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Sunspring - the hilarious short movie written by a Recurrent Neural Network

January 2, 2018

This is definitely worth a watch for those of you into Deep Learning & Neural Networks.  In 2016 a LTSM Recurrent Neural Network was fed a corpus of dozens of sci-fi screenplays. The system analysed them and learned to predict, and produced it's very own screenplay.  The screenplay is then brilliantly acted out in the below 9min short movie.

 

Find the original article here

"Sunspring, a short science fiction film that's not entirely what it seems. It's about three people living in a weird future, possibly on a space station, probably in a love triangle. You know it's the future because H (played with neurotic gravity by Silicon Valley's Thomas Middleditch) is wearing a shiny gold jacket, H2 (Elisabeth Gray) is playing with computers, and C (Humphrey Ker) announces that he has to "go to the skull" before sticking his face into a bunch of green lights. It sounds like your typical sci-fi B-movie, complete with an incoherent plot. Except Sunspring isn't the product of Hollywood hacks—it was written entirely by an AI.

 

To be specific, it was authored by a recurrent neural network called long short-term memory, or LSTM for short. At least, that's what we'd call it. The AI named itself Benjamin.

 

 

Knowing that an AI wrote Sunspring makes the movie more fun to watch, especially once you know how the cast and crew put it together. Director Oscar Sharp made the movie for Sci-Fi London, an annual film festival that includes the 48-Hour Film Challenge, where contestants are given a set of prompts (mostly props and lines) that have to appear in a movie they make over the next two days. Sharp's longtime collaborator, Ross Goodwin, is an AI researcher at New York University, and he supplied the movie's AI writer, initially called Jetson. As the cast gathered around a tiny printer, Benjamin spat out the screenplay, complete with almost impossible stage directions like "He is standing in the stars and sitting on the floor." Then Sharp randomly assigned roles to the actors in the room. "As soon as we had a read-through, everyone around the table was laughing their heads off with delight," Sharp told Ars. The actors interpreted the lines as they read, adding tone and body language, and the results are what you see in the movie. Somehow, a slightly garbled series of sentences became a tale of romance and murder, set in a dark future world. It even has its own musical interlude (performed by Andrew and Tiger), with a pop song Benjamin composed after learning from a corpus of 30,000 other pop songs.

 

Benjamin is an LSTM recurrent neural network, a type of AI that is often used for text recognition. To train Benjamin, Goodwin fed the AI with a corpus of dozens of sci-fi screenplays he found online—mostly movies from the 1980s and 90s. Benjamin dissected them down to the letter, learning to predict which letters tended to follow each other and from there which words and phrases tended to occur together. The advantage of an LSTM algorithm over a Markov chain is that it can sample much longer strings of letters, so it's better at predicting whole paragraphs rather than just a few words. It's also good at generating original sentences rather than cutting and pasting sentences together from its corpus. Over time, Benjamin learned to imitate the structure of a screenplay, producing stage directions and well-formatted character lines. The only thing the AI couldn't learn were proper names, because they aren't used like other words and are very unpredictable. So Goodwin changed all character names in Benjamin's screenplay corpus to single letters. That's why the characters in Sunspring are named H, H2, and C. In fact, the original screenplay had two separate characters named H, which confused the humans so much that Sharp dubbed one of them H2 just for clarity."

 

- https://arstechnica.com

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