I remember reading somewhere, maybe in an essay by John Updike, that Abstract Expressionists like Jackson Pollock, who aimed to produce purely nonrepresentational paintings, had to be careful that face-like figures did not appear in their works unintentionally. They wanted to create art that had aesthetic value without recognizable images, and the effect they were seeking would be destroyed by an accidental smiley face or two among the vigorous brush strokes and dripped paint.
I use midjourney to create images inspired by abstract art and I usually add '--no person' for this very reason.
(I wanted to avoid the phrase 'create abstract art' since I don't want to claim that it actually is art (at least I wouldn't want to claim so here on HN))
A friend in primary school used that to create comic faces: doodle randomly, find a face in the tangle and perfect it. Usually they were profiles with large noses and other exaggerations. Quite entertaining.
That reminds me of the difficult constraint they must have had in making art and architecture for the game The Witness: nothing could ever accidentally seem to be, from any viewing place, one of the world's simplest shapes. Only by design.
Huh, an image search for "plaster painting" turns up lots of people doing basically stucco bas-relief, like back in antiquity. I had no idea this was trendy.
This sounds a little like it might be related to how adversarial images work, because it sounds like the same kind of idea - you trick an image classifier into believing that it sees something that isn't really there.
In a way, I guess pareidolia is just our version of adversarial images - It's just that we ascribe more obvious things (things that look like eyes, noses, mouths, etc) to the reason why we see faces, whereas I imagine an image classifier just happens to see random pixels that are the same or something like that.
I must link https://www.reddit.com/r/Pareidolia/ for anyone who likes findings faces in random places. There was another sub about things we see in clouds, can't find it.
Just the other day I was at the Mille Lacs Indian Museum in Northern Minnesota. It has a really beautiful and well put together feature showing a collection of full sized Wigwams across the seasons.
One of the wigwams for the Winter season had a very large piece of birch bark with a very obvious face in it. It was so obvious that I thought it had to be some sort of Easter egg by the museum.
Pointing it out to my wife however, she couldn't seem to see it. She was like "maybe it looks like a face if I really try". Brain really plays tricks.
This is exactly what CNNs do. Recognize patterns in transferrable areas of images. Once that feature map is generated, successive layers just look for the same patterns. We see patterns in faces, and so does AI if it uses a CNN or CNN-like model.
There's an area of the brain called the fusiform face area which, despite its name, may actually be an area that's involved in visual expertise rather than faces per se: https://en.wikipedia.org/wiki/Fusiform_face_area
This is interesting in that I imagine this is similar to visual expertise rather than faces as such - I presume you could train a model to see areas of images as birds in the same way.
Trying to suggest a serious link between the two is a bit ridiculous - rather like the idea that plants which look like dogs can heal dog bites (which is itself a form of over-recognition!) - but I find the parallel curious.
Back in 2018, I ran a little test to see if I could push Google Cloud Vision to recognize objects, shapes, or patterns in clouds. No matter how I treated the images ahead of time, the answer always came back: clouds.
Would be interesting to see how much free-association and hallucination have "improved" the results with the current generation.
The image recognition of google at 2018 most certainly was trained on a database of labelled images, and I would bet that the labels should have been short and distinct, not "a cloud with a vague representation of Bruce Willis' face" !
I used to be so good at this. Then I started smoking cannabis. Then I became ultra good at this. Stains on walls became unbelievable works of art. I miss those days. I also use to hear symphonies in my brain as I’d fall asleep. Crazy, except it was beautiful
A large part of the brain is used for face recognition. There are dozens of regions each dedicated to process one feature of the face. The brain is also a generation machine. With only a few features recognized the brain can generate the rest of the face features, thus recognizing it as a face.
as a potential step up from overly sensitive pattern matching: somewhere I ran across the idea that our close primate relatives enjoy sleight-of-hand magic tricks, but more distant ones do not.
Next series: You should take probiotics for your gut bacteria and so should AI (sponsored by nature.com and Yakult[tm]).
What is even science-worthy about this? If you can see a face in a cartoon drawn with a few lines, then those lines may appear in a cloud, stone, whatever. News at 11.
I wonder how much further along we will get creating human-like intelligences until Occam's razor suggests that the (in evolutionary scale) sudden emergence of human intelligence ~20,000 years ago was the result of the efforts of an intelligent force
Human intelligence arose slowly, over multiple species adaptions, and much longer ago than 20,000 years. For example, cooking predates modern humans[1] by at least hundreds of thousands of years.
Please provide a simpler explanation than “species begins eating calorically dense food, increasing brain size, and becoming smarter”. Your supposedly simpler explanation must involve an unknown outside intelligence of some kind. I’ll wait.
Because it begs the question, do you have intelligent beings designing intelligent beings all the way down? An infinite regression of writers writing writers?
This is one of the biggest mistakes in reasoning people make, they come up with fantastic explanations that require fantastic explanations, solving nothing. People like you are really INTERESTING.
I remember reading somewhere, maybe in an essay by John Updike, that Abstract Expressionists like Jackson Pollock, who aimed to produce purely nonrepresentational paintings, had to be careful that face-like figures did not appear in their works unintentionally. They wanted to create art that had aesthetic value without recognizable images, and the effect they were seeking would be destroyed by an accidental smiley face or two among the vigorous brush strokes and dripped paint.
I use midjourney to create images inspired by abstract art and I usually add '--no person' for this very reason.
(I wanted to avoid the phrase 'create abstract art' since I don't want to claim that it actually is art (at least I wouldn't want to claim so here on HN))
Claim away, but in no universe is it your art.
