Data acquisition (sensors) and manipulation (memory,
computation, communications, data mining) in its many forms drives and fuels
our civilization. Scientific and technological developments in the last 50
years, have led to the invention of highly sophisticated data acquisition and
manipulation machines. Since biological systems can, in many cases, outperform
artificial systems a natural question arises. Can biology provide, some high
level, guiding principles useful for the development of revolutionary, new
concepts for the development of artificial, intelligent systems ?
I will describe attempts to answer the US White House Nanotechnology-Inspired Grand Challenge for Future Technology: “Create a new type of computer that can proactively interpret and learn from data, solve unfamiliar problems using what it has learned, and operate with the energy efficiency of the human brain” .
The work was supported as part of the “Quantum Materials for Energy Efficient Neuromorphic Computing” an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science