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Facebook AI Director Discusses Deep Learning, Hype, and the Singularity

Posted by timothy on from the you-like-this dept.

An anonymous reader writes In a wide-ranging interview with IEEE Spectrum, Yann LeCun talks about his work at the Facebook AI Research group and the applications and limitations of deep learning and other AI techniques. He also talks about hype, 'cargo cult science', and what he dislikes about the Singularity movement. The discussion also includes brain-inspired processors, supervised vs. unsupervised learning, humanism, morality, and strange airplanes.

4 of 71 comments (clear)

  1. Very informative article by gurps_npc · · Score: 4, Insightful
    Glad to hear from an intelligent person, rather than an obsessed 'futurist' that has mistaken wishful/paranoid thinking for scientific projections.

    I would have added that the concept of the 'singularity' assumes multiple 'facts' that are extremely unlikely. In part because if they were true, science would already have been much farther along. Also in part because they confabulate different definitions of words, most often 'intelligence'. When AI people are talking about intelligence they are generally not using the word in the same way that a biologist, or worse, a priest. would.

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    excitingthingstodo.blogspot.com
    1. Re:Very informative article by Tyler+Durden · · Score: 3, Insightful

      2) Observe that technological progress seems to be accelerating. So, the reach of any predictive models we have today will be even shorter when used tomorrow.

      I think LeCun covers this quite well when he quotes, "the first part of a sigmoid looks a lot like an exponential." There's nothing that says the acceleration of technological progress has to continue as it has.

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      Happy people make bad consumers.
    2. Re:Very informative article by dpidcoe · · Score: 4, Insightful

      The big error is assuming the the accelleration will continue at the same rate it currently is. It won't.

      Look at the curve for other technologies now considered "mature" fields. When they were initially discovered there were huge leaps and bounds made, then it all started to dry up once the low hanging fruit was picked. Now there's little new development except for highly specialized breakthroughs that effect some niche uses as the technology starts to encounter hard limits oh physics or limitations from other fields (e.g. manufacturing technology)

      we'll see the same thing happen with computers. Eventually transistors hit the smallest physical size possible, and that's the end of moors law. Most of the really interesting things in computer science (such as these learning algorithms) are very non-linear in their computing requirements (usually some O(2^n) or worse), so all the work to increase computing power isn't going to be as much of a payoff as it's historically been. Quantum computing is only fast at certain kinds of things and so isn't going to be the savior a lot of people think it is.

  2. Cargo Cult Science by Kunedog · · Score: 5, Insightful

    If you've never read it before, Feynman's original essay is more worth your time (especially the part about the lab rats).
    http://neurotheory.columbia.ed...