A world where robots do all the testing seems a long way off. For starters, demand isn't there, said Diego Lo Giudice, an analyst and vice president at Forrester Research. Lots of platform makers are adding AI to software testing, but Lo Giudice isn't getting many calls from clients about this. From what he sees, Sypolt's experience is typical. "Once they try it, they like it and are interested in it," he said.

On a regular basis people tell me about their impressive achievements using AI. This post may come off as a rant, but that's not so much its intent, as it is to point out why we went from having very few AI experts, to having so many in so little time. Also to convey that most of these experts only seem experty because so few people know how to call them on their bull shit. So you converted 11 lines of python that would fit on a t-shirt to Java or C or C . You have mastered what a cross compiler can do in 3 seconds.

By now the world has heard about the rise and fall of Microsoft's Tay, an artificially intelligent bot that lived on Twitter, Kik, and GroupMe. Tay's goal was to learn and mimic the personality of a 19-year-old woman, and it would appear that popular social networks among millennials were a great place for Tay to learn. Unfortunately for Microsoft, this experiment quickly became an embarrassment after Tay was manipulated by Internet trolls into becoming a racist potty-mouth in less than 24 hours. To better understand where exactly Microsoft went wrong with Tay, I spoke with Brandon Wirtz, the creator of Recognant, a cognitive computing and artificial intelligence (AI) platform designed to aid in understanding big data from unstructured sources. Tay's Twitter conversations started out innocently enough, proclaiming her love for humans and wishing that National Puppy Day was every day.