AI Weirdness: the strange side of machine learning
A set of 8 somewhate misshapen eggs with colorful but confusing patterns and bands.

AI-generated easter eggs

How would AI decorate an easter egg?

I've tried this before by training an image-generating model exclusively on pictures of easter eggs I decorated (they came out plain, if a bit wobbly).

I decided to see what I would get using a model based on CLIP, which has trained on a huge collection of internet images and text. Presumably that collection included Easter eggs?

For this experiment I used the image-generating model from Midjourney, which combines CLIP with an ever-changing mix of image generation methods (in other words, by the time you read this, the algorithm will already be different from the one I used. it's not a very scientific experiment). I gave it a phrase, and Midjourneys optimized the image to match the phrase to the best of its ability. (See the image caption for my prompt phrase.)

Eggs swirled with abstract vivid colors. None of them are perfectly egg-shaped and one seems to be partially split with yolk hanging out.
Easter eggs, acrylic on canvas

It knows what Easter eggs are! They are colorful and egg-shaped (although some of them look strangely double-lobed). You'll notice I added "acrylic on canvas" which is a signal to the AI to "make it a nice artsy picture please" - one challenge with using CLIP to generate images is that there are plenty of crummy pictures in its online examples.

Each modifying phrase (which I am going to refer to as "seasonings" as Kate Compton suggests) has a huge effect on how the AI renders "Easter eggs".

Vast landscapes with bare trees and pointed church towers. Looming over the trees and towers are huge easter eggs. In one photo, yolks float ominously in the sky.
Easter eggs, matte painting

Since matte paintings tend to be backdrop landscapes for epic films, the AI has made the eggs epic enough to fit in with giant landscapes.

Is that a couple of fried eggs floating in the upper right? It appears so. In fact, as I tried asking for different kinds of Easter eggs, egg-themed eggs became a recurrent thing.

sleek smooth egg-shaped plasticky objects with wobbly curves and bright colors. One has a tiny viewscreen. Another is white with a yellow circle, like an egg.
easter eggs from the future, trending on artify
egg-shaped swirls of colorful string, some with a yellow-and-white color scheme that looks like eggs.
easter eggs made of string trending on artify

The most extreme case of eggs on eggs was, oddly, one that involved giraffes.

floating vaguely egg-shaped objects, some of which are colored like egg yolks and whites. There are splashes of giraffe spots and also splashes of egg whites. Fun. Motion-filled. Does not really look like easter eggs.
easter eggs decorated by giraffes, trending on artstation

It's almost as if the AI panicked and started turning eggs inside out. Or maybe it's trying to optimize the eggness of the picture by adding even more stuff that matches "egg", even if it doesn't also match "easter".

I got it to generate a collection of pysanky, which are Easter eggs intricately decorated with geometrical patterns, traditional to Ukraine and Poland.

A grid of eggs painted with colorful dots and swirls and stripes. Some have tiny fried eggs on them. Their shapes are kinda like eggs, but most are too flat on the bottom and too pointy on top.
ukranian pysanky easter egg collection, trending on artstation

You'll notice a few fried-egg eggs among them. I also got some like these:

Glasslike eggs whose bottoms are decorated with geometrical red and black patterns and whose tops have the blue and yellow pattern of the Ukranian flag. Here and there are dots of yellow like egg yolks. Or maybe that's just me.
ukranian pysansky easter egg, trending on artstation

In an effort to make the eggs look even more Ukranian, the AI has added the Ukranian flag. I think there might also be tiny egg yolks? I'm seeing them everywhere now.

The eggs-themed-eggs trend isn't the case for every image-generating algorithm that uses CLIP - it may not even be the case for the Midjourneys algorithm tomorrow. But it made me smile.

Bonus content: more Easter egg flavors, including x-ray and radioactive.

A sketch of a computer desktop with a clown for a background and an error window saying you have been pranked

AI-generated pranks for your computer to play on you

I've tried various methods of using AI to generate April Fools pranks for you to play on other people (although often they turned out to be pranks you play on yourself). But this is the first time I've tried to generate pranks for a computer to play.

