For decades now, researchers have been trying to get computers to behave like artificial brains instead of merely binary data crunchers. One of the obstacles in creating this capability has been that computers are based on silicon CMOS chips rather than the dendrites and synapses found in the human brain. One of the drawbacks with silicon chips is that they lack what is known as "plasticity" in which the brain's neurons adapt in order to learn and remember.
To overcome such limitations, nanotechnology has been offering alternatives to silicon chip architecture that will more closely resemble the human brain. DARPA's SyNAPSE project is one example.
Now researchers at the Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) at Trinity College in Dublin are pursuing a new nanomaterial-based approach to neural networks that combines work in nanowires and memristors. The aim of the project, for which the researchers have just received a €2.5 million research grant from the European Research Council (ERC), is to develop a new computing paradigm that mimics the neural networks of the human brain. A video describing the CRANN research can be seen below.