Scientific Sense Podcast

Monday, May 16, 2016

Small step toward bigger hype

Recent research from the University of Liverpool (1) suggests a method by which computers could learn languages by semantic representation and similarity look-ups. Although this may be in the right direction, it is important to remember that most of the work in teaching computers language or even fancy tricks, is not in the realm of "artificial intelligence," but rather they belong to the age old and somewhat archaic notion of expert systems. Computer giants, while solving grand problems such as Chess, Jeopardy, Go and self driving cars, seem to have forgotten that rules based expert systems have been around from the inception of computers, much before some of these companies were founded. The fact that faster hardware can churn larger set of rules quicker is not advancing intelligence but it is certainly helping efficient computing.

Engineering schools appear to still teach ideas that are already obsolete. Programming languages have been frozen in time, with prescriptive syntax and rigid control flow. Today's high level languages are certainly practical and immensely capable of producing inferior applications. Even those who could have "swiftly," assembled knowledge from previous attempts seem to have concocted together a compiler that borrows from the worst that have gone before it. As they proclaim "3 billion devices already run it," every hour an update is pushed or conduct conferences around the globe dotting and netting, the behemoths don't seem to understand that their technologies have inherent limitations.

Computer scientists, locked behind ivy walls, are given skills that the world does not need anymore.


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