Neuromorphic computers or chips—also known as brain-inspired components—are modeled after biological systems or components, such as neurons and synapses. These may be implemented in analog, digital, or hybrid hardware. Neuromorphic hardware is typically designed to learn by experience over time, rather than by programming.
Much of the research in scalable neuromorphic computing to date has been sponsored by government agencies, including the Defense Advanced Research Projects Agency (DARPA), which supported the SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) project. For example, development of IBM’s True North chipset was funded in part by the SyNAPSE project. Qualcomm’s Zeroth chip is a mobile phone neuromorphic handset component that tracks behavior and is already in production.
Representative Vendors: Artificial Learning, IBM, and Qualcomm.