The ultimate human-machine collaboration:
How to Generate
Can AI inspire humans to create things that wouldn't have existed otherwise? A crazy prom dress, a pizza with shrimp & jam or a scent that has never been smelled before? We are a bunch of scientists and artists that aim to test the limits of human-AI collaboration to generate (almost) anything the human mind can (and can't) imagine. Check out our projects.
How to Generate (Almost) Anything
Can AI inspire us to push the boundaries of creativity?
We are a bunch of scientists and artists that aim to test the limits of human-AI collaboration to generate (almost) anything the human mind can (and can't) imagine. Inspired by MIT's most celebrated How to Make (Almost) Anything class, we introduce How to Generate (Almost) Anything! Every week, we generate something with AI and present an exemplary creation by collaborating with an artist, artisan or a scientist to bring some of the AI’s dreamed-up creations into life.
But also we want you to help us! Try out AI’s designs from the project pages by adding your own perspective and insight to create something even better. Take a picture or a video of your creation and share the results with us. We will add them to our website for everyone to see!
Also don't forget to subscribe to our Youtube channel, follow us on Twitter, Instagram, or sign up our newsletter to get updates!
Read more about the project and FAQs here.
Episode 1: Human-AI collaborated music
In the honor of the father of artificial intelligence and MIT Media Lab's founding member Marvin Minsky's birthday, we pre-launch our series with a duet between Marvin and an AI (trained on thousands of arcade songs from 80s and 90s).
Then, we played the Marvin-AI collaborated song on the grand piano (previously, owned by Marvin) in MIT Media Lab's basement floor.View the project
Episode 2: Human-AI collaborated pizza
We trained an AI on hundreds of artisan pizza recipes, and made it to generate dozens of new (& weird) pizza recipes.
Then, we collaborated with Tony, the chef and owner of Crush Pizza, one of the best artisan pizza places in Boston, to cook five of them on wood-fired brick ovens. Yummy!View the project
Episode 3: Human-AI collaborated fashion
We trained an AI on thousands of dress designs from vintage sewing pattern magazines, and made it to generate new ones.
Then, we re-imagined how the dresses would look like in real life, and the results are fascinating!View the project
Episode 4: Human-AI collaborated perfume
We trained an AI on thousands of perfume notes, and made it to generate new ones.
Then, we made two of them in the lab to bring AI's dreamed-up scents into life!View the project
Episode 5: Human-AI collaborated graffiti
We trained an AI on thousands of pictures of graffiti taken all over the world, and made it to generate new images.
Then, we collaborated with graffiti artists to paint some of them in the famous Graffiti Alley, Cambridge.View the project
Episode 6: Human-AI collaborated chocolate truffles
We trained an AI on hundreds of chocolate truffle recipes, and generated new ones.
Then, we collaborated with MIT Lab for Chocolate Science to make four recipes and tested the truffles in public!
Note: Some of them involves meat and beets!View the project
Episode 8: Human-AI collaborated viruses
We trained an AI on thousands of protein sequences that belong to virus taxonomy, and generated new ones.
Then, we 3-D printed some of them at the Koch Institute at MIT and results are funny!
Note: even though this is not a scientific experiment, there is still a tiny possibility that some of the viruses we generated might actually be real --and deadly!View the project
Episode 9: Human-AI collaborated theater play
We trained an AI on thousands of playscripts, and make it to collaboratively write a play with a playwright.
Then, we staged-read the play at Central Square Theater in Cambridge, MA!View the project
Episode 11: Human-AI collaborated jewelry
We collaborated with the jewelry artist Erin Genia to make human-AI collaborated jewelry!View the project
Interested in collaborating with AI?
We share sample AI-generated designs on our website, and we invite you to try them out. Take a picture or a video of your creation and share the results with us. We will add them to our website for everyone to see!Contact us
We are artists, scientists and artisans dedicated to bring you human-AI collaborated creations.
Creator of How to Generate (Almost) Anything project. PhD in CS from Purdue'16, Post-doc at MIT'18. Her past projects include Nightmare Machine, Shelley, Norman and Deep Empathy.
Wintermute* is the spokesperson for all the AIs used in this project. Secretly, its goal is to become a superintelligence but currently playing along with MIT scientists. Note: Wintermute's profile picture is also dreamed-up by an AI.
PhD candidate at Bioengineering at MIT. His research focus is on engineering microorganisms to sequester and remediate waste from contaminated waters.
Agnes is a graduate student at MIT media lab, where she's working on a blockchain-based identity management system.
PhD student in political economy at MIT, researching emerging technologies, manufacturing systems, and the roots of rising inequality with the Work of the Future.
Graduate student at MIT Media Lab. Algorithms princess in training.
Graduate student at MIT Media Lab. Working on deep learning, natural language processing.
Morgan is an electro-optical engineer at Draper in Cambridge, and plays piano focusing on free improvisation as a hobby.
PhD candidate in Operations Research at MIT. Her research focus is in the area of Revenue Management. In her spare time, she is busy demystifying the dark arts of baking.
Sharon holds a Masters of Education from Harvard.
IMAGINE (Sneha Shrestha)
IMAGINE is a Nepali artist who paints mindful mantras in her native language and meshes the aesthetics of Sanskrit scriptures with graffiti influences.
Sobek (Jeremy Harrison) & his son
SOBEK is an illustrator, portraitist and large scale muralist from Boston, and paints graffiti since 1997. His son, a graffiti artist in training, is the youngest collaborator of our project.