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Mapping The Brain To Build Better Machines (quantamagazine.org) 110

An anonymous reader quotes a report from Quanta Magazine: An ambitious new program, funded by the federal government's intelligence arm, aims to bring artificial intelligence more in line with our own mental powers. Three teams composed of neuroscientists and computer scientists will attempt to figure out how the brain performs these feats of visual identification, then make machines that do the same. "Today's machine learning fails where humans excel," said Jacob Vogelstein, who heads the program at the Intelligence Advanced Research Projects Activity (IARPA). "We want to revolutionize machine learning by reverse engineering the algorithms and computations of the brain." By the end of the five-year IARPA project, dubbed Machine Intelligence from Cortical Networks (Microns), researchers aim to map a cubic millimeter of cortex. That tiny portion houses about 100,000 neurons, 3 to 15 million neuronal connections, or synapses, and enough neural wiring to span the width of Manhattan, were it all untangled and laid end-to-end.
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Mapping The Brain To Build Better Machines

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  • Stay away from the right parietal lobe...

    • There are 7 billion people and counting on this planet - why do we need a build a poor electronic fascimile of a human when we have so many real brains here? This is nothing more than ego on the part of the researchers.

      And before someone quotes the industrial revolution at me - that replaced physical strength, something that humans even compared to other animals are poor at. However we are exceptionally good at thinking (as a species , not necessaily per individual) so other than the glory of the people inv

      • by rolias ( 2473422 )
        Because a lot of tasks are painfully boring for a human to work on, and computers don't care. Computers that emulate some human ability, like neural networks, can be improved on by using more accurate models than the old neural networks. They still have many useful applications, despite being based on simplistic or incorrect models of how real neurons behave. You don't need a full human mind emulation to do useful work. Though, this is one small step in that direction.
        • by Viol8 ( 599362 )

          Even insects appear to get bored so any sufficiently complex neural net may well exhibit similar properties. If you want a mindless automaton that does the same task over and over you're better off with a programmed computer with maybe a tiny neural net for some pattern matching, not a brain simulation which is what these guys are aiming at.

          • That's easy: You just erase the used net after each computation and copy it back from the known-good state.

            I don't think they want a brain simulation, skimming through. It looks more like they want a specialised neural net, but don't know how to build one. So they are mapping a chunk of brain and will try to figure out how it works, and use the knowledge thus gained as a guide for creating specialised artificial networks for visual processing.

          • Large parts of our brains perform mindless tasks all day without getting bored.
      • Humans thinking is not particularly good, it is actually quite poor compared to a reasonable ideal.

        A properly developed AGI will probably be able to solve many problems that are difficult or even impossible for humans to solve.

  • Pure delusion (Score:5, Interesting)

    by Anonymous Coward on Wednesday April 06, 2016 @10:09PM (#51857871)

    This cargo-cult approach to AI is ridiculous. Decades of effort have produced absolutely no result. Oh, but this time we're way smarter and better informed, surely we'll produce something of value this time. Gimme the grant monies, plz.

    Oh, but this one is worse. It's not that gigantic failure. The laughable failure they're repeating this time is far, far, older: "We want to revolutionize machine learning by reverse engineering the algorithms and computations of the brain."

    Computationalism?! Seriously? Not only is that laughable, it's been laughable for ages! Don't think so? People have been born and died of old age waiting for that bit of fiction to produce any results. So far? Nothing. On top of it all, there's more than one good reason to suspect it's never going to produce any results.

    Let's base one retarded idea on another retarded idea and mix in a bunch of childish thinking about the function of the brain based on zero evidence. AI breakthrough!

    • by Anonymous Coward

      Cynicism isn't productive or warranted. The mechanisms of the brain are already the basis of the most useful machine learning algorithms. Statistical inference only goes so far and really relies on assumptions that limit application to an ever smaller subset of the real world's problems. Don't let the problems from media hype and marketing jargon delude you into ignoring the real and practical utility of this approach. It is modeling the network of that region of the brain and using our existing cognitive p

      • Re: (Score:2, Interesting)

        by Anonymous Coward

        Cynicism isn't productive

        Neither is computationalism. It's like saying they're going to crack strong AI through phrenology.

        or warranted.

        Oh, I'd say it's warranted. What other reaction could a reasonable person have to this? Imagine if someone announced that they're going to make significant advances in perpetual motion thanks to phlogiston theory. That's exactly what this sounds like to anyone who isn't a Kurzweil cultist.

