  This essay examines how what is considered to be artificial intelligence (AI)
has changed over time and come to intersect with the expertise of the author.
Initially, AI developed on a separate trajectory, both topically and
institutionally, from pattern recognition, neural information processing,
decision and control systems, and allied topics by focusing on symbolic systems
within computer science departments rather than on continuous systems in
electrical engineering departments. The separate evolutions continued
throughout the author's lifetime, with some crossover in reinforcement learning
and graphical models, but were shocked into converging by the virality of deep
learning, thus making an electrical engineer into an AI researcher. Now that
this convergence has happened, opportunity exists to pursue an agenda that
combines learning and reasoning bridged by interpretable machine learning
models.
