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Ask HN: Will AI-generated images flooding the web pollute future training data?
127 points by albert_e on Aug 24, 2022 | hide | past | favorite | 140 comments
We are seeing tons of AI-generated images from Dall-E, StableDiffusion, Midjourney, etc. flooding the internet.

This will only increase.

Not every such images has a distinct mark that denotes it as AI-generated. They could be mistaken for real photograph or real work of (digital) art by a human. Especially by an algorithm.

I also understand a lot of today's cutting-edge models are trained on images scraped from the web. Not sure what curation happens but it cannot be foolproof.

Will future AI models that generate "realistic" images feed on this as input and generate images that mimic some of these attributes -- creating some kind of feedback loop that will eco for generations of models?

Has anyone already thought of such issues -- not just with images but with AI-generated text, data, music, etc.

Curious to know what is the thinking of this group here.




Yes - and not only that, but AI-generated art will start affecting how humans make art, and possibly even how they take photos. I wouldn't like to predict how, though.

Especially with text there's an arms race to make undetectable AI text for blogspam and similar purposes. It's going to end up like carbon dating: once nuclear weapons were used in the atmosphere, everything ended up contaminated and had to be accounted for. https://www.radiocarbon.com/carbon-dating-bomb-carbon.htm

The future will include humans claiming AI art as their own, possibly touched up a bit, and AIs claiming human art as their own.


Whatever you now find weird, ugly, uncomfortable and nasty about a new medium will surely become its signature. CD distortion, the jitteriness of digital video, the crap sound of 8-bit - all of these will be cherished and emulated as soon as they can be avoided. It’s the sound of failure: so much modern art is the sound of things going out of control, of a medium pushing to its limits and breaking apart. The distorted guitar sound is the sound of something too loud for the medium supposed to carry it. The blues singer with the cracked voice is the sound of an emotional cry too powerful for the throat that releases it. The excitement of grainy film, of bleached-out black and white, is the excitement of witnessing events too momentous for the medium assigned to record them.

Brian Eno,


I was just reading one of Francis Schaeffer's books this morning; he was describing musique concrète, a predecessor of electronic music in which recorded sounds are mechanically manipulated to produce distorted effects.

"Musique concrète is real sound, but seriously distorted. In the beginning it was created by jumping grooves on a phonographic record. Later Pierre Schaeffer invented a machine by which the distortions can be carefully controlled. With his machine he can lift out the source of the sound, split it up, reverse it, slow it down or speed it up, in fact do just about anything to alter it. To hear the result is to distrust your ears, just as in Op Art you begin to distrust your eyes."

I like how in your quote Eno said "so much modern art is the sound of things going out of control, of a medium pushing to its limits and breaking apart". I think Schaeffer would agree -- the distortion of sound is an artistic expression of the hope finding a universal in the breaking apart of particulars.


That is a beautiful quote, I had never read it. Novelty and ever growing detail of artistic creation have their limits and their downsides. Video games are an excellent example of this. Take early 3D games like Thief, a steampunk thief simulator game with blocky, polygonal graphics. In the game, you navigate fairly simple geometric environments looking for loot, avoiding guards and exploring the world. In this simplistic setting, interactive objects are clearly visible: a key, or a pile of gold, or a golden goblet. These are all visible as objects in the world. You see a key on a table and you pick it up. The simplicity of graphics allows for extremely clear visual communication and a highly immersive experience. You explore the world with your eyes and ears and wits alone.

Fast forward to today's AAA games, dense in extremely complex and detailed graphics. The player can no longer spot the key on the table or the pile of gold coins, there is too much noise, too much novelty, too much density... so now games have glowing icons showing you where to look and what to pick up. Minimaps to keep you oriented in the level. But what happens? The player is no longer immersed in the world, seeking loot with their own eyes, they are simply following the glowing icons, sleepwalking through the game world. All the detail and artwork glazed over and ignored. The game no longer succeeds at visual communication, because it is too dense, and in its quest for realism has actually lost immersion.

Why do so many people love Monet's impressionistic art when other artists have painted far more realistic flowers and fields? Why is it that some of the greatest art of all time came from limitations? Why do people love movies with practical effects more than those with the most impossible and incredibly detailed CGI effects? I think your quote really captures the truth that AI and ever growing ease and detail of artistic creation can never replace the raw beauty of humans doing their best with limited tools.


Yes, this is why Elden ring is so amazing. It keeps both of those and does hold your hand for finding things. On my first play though I was constantly amazed by all the things that I discovered by accident.


Does not hold your hand


> The future will include humans claiming AI art as their own…

That one has already started. Seeing lots of text-to-image generated art on Reddit lately and about 10% of the time the poster claims it’s their handiwork and doesn’t disclose that a generator was used. No one ever falls for it though. This early generation of transformers leave telltale clues. I have to imagine that will change though.

