Supercomputer Simulates Human Visual System

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?"

Comments

The Last Step For Ubiquitous Robotics?

[TheLazySci-FiAuthor]

Visual object recognition systems have been a thorn in the side of robotics since the beginning. The other annoynace of battery power will likely be solved by the nanowire battery - therefore leaving 'sight' as the real final technological step for our lovely robots.

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.

Re:New goal...

[spun]

Something like a Mantis Shrimp? Some species can detect circularly polarized light; each stalk mounted eye, on its own, has trinocular vision; they have up to sixteen different types of photoreceptors (not counting the many separate color filters they also have) to our four; and the information is transmitted from the retina in parallel, not serially down a single optic nerve like ours.

These are also the little dudes who can strike with the force of a .22 caliber bullet, fast enough to cause cavitation and sonoluminescence.

Go Super Shrimp!

The hardware is apparently there

[overtly_demure]

There are roughly 10^15 synapses in a human brain. If you place 10 Gb of RAM (10^10 bytes) on a 64 bit multicore computer and simulated neuronal activation levels with a one-byte value, it would take a 100,000 such computers (10^10 * 10^5 = 10^15) to pretend they have roughly the synaptic simulation power of a human brain. It is apparently now feasible, at least in principle.

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.

"interpretation" at what level?

[electric joy boy]

"aiming to produce a machine that can see and interpret as well as a human."

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.

1. perception: at one level you could argue (not very effectively) that interpretation just means perception... that's an eyeball/optic nerve visual cortex thing. e.g. You can perceive a face.
   
2. recognition/categorization: of visual forms involves the visual cortex/occipital lobe. e.g. you can recognize if that face is familiar
   
3. interpretation: involves assigning meaning to a stimulus and this involves many more parts of the brain than the visual cortex. It's obviously tied to memory which is closely tied, physiologically, to emotion. It also involves higher order thinking since, when most humans interpret a real world stimulus, there are multiple overlapping and networked associations that must be processed into a meaningful whole. e.g. you can recognize how threatening that face is, why it is threatening or not (and in what substantive domains it is or is not threatening), and even what you should do about it.
   

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?

Don't hold your breath

[videoBuff]

Human vision and associated perception has confounded AI folks right from the beginning.

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.