Humanifold is a new way to understand how individuals map into the current manifold of humanity using social media and neuromorphic learning algorithms. By taking the data from a users’ various social media profiles, such as Facebook, Twitter, and Instagram, and using them as inputs to a personal artificial neural network, Humanifold creates a high-dimensional “profile” of the individual that stores none of the original data, but contains the essential elements of the input and, therefore, of the user. The idea is simple: you take a complicated input and turn it into an output that allows for better characterization and discrimination. For millennia, human brains have used this idea to convert external stimuli, like light and sound, into meaningful representations like pictures and music. Now, we intend to apply it to the ever-growing world of the Internet, in order to allow people to connect in deeper ways than previously provided by social media. By encouraging these new connections, Humanifold will act not only as a way to unify the users’ seemingly disparate social media profiles but also as a way to map the international connections being made every day through social media.
Ignition Fund Recipient, Spring 2015