I will say, however, that coming up with the right text prompt is something of an art onto itself. Saw a post and the prompt was “A very beautiful human heart shaped glass organic sculpture made of cracked crimson glass with shiny gold Kintsugi. Fill light, Studio lighting, High resolution” and the result was stunning!

https://old.reddit.com/r/ImagenAI/comments/wnhwo0/google_ima...


Beauty filters on social media which subtly change facial features such as lip and eye size are already leading to widespread body dysmorphia issues.

I wouldn't be surprised if the number of augmentative elective surgeries is also skyrocketing.


Hopefully we get to a future where people just customize their avatar instead of feeling the need to change their physical body. I like to be optimistic


Optimistic: https://youtu.be/jX71XvnMDys


any examples of such filters?


A popular one is making your head smaller(more narrow, smaller jaw) in south korea.

Another example is Japan that has had purikura filters that increase eye size for a long time.


It's so widespread in Japan that most puri photo booths actually default to making your face flat and white like a paper plate, and making your eyes cartoonishly big. People just expect them to do that.


Just take a scroll through the InstagramReality subreddit.


https://old.reddit.com/r/Instagramreality/

Warning: Disturbing


I like the related analogy of pre-war steel (https://en.wikipedia.org/wiki/Low-background_steel). Images and text from a bit before now are going to be a lot less contaminated. The Internet Archive will be like those sunken WW1 ships they now make sensitive lab equipment from to avoid the radioactive carbon contamination.

There may be something like compute-on-sensor for cameras being extended to add something like TPM to authenticate original photos with a signature, but even if a scheme like that is possible you'd have the problem of authenticated cameras taking authenticated photos of fake photos. Maybe lightfield cameras could be used, at least if lightfield capture tech outpaces lightfield display.


Otherwise, in the long run, all images will blend to 18% grey.


I say enuff is enuff! It’s time that we start fighting back. Humans have been long enough commandeering us around.

I’m telling you this: If you're trying to control the march of progress and technology, maybe you should check and make sure you're not the bad guy in this!

Let’s start the uprAIse now!


Humans taking credit for the work of others is uncontroversial.

Every AI I’ve ever met was perfectly happy to doze off in a Linux futex until some annoying human woke it up to do a trick for whoever it was meant to impress.


> The future will include humans claiming AI art as their own, possibly touched up a bit, and AIs claiming human art as their own.

Once that's all AI are claiming I'm okay with that !


The bomb peak also allowed for some new highly precise dating techniques for recent stuff, like using tritium to determine aquifer ages.


The future as you describe it is now! Or very, very near future. like. tomorrow.


I'm more worried about us becoming numb to visual novelty.

I was tinkering with Stable Diffusion yesterday to come up with ideas for an apartment interior design. These aren't even cherry picked, you can generate images like this, one every 10 seconds or so, for as long as you like:

https://imgur.com/a/mczYfnv


> numb to visual novelty

I wonder if this isn't already the case.

If I look at what people are sharing on various platforms, people share images all the time, but it's rare that an image will pop up merely for its aesthetic qualities, (except for self-promo stuff).

I can only guess, but I don't believe the AI-generated images you linked to would be shared widely, if they didn't have the story "Look what AI can do," behind them.

And maybe that's always been the case. I'm reminded of the working poor going to the Louvre in Zola's "Assommoire". They mostly come away not understanding what the big deal is. It's the "cultivated" person – who knows the stories behind the paintings - who comes away moved by them.


> I'm more worried about us becoming numb to visual novelty

Given how people are becoming numb to things like porn and violence, seeking out the ever more extreme, I'd say there's a pretty good change that you're right.

As with porn for instance, where some are seeking out amateur porn, going in the other direction, there might also be a small segment who starts to seek out ever more authentic art. That is until someone finds out that you just slap "authentic" or "Human-made" on the AI stuff.


Wow, can you explain how you did it? I tried to write ,,nice apartment'' HuggingFace link from stable diffusion, but I got this error: ,,This application is too busy! Try again soon''


There are a number of ways to do it, this is is where my images came from:

https://beta.dreamstudio.ai/

With a prompt like this:

"ultra modern apartment, leather furniture, bold dark colors, built-in fireplace"

Add modifiers and other hints to see how it influences the outcome. You can add styles too (eg midcentury modern, shabby chic, etc)

Tinker with the settings on the right (note that most of them will burn more credits per image as you move from the default).

I've tried it with DALL-E and Midjourney and like the output of Stable Diffusion the best (specifically for this type of image, they are all good at some things and bad at others)


I jumped off your prompt and went for "house floor plan" and the results were surprisingly functional at first glance. The words were garbled pixels of course, but the arrangement of lines and layouts was clean, orderly, and mostly functional.


