Digital information may appear to exist as abstract ones and zeroes, flipping effortlessly from one to another. But in fact there is a minimum amount of energy required to run any computation system, regardless of how “energy efficient” are its component parts. A recent paper from Jim Crutchfield and Alex Boyd at the UC Davis Complexity Sciences Center with Dibyendu Mandal at UC Berkeley shows that there is some inescapable friction, or “grit in the gears” between the levels of organization in an information system.
By Aditi Risbud Bartl
Sometimes, one darn thing leads to another in a series of cascading failures. Understanding the weak points that lead to such cascades could help us make better investments in preventing them.
In the Nov. 17 issue of Science, Raissa D’Souza, professor of computer science and mechanical and aerospace engineering at UC Davis, wrote a perspective article about cascading failures that arise from the reorganization of flows on a network, such as in electric power grids, supply chains and transportation networks.
Jim Crutchfield wants to teach a machine to “see” in a new way, discovering patterns that evolve over time instead of recognizing patterns based on a stored template.
It sounds like an easy task – after all, any animal with basic vision can see a moving object, decide whether it is food or a threat and react accordingly, but what comes easily to a scallop is a challenge for the world’s biggest supercomputers.