        Here's a neat idea. Let's let go of old, long disproved, ideas and try something new. The alternative, after all, is t

    • Re:Pure delusion (Score:5, Insightful)

      by Anonymous Coward on Thursday April 07, 2016 @01:12AM (#51858375)

      This cargo-cult approach to AI is ridiculous. Decades of effort have produced absolutely no result. Oh, but this time we're way smarter and better informed, surely we'll produce something of value this time. Gimme the grant monies, plz.

      Oh, but this one is worse. It's not that gigantic failure. The laughable failure they're repeating this time is far, far, older: "We want to revolutionize machine learning by reverse engineering the algorithms and computations of the brain."

      Computationalism?! Seriously? Not only is that laughable, it's been laughable for ages! Don't think so? People have been born and died of old age waiting for that bit of fiction to produce any results. So far? Nothing. On top of it all, there's more than one good reason to suspect it's never going to produce any results.

      Let's base one retarded idea on another retarded idea and mix in a bunch of childish thinking about the function of the brain based on zero evidence. AI breakthrough!

      What is your approach to building a strong AI then? We are waiting for your reply.

      In other news, the amount of progress into AI research depends on what fronts you judge the progress and there have been numerous steps forward but none of them have resulted in C3P0 style robots because that is not the goal.

      There are functionalists who largely congregate at MIT and Harvard who do not believe that studying the human brain will yield any immediate results that can be implemented in silicon

      There are the Cal tech researchers who are largely behavioralists who believe studying psychology and to a limited degree physiology will point the general direction in terms of large milestones that have to be achieved to build a strong AI, using nature as a guide.

      Then there are the Connectionists and this includes Francois Crick, who believe that the neural connections as a functional network will yield a base cortical algorithm which can be applied to a number of things that also include the beginnings of building a Strong AI.

      There are a lot of things that have been gained by these approaches to the problem so to say as you did that nothing has been accomplished is about as wrong as wrong can get. We know for instance, that the processing "program" of the human brain uses the same functional unit that is repeated over and over and is adapted and adaptable to vision processing, audio processing, kinesthetic processing and very likely (almost certainly) everything else in terms of recognizing adapting to and predicting (prediction is a strong indicator of intelligence among other behavioral emergent patterns) patterns and sequences of patterns between inputs and outputs. If you surgically connect auditory nerves to visual cortex the visual cortex adapts to process inputs from the eardrums, if you connect optic nerves to audio cortex, audio cortex processes visual information.. with no further manipulation.. that is quite a big value for "nothing being accomplished" as you put it.. Heres the kicker of how wrong you are:

      A camera device has been developed that non-invasively communicates digital information as points of pressure onto the tongue of the wearer, thereby allowing a completely blind person to navigate and "see" through the camera via the sensation on the tongue. But no, we have not accomplished anything involving the understanding of how the brain processes information and yes we just should abandon this line of research because it will not accomplish anything at all.

      You are right man, Deep Blue did not beat Kasparov and no IBM's Watson did not win against champion humans on Jeopardy.. so we might as well not even try.

      Sheesh! Don't even bother to answer unless you have actual points to make with cited references.. go back to putzing around in Minecraft ok?

      • by narcc ( 412956 )

        What is your approach to building a strong AI then? We are waiting for your reply.

        I don't have one. Of course, neither does anyone else. That said, beating on long disproved approaches isn't exactly going to get us anywhere.

        Computationalism is as dead as spontaneous generation. You don't need an alternative to find out that something doesn't work, and is never going to work. You'd have us repeat the same failure over and over rather than work toward finding a new approach because ... you can't personally think of any alternative so the provably wrong approach must be correct?

        In other news, the amount of progress into AI research depends on what fronts you judge the progress and there have been numerous steps forward but none of them have resulted in C3P0 style robots because that is not the goal.

        Oh, okay

        • I don't have one. Of course, neither does anyone else. That said, beating on long disproved approaches isn't exactly going to get us anywhere. Computationalism is as dead as spontaneous generation. You don't need an alternative to find out that something doesn't work, and is never going to work. You'd have us repeat the same failure over and over rather than work toward finding a new approach because ... you can't personally think of any alternative so the provably wrong approach must be correct?

          If you don't have a better plan, then it doesn't hurt to keep working on the old one. How long have people worked on human powered helicopters before they finally had some success ? I don't see you offering any fundamental reason why computationalism is dead.

      • We know for instance, that the processing "program" of the MAMMALIAN brain ...

        FTFY

        A mammalian brain is not necessarily a human brain. It is the human brain we want to model.

    • This cargo-cult approach to AI is ridiculous. Decades of effort have produced absolutely no result.

      Says someone who clearly hasn't kept up with recent advances in cognitive science.