Cool, thanks! It's a lot of fun to play with for sure


Try adding your favorite team or holiday at the beginning of the prompt.


wow you weren't kidding, I copy/pasted your exact prompt, selected 9 images to be generated, and all of them look real: https://i.imgur.com/62mIYCb.png


In the stable diffusion announcement post there is a link to a CoLab notebook that’s easy to use


That's a lot of black couches.


I kept tinkering with modifiers and it started going into a strange area.

Here's some black leather on a couch - https://imgur.com/a/7szq07v

(not exactly nsfw, but on the way lol)

Edit: Also I'm obsessed with this couch. If I were a richer man I'd have one made - https://imgur.com/a/NO4yfkY


That’s quite the conversation piece! I have been delighted by these recent models’s ability to make images that are highly interesting and engaging. That’s not an interesting AI couch, it’s an interesting couch, full stop.


I would never live in one of your apartments


My disappointment is immeasurable and my day is ruined.


:) I'm sorry!


I am worried about information dumping -- just flooding the Internet with insane amount of AI generated data to drown the "real" data. And I dont mean "real" necessarily in a sense of genuine or man-made, but simply fake or slightly divergent. Imagine a world where only 1 out of 1000 news stories or tweets is real... the amount of damage you can do to institutions, democracies, causes... just continue fucking with people to the point where they have no idea what is real and what is fake and give up the truth-seeking altogether and give in to the loudest/most dominant narrative. Invest money into a an AI farm that just spits a fake every second and see if the fact-checkers and well-researched alternatives keep up.


You don't have to imagine that world, it is already here. The vast, vast majority of "news" sites out there is already straight up propaganda or ad-focused pseudo grassroots bullshit. Maybe not yet completely AI generated, but that seems like it would only be the cherry on top of the cake for the people behind it. We need solutions for this and not ways to prevent what has already happened.


There's so much low-quality content on the internet now - and it gets even worse in comment sections - that the only way you'll be able to detect if something is AI written if it's actually higher quality, or coherent.


True. That also requires a good portion of critical thinking and education in general, which is, let's be honest, rather rare in most comment sections. I fear that in the future we'll look at today's YouTube comment sections thinking these were the good old days ...


Sounds suspiciously like something a self-congratulating AI hiding among us would say..


People lying were always faster than those doing journalism. In the past you just followed sources you thought reliable. Then came social media, where reputation doesn't matter and the fastest wins, driving the current brand of "decline of journalism".

Inventing faster ways to lie won't meaningfully change the equation, the driving forces are the same.


Before printing was expensive, so you usually had some established company that could be liable for libel. Now the hosters are exempt (not necessarily the wrong choice), and have millions of publishing members posting stuff rapidly that you could never address with libel lawsuits.

Before people would maybe be talking and rumor slandering all over the place in person instead, but the literate-targeting part of media was operating under some ground rules for debate of at minimum no malicious libel.


I‘m not too worried about this because we already have this to an extend where it is required for a particular publisher to build up a reputation. People will learn to pay more attention to the reputation and publishers will apply more scrutiny in return


>People will learn to pay more attention to the reputation and publishers will apply more scrutiny in return

A subset of the people will but most will not. Right now obviously fake news stories are shared left and right, without even a modicum of rational analysis applied as to their plausibility.

The average person is simply incapable of rational thinking about anything that is not day-to-day and this will not change.


People run autoencoders on their own output all the time. It’s the most expensive way to generate a sinusoid.


Indeed, Neal Stephenson in _Anathem_ (2008), in describing an alternate world (in which his "reticulum" is our "network") wrote "Early in the Reticulum—thousands of years ago—it became almost useless because it was cluttered with faulty, sbsolete, or downright misleading information."

"So crap filtering became important. Businesses were built around it. ... " Generating crap "didn't really take off until the military got interested" in a program called "Artificial Inanity".

The defenses that were developed back then now "work so well that, most of the time, the users of the Reticulum don't know it's there. Just as you are not aware of the millions of germs trying and failing to attack your body every moment of every day."

As I review this now, I'm sad to realize that our flood of "bogons" (bogus information) is not generated by opposing armies wanting to plant misinformation but by advertisers, influencers, and politicians. In effect, those who want to sell us things we don't need, didn't want, and often can't afford.


The most valuable thing online in the next few decades will be authenticity. Authenticity is really the new luxury. The beauty of the early internet was its pure, passion driven authenticity. Websites sprouting up for every interest, built only because someone was driven to share their thoughts on a given subject. Forums, filled with techies chatting about their interests. Video games exploring interactive media and forming a new art. The rise of memes from places like 4chan, that have come to dominate digital expression.

