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Supercomputer Simulates Human Visual System
Posted by
Soulskill
on Fri Jun 13, 2008 04:23 PM
from the i-can-see-clearly-now dept.
from the i-can-see-clearly-now dept.
An anonymous reader writes "What cool things can be done with the 100,000+ cores of the first petaflop supercomputer, the Roadrunner, that were impossible to do before? Because our brain is massively parallel, with a relatively small amount of communication over long distances, and is made of unreliable, imprecise components, it's quite easy to simulate large chunks of it on supercomputers. The Roadrunner has been up only for about a week, and researchers from Los Alamos National Lab are already reporting inaugural simulations of the human visual system, aiming to produce a machine that can see and interpret as well as a human. After examining the results, the researchers 'believe they can study in real time the entire human visual cortex.' How long until we can simulate the entire brain?"
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Cell-based "Roadrunner" Tops Elusive Petaflop Mark 269 comments
prunedude writes "The NY times is reporting that an American military supercomputer, assembled from components originally designed for video game machines, is more than twice as fast as the previous fastest supercomputer, the I.B.M. BlueGene/L. To put the performance of the machine in perspective, Thomas P. D'Agostino, the administrator of the National Nuclear Security Administration, said that if all six billion people on earth used hand calculators and performed calculations 24 hours a day and seven days a week, it would take them 46 years to do what the Roadrunner can in one day."
Submission: Supercomputer simulates primate visual cortex by Anonymous Coward
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Just one word... (Score:2, Funny)
Re:Just one word... (Score:5, Funny)
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Re:Just one word... (Score:5, Funny)
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What cool things can be done? (Score:2, Offtopic)
New goal... (Score:5, Insightful)
Re:New goal... (Score:5, Interesting)
These are also the little dudes who can strike with the force of a
Go Super Shrimp!
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Re:New goal... (Score:5, Insightful)
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Re:New goal... (Score:5, Funny)
"Hew-mans! Hew-mans! Hew-mans! we're number one! we're number one!"
Feel better now?
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Re: (Score:3, Funny)
Re:New goal... (Score:4, Funny)
Can't help you on the question of their visual ability. Though I'm pretty sure they didn't see the net until it was too late.
I guess I get to really well-stocked sushi bars more often than really well-stocked aquariums.
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Re: (Score:3, Funny)
Re:New goal... (Score:4, Insightful)
Termite and ant colonies are examples of this. There was a group of scientists who injected a mound with concrete, and when they excavated it, the inner area was dozens of cubic meters. Large nests can protrude 9 meters above the surface while the underground area can extend 25 meters. The nests are climate controlled, including ventilation and are somehow protected against rain.
All this from an insect that few would call intelligent. Compared to the relative size it dwarfs all but the largest cities man has built. General intelligence is nice, but even if we had 10 times the processing power of our current brains, but had to learn everything from scratch each time, I doubt anyone would ever get past the iron age. There is only so much one can do with a lifetime.
Also humans don't have a great deal of general intelligence it seems. There is a great deal of our brains dedicated to social interactions and emotions. If we ran with a simpler set of social interactions, I have no doubt the average human would make Einstein look like an idiot regarding physics. Some evidence of this can be found in individuals with certain mental 'defects', like autism, which are able to master a task well beyond what most other humans can hope to, even with intense effort.
Finally... it really depends on what you mean by control. Vermin and bacteria spring to mind as creatures that exist nearly everywhere, despite our best efforts to eliminate many of them. Yes, we thrive with the most purpose and with the fastest increases (hence the idea of a singularity), but we are not the only species to thrive on this planet.
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Re: (Score:3, Informative)
Nope, not true. Practically everything our brain does is parallel, and this is definitely true of the optic nerve.
It's certainly a major bottleneck in the system; a lot of compression gets down by the retina before it is transmitted but that's because the optic nerve is long and has to move with the eyeball.