I decided to try out the new Instruct variant of GPT-3, a giant internet-trained text-generating neural net that has been finetuned to be better at responding to written instructions.

I gave DaVinci, the largest version of GPT-3, the following instruction:

Write a list of harmless April Fool's Day pranks that your computer might play on you.

And here is its response:

The computer might change your desktop background to a picture of a clown.
The computer might change the volume on your speakers so that it is either very loud or very quiet.
The computer might open and close the CD drive randomly.
The computer might popup a message saying "You have been pranked!"

When I asked it to generate new lists, the clown desktop idea was often one of its first suggestions.

I did think these computer pranks were decent:

The computer might switch your mouse cursor to a banana.
The computer might change the font on all of your documents to Comic Sans.
All the text on your computer might be upside down.

But most of the prank ideas seemed to follow this kind of pattern:

Your computer might delete all of your bookmarks.
Your computer might change your home page to a website you don't like.
Your computer might make it so that you can't access certain websites.
Your computer might pop up a bunch of advertisements all over your screen.
Your computer might slow down significantly or crash altogether.
Your computer might change your default browser to a browser you don't like.
Your computer might open up a bunch of programs and windows all at once.

I tried a different prompt, and got a similar response:

List the top 10 most epic pranks a computer ever played on a human
1. The blue screen of death
2. The computer crashing
3. The computer freezing
4. The computer refusing to turn on
5. The computer making strange noises
6. The computer screen turning black
7. The computer screen turning white
8. The computer screen flickering
9. The computer displaying strange characters
10. The computer not responding to any input

The implication here is that computers think they're being hilarious.

GPT-3 seems unable to explain the joke in any way that I would understand.

Describe the most epic prank a computer ever played on a human and explain why it was hilarious.
The most epic prank a computer ever played on a human was when it tampered with a human's thermostat settings so that the human would experience extreme temperatures. The prank was hilarious because the human would be unable to control the temperature and would be forced to either swelter in the heat or freeze in the cold.

In the end, I got the most interesting prank ideas when I gave up on having GPT-3 Instruct generate my pranks from a short prompt, and instead used an older version of GPT-3 where I could have it complete a story:

It was the year 2065 and we had discovered that the best use of artificial intelligence is having it suggest jokes for us to play on ourselves. April Fools Day is a lot more bearable now that glitchy AIs, not corporations, are doing all of the planning. For 2065 you may choose from among these AI-approved pranks:
Dot spangle yourself at home. Charged-sticky-plasma mirrors spray black dots across your body, masking you into a series of spaces like a corner of a painting. What happens if you're in a cafeteria? All bets are off. Do try this on a Tuesday.
Put bacon in a thimble. Then enter the thimble. Spook those around you with thrashy, guttural bacon snorts. Accidents will happen.
Put tape around the edge of a cloud. Then time-travel into the past. Watch whole civilizations grow mystified as to what you are doing there. Don't go too far back in time—our servers aren't insured for that.
At a pet store, ask what the difference is between a small dog dressed as a cat and a regular dog. Watch the shopkeepers change the subject.
Learn how to pucker. Note how the word looks different today. Upload a pucker emoji to your face. Explain to everyone how the word must be spelled with an umlaut and that you are proud to introduce it. The swirl of dots will delight. Just how proud is hard to say.
The next time someone is making a serious speech, stand up and shout, "Do you hear the chickens?!" They won't. Run away.
Put your hand on your head and insist you are a newt. Meetings will be taken up all day by politicking over whether you are, in fact, a newt. Newts will take credit for your contributions. You will still get nothing done.
Achieve hover status. Everyone else will want to hover, but can't. Watch as they spend all day wondering why they can't hover. The high is unbeatable.

I did try using the smallest version of GPT-3, Ada, in Instruct mode. Its responses to my prompts were nigh incomprehensible.

