Redefining the transistor: The ideal building block for artificial intelligence
National University of Singapore (NUS)The team led by Associate Professor Mario Lanza from the Department of Materials Science and Engineering in the College of Design and Engineering at the National University of Singapore, has just revolutionised the field of neuromorphic computing by inventing a new super-efficient computing cell that can mimic the behaviour of both electronic neurons and synapses. They found an ingenious way to reproduce the electronic behaviours characteristic of neurons and synapses in a single conventional silicon transistor. This discovery is revolutionary because it allows the size of electronic neurons to be reduced by a factor of 18 and that of synapses by a factor of 6. Considering that each artificial neural network contains millions of electronic neurons and synapses, this could represent a huge leap forward in computing systems capable of processing much more information while consuming far less energy.