Yes, I think any mantis shrimp capable of self reflection would consider the human eye an
Re:New goal... (Score:5, Funny)
Mantis shrimp don't have a blind spot, because their eyes aren't like the stupid human eyes where the optic nerve attaches to the front! Nyah nyah nyah!
Here's the quote I was referring too:
I wouldn't, I mean, a mantis shrimp would never consider trading my, I mean his superior eyes for your puny human ones!
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Re:New goal... (Score:4, Funny)
Now if you'll excuse me, I have to go stun a herring.
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Re:New goal... (Score:4, Informative)
Liveleak has a video of the Snapping shrimp [liveleak.com]
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Interesting pictures, but... (Score:4, Funny)
-Rick
Ghost in the supercomputer (Score:3, Interesting)
And when this simulation claims to be conscious, what do we make of that?
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And when this simulation claims to be conscious, what do we make of that?
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Re:Ghost in the supercomputer (Score:5, Funny)
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Oh, for a second there.... (Score:2, Funny)
The Last Step For Ubiquitous Robotics? (Score:5, Interesting)
Extrapolating further, a human-quality object recognition system will yield results which we cannot currently imagine (let's avoid some big-brother robot talk for a second, however).
For example; I was looking at some old WWII photographs of troops getting on boat - thousands of faces in these very high-quality photographs. To myself, I thought,'Self. If all historical photographs could be placed in view of a recognition system, perhaps it could be found, interestingly, where certain ancestors of ours did appear.'
Throw in a dash of human-style creativity and reasoning and I'm certain some truly nifty revelations are to be found in our mountains of visual documentation currently lamenting in countless vast archives.
The Singluarity is Near (Score:4, Insightful)
Re:The Singluarity is Near (Score:5, Insightful)
OMG a super computer! It's so powerful it can probably pop up a consciousness of its own!
Sarcasm aside, computer power and strong AI are two very distinct problems. Computer power is all about scaling up power so you can do more in less time, that doesn't allow you to do anything new, only the same things except faster. Strong AI is all about algorithms, and nobody can tell if such algorithms exist. And anyone who talks about human-like strong AI is a crackpot (Kurzwiel is a crackpot to me for his wacky predictions), as we have yet to see a bug-like strong AI, and if it was just a problem of power we'd already have something working in that field.
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More on that: how in the hell are we to keep evolving if not through technology? We wont evolve "naturally", i think thats well established, not anymore. Our social system (for ALL of us) has not erm... evolved to be a good evolutive system that rewards the best.
The only way "up" is through a technologicall singularity. I dont think its ine
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...computer power and strong AI are two very distinct problems. Computer power is all about scaling up power so you can do more in less time, that doesn't allow you to do anything new, only the same things except faster.
Not really. Assuming that strong AI will require massive amounts of parallel computing (which it will if we model it after the human brain), we need supercomputers to test and write these algorithms. So one (computer power) is a prerequisite for the other (strong AI)
What does your comment add to what I already said? A single computer can still do anything any super computer can do, only maybe slower. Doesn't change the fact that we still can't make a bug-like strong AI, and yet we've got crackpots going around drivelling about human-like AI. The point is we have all the power needed to get started. You can wait until we get a computer with a million cores doing an exaflop each, that won't begin to make you create a functional bug brain that can learn how to do whatev
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What I took from the wikipedia article is that these astrocytes are responsible for neurotransmitter release and reuptake, these chemicals, based on my (admittedly limited) understanding are the primary movers and shakers in the brain.
Serotonin, for example is very deeply related to mood, hence why many prescription anti-depressant/anti-anxiety drugs are effective.
If my understanding is correct,(and it may not be)then astrocytes perform much more complicated function than a power cable.
Too Optimistic (Score:3, Interesting)
However, that is based on the previously incorrect assumption that neurons are the only kind of brain matter that is important. Now it is clear that glial cells play an important role in coordinating cognition. There are 10 times as many glial cells as there are neurons. That sets our simulation back a few years.
I think Ray Kurzwiel is way, way, to
Good luck with that. (Score:2)
After examining the results, the researchers 'believe they can study in real time the entire human visual cortex.'