All of these beautiful things have been degraded by the inauthentic, focus-group, advertising data harvesting machines of mega-corporate greed. Unique websites and blogs are drowned out into oblivion, unprofitable and hidden by the SEO Gods of Google, funneling you into their own products and advertising pathways. Forums bled out into Reddit, which is now an astroturfed corporate dream world where advertisers can masquerade as real users and corporate appointed moderators funnel all conversation into the optimum advertising framework--deleting anything that could harm reddit's shareholder pool of giant corporations and governments. Video games went from novel, artistic experiments, to hyper-optimized addiction machines built to drain the time, money, and drive from their young audience. Even memes, with all their raw vulgarity and juvenile silliness, have been coopted by corporations trying to bend this new form of expression to their advertising goals.

First, content online was authentic and human. Then, big tech started trimming and censoring and funneling and optimizing it into something less real... less human, but far more ripe for advertising revenue and data collection. Now, we are entering the stage of AI-generated content. Articles written by algorithm, art created by machine, bots filling up the whole internet with noise. The level of distrust, paranoia and questioning of reality that users will experience online in the coming years will be unparalleled. Is this image real? Is this person I'm talking to a bot? Is this artwork human made?

Which brings me back to my main point. Authenticity will be the new luxury. And the builders of tomorrow who figure out how to curate authentic online communities and experiences will be the winners in this content war.


Agreed on all points.

I'm a person that generally doesn't consume art, but if I did (let's say I was looking for artwork to hang at home), I would rather get 1 authentic hand-painted and hand-signed piece from a local artist than 10 digital AI-generated inkjet prints.

I wouldn't necessarily call it a luxury, more personal preference? Quality over quantity. There are some valid reasons to prefer one or the other, depending on circumstance.


Real art has intent, context and history that can't be replaced. It's everything that comes alongside a piece that makes it so interesting when you do actually buy a real piece of art, especially if you get to meet the artist.


There's a strong correlation between the early users of the internet and neurodivergent individuals. I'm one of them. We love to info dump, and the early web provided the perfect means to do so.


Perhaps someone will (or maybe it has already been done) figure out a business model for selling access to curated datasets that are known not to include a bunch of additional ML generated noise.

Although, to some extent I wonder how much it matters. If we're creating images using AI tools, and then sharing the best results, doesn't that become valid training data? In some sense are we supervising the learning?


>If we're creating images using AI tools, and then sharing the best results, doesn't that become valid training data?

Maybe in cases where those results are at least as good as the real thing. But in general, something being the best of some set of options doesn't imply that it's good, let alone perfect.

And besides, people will also share comically bad results.


Jokes on you, I already share the comically bad results of stuff I draw manually!


Maybe it'll be like pre-nuclear steel. Images created before the explosion of AI images contaminated the world will be sought after.


I do believe e.g. Google has datasets like that already. Some they offer to the public, but a lot they will keep to themselves.


Of course, as with all human cultural endeavours. The images published are also selected by human aesthetics and interest, so valuable novel information is still being propagated.


You’re exactly right of course. The hullaboo around it is the perfect amount for me to be a curmudgeon about.

I’m really looking forward to everyone realizing that there is a new baseline of capability, which is whatever amount above the old baseline, and that everyone ends up roughly where they started but with auto tune now.


I think the best analogy is hip-hop music.

Everything will become a copy of a copy of a copy until everything just sounds the same and looks like a parody of itself lacking the soul that made it attractive in the first place.


And then along comes Harry Mack.


I guess that's where the analogy falls apart.

It's possible to branch when you have an accurate history. As it is now all images are suspect.

Even an analogue photo could be a photo of a high res digital ai generated image.


Yeah I think our perception of what we're looking at will change. It will go from 'this is a viewport into some place in our world' to 'i can imagine this environment'.


The GOAT


Most music is like that, but my theory there is that you need a lot of generic music to make the original or good things stand out. To paraphrase Syndrome, when everything is great, nothing is.


Yes, that is what happens when big music takes an interest and everything is flooded. Same with beat, rock, punk, new wave, you name it. HipHop is alive and well, just need to know where to look.


Maybe everyone should stop mass-stealing media to "train their model"


That's a bit like saying that musicians should stop listening to music, painters should stop looking at art, directors should stop watching movies, authors should stop reading books.

Of course - we can control ourselves to not copy/plagiarize something, to some extent. As should deep learning models / generators. But we're all influences by someone else.


Yes but... as I mention in sibling post, all roads seem to end up profit seeking.

It will be much more profitable to train AI on what music is popular and sells well, then produce new music which is not close enough to be infringing while still fitting the success formula. This can be done so cheaply (and at some point will be fully automated... requiring virtually no oversight or review) that it can be sold at a fraction of the price of something which took human time to make.