Says who?
That's happened to me with ordinary landscapes sometimes. Viewers: "there's a face in the clouds". Shit.
The number of mountains named for the shape of a lady indicates plenty of us get confused like this all the time! ;)
A friend in primary school used that to create comic faces: doodle randomly, find a face in the tangle and perfect it. Usually they were profiles with large noses and other exaggerations. Quite entertaining.
That reminds me of the difficult constraint they must have had in making art and architecture for the game The Witness: nothing could ever accidentally seem to be, from any viewing place, one of the world's simplest shapes. Only by design.
This annoyingly persists in one of the first of a series of my large format plaster paintings
My youngest daughter loves it so, I’m stuck with it luckily
Huh, an image search for "plaster painting" turns up lots of people doing basically stucco bas-relief, like back in antiquity. I had no idea this was trendy.
This sounds a little like it might be related to how adversarial images work, because it sounds like the same kind of idea - you trick an image classifier into believing that it sees something that isn't really there.
In a way, I guess pareidolia is just our version of adversarial images - It's just that we ascribe more obvious things (things that look like eyes, noses, mouths, etc) to the reason why we see faces, whereas I imagine an image classifier just happens to see random pixels that are the same or something like that.
I must link https://www.reddit.com/r/Pareidolia/ for anyone who likes findings faces in random places. There was another sub about things we see in clouds, can't find it.
Just the other day I was at the Mille Lacs Indian Museum in Northern Minnesota. It has a really beautiful and well put together feature showing a collection of full sized Wigwams across the seasons.
One of the wigwams for the Winter season had a very large piece of birch bark with a very obvious face in it. It was so obvious that I thought it had to be some sort of Easter egg by the museum.
Pointing it out to my wife however, she couldn't seem to see it. She was like "maybe it looks like a face if I really try". Brain really plays tricks.
This is exactly what CNNs do. Recognize patterns in transferrable areas of images. Once that feature map is generated, successive layers just look for the same patterns. We see patterns in faces, and so does AI if it uses a CNN or CNN-like model.
There's an area of the brain called the fusiform face area which, despite its name, may actually be an area that's involved in visual expertise rather than faces per se: https://en.wikipedia.org/wiki/Fusiform_face_area
This is interesting in that I imagine this is similar to visual expertise rather than faces as such - I presume you could train a model to see areas of images as birds in the same way.
Trying to suggest a serious link between the two is a bit ridiculous - rather like the idea that plants which look like dogs can heal dog bites (which is itself a form of over-recognition!) - but I find the parallel curious.
Back in 2018, I ran a little test to see if I could push Google Cloud Vision to recognize objects, shapes, or patterns in clouds. No matter how I treated the images ahead of time, the answer always came back: clouds.
Would be interesting to see how much free-association and hallucination have "improved" the results with the current generation.
Your problem was right there in the name - google "cloud" vision.
I think it highly depends on the technique.
The image recognition of google at 2018 most certainly was trained on a database of labelled images, and I would bet that the labels should have been short and distinct, not "a cloud with a vague representation of Bruce Willis' face" !
I used to be so good at this. Then I started smoking cannabis. Then I became ultra good at this. Stains on walls became unbelievable works of art. I miss those days. I also use to hear symphonies in my brain as I’d fall asleep. Crazy, except it was beautiful
It sounds like it was temporary. Did you stop? Did it stop working? What happened?
A large part of the brain is used for face recognition. There are dozens of regions each dedicated to process one feature of the face. The brain is also a generation machine. With only a few features recognized the brain can generate the rest of the face features, thus recognizing it as a face.
With generative AI, it works the same way.
But does the “AI” realise these aren’t real faces?
as a potential step up from overly sensitive pattern matching: somewhere I ran across the idea that our close primate relatives enjoy sleight-of-hand magic tricks, but more distant ones do not.
There's a related line of research that concerns computer vision models and optical illusions.
pareidoilia are a natural side effect of any pattern recognition machine
I imagine faces on the fronts of people's heads. I know that this is common. Is this a consensual hallucination?
One half of the entire basis of modern machine learning is creating algorithms capable of reaching the pattern recognition levels of humans.
This is a given.
Next series: You should take probiotics for your gut bacteria and so should AI (sponsored by nature.com and Yakult[tm]).
What is even science-worthy about this? If you can see a face in a cartoon drawn with a few lines, then those lines may appear in a cloud, stone, whatever. News at 11.
I wonder how much further along we will get creating human-like intelligences until Occam's razor suggests that the (in evolutionary scale) sudden emergence of human intelligence ~20,000 years ago was the result of the efforts of an intelligent force
Human intelligence arose slowly, over multiple species adaptions, and much longer ago than 20,000 years. For example, cooking predates modern humans[1] by at least hundreds of thousands of years.
[1]: https://en.wikipedia.org/wiki/Cooking#History
I’m not sure you understand Occam’s Razor. What you are proposing is absolutely not the simplest explanation.
Why not? Whatever your bayesian priors are, they certainly don't match mine.
Please provide a simpler explanation than “species begins eating calorically dense food, increasing brain size, and becoming smarter”. Your supposedly simpler explanation must involve an unknown outside intelligence of some kind. I’ll wait.
Because it begs the question, do you have intelligent beings designing intelligent beings all the way down? An infinite regression of writers writing writers?
This is one of the biggest mistakes in reasoning people make, they come up with fantastic explanations that require fantastic explanations, solving nothing. People like you are really INTERESTING.