There is a new technology on the horizon that should greatly change electronic devices, especially computers. It is an excellent case of theoretical physics meeting practical reality. In 1971 (not all that long ago), a physicist name Leon Chua theorized that a fourth primary electronic device should exist based on symmetry. The first three devices are known as the resister, capacitor, and inductor. They help control voltage, current, charge, and flux. This fourth device Chua named "Memristor" to stand for memory resistor. This device was hypothesized to store changes in current. Who would have expected that a fundamental electronic device would be discovered today, a couple hundred years after electricity became widely studied.
Fast forward 37 years. At HP labs, Stanley Williams and co-authors Dmitri Strukov, Gregory Snider and Duncan Stewart were able to formulate a physics-based model of a memristor and build nanoscale devices in their lab that demonstrate all of the necessary operating characteristics to prove that the memristor was real. They created the world's first memristor switch, capable of storing 1s and 0s for electronic computing. With this invention,
"Engineers could, for example, develop a new kind of computer memory that would supplement and eventually replace today's commonly used dynamic random access memory (D-RAM). Computers using conventional D-RAM lack the ability to retain information once they are turned off. When power is restored to a D-RAM-based computer, a slow, energy-consuming "boot-up" process is necessary to retrieve data stored on a magnetic disk required to run the system."Besides the change in computer components, HP predicts:
"As for the human brain-like characteristics, memristor technology could one day lead to computer systems that can remember and associate patterns in a way similar to how people do.HP says that by 2012, the first memristor devices will be on the market.
"This could be used to substantially improve facial recognition technology or to provide more complex biometric recognition systems that could more effectively restrict access to personal information.
"These same pattern-matching capabilities could enable appliances that learn from experience and computers that can make decisions."