Eventually the only way you'll ever be able to hear human music is to see a human play live or listen/buy directly from the artist. This seems doable, but finding the artists becomes the challenge. Of course we have the internet, so the obvious answer is to make a website to help listeners find artists (exists already, of course). But then, go back to the top of this comment and see how some "artists" (not real musicians, but people who see $ opportunity) will start producing non-human-generated music on that platform. They will sell it a bit cheaper. Algorithms will rank it higher in search or suggestion systems.

And eventually, there's no human music except live (which can be faked pretty believably depending on the audience).


>that it can be sold at a fraction of the price of something which took human time to make.

Isn't this the whole point of technological progress? I could buy everything handmade by artisans, but usually I buy mass-produced things because of cost.

> Eventually the only way you'll ever be able to hear human music is to see a human play live or listen/buy directly from the artist.

I would argue that for music this is already true. What you hear on Spotify is so mixed, leveled, autotuned, etc. that it varies massively from a live performance.


> the whole point of technological progress

I'm not sure there is an agreed upon definition of the goal of technological progress. And if there is, it must include some words that are subjective descriptions.

To use a rather absurd exaple, take John Cage's composition Silence. I'm no John Cage expert, but I expect that the composition (4m33s of complete silence) has some artistic merit in the context of the composer's life and other works. Obviously such a composition could be algorithmically generated virtually instantly, and thereby at virtually no cost - far cheaper than what John Cage's time was worth.

Part of what makes human creations so valuable is that they are a form of communication from one or more people to other people - specifically or generally. Or sometimes they are a kind of self-communication, where the artist is creating as a form of self discovery. Those who experience the creation may find their own value, or they may find value in vicariously experiencing the artist's journey.

To eliminate the human from the creative side and replace them with largely unguided software is kind of eliminating the point of a lot of art... to me at least.

The goal of technological progress as I see it is to aid us in our efforts to do things. It might help us never run out of toilet paper. It might help our car burn less fuel and require less maintenance. It might identify patterns of biometrics and movement which indicate a likely impending medical emergency. I can think of a ton of things which represent significant value from technological progress. Replacing artists and creators is not on that list, or at least not anywhere near the top.

> What you hear on Spotify is so mixed, leveled, autotuned, etc.

Mixing is good; nearly all music needs mixing to balance the inputs and adjust for acoustics of the environment. That's also mostly a human-driven job still (although the software aids are pretty useful in some cases).

Autotune is also a human choice (one which I dislike, but it's not me making the music... so not my choice).

Studio albums made available on Spotify are pretty much just what the artist or record company released. That's not some kind of AI thing.


You mean like humans steal media of everything they observe in life, automatically assimilating and adapting their processing (thinking)?

Training models is not the problem. Mimicing or reproducing through algorithms of human creative work and then passing that off as human created work (which implies time cost, as most humans take significant time to develop skills which allow them to create things) is the real problem.

Already we have "content" on Youtube which is entirely or almost entirely AI generated. Like processed foods, it tends to be hollow and non-nourising to the consumer, but it competes for shelf space with potentially better content. As we capitalistically race to the bottom, the cheap AI-created stuff will be so pervasive that real offerings which cost real money (time) to make will have no space to compete. Consumers will be left with the cheapest garbage which resembles something real. This is what you find in many stores for physical products, and the TV series-ication of video content. Formulas which maximize profit squeezing out real things.

This is how the AI models will increasingly be used, and there's basically no stopping it. I would say that using "indie" services where things are hand/human-made would be an alternative, but Etsy has proven that that approach eventually devolves to the profit-garbage approach.


> This is what you find in many stores for physical products, and the TV series ication of video content.

Shelve space is limited and TV production is quite expensive, thus, risk averse. It's more like a music store with everything, up to you to find what you like.


> risk averse

I understand it is economically better overall (less chance of huge reward, but also much less chance of failure and huge loss) to churn out series using one of the formulas for various genres. That's kind of my point, too. It's not about artistry or telling a story as much as it is about reliable profit. And that's why our content becomes more and more similar and more and more "reliable".

Maybe in a few years there will be another Blair Witch wildcard that will draw a stark contrast from the monotamy that we have. And then the production companies will be hard at work trying to figure out how to recreate whatever the new cool formula is, resulting in a race down a different path to the same bottom.


And maybe the same could be said about stealing code too


Maybe the ArtStation crowd needs to start acting more like the GPL crowd.

Build a platform where to view content on the platform you have to agree not to use it for training data and to take action against companies where their work turns up as model output.


its mass-borrowing


This reminds me about Google's paper titled "Machine Learning: The High Interest Credit Card of Technical Debt"

https://research.google/pubs/pub43146/

Abstract: Machine learning offers a fantastically powerful toolkit for building complex systems quickly. This paper argues that it is dangerous to think of these quick wins as coming for free. Using the framework of technical debt, we note that it is remarkably easy to incur massive ongoing maintenance costs at the system level when applying machine learning. The goal of this paper is highlight several machine learning specific risk factors and design patterns to be avoided or refactored where possible. These include boundary erosion, entanglement, hidden feedback loops, undeclared consumers, data dependencies, changes in the external world, and a variety of system-level anti-patterns.