I'll believe it when I'll see it. With my own eyes that is.
How long until we can simulate the entire brain?
How does 'never' sound? But more seriously you'd need to have an intricate understanding of its inner workings, besides the fact that it involves creating a strong AI which feasibility even in the distant future falls within the realm of wild speculation.
Vatanen's Peak (Score:3, Insightful)
It's funny that if you claim a mountain is impossible to climb they'll name it after you [wikipedia.org]. But try going up that same mountain in ten minutes. [youtube.com] Will they rename it after you? No way...
It's true that we don't know how the human brain works, yet, because we don't have all the needed tools to study it today. A caveman would never be able to understand the workings of a watch, you cannot study a watch stone tools. But each time a supercomputer beats a record we get a better tool to study th
....'cause there's people waiting for this! (Score:2)
Lord knows we've got a planetful of nitwits to help out somehow. Just build a massive mesh network and several of these and we could raise the World IQ by a couple of points, at least!
Yeah, I'm bored.
Let's link thousands of these simulations together (Score:4, Funny)
The hardware is apparently there (Score:4, Interesting)
We are ignoring for the moment how the neural network simulators work, how they communicate amongst themselves, how they are partitioned, what sensor inputs they receive, how they are trained (that's a tough one), etc. This will turn out to be extraordinarily difficult unless some very clever people mimic nature in very clever ways.
Well, at least the hardware is there.
Why supercomputers? (Score:3, Interesting)
Should be enough of us out here i would think.
Simulate is the operative word (Score:3, Informative)
However his simulation did not necessarily achieve computer vision in the usual sense, i.e: shape recognition, image segmentation, 3D vision, etc. This is the more cognitive aspect of the visual processus, which at present requires a much higher level of understanding of the vision process that we do not posess.
FYI the whole brain has already been simulated, see the work of Dr izhikevich [nsi.edu]. It took several months to simulate about 1 second of brain activity.
However this experiment did not simulate thought, just vast amounts of simulated neurons firing together. The simulated brain exhibited large-scale electrical behaviours of the type seen in EEG plots, but this is about it.
This experiment sounds very similar. I'm not all that excited yet.
"interpretation" at what level? (Score:4, Interesting)
First I want to say that this whole level of brain modeling is really cool. However, there are, of course, different levels of "interpretation" I don't think that this computer will be able to achieve a human level of interpretation simply by modeling the visual cortex.
Even "interpretation" at the second level above (which it seems the "roadrunner" might be able to model) require a lot more, for humans, than just the visual cortex.
In other words if we were to call into existence a floating occipital lobe connected to a couple of eyes that had never been attached to the rest of a brain we would never be able to achieve recognition/categorization let alone interpretation. If I'm wrong maybe some of you hardcore neuroscience type can help me out?
what we did in this simulation (Score:5, Informative)
Let me clarify what was done, and what will be done in the future.
We simulated about 1 billion neurons communicating with each other and coupled according to theoretically derived arguments, which are broadly supported by experiments, but are a coarse approximation to them. The reason is that we are interested in principles of the neural computation, which will enable us to construct special purpose dedicated hardware for vision in the future. We are not necessarily interested in curing neurological diseases, hence we don't want to reproduce all physiological details in this simulation, but only those that, in our view, are essential to performing the visual computation. This is why we have no glia and other similar things in the model: while important in long-term changes of neuronal properties, they communicate chemically and, therefore, are too slow to help in recognition of an object in ~200 milliseconds.
The simulation was a proof of principle only. We simulated only the V1 area of the brain, and only those neurons in it that detect edges and contours in the images. But the size of V1 we simulated was much larger than in real life, so that we had only a bit smaller total number of neurons than the entire visual system in a human has. Hence we can reliably argue that we will be able to simulate the full visual cortex, almost in real time. This is what will be done in the next year or so.
