A Dartmouth-affiliated startup bridging the gap between algorithms and computing hardware. Our goal is to drastically improve AI and multivariate sensor processing applications, on the edge, and eventually in datacenters.

We are doing this through cutting edge algorithms and a novel parallel neuromorphic hardware architecture (hardware designed from studying brain circuitry). This combination reduces price and improves Watt performance by an order of magnitude by allowing large numbers of independent processing streams, none bottle-necked by a typical monolithic memory unit.