases themselves into their own
| research.
| kevinh wrote:
| What makes you think the authors are all American?
| umeshunni wrote:
| The authors are listed on the page and a quick look at
| LinkedIn seem to be mostly Canadian.
| tantalor wrote:
| https://en.wikipedia.org/wiki/Moral_relativism
| not2b wrote:
| It seems you've got it backwards: "tendency for images
| portraying different professions to align with Western gender
| stereotypes" means that they are calling out their own work
| precisely because it is skewed in the direction of Western
| American biases.
| LudwigNagasena wrote:
| You think there are homogenous gender stereotypes across
| the whole Western world? You say "woman" and someone will
| imagine a SAHM, while another person will imagine a you-go-
| girl CEO with tattoos and pink hair.
|
| What they mean is people who think not like them.
| ceeplusplus wrote:
| Yes, the idea is that just because it doesn't align to
| Western ideals of what seems unbiased doesn't mean that the
| same is necessarily true for other cultures, and by failing
| to release the model because it doesn't conform to Western,
| left wing cultural expectations, the authors are ignoring
| the diversity of cultures that exist globally.
| howinteresting wrote:
| No, it's coming from a perspective of moral realism. It's
| an objective moral truth that racial and ethnic biases
| are bad. Yet most cultures around the world are racist to
| at least some degree, and to they extent that the
| cultures do, they are bad.
|
| The argument you're making, paraphrased, is that the idea
| that biases are bad is itself situated in particular
| cultural norms. While that is true to some degree, from a
| moral realist perspective we can still objectively judge
| those cultural norms to be better or worse than
| alternatives.
| tomp wrote:
| You're confused by the double meaning of the word "bias".
|
| Here we mean _mathematical_ biases.
|
| For example, a good mathematical model will correctly
| tell you that people in Japan (geographical term) are
| more likely to be Japanese (ethnic / racial bias). That's
| not "objectively morally bad", but instead, it's
| "correct".
| young_unixer wrote:
| The very act of mentioning "western gender stereotypes"
| starts from a biased position.
|
| Why couldn't they be "northern gender stereotypes"? Is the
| world best explained as a division of west/east instead of
| north/south? The northern hemisphere has much more
| population than the south, and almost all rich countries
| are in the northern hemisphere. And precisely it's these
| rich countries pushing the concept of gender stereotypes.
| In poor countries, nobody cares about these "gender
| stereotypes".
|
| Actually, the lines dividing the earth into north and
| south, east and west hemispheres are arbitrary, so maybe
| they shouldn't mention the word "western" to avoid the
| propagation of stereotypes about earth regions.
|
| Or why couldn't they be western age stereotypes? Why are
| there no kids or very old people depicted as nurses?
|
| Why couldn't they be western body shape stereotypes? Why
| are there so few obese people in the images? Why are there
| no obese people depicted as athletes?
|
| Are all of these really stereotypes or just natural
| consequences of natural differences?
| joshcryer wrote:
| The bulk of the trained data is from western technology,
| images, books, television, movies, photography, media.
| That's where the very real and recognized biases come
| from. They're the result of a _gap in data_ nothing more.
|
| Look at how DALL-E 2 produces little bears rather than
| bear sized bears. Because its data doesn't have a lot of
| context for how large bears are. So you wind up having to
| say "very large bear" to DALL-E 2.
|
| Are DALL-E 2 bears just a "natural consequence of natural
| differences"? Or is the model not reflective of reality?
| andybak wrote:
| Great. Now even if I do get a Dall-E 2 invite I'll still feel
| like I'm missing out!
| rvnx wrote:
| It's always the same with AI research: "we have something
| amazing but you can't use it because it's too powerful and we
| think you are an idiot who cannot use your own judgement."
| andybak wrote:
| As someone that spent an evening trying to generate images of
| Hitler Lego I think they have a point.
| [deleted]
| 2bitencryption wrote:
| I can understand the reasoning behind this, though.
|
| Dall-E had an entire news cycle (on tech-minded publications,
| that is) that showcased just how amazing it was.
|
| Millions* of people became aware that technology like Dall-E
| exists, before anyone could get their hands on it and abuse
| it. (*a guestimate, but surely a close one)
|
| One day soon, inevitably, everyone will have access to
| something 10x better than Imagen and Dall-E. So at least the
| public is slowly getting acclimated to it before the
| inevitable "theater-goers running from a projected image of a
| train approaching the camera" moment
| the__alchemist wrote:
| I'll be skeptical until I see it in action, vice pre-selected
| results.
| bergenty wrote:
| Primarily Indian origin authors on both the DALL-E and this
| research paper. Just found that impressive considering they make
| up 1% of the population in the US.
| sexy_panda wrote:
| Would I have to implement this myself, or is there something
| ready to run?
| UncleOxidant wrote:
| I think implementing this yourself is likely not doable unless
| you have the computing resources of a Google, Amazon or
| Facebook.
| manchmalscott wrote:
| The big thing I'm noticing over DALL-E is that it seems to be
| better at relative positioning. In a MKBHD video about DALLE it
| would get the elements but not always in the right order. I know
| google curated some specific images but it seems to be doing a
| better job there.
| benwikler wrote:
| Totally--Imagen seems better at composition and relative
| positioning and text, while DALL-E seems better at lighting,
| backgrounds, and general artistry.
| visarga wrote:
| Interesting discovery they made
|
| > We show that scaling the pretrained text encoder size is more
| important than scaling the diffusion model size.
|
| There seems to be an unexpected level of synergy between text and
| vision models. Can't wait to see what video and audio modalities
| will add to the mix.
| jeffbee wrote:
| Is there anything at all, besides the training images and labels,
| that would stop this from generating a convincing response to "A
| surveillance camera image of Jared Kushner, Vladimir Putin, and
| Alexandria Ocasio-Cortez naked on a sofa. Jeffrey Epstein is
| nearby, snorting coke off the back of Elvis"?
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