Slashdot Mirror
Building a Silicon Brain
prostoalex tips us to an article in MIT's Technology Review on a Stanford scientist's plan to replicate the processes inside the human brain with silicon. Quoting: "Kwabena Boahen, a neuroengineer at Stanford University, is planning the most ambitious neuromorphic project to date: creating a silicon model of the cortex. The first-generation design will be composed of a circuit board with 16 chips, each containing a 256-by-256 array of silicon neurons. Groups of neurons can be set to have different electrical properties, mimicking different types of cells in the cortex. Engineers can also program specific connections between the cells to model the architecture in different parts of the cortex."
that's great, but will it run linux?
now is the winter of our discotheque
[pinky finger]
Bet you could train that to do some cool stuff.. assuming it runs in realtime, as advertised, and what kind of back-propagation algorithms are implemented?
Neat though.
How we know is more important than what we know.
prostoalex tips us to an article in MIT's Technology Review on a Stanford scientist's plan to replicate the processes inside the human brain with silicon.
So how long until we get AI that's addicted to World of Warcraft?
Wizard Needs Food, Badly
will be mimicking the actual communication between the neurons. One problem that springs to mind is that many neurons will behave differently when presented different concentrations of the same neurotransmitter. This will be difficult to represent with an 'on-off' electrical switch. I think the idea is great though. Systems biology and model neural circuits will become excellent models systems for biologists
...to accurately model most American thought processes.
Gotta go - American Idol's back on.
Dave, my mind is going. I can feel it...
Obe Wan Kenobi
Life is not for the lazy.
16*256*256 = 1048576 hardware neurons.
Maybe that project would have made sense in the 1970's, but today this can be simulated in software at neck-breaking speed.
Lots of silion in Hollywood....oh you said BRAINS not BREASTS.
These posts express my own personal views, not those of my employer
Does anyone know what they mean by simulations? What are they trying to do?
Silicon tits were better....
It is dangerous to be right when the government is wrong.
One thing you don't hear much about, is what progress, if any, is being made in interfacing electronic systems into biologic ones, and growing biologic circuits. Perhaps our understanding of biological computation and storage simply isn't complete enough to make such a system practical, even if we were able to somehow interface a clump of neurons to the outside world electronically, but it certainly seems like the data storage capacity of biologic systems is far greater (per mass/volume) than anything devised artificially. Although, I suppose it's impossible to equate, since it's not clear how 'compressed' information is, when it's encoded by the mammalian brain as memories.
"Ladies and gentlemen, my killbot features Lotus Notes and a machine gun. It is the finest available."
This is hardly something new. Intel had a chip a number of years ago, called ETANN that was a pure-analog neural network implementation. Another cool aspect of this chip was that the weight values were stored in EEPROM-like cells (but analog) so the training of the chip would not be erased if it lost power.
But the whole technology of neural networks almost pre-dates the Von Neumann architecture. Early analog neural networks were constructed in the late 40's.
Not only are these simulations nothing new but they are in every-day products. One of the most common examples is the misfire detection mechanism in Ford vehicle engine controllers. Misfire detection in spark ignition engines is based on so many variables that neural networks often perform better than hard-coded logic (although not always, just like the wetware counterparts, they can be "temperamental").
There are several other real-world neural network applications (autofocusing of cameras for example).
Ahh the hidden magic of embedded systems...
What the heck do you put in the boot ROM for this kind of thing?
Moderators should have to take a reading comprehension test.
SLI on that puppy! (obligatory "Beowulf cluster of these" comment)
This is the most ambitions??? What about Markram & IBM? They must be just fooling around with that Blue Gene (actually I do think they are fooling around, but that's beside the point). What about Izhikvich? He simulated just a puny 100 billion neurons. That's *nothing* compare to this "most ambitious" million.
I would think a BOINC project might produce enough muscle to get a really big brain going. Imagine a BOINC cluster of...
;-)
If you mod me down, I shall become more powerful than you could possibly imagine.
But maybe I'll eat my words. Doubtful.
I have to wonder what the purpose is.. You can model simplified 'point' neurons, and various aggregates that can be drawn from them (eg, McLoughlin's PDEs)... or you can run a simplified temporal dynamic (eg. Grossberg's 3D LAMINART), and easily include 200k+ neurons in the model easily to capture a broad range of function. For those would like running more detailed models of individual neuronal dynamics, you have Markram's project simulating a cortical column with compartmental models, or what Izhikevich is doing with delayed dynamic models.
Although this setup may be able to run ~1mil neurons, in total, it would seem that with 16 chips of 256x256 each, the level of interaction would be limited, and the article has no indication that these are the more complicated (and realistic) compartmental models of neurons that can sustain realistic individual neuronal dynamics (and for example Izhikevich, Markram and McLoughlin have spent a lot of time trying to simplify), or whether this is just running point style neurons a bit faster than is traditional.. and I have to wonder here, whether if these chips can't do compartmental models, why not just run this on a GPU?
I checked out this guy's webpage, and he seems smart.. but this project is years away from contributing.. I wonder, especially with the Poggio paper yesterday, when the best work being done just at MIT in Neuro/AI right now is probably in the Torralba lab, whether slashdot editors may want to find some people to vet the science submissions just a tad.
August 29, two thousand seven.
I was under the impression neurons used neurotransmitters to communicate info between two cells but this article implies electrical signals do that. It would be nice to read some text on this subject that tried to explain the abstract difference between what transmits what information.
Building a hardware version of that sentient computer program is unnecessarily expensive. A software model of the actual hardware should be sufficient to prove the validity of the idea.
However, some scientists believe that consciousness is not newtonian. Rather, human consciousness is derived from quantum processes.
I, for one, welcome our new silicon-brain overlords.
when there is a computer error...
HAL's shutdown from http://www.imdb.com/title/tt0062622/quotes
HAL: I'm afraid. I'm afraid, Dave. Dave, my mind is going. I can feel it. I can feel it. My mind is going. There is no question about it. I can feel it. I can feel it. I can feel it. I'm a... fraid.
Good afternoon, gentlemen. I am a HAL 9000 computer. I became operational at the H.A.L. plant in Urbana, Illinois on the 12th of January 1992. My instructor was Mr. Langley, and he taught me to sing a song. If you'd like to hear it I can sing it for you.
Dave Bowman: Yes, I'd like to hear it, HAL. Sing it for me.
HAL: It's called "Daisy."
[sings while slowing down]
HAL: Daisy, Daisy, give me your answer do. I'm half crazy all for the love of you. It won't be a stylish marriage, I can't afford a carriage. But you'll look sweet upon the seat of a bicycle built for two.
[fade to blue screen of death]
if (!sig) { printf("Signature Unavailable\n"); }
About the only thing impressive about 1 million neurons is that it is slightly more than the square root of the number of neurons in the human brain.
Wake me up after the exponential growth has been going on a little while longer and they have made up the 6 orders of magnitude they need to make it worth of the term "brain".
But it's just going to be a massive comptuer....large processor, etc. or did I miss something?
The neuroscience community is invested in models that don't very well describe what brains actually do. Let me restate that, the descriptions of observed phenomena are unnecessarily complicated and also incomplete.
This project is destined to be like training elephants to knit. It'll be impressive, but the outcome won't be something you want to wear.
I for one welcome our new silicoid masters.
With their superior brain power, they may be able to devise a new way to say, "I for one welcome our new X masters."
For those interested in this field, may i suggest a book, Naturally Intelligent Systems? It's slightly older, but it explains a wide gamut of neural networks without a single equation, and manages to be funny and engaging at the same time. it is one of the three books that changed my life (by it's content and ideas alone - i'm not otherwise into AI). highly recommended: Naturally Intelligent Systems on amazon
CS majors know the time/space tradeoff, but they never get taught the 3rd, crucial, tradeoff of the set: comprehension!
First invented to help their masters.
Then they killed their masters.
The war between humans and Cylons began.
Why would you experiment with neural logic in hardware when software is infinitely scalable and programmable and arguably more valuable in the reserch of neural networks? Of course software is a degree slower in response time, but speed is not of the essence for researching the "how" of neural nets.
I would think that in the hardware world, generally you would want a working software model and then duplicate it with the more expensive hardware for performance. The same principal applies when ASIC engineers design in the less expensive, disposable FPGA format and when they get something working, eventually migrate the design to ASIC technology for increased performance.
It doesn't seem like there is discovery value in the hardware when the discovery should have been made in advance through software and at dramatically reduced cost. I have a feeling this guy's just trying to make headlines for himself...
The way I remember this working is that ion exchange is what causes the nerve signal to propagate through a single neuron, and the communication between neurons happens via neurotransmitters being released into the gap between the neurons.
So, when you slam your hand in a door, a signal travels as an electrical impulse the whole length of the nerve from your hand to the spinal column, then it crosses the gap to your spine as a cloud of neurotransmitters, then shoots up your spine as an electrical impulse to the brain, where it goes through the same process over andover again, until it triggers a response somewhere in your brain that makes you say a bad word.
Much more information here:
http://en.wikipedia.org/wiki/Neuron
Looking at this thread, I'd say that they have these chips hooked into the Internet already. Wow.
The brain is not an electrical based computing system, it is a quantum based computing system. That is how the 'connect' between the physical world and the 'thought/mind' world is made.
So any artificial silicon 'brain' will have have to behave appropriately (ie. quantumly) for such a 'simulation' (or any 'thought' based computation) to work or at least yield