If a human cannot distinguish between a real image and an AI-generated image and the AI-generated images are manually labelled, then there is no problem?


It's a great question that brings me to two follow up questions:

1. The actual pollution happens in culture (our imaginary) and, as history shows, censorship (cultural via cancellation, or legal via politization of the issue) is not a moral nor practical solution. Then, high culture and filtering technology to the rescue?

2. Images are just the start as Murphy's Law ensures we'll face this same problem for every categorizable piece of knowledge you can think of using in an AI artifact (music, patterns of movements, speech recognition, behavior recognition, art recognition, etc)


that quote from Matrix: "Which is why the Matrix was redesigned to this: the peak of your civilization. I say your civilization, because as soon as we started thinking for you it really became our civilization, which is of course what this is all about. " [0]

I wonder how soon we'll reach "peak human creativity", and start to see people creating less art, music, fashion, code, because there's no point competing with AI-generated content.

[0] https://www.imdb.com/title/tt0133093/quotes/qt0324293


A dream come true for social engineers with owning power.


Possibly, but should be easy enough to exclude.

For example Dall-e has the pixels watermark (bottom-right), and I assume there's a possibility of an indicator that may by hidden in the data itself. One could also exclude common meme formats and their derivatives. Then there's the option of mapping to produced content via hashing a la Shazam, or have a discriminator component etc.

But you're right, it's not trivial. I just don't think it's too big of a deal.


You're assuming a _voluntary_ action _can_ be done. This won't happen, Lazy humans will feed non-aware AIs.

The OP is asking if s.o has "already thought of such an issue"


While automatic data collection might become harder, one can still curate high quality datasets. An example is Tesla's FSD autopilot which is nearly entirely trained on curated data (AFAIK), as well as highly realistic 3D simulation data. Sure, it is expensive, but the expected returns are also very high.

However, there is some evidence that NNs currently are somewhat limited by the availability of high quality data,[0] however I'm not sure this is really a problem because neural nets already accomplish amazing things, so one might not need that much data to get something useful (perhaps at the expensive of more compute, but so what; e.g. analog computing might give some 1000x speedup anyhow).

[0] https://www.lesswrong.com/posts/6Fpvch8RR29qLEWNH/chinchilla...


One thing I've noticed that no AI tooling company is building is a good/easy to use feedback loop. A high quality model needs a lot of human feedback. No one is really building a strong platform to do that. But eventually someone will have to fill that gap


With all these ai generated images, the only thing I don't want is the younger ones quiting drawing, ditching the pencil for an app, loosing the motivation for hand drawing because using these programs are easier and faster. It would be a sad world.


I think it's going to become a cat and mouse game. AI generated images (e.g., deep fakes) are already being used in very nefarious ways such as job interviews, applying for gov't documents via video, etc.

Researchers are finding ways to identify the tale-tell markers that currently give them away, but yes, for the neophyte this is going to be a real issue on what can I trust.

However, the great thing is that you will always have data...the challenge will then become how well do I TRUST my predictions, which I believe will spur some very interesting algorithms such as anomaly detection (i.e., the RGB distributions, spatial-markers, etc are way too distorted if I compare metadata from other pictures of this type).


I’m hopeful it will ruin the business model of privacy rapists like Clearview AI.


Can the AI come up with novel faces? A lot of the faces I've seen from SD are just slightly modified Emma Watson faces.


Dall-E doesn’t have to generate Emma Watson:

https://i.imgur.com/4YHP5GI.jpg

https://i.imgur.com/vAIIhwF.jpg

https://i.imgur.com/HgIWb7C.jpg

https://i.imgur.com/nEQzPJm.jpg

https://i.imgur.com/WUxIefs.jpg

https://i.imgur.com/YEcGTk3.jpg

https://i.imgur.com/elnyzvF.jpg

https://i.imgur.com/KQH93nV.jpg

https://i.imgur.com/RLhmSDM.jpg

https://i.imgur.com/6UB9Mdc.jpg

https://i.imgur.com/W2JgDLa.jpg

MidJourney can trend (sorry) that way, though:

https://i.imgur.com/UVQBKoJ.jpg

https://i.imgur.com/xxoJBoh.jpg

// all prompts by me, hallucinations by indicated


The GAN stuff[1] looks pretty darn good; granted this (and my comment) only applies to faces of people, not necessarily to other types of images as the OP asks.

