From Thought to Bot: The Rise of Commercial AI
Public awareness of the term “artificial intelligence” is at an all-time high, but beyond vague (and at times frightening) connections with robots and computers, many people aren’t as familiar with what AI actually is, or what it might possibly become. Precursors and early efforts While the term “artificial intelligence” was coined in the 1950s, people have been dreaming of artificial minds and thinking machines for several hundred years. From various humanoid automata in royal courts around the ancient world to the Czech play, R.U.R., which gave us the term “robot”, people have tinkered with ideas (or actual machines) that aim to mimic or replace humans in various capacities. The invention of the digital computer at the dawn of the information age in the 20th century gave people a glimpse of things to come. Business could buy machines that performed clerical and accounting tasks in a fraction of the time that a calculator-wielding human could manage, and these machines quickly entered our offices and homes. Researchers began to explicitly model human decision making (albeit poorly) using lists of predefined rules of the “if this happens, then do that” variety. This tradition in AI proved a colossal failure because it was nothing like the way humans actually solve problems, and was later termed “good old-fashioned AI” (GOFAI). Machines that learn Later on, AI researchers discovered techniques that allowed computer software to modify itself based on the feedback it received – in other words, computer programs began to learn from their experience. These techniques vaguely mimicked the way that neurons in human and animal brains operate, and were misleadingly named “neural networks” by some, and “connectionist networks” by others. While still a long way off, researchers had begun inching in the right direction, towards the goal of creating a