Smart Until It's Dumb: Why artificial intelligence keeps making epic mistakes⁠—and why the AI bubble will burst

by Emmanuel Maggiori

But it’s important to remark that there isn’t one piece of software that serves all those tasks. Instead, machine learning is narrow—each task is tackled separately with its own model, assumptions and data.

Machine learning operates on a “quantity of evidence” basis. It

“Current systems are, in essence, glorified pattern-matching machines, rather than intelligent visual learners.”

Stanislas Dehaene wrote, “The state of the art in machine learning involves running millions, even billions, of training attempts on computers. […] In this contest, the infant brain wins hands down: babies do not need more than one or two repetitions to learn a new word.”