Researchers take 'important step' in artificial intelligence
12 May 2015
In what could prove to be a significant step forward for artificial intelligence, researchers at UC Santa Barbara have demonstrated a simple artificial neural circuit.
For the first time, a circuit of about 100 artificial synapses was proved to perform a simple version of a typical human task: image classification.
"It's a small, but important step," says UCSB's Professor Dmitri Strukov. With time and further progress, the circuitry may eventually be expanded and scaled to approach something like the human brain's, which has an estimated quadrillion synaptic connections.
In the researchers' demonstration, the circuit implementing the rudimentary artificial neural network was able to successfully classify three letters ('z', 'v' and 'n') by their images, each letter stylised in different ways or saturated with 'noise'.
Key to the technology is the memristor, an electronic component whose resistance changes depending on the direction of flow of the electrical current. Unlike conventional transistors, which rely on the drift and diffusion of electrons and their holes through semiconducting material, memristor operation is based on ionic movement, similar to the way human neural cells generate neural electrical signals.
"The memory state is stored as a specific concentration profile of defects that can be moved back and forth within the memristor," says Strukov. "The ionic memory mechanism brings several advantages over purely electron-based memories, which makes it very attractive for artificial neural network implementation."
Potential applications already exist for this emerging technology, such as medical imaging, the improvement of navigation systems or searches based on images rather than on text.