Don't believe the hype when it comes to AI

Thanks to neural networks - digital approximations of the way that the human brain learns - artificial intelligence has made enormous breakthroughs in everything from creating machines that can recognise faces with more accuracy than a human, to building cars capable of driving themselves, to recently, a computer "Turing test for sound" which can watch silent videos and predict the sounds that should accompany them. But it very nearly didn't happen like this. Forty years ago, research into neural networks almost stopped altogether. Budgets were slashed, plugs were pulled and students were advised by their teachers that researching neural networks was a bit like dating the loser in school: they'd never amount to anything and you'd just get hurt in the process. Certainly there were things neural networks weren't capable of at the time, but it's equally true that a large amount of the backlash the field suffered came down to the massive amount of hype it had received. Researchers, particularly in the rival, more established field of symbolic AI, were perturbed by articles like the one Science magazine published in 1958 about neural nets, entitled "Human Brains Replaced?"