New processors in the cloud accelerate AI and big data

One of the ironies of cloud computing is that, the more its cookie-cutter architecture allows it to scale, then the more it becomes possible to reintroduce diversity into that architecture. While cloud computing's early successes came from working out how to automatically manage serried ranks of identical general-purpose commodity computers, the vast scale that providers have now reached makes it economically and operationally viable to introduce pools of specialized computing into that infrastructure. Nowhere is this more pertinent than in the analysis of huge volumes of data, in applications such as big data and, increasingly, machine learning. In search of high performance in these applications, the leading cloud providers are investing in increasingly esoteric processor technologies, even to the extent of custom-building their own designs, as both Google and IBM are known to have done, while Microsoft and Amazon are thought to be doing the same -- perhaps also Apple and Facebook. Google's Tensor Processing Unit (TPU) is a case in point.