“Researchers at NVIDIA have harnessed the power of a generative adversarial network (GAN) — a class of neural network — to generate some extremely realistic faces. The results are more impressive than anything we’ve seen before.” — Futurism
Benjamin is an LSTM recurrent neural network, a type of AI that is often used for text recognition. To train Benjamin, [researcher, Ross] Goodwin fed the AI with a corpus of dozens of sci-fi screenplays he found online—mostly movies from the 1980s and 90s.
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 [the director] 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.
For Sharp, the most interesting part of the Benjamin experiment has been learning about patterns in science fiction storytelling. Benjamin’s writing sounds original, even kooky, but it’s still based on patterns he’s discovered in what humans write. Sharp likes to call the results the “average version” of everything the AI looked at. Certain patterns kept coming up again and again. “There’s an interesting recurring pattern in Sunspring where characters say, ‘No I don’t know what that is. I’m not sure,'” said Goodwin. “They’re questioning the environment, questioning what’s in front of them. There’s a pattern in sci-fi movies of characters trying to understand the environment.”
In the wake of Google’s AI Go victory, filmmaker Oscar Sharp turned to his technologist collaborator Ross Goodwin to build a machine that could write screenplays. They created “Jetson” and fueled him with hundreds of sci-fi TV and movie scripts. Building a team including Thomas Middleditch, star of HBO’s Silicon Valley, they gave themselves 48 hours to shoot and edit whatever Jetson decided to write.