Low-Code AI

Preface

Artificial intelligence (AI) can be defined as the broad field of study where computers show intelligence. The phrase “show intelligence” is vague; it could be interpreted as a computer making a decision that we would expect from a living being. The concept of AI has existed since ancient times, at least in mythology. A famous example of this is the Greek myth featuring Talos, a bronze automaton made to protect Europa from invaders who wished to kidnap her. As the centuries passed, basic forms of AI passed from the realm of myth to real life.

In modern times, AI has found its home in augmenting human abilities and automating decision making and other processes that are time-consuming for people. Expert systems, first developed in the 1970s, are one such example of modern AI. An expert system leverages a knowledge base, a collection of facts and rules, and an inference system to synthesize new knowledge. The main disadvantage of an expert system is that it needs domain expert time and effort to create the facts and rules for the knowledge base.

In recent decades, another form of AI has become more ubiquitous. Machine learning (ML) is the discipline of having computers learn algorithms from the data provided rather than the programmer having to provide the algorithms. Another way to phrase this in contrast to expert systems is that ML is about using data to discover the rules versus having experts write the rules for you.

ML touches almost every industry nowadays. In retail, ...