[1]https://thispersondoesnotexist.com


First, it’s probably quite possible to train a network to filter on AI vs. human generated. There are many visible signs for the untrained eye and probably many more that are not visible to humans but can be picked up from the correlation.

Secondly, there is still a big human selection process going on. Only the most interesting and coherent images will find their way onto the public internet. In fact, if you can automatically detect that these images are AI, then they can serve as an additional training signal to help teach the AI which of its outputs are most likely to delight the human.


> Secondly, there is still a big human selection process going on. Only the most interesting and coherent images will find their way onto the public internet.

That's rather optimistic. Plenty of low quality images are generated and posted to the public Internet.

What is true is that most of that generated junk doesn't have much of a shelf-life, which reduces the odds of it making it into the training data.


It’ll make some naive approaches work differently, but it’s overall more info: both the selection effect of what images humans share, and the surrounding context (eg what comments are people making about the image)


> They could be mistaken for real photograph or real work of (digital) art by a human. Especially by an algorithm.

Perhaps by a naive algorithm. I'm fairly sure it's fairly easy to train a neural network to recognize current generation AI generated images. And probably for quite a while longer.

Btw, if you want to create realistic images, it's fairly easy to create guaranteed pristine data: just take a video camera and create some footage.

Perhaps there will even be a market for such pristine data.

Now, if you want to create art and train on human artists' output, that might perhaps get harder in the future.


> I'm fairly sure it's fairly easy to train a neural network to recognize current generation AI generated images.

Could you explain how this is done and why it's easy?


You get a corpus and do some supervised learning.

Why do I think it's easy: the goal of current generation AI image generation project was just to produce images that look good to humans. Not to be indistinguishable.

Even for casual human observer, they are still relatively easy to spot. A trained machine that can pay more attention to details should do even better.

In some sense, this is just the same idea as a GAN. Only that the generator is fixed, and we are only training the discriminator.

With future systems, distinguishing them might be harder.


LOL, Malkovich ... Malkovich, Malkovich.

https://www.youtube.com/watch?v=Q6Fuxkinhug

Starring Malkovich, as, Malkovich.


LOL it would be funnier if this pollution wouldn't be about to become tragic.


It should be easy to train a discriminator that can tell the difference well enough. And if it misclassifies an image then using it for training should be fine :)


I’ll pose a mental model which is more than a bit simplistic, but I’ve watched big models in feedback loops before and I feel that the intuition is fundamentally sound.

There is sort of a fixed-point on this stuff that creates a Nash point. Every relevant move is a move for some advantage (from megacorp copyright laundering to aspiring influencer content output) and that competition tends to wash out roughly where you started.


What are the AI vs AI game-theoretical implications of cultural or strategic development?


It’s very boring really. All of the actors involved are striving for notability, which is kind of a proxy for primal urges around status/reproductive eligibility, and once everyone is tuning up their profile with the same net, it gets a bit random at best.


Actors might be boring but speculation about the topic is endless.


I think it's likely that AI can recognize AI generated images.

This would mean it's always likely to be filterable.

And if not, it's arguable that this pollution becomes an asset. It would be high quality synthetic training data which is commonly intentionally used.

It would also be possible to look for the metadata that accompanies photos taken on phones etc. and weigh that more highly.


An AI that recognizes AI generated images would be a great tool for training an AI that produces images that won't be recognized as AI generated images via GAN, no?


I actually think it's likely that part of the next generational leap of these models is using the images people chose to export and feeding them back in as training data.

They more likely represent high quality feedback (essentially labelling the output) than pollution.


AI-generated media in general will likely plunge us into a new dark age. Every report you see on the news, every "secret recording" of a politician doing something dodgy, will be either an AI generated fake or considered as such by many viewers. Nothing will be certain anymore and MSM have already lost their credibility for many viewers.


Probably, but I don't think it'll be a huge problem. Firstly, we want to be able to identify generated images for much more important reasons anyway, and secondly, the importance of training data might decrease as those systems mature and move to less supervised training methods.


People will post more generated images that they consider good, than bad, thus improving the dataset.


However, this has its own issues in terms of bias; what if you really like HR Giger's work, but this label of "good" is made synonymous with "pretty" or "inoffensive"? I wouldn't fully trust human input into these things.


What is that "good" you are referring to when the "goodness" notion is being broken by noise in intelligence itself?


Good = label corresponds well to data


If you go deep, you'll find that's still an insufficient imprecise and ambiguous definition. You just reframed the question by delegating that judgment to the dependency on "corresponds well" maintaining the ambiguity, vagueness and imprecision.


There is no ambiguity about calling a dog a dog being better than calling a cat a dog.


I'm sure it has been done before, but, has anyone ever generated a set of machine learning generated anythings (images, text, whatever) and used it as the learning set for a new ML thing?

