We are creating a platform in which our computing systems can develop, learn, and evolve to provide emergent behavior out of the interactions between data and users.

A first demonstration of this approach is a project called “Assembly” in which an algorithmic basis of evolutionary processes has been created.

A synthetic system of encoding characteristics, and a set of rules akin to the chemistry and physics of an environment, provide the basis for creating increasingly complex emergent behavior.

These genetic and environmental conditions are abstractions of an underlying scheme which can be applied to varied types of data. In the Assembly project we show this by working through three levels of representation that evoke 1) the cellular, 2) the organism, and 3) the socio-cultural.