Future Computing Hardware for AI

Abstract

Hardware has taken on a supporting role in the maturation and proliferation of narrow AI, but will take a leading role to enable the innovation and adoption of broad AI. The concurrent evolution of broad AI with purpose-built hardware will shift traditional balances between cloud and edge, structured and unstructured data, and training and inference. Heterogeneous system architectures are already being delivered where varied compute resources, including high-bandwidth CPUs, specialized AI accelerators, and high-performance networking are infused in each node to yield significant performance improvements. Looking to the future, we envision a roadmap of specialized technologies to accelerate AI, starting with heterogeneous digital von Neumann machines, exploring reduced-precision accelerator approaches, finding the limits of conventional device power-performance with analog AI devices, and finishing with quantum computing for AI.