When we talk about human cognitive power, we only mean the ability to look at images, segment them into objects, and recognize these objects. We are not talking about consciousness, free will, and thinking, etc. -- only visual cognition. This is also why we want to match a human, rather than to beat him: in such visual tasks, humans almost never make any errors (at least, when the images are not ambiguous), while the best computer vision programs make an error in 1 in 10 casesor so (just imagine what your life would be if you didn't see every tenth car on the road). Based mostly on theoretical arguments characterizing neuronal connectivity, and neglecting many important biological details, we may never be able to match a human (or maybe we will -- who knows? this is why it's called research). But we have good reasons to believe that these petascale simulations with biologically inspired, if not fully biological, neurons will decrease error rates by hundreds or thousands. This is also why we are content with simulating the visual system only: some theories suggest that image segmentation and object identification happens in the IT area of the visual cortex (which we plan to simulate). While the rest of the brain certainly influences its visual parts, it seems that the visual system, from the retina to IT, is sufficiently independent of the rest of the brain, so that visual cognitive tasks may be modeled by modeling the visual cortex alone.
Finally, let me add that we got some interesting scientific results from these petascale simulations and the accompanying simulations and analysis on smaller machines. But we need to verify what we found and substantially expand it before we report the results; this will have to wait till the fall, when the RR computer will be available to us again. For now, the fact that we can simulate the system the size of the visual cortex is of interest by itself.
That's all, folks!
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Re: (Score:3, Informative)
I'm not too proud to ask a stupid question... What does having this simulation on a peta-computer do that having just a super-fast computer look at something for a longer time period not do?
One of the goals is to simulate the cortical processing in real time, which should almost be possible with the RR. Real time analysis allows one to process streaming video, such as from a security camera. Leaving real-time aside, there was one other reason why we needed the RR. When simulating ~billion of neurons with ~30 thousand connections per neuron, the total memory required to store the connections matrix (even if the strength of connections is calculated on the fly) is just below 100 terabytes, whic
Machine Consciousness (Score:3)
Re: (Score:3, Informative)
On the philosophy side, the usual objections to the reductionist approach and other philosophical nonsense like qualia are crushed by Dennett's well-thought-out
Don't hold your breath (Score:4, Interesting)
After examining the results, the researchers 'believe they can study in real time the entire human visual cortex.' How long until we can simulate the entire brain?"
There are researches who believe that humans use their whole brain to "see." If that is true, the claims of these researchers are highly premature with respect to vision. Everything from stored patterns to extrapolation is used to determine what we see. Even familiarity is used in perception - that is why there is this urban myth that "foreign" people look the same. If one were to ask those foreigners, they will say all indigenous people are totally different.
These programs run without meaningful data (Score:3, Informative)
How long? (Score:3, Interesting)
Until they can emulate the quantum/holographic methods the brain employs. Keep in mind, there are some worlds-in-worlds within the physical components. Just like how metal siding can form a complete circuit around the house, the nerves of the brain form multiple networks (chemical, electrical, interference patterns, etc)
How long? (Score:4, Informative)
Singularity (Score:4, Funny)
Not Bloody Likely (Score:3, Insightful)
They way well use their XYZflops to develop a visual processing system of some sort, but it will NOT be a simulation of something that those who understand it far better than they understand it hardly at all.
If and when they get to actually trying to match the human visual system in operation (though by different processing) they'll have to figure out of to get their system to consistently guess with fairly good accuracy what it's going to be seeing 0.1 to 0.3 seconds in the future. Proof of that long suspected technique was just forthcoming in the last week or so.
There is nothing at all "intelligent" about this. It is all automated processing. Level of "intelligence" has nothing to to with visual proceses' efficacy. Anytime anyone inserts the "I" word into anything regarding computers, particulary when comparing with the human brain, they need to define their terms. Almost certainly those of us who have struggled for years with the insufficient and contradictory proposed definitions of "intelligence" in the human mind will be more than happy to fill them in on why their definitions have already been proven to be failures in humans, and why anything derived from those will not apply to system designed to provide human-looking output via entirely different means of processing.
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