Have we reach the limits of AI?

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We make sense of new phenomena in terms of things we already understand. We break a domain down into pieces and learn the pieces. Eyal is a mathematician and computer programmer, and he thinks about tasks—like making a soufflé—as really complex computer programs. But it’s not as if you learn to make a soufflé by learning every one of the program’s zillion micro-instructions, like “Rotate your elbow 30 degrees, then look down at the countertop, then extend your pointer finger, then …” If you had to do that for every new task, learning would be too hard, and you’d be stuck with what you already know. Instead, we cast the program in terms of high-level steps, like “Whip the egg whites,” which are themselves composed of subprograms, like “Crack the eggs” and “Separate out the yolks.”

Computers don’t do this, and that is a big part of the reason they’re dumb. To get a deep-learning system to recognize a hot dog, you might have to feed it 40 million pictures of hot dogs. To get Susannah to recognize a hot dog, you show her a hot dog. And before long she’ll have an understanding of language that goes deeper than recognizing that certain words often appear together. Unlike a computer, she’ll have a model in her mind about how the whole world works. “It’s sort of incredible to me that people are scared of computers taking jobs,” Eyal says. “It’s not that computers can’t replace lawyers because lawyers do really complicated things. It’s because lawyers read and talk to people. It’s not like we’re close. We’re so far.”

Full article here: https://www.technologyreview.com/s/608911/is-ai-riding-a-one-trick-pony/

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