Artificial intelligence (AI) can transform a digital business, but a successful strategy means looking beyond the hype and the overstated expectations that surround it by keeping a pin-sharp focus. While the case for its use has long been compelling, from enhancing the customer experience to reinventing entire business models, few can rival the technology's distracting narrative of conflicting opinions, difficult questions and speculation. Will it take our jobs or outperform us at chess? Or perhaps it will exist simply to serve us in the vein of some of its most mainstream iterations, such as the digital personal assistants of Siri and Alexa. Inevitably, it's the former element that sparks the most alarm and feeds into the more complex and ambiguous territory known as general AI. This is a world in which machines are increasingly humanized and are sophisticated enough to reason on par with, and even better than their living, breathing counterparts.

The main feature of perceptrons is that they can be trained (or learn) to behave a certain way. One popular beginner's assignment is to have a perceptron model (that is, learn to be) a basic boolean function such as AND or OR. Perceptron learning is guided, that is, you have to have something that the perceptron can imitate. So, the perceptron learns like this: it produces an output, compares the output to what the output should be, and then adjusts itself a little bit. After repeating this cycle enough times, the perceptron will have converged (a technical name for learned) to the correct behavior much like a child learns new words like glriber.