    • Here's an interview with Yann Lecun. He's also sceptical about such undertakings, but he argues more convincingly: http://spectrum.ieee.org/autom... [ieee.org]
    • You act like computationalism was disproven or has been generally discarded. This is not the case. Not by a long shot.
  • Very important factor.
  • If this approach does bare fruit (and I tend to think it will even if it requires some years yet of innovation), applying Mores law would mean we will have machines with the same number of neurons and connections as the human brain in about 30 years, and in less than 50 years such a machine will exceed the neural capacity of all humans on the planet.

  • by jeffb (2.718) ( 1189693 ) on Wednesday April 06, 2016 @10:34PM (#51857945)

    I did a double-take at that -- it just didn't sound plausible. But, sure enough, Manhattan is just a couple of kilometers wide, and a kilometer is a million millimeters. If there are millions of axons passing through that cubic millimeter of cortex, that's about how far the segments would stretch in total.

    • by Anonymous Coward

      Also, not knowing the width of manhattan, made the whole declaration useless to me.

      • by Quirkz ( 1206400 )

        It told me it was somewhat longer than my small intestine, and somewhat shorter than my daily commute. In between, I'm not sure I'm really impressed/concerned/informed by knowing the sum length of my neurons.

  • Nice to hear the government is doing some good with my taxes instead of wasting them bombing wedding on the other side of world. When I was in school, I took some AI classes and my prof had no interest in the biological neurons. Machine Learning has made some great progress, but it's still just a bag of specialized tricks. They're too brittle and don't generalize well. If we're going to ever develop a true artificial general intelligence, we're going to have to model it after our neocortex. This is a good

    • by narcc ( 412956 )

      If we're going to ever develop a true artificial general intelligence, we're going to have to model it after our neocortex. This is a good start.

      A good start? They've been at that for ~40 years. We're still at the 'poke it with a stick' phase. Color me skeptical.

      • by chthon ( 580889 )

        50 years even. I have at home an issue of an old electronics magazine. It is from 1965, because it iintroduces the compact cassette.

        In this magazine is also a schematic from an electronic neuron, built around a single transistor.

      • The sticks are getting more sophisticated. Progress is painfully slow, but still progress.

  • They are working at building a brain. That would be like tasking the Ancient Roman Empire with replacing Chariots with electric cars, when they don't have any of the pieces necessary.

    You aren't born knowledgable, but every AI works hard at starting from a base of knowledge. You aren't born with rules and constraints, yet every AI puts them in.

    The brain is not a computer. The brain is composed of 90 Billion dumb computers that interact. Though AI wasn't powerful to follow that when Neural Nets were tri
  • by Anonymous Coward

    There's a better way to do it, and it could potentially image the whole brain, all at once. [youtube.com] It can image whole brains of mice and other smaller mammals at the neuronal level, and we can tag each type of brain cell automatically.

    Once you've got the raw data a simple AI program could map the structure logically by recognizing the tracers and plotting the connections...

    Of course, this cheap and simple method may not put money in the right pockets. See what I'm thinking?

  • In case anyone was wondering how much they got for this project, it's part of a $100million NIH project [nih.gov].
  • Understanding how the brain works by modeling one cubic mm of cortical matter? It sounds like: "We want to understand the global ecosystem, and we start by simulating what's happening on this square meter of soil". First of all, there is likely going to be a huge diversity in terms of the structures and behavior of a cubic mm of cortical matter, depending on what part of the brain you look at. Secondly, it is relatively undisputed that the functional behavior of the brain is determined by structures at scal
    • by Bengie ( 1121981 )
      More like "We want to understand super-cluster orbits, and we will start by modeling our solar system".
  • Mind Uploaded comes a little closer. 1 cublic millimeter uploaded. Now they have to scale up by about a million times (1 litre), and we'll have an uploaded human
    • The first uploaded organism is already done. It's a worm. It actually a composite of several worms - C. elegans has the useful feature of every individual being absolutely identical in cell layout.

      Here's the worm having been Matrixed into a simulated body and environment: https://www.youtube.com/watch?... [youtube.com]

      Interestingly, it swims just fine without neurons. Basic motion seems to be a function of muscle cells alone - the nervous system just determines where to go.

  • for another AI winter.

    Strong AI:

    Our motto is: over-promising and under-delivering since 1951.

    Our main algorithm is:

    1) Remarkable step on a well defined area in AI is made (e.g. AlphaGo)
    2) Issue lots of press releases
    3) Claim that single isolated step is proof that all remaining thousands of steps needed are just around the corner
    4) Apply for grants/create startups
    5) Profit!
    6) Ten years later AI winter sets in
    7) A few years later, serious AI researchers who have quietly been plodding along make another remar

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