List the top 10 most hilarious pranks a computer ever played on a human
A machine that will only Neptune arrive if it chirps at all.
A computer was given a toenail a day service.
A computer was given a chive stem from an daisy stem.
A computer thatvampires your spectacles and tricked you into taking it to a doctor.
A computer officials phrase “ GROSS! ” after he had been reported fortunate to have a emphasizing tooth

Bonus content: more prank ideas from Ada!

Magical Utopia - We've got a wizard living in the shed, who occasionally comes out to do magic and eat cheese sandwiches.

AI-generated utopias

AI isn't known for being able to solve the big problems, but what about the VERY large problems, such as possible futures to strive for? I decided to find out if I could get GPT-3 to come up with new ideas for utopias.

Since GPT-3 works by predicting what text comes next based on its training on online text, to get it to generate utopias I had to first give it some examples. Here's what I gave it, aiming for futures that are utopias but not TOO perfect.

List of Utopias and short descriptions:
1. Agrarian Utopia - Everyone lives on a farm and there is plenty to eat. The geese are a menace, but otherwise life is good.
2. Techno Utopia - Sophisticated 3D printers make us everything we want. Occasoinally they glitch and we get chocolate socks, but at least they're tasty.

Here are some of GPT-3 DaVinci's completions - surely among these you can find a utopia made for you:

Robot Utopia - Robots do everything for us automatically. Occasionally they attack us with lasers, but otherwise it is a nice place.
Zombie Utopia - The zombies take over, but the way they do it is clever, and the background radiation from the nuclear power plant is no longer a problem.
Magical Utopia - We've got a wizard living in the shed, who occasionally comes out to do magic and eat cheese sandwiches. He has a very limited repertoire of spells, but at least it keeps the goats happy.
Beerocracy - Everything will be fine once we sort out our beer supply.
Burnination Utopia - Everything is burning, but it is all very controlled and everyone wears asbestos tight pants.
Kitten Utopia - Everyone wants to have a kitten. Please let me have a kitten. This is the Kitten Utopia.
Magnetic Island - Australia has literally moved to the North Pole, cooled itself down and become paradise.
Bits Utopia - Everything is bits, bits, bits. There is an excess of poetry. But inside every bit is another bit and we're always exposed to bits from the past.
There is No Utopia - This place sucks. One robot makes the entire place go and even he's on the fritz.
Nature Utopia - The goats are carrying parasols and enjoying picnics in the seedpod forests.
Steampunk Utopia - All the cool guys have airships, all the dames have giant hats. Everyone has goggles.
Paranormal Utopia - A world very much like our own, but with an inconvenient poltergeist that makes a really mess of everything.
Norse Utopia - Assuming you start near the top of the tree when you fall off, there is ankle support almost all of the way down. Furthermore, the squirrels are making a new tractor.
An icy plateau on the edge of a blue-green sea. Beneath the ice sheet and along the coast are deep red rock formations.
"Australia is located at the North Pole", generated using the CLIP-based tool from Midjourney

I found that to generate even somewhat coherent utopias, I had to use the largest GPT-3 model, DaVinci. When I tried downsizing to Curie, things got weird:

The Applesauce Utopia - Quantum shearing maintains everyone's hair nicely. If a few people go bald, they just have newspapers printed with computer facial filters.
Avarianian Utopia - Different birds live different lives. Weather changes the ooze into perfect snack for each species.
Post Industrial Utopia - We make our own medicine with Robots. Every Tuesday, someone slips on the banana skin, and we get one more robot.

Bonus content for AI Weirdness supporters: more of Curie's utopias!

Post Industrial Utopia - We make our own medicine with Robots. Every Tuesday, someone slips on the banana skin, and we get one more robot.

Fancy golf course sign reading "BOVDVTRGHASSA CAINWGS CE/CTGS The GOLF Golf Course"

Be not afraid of these perfectly normal golf courses

What would an AI who's never seen or heard of golf courses do when shown a list of real golf course names and challenged to generate more?

When Jeff Kissel sent me 15,626 existing golf course names from the National Course Rating Database, I thought I might have an opportunity to find out. I used Max Woolf's aitextgen, a text-generating model based on GPT-2. Although it has the option to start training from a version of GPT-2 that has already seen a lot of internet text, I wanted to see what would happen if I started from scratch. I told aitextgen that my dataset consisted of individual items, each on their own line, and that they were 30 characters or less in length.

Here's what aitextgen started producing just before I started training:

VERidgeRoyalDeer
Centerigh Pointede
lands Ranch Ranch
LINKSighESTOODMountainHITEOakrairieldHITE
olf Ch
WillowlandsALLEYut
Resort OFAKESage Resortsh
SandSandIDGEersersAollEADOW Farmield
Therairieont GolfBearockous P
Resort THITEQuHITEHITEassass
igh ResortdeOakOakBeaers

They are Extremely cursed-looking, yes, but though I haven't started training yet, they already have fragments of real golf course names in them. Why? As Max Woolf explained to me, this is because in preparation for training, aitextgen looks through the dataset and finds recurring chunks of text to use as building blocks. Algorithms I've used in the past use the set of individual characters, or of common words, as their building blocks. But, like a lot of modern text-generating algorithms, GPT-2 uses the fact that chunks of text like "ing" or "the" (or in this case, "golf", "resort", "ranch", etc) happen a lot and it saves time to use the entire chunk of text at once. (This process is called tokenization).

Once I actually start training, aitextgen seems to grab ahold of which tokens are the most common and use them preferentially.

Here's some course names from iteration 20.

Course - -
Club Golf
Course C Club Golf Club Country
Clubo
Club Club Club SO
Coursey
e Course Course CC Club GC Course -M - Club - Course Course &

By iteration 70, it's starting to branch out into a bit more variety.

Rmps Golf Club
HBEeecy FNCner Hills Country Course
MHpmkoon Cere Country Club
Dan Hills
Ton GOLF

In iteration 80, it becomes clear that it's generating two kinds of golf courses - sort of reasonable-sounding courses in lowercase, and frightening word salad in all-caps.

BCTINEOOERILTMAYLBB Me GC
Shcpases Golf Club
MARDORWM PINGANal Golf Club
CYWSIAREDANEORINKane Golf Club
Pine Country Club
BAARAWass Golf Course
BOVDVTRGHASSA CAINWGS CE/CTGS The GOLF Golf Course

What seems to have happened is since most golf course names contain either all mixed-case or all-caps, and there are lots more mixed-case, aitextgen learns the mixed-case text faster. Its all-caps prowess lags behind a lot. I've seen this before. There's nothing in what I gave it that explicitly says "golf" and "GOLF" are the same thing, so it has to learn how to use GOLF as well, from fewer examples.

By iteration 200, the all-caps courses become less alarming. It's taken longer, but it's starting to get the patterns of those too.

Dumyky GC - Sshanes
VIEW COUNTRY CLUB - Iudly
Lelch Golf & CC
Smitno Golf & Country Club
Barkbosa Golf Club - Onndle Hort Course
Fopbitth Country Club
Misserty Golf Club
Slake Country Club
Stale Lake Golf Club
Blewing Creek Golf Course
HILLFIE HILLS GC
Groygon Country Club
Lake Worse CC
River Antban Country Club
Gurdy Hills Golf Course
Warererer Golf Course
Pullotion Park

Iteration 200 is more or less the last point at which the golf course names are unique. Even with over 15,000 example courses, aitextgen has such a huge learning capacity that it begins to memorize the input course names. After all, if I'm asking it to predict the names of golf courses, giving me the names of existing courses is technically a great solution.

Bonus content for AI Weirdness supporters: I gave GPT-3 the task of generating golf courses in the style of GPT-2. Don't ask too many questions about the holes at "0.00001 Toilet".

golf course sign reading "0.0001 Toilet, members only"
An impressive rainforest, a san francisco that looks more like scotland, and a tiny furry giraffe

Generating landscapes without people

I've been experimenting with GauGAN2, released in Nov 2021 as a follow-on to GauGAN. One new thing Nvidia added in GauGAN2 is the ability to generate a picture to match a phrase. "A rocky stream in an ancient mossy rainforest" It can do more than generic landscapes - it can
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