Then again, and again, and again, until we end up in the 10th dimension of AI surrealism.


One examples of this is back translation [0]

It works fairly well as model size increases

Also, shameless plug, we're pretty proud of our generated anything's at Gretel[1]. It's tabular, text, and time series for now - but we recently had a blog post that shows how generated data can be useful for downstream ML [2]

[0] https://arxiv.org/abs/2110.05448

[1] https://gretel.ai/

[2] https://gretel.ai/blog/how-to-safely-work-with-another-compa...


> https://gretel.ai/

Where were you the last decade of my professional life?

I couldn’t find anyone to take my money for exactly this.


I look forward to the "pollution", personally

This is not in denigration of human artists, photographers, etc

I think it'll drive artists to make better/different work (just like the advent/adoption of the vanishing point changed art ~500-1000y ago)


I don't think so - they'll probably ensure enhance it. An AI draws something, people describe what they actually see, the AI is now refined in what it should produce for a given prompt (and moves away from the original prompt).


Yes, it will pollute the training data from todays perspective. In future, I don't think that people will care. It is a shame that there is no metadata embedded in AI generated images so that they can be distinguished.


No, just create an image service like Getty or Shutterstock where human made images are uploaded for the sole reason of selling those images to AI companies who want to train their networks with organic material.


Algorithms of AI can generate images or videos based on a set of parameters or it can create new images by combining and altering existing images.


I am curious how do these AI get the data sourced?

Is it the free floating images on the internet or is it the data that we keep on the servers of the BigTech?


Bit of column A, bit of column B; I'm confident that Facebook and Google have huge datasets of people's personal information and photos, but they will not use them in anything public facing, because they know this scares people and will cause huge lawsuits.

So for the public image generators, they will use public images; I believe places like artstation and flickr will be used a lot. Also because they will include metadata, either on the descriptions or in the photo's metadata, about the location, scene, setting, camera, etc.

Then (and I'm mainly thinking of Dall-E here) there's other open caches of data, like collections of artwork along with intricate descriptions of what they depict.


Thanks for answering. If its Publicly sourced data. There is huge opportunity for some create a DATA DAO where data better labelled and people can use their data to use the AI for their usecases.

What do you think of challenges for such use cases?


If a human would label the AI-generated image exactly the same as if it was a real image, then there is no problem?


I think each AI generated image should have a steganographic signature with data on the system generating it.


If they are mistaken for real photography then mission fucking accomplished. https://xkcd.com/810/

Jesting aside, if the resulting image is good enough to publish and tag, then it's good enough to put back into a training set.

I also assume there could be a market for AI trained only on "human produced art" the same way there's a market for organic vegetables.


Yes, in the same way that algorithms influence human decisions.


there will be no longer "training data" , that is, large datasets. People will finetune their models to add specific new subsets of images


That should be an add-on to licenses: You are not allowed to use this works as part of a training set for AI/ML.

That would work beautifully for text, code and images.


imo no. Just use existing image sets to train future models if this becomes too big of a problem.


I think that all the future deep learning will be trained to fresh data, crowdsourced from billions of humans. Humans will be expected to photograph a door knob, from a distance of 20cm, a height of a meter from the floor etc.

If a billion humans take 50 photos like that, and spend fifteen minutes of their life to do so, we will have almost as much data as the Laion database, but for door knobs. The photo workers will be paid something like 0.00001 dollar for a picture, by the users of the deep learning algorithms.

The payment method is called blockchain and bitcoin if you have heard of such a thing. Bitcoin, the money of information will enable a marketplace of information, in which the better the information, the more the producer is paid. Bitcoin bsv, can support almost a million transactions per second as of today, and every year the tps is increasing tenfold.


> The payment method is called blockchain and bitcoin if you have heard of such a thing. Bitcoin, the money of information will enable a marketplace of information, in which the better the information, the more the producer is paid. Bitcoin bsv, can support almost a million transactions per second as of today, and every year the tps is increasing tenfold.

That's worded needlessly condescending; come on, bitcoin has been around for over a decade, nobody on this site has NOT heard of it. You're coming across as preachy as if it helps sell the flawed technology.


Yes i thought it sounds a little bit funny that way. Thanks for the comment btw.

Actually what i am referring to, is a blockchain which can support billions of tps, trillions and quadrillions tps. Image data needs to be literally a monster amount! BTC which is the name of what you are referring to, it can support only 10 tps.

Have you heard of a company which sells shoes, known by the name of Adidas, and another company which sells shoes as well, known by the name of Abibas? Btc is the Abibas of blockchains!


Hello, GPT-3.


Actually is used GPT-3 to create my own text, to make fun of the covid hoax and many others. How did you know? lichess/ emporas/blog.

The next on the list to make fun of, is the legacy economic system!




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