The author – inspite of running an AI service provider for corporates – says that AI is being overhyped and overpromoted. He believes that:

“We have much faster computers, thanks to Moore’s law, but the underlying algorithms are mostly identical to those that powered machines 40 years ago. Instead, we have creatively rebranded those algorithms. Good old-fashioned “data” has suddenly become “big”. And 1970s-vintage neural networks have started to provide the mysterious phenomenon of “deep learning”.”

He highlights that celebrated AI success stories like IBM’s Watson and Google’s Deep Mind have performed disastrously in the real world. That begs the question: what is AI good for? Chishti’s answer, “What it has always been good for: the identification of patterns in complex data. Medical image anomaly detection, hydrocarbon detection, consumer behavioural prediction and fraud detection have all benefited from advances in computational capacity. These all share two things: large volumes of well-structured input data and well-defined endpoints.”

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