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Google Brain's Co-inventor Tells Why He's Building Chinese Neural Networks

Posted by samzenpus on from the build-a-brain dept.

An anonymous reader writes "Here's an interview with Andrew Ng, former leader of Google Brain, discussing Baidu, Deep Learning, computer neural networks, and AI. An interesting excerpt from the interview on biological vs. computer neural networks: "A single 'neuron' in a neural network is an incredibly simple mathematical function that captures a minuscule fraction of the complexity of a biological neuron. So to say neural networks mimic the brain, that is true at the level of loose inspiration, but really artificial neural networks are nothing like what the biological brain does."

7 of 33 comments (clear)

  1. Re:hu? by RightwingNutjob · · Score: 2

    Having crossed paths with this fella about 10 years ago, you're not too far off. Minus the racism.

  2. On the other hand ... by PPH · · Score: 4, Funny

    artificial neural networks are nothing like what the biological brain does.

    ... there are quite a few people around who tried to overclock their brains during the '60s and '70s.

    --
    Have gnu, will travel.
    1. Re:On the other hand ... by ArhcAngel · · Score: 2

      Why were the first cars called horseless carriages? Because the carriage pulled by a horse was something that was familiar. and automobile sounded funny. We ended up dropping the horseless part and shortening carriage to car eventually though.

      --
      "A person is smart. People are dumb, panicky dangerous animals and you know it." - K
    2. Re:On the other hand ... by ShanghaiBill · · Score: 5, Insightful

      If the 'neuron' of machine learning is so very different from a biological neuron, why are people insisting on calling it a 'neuron'.

      You could say the same about the 'wing' of an airplane and a biological wing. The wing of a hummingbird or mosquito is vastly more complicated and capable than the wing of a 747. It provides thrust as well as lift, can do a vertical takeoff without a runway, and can go instantly from forward flight to hovering. On the other hand, a hummingbird can't go from SFO to Narita in 8 hours.

  3. Nothing like Biological by NReitzel · · Score: 2

    To say that "artificial neural networks are nothing like what the biological brain does" is no more correct than to say "artificial neural networks are just like the brain."

    Machine learning neural networks do the same flavor of thing that a real organic brain does, but at a complexity that is -many- orders of magnitude smaller. They also tend to be directed at a single skill, and don't have to cohabit the network with, well, everything.

    They're not the same, but they're not totally different, either. Truth is not well served by hyperbole.

    --

    Don't take life too seriously; it isn't permanent.

    1. Re:Nothing like Biological by TapeCutter · · Score: 2
      Exactly, an artificial neuron is a mathematical model of a real neuron, it's the "spherical cow" of computer science.

      They also tend to be directed at a single skill

      Yes, The single skill problem is the main reason neural nets were seen as curious toys for 50ys but I think IBM solved that problem with Watson in the mid-noughties. How? - I'm not sure.

      --
      And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
  4. Biggest difference is timing. by aberglas · · Score: 4, Interesting

    Certainly biological neurons are much more complex than artificial neural net neurons. The simplest "Integrate and Fire" (IF) model of a biological neuron perform a leaky integration over *time*, and if the voltage ever reaches the trigger value the fire. So the timing of stimulations is critical, whereas most Artificial Neural Networks (ANNs) does all its calculations (logically) at the same time. The ANN is both simpler and cleaner to work with. Biological synapses are very complex, but much of that complexity just reflects the wet technology that they are made from.

    If you want to understand how the brain works, study biological neurons. If you want to understand how to build an intelligent machine, engineer ANNs.