The world demand for faster, more energy-efficient information processing is growing exponentially as artificial intelligence becomes more and more prevalent in our everyday lives. Conventional digital processing hardware cannot keep up with this demand, and so researchers are considering alternatives that take inspiration from the brain, where massively connected networks of artificial neurons and synapses process information with extremely high energy efficiency. The new hardware devices, architectures and algorithms being developed have entirely new functionality, which requires creation of a whole new set of measurement techniques and protocols. This program is aimed at developing the necessary device-level and circuit-level measurements and theory to support the evolution of this technology from laboratory research to commercial application.
The Alternative Computing Group has four projects in Hardware for Artificial Intelligence. Click on the links below for more information.