Mike, MIKE TINTNER #####> Hawkins' point as to how the brain can decide in a hundred steps what takes a computer a million or billion steps (usually without much success) is:
"The answer is the brain doesn't 'compute' the answers ; it retrieves the answers from memory. In essence, the answers were stored inmemory a long time ago. It only takes a few steps to retrieve something from memory. Slow neurons are not only fast enough to do this, but they constitute the memory themselves. The entire cortex is a memory system. It isn't a computer at all." [ON INtelligence - Chapter on Memory] ED PORTER #####> "When you say "It only takes a few steps to retrieve something from memory." I hope you realize that depending how you count steps, it actually probably takes hundreds of millions of steps or more. It is just that millions of them are performed in parallel, such that the longest sequence of any one causal path among such steps is no longer than 100 steps. That is a very, repeat very, different thing that suggesting that only 100 separate actions were taken. You many already know and mean this, but from a quick read of your argument it was not clear you did. So I don't know which side of the "Do we need massive computational capabilities?" you are on, but we do need massive computational capabilities. That 100 step task you referred, which often involves recognizing a person at a different scale, angle, body position, facial expression, and lighting, than we have seen them before, would probably require many hundreds of millions of neuron to neuron messages in the brain, and many hundreds of millions of computations in a computer. I hope you realize that Hawkin's theory of Hierarchical memory means that images are not stored as anything approaching photographs or drawings. They are stored as distributed hierarchical representations, in which a match would often require parallel computing involving matching and selection at multiple different representational levels. The answer is not retrieved from memory by any simple process, like vectoring into a look-up table, and hopping to an address where the matching image is simply retrieved like a jpg file. The quote retrieval is a relatively massively parallel operation. You may already understand all of this, but it was not obvious from your below post. Some parts of your post seemed to reflect the correct understanding, others didn't, at least from my quick read. Ed Porter -----Original Message----- From: Mike Tintner [mailto:[EMAIL PROTECTED] Sent: Friday, December 07, 2007 3:26 PM To: [email protected] Subject: Re: [agi] Do we need massive computational capabilities? Matt, First of all, we are, I take it, discussing how the brain or a computer can recognize an individual face from a video - obviously the brain cannot match a face to a selection of a billion other faces. Hawkins' answer to your point that the brain runs masses of neurons in parallel in order to accomplish facial recognition is: "if I have many millions of neurons working together, isn't that like a parallel computer? Not really. Brains operate in parallel & parallel computers operate in parallel, but that's the only thing they have in common".. His basic point, as I understand, is that no matter how many levels of brain are working on this problem of facial recognition, they are each still only going to be able to perform about ONE HUNDRED steps each in that half second. Let's assume there are levels for recognising the invariant identity of this face, different features, colours, shape, motion etc - each of those levels is still going to have to reach its conclusions EXTREMELY rapidly in a very few steps. And all this, as I said, I would have thought all you guys should be able to calculate within a very rough ballpark figure. Neurons only transmit signals at relatively slow speeds, right? Roughly five million times slower than computers. There must be a definite limit to how many neurons can be activated and how many operations they can perform to deal with a facial recognition problem, from the time the light hits the retina to a half second later? This is the sort of thing you all love to calculate and is really important - but where are you when one really needs you? Hawkins' point as to how the brain can decide in a hundred steps what takes a computer a million or billion steps (usually without much success) is: "The answer is the brain doesn't 'compute' the answers ; it retrieves the answers from memory. In essence, the answers were stored inmemory a long time ago. It only takes a few steps to retrieve something from memory. Slow neurons are not only fast enough to do this, but they constitute the memory themselves. The entire cortex is a memory system. It isn't a computer at all." [ON INtelligence - Chapter on Memory] I was v. crudely arguing something like this in a discussion with Richard about massive parallel computation. If Hawkins is right, and I think he's at least warm, you guys have surely got it all wrong. (although you might still argue like Ben that you can it do your way not the brain's - but hell, the difference in efficiency is so vast it surely ought to break your engineering heart). Matt/ MT: > Thanks. And I repeat my question elsewhere : you don't think that the > human > brain which does this in say half a second, (right?), is using massive > computation to recognize that face? So if I give you a video clip then you can match the person in the video to the correct photo out of 10^9 choices on the Internet in 0.5 seconds, and this will all run on your PC? Let me know when your program is finished so I can try it out. > You guys with all your mathematical calculations re the brain's total > neurons and speed of processing surely should be able to put ball-park > figures on the maximum amount of processing that the brain can do here. > > Hawkins argues: > > "neurons are slow, so in that half a second, the information entering your > brain can only traverse a chain ONE HUNDRED neurons long. ..the brain > 'computes' solutions to problems like this in one hundred steps or fewer, > regardless of how many total neurons might be involved. From the moment > light enters your eye to the time you [recognize the image], a chain no > longer than one hundred neurons could be involved. A digital computer > attempting to solve the same problem would take BILLIONS of steps. One > hundred computer instructions are barely enough to move a single character > on the computer's display, let alone do something interesting." Which is why the human brain is so bad at arithmetic and other tasks that require long chains of sequential steps. But somehow it can match a face to a name in 0.5 seconds. Neurons run in PARALLEL. Your PC does not. Your brain performs 10^11 weighted sums of 10^15 values in 0.1 seconds. Your PC will not. > > IOW, if that's true, the massive computational approach is surely > RIDICULOUS - a grotesque travesty of engineering principles of economy, > no? > Like using an entire superindustry of people to make a single nut? And, of > course, it still doesn't work. Because you just don't understand how > perception works in the first place. > > Oh right... so let's make our computational capabilities even more > massive, > right? Really, really massive. No, no, even bigger than that....? > > > > > Matt,:AGI research needs > > >>> special hardware with massive computational capabilities. > > > > > > > Could you give an example or two of the kind of problems that your AGI > > system(s) will need such massive capabilities to solve? It's so good - > > in > > fact, I would argue, essential - to ground these discussions. > > For example, I ask the computer "who is this?" and attach a video clip > from > my > security camera. > ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?&; ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=8660244&id_secret=73825318-a6931f
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