The electronics industry over the past several years has made tremendous strides in creating artificial intelligence in a manner imagined by Allen Turing in the 1940s. The convergence of algorithmic advances in multilayer neural networks, the evolution of PC graphics processing units as massively parallel processing accelerators, and the availability of massive data sets fueled by the Internet and widely deployed sensors -- big data -- has enabled a renaissance in software neural network modeling techniques commonly referred to as "deep learning," or "DL." In addition, the evolution of 3D graphic shader pipelines into general purpose compute accelerators drastically reduced the time required to train DL models. Training time for applications as diverse as image recognition and natural language processing has been reduced from months to days -- and in some cases, hours or even minutes. These solutions have enabled new AI applications ranging from computational science to voice based digital assistants like Alexa and Siri.

R1 is a rule-based program that configures VAX-11 computer systems. Given a customer's purchase order, it determines what, if any, substitutions and additions have to be made to the order to make it consistent and complete and produces a number of diagrams showing the spatial and logical relationships among the 90 or so components that typically constitute a system. The program has been used on a regular basis by Digital Equipment Corporation's manufacturing organization since January of 1980. R1 has sufficient knowledge of the configuration domain and of the percliarities of the various configuration constraints that at each step in the configuration process, it simply recognizes what to do; thus it requires little search in order to configure a computer system.