Carver Mead, the father of neuromorphic engineering, is a giant in the history of the semiconductor industry. He taught the world’s first VLSI design course; he designed the first gallium arsenide gate FET; he co-created the first silicon compiler; he played a key role in the fabrication of the first CMOS chip; he co-founded at least twenty companies; he is even credited with coining the expression “Moore’s law”. This is why his interest for mimicking biological brains – dating back to the late 80s – sounds even more significant: in other words, if Carver Mead took neural inspiration so seriously, it must be a serious thing indeed.
Carver Mead. Image credit: Norman Seeff
Today, thirty years later, neural networks are booming; however, most of the commercial AI/ML applications are only loosely inspired to biological brains. Most of them do not use spiking neural networks; most employ a training technique (backpropagation) that has no direct equivalent in nature. The approach pioneered by Carver Mead, more closely inspired by biological brains, is today embodied in the neuromorphic research, still mostly carried out in labs and universities – but holding the potential for more practical applications. Over the past few months, EDACafe has provided overviews of three neuromorphic chips: Loihi (Intel), TrueNorth (IBM) and SpiNNaker (University of Manchester). This week we will take an extremely quick look at other neuromorphic devices that have been developed – over the past few years, and recently – by universities around the world. Technical details about most of these chips can be found in a paper (main source for this article) co-authored by fifteen prominent researchers, including some of those mentioned below.
