nobrashfestivity:

SOL LEWITT, All ifs ands or buts connected by green lines , 1973

ultrafacts:

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*Once you learn about the tomason, you’ll be able to perceive them everywhere.

https://simple.wikipedia.org/wiki/Tomason

lewisandquark:

So Prof. Mark Reidl of Georgia Tech is the best kind of geek, and used some cool scripting to extract all the things on Wikipedia with plot summaries: movies, books, tv episodes, video games, etc. That’s a lot of plot summaries: 112,936, to be exact. 

With a dataset this large, a neural network can achieve impressive results. Sure enough, when I trained this open-source neural network framework on just the titles alone, it consistently came up with titles that were both varied and (usually) plausible. 

Below are some of my favorites, arranged roughly by apparent genre:

Action/Adventure

Titanic Buffalo
Pirates: A Fight Dance Story
The Bad Legend
Conan the Pirate
O Bullets
Home Transformers
Shurk Hat Dies!
An Enemy of Bob (Homicide: Life on the Street)
Cannibal Spy II
American Hero: Fire of Crusty
Lego Man Hunt
Nancy Drew: The Last Day (film)
Surf Crisis
Legend of the Experience of Scarlet Freedom Damageboo
American Midnight: Swear Dragon
Problem

Scifi/fantasy

Under the Daleks
Batman and Flancles: The Fun Tree
The Legends of World Planet
Bomberman’s Love
The Enchanted Feed
The Star Wars: The Santa Contact
The Long Ninja Dove in the Air (film)
The History of the Galaxy Bunny Lada
City of the Stupid (film)
Shy Castle
Hamburger (Star Trek: The Next Generation)
Swords and Batman: Summer Party ?

Kids/Family

The Boordeeple (2011 film)
A Dog’s Toy Friends
Boop (Adventure Time)
A Dinosaur Quest
Colonel Corn (video game)
Scooby-Drum
New Bear
Borky the Pig (film)
Excellent Very Broken Christmas
The Great Bother Cat (film)
Happy Cat in the Yaku Wonder
Fireman and Halloween Rules
Big Can Flower Home
The Green Yaurglar Pig
Scooby-Doo'Wagon Traps (video game)
Book Dog (film)

Horror

Terror Dog
Tree Screaming
Zombies of Florence
The Trunkelling
A Vampire Time for Monster
Murder’s Eagle
Frozen Bat (film)
Haunted Place
The Sheep of Evil
Barney’s The Devil’s Treachery
Merry Scroobers: Crown of Evil
The Steel-Pounted Murder King
The Shadow of Life of Very Worgy (film)
The Mystical Booged of California

Documentary

Market that Knave
Spork at Bliss
The White Soup
An Indiana Office
The Last Fish Show
The Fish of Education

Restricted section (there were quite a few more of these)

Absilloved Lovers 2: Black Bearfly Dawn
Horse Man Academy 5-R: Cowboy Sheeper Wydex
Breed Bot 3: The Journey Kitchen
Wild Bad Party 109
Pink Moon
Indiscreet Maidman

And finally, a list of the most quintessential story titles, obtained by setting the creativity to near zero on a highly-trained network:

The Story of the Stranger (1994 film)
The Last Day of the Story
The Lost Princess (film)
The Stranger (1994 film)
The Last Star (1994 film)
The Secret of the Story of the Stranger (1996 film)
The Stranger (2014 film)
The Story of the Stars
The Story of the Stranger (1999 film)
The Last Day of the Sun
The Story of the Star Trek: The Secret of the Story of the Star Wars

TAG YOURSELF IM AMERICAN MIDNIGHT SWEAR DRAGON 🇺🇸🕛🗯🐉

the internal priority shift was part of a larger trend I wrote about

How many does your dog know?

lewisandquark:

I trained the neural network to generate superhero names, based on the list from this site.  I thought the database was going to be way too small, but the network proved me wrong.

Speet Stank
Red Fart
Mister Man
Rad Food
Sapgirl
Woop
Ann Man
Boomss
Boark II
Supperman
Superbore
Slonk
Lid Man
Green Hooter II
Starm Surper
Shartar
Goons
Nana
Rider Farm
Captain In
Redink
Wolver Man
Wizler

i started laughing at “Speet Stank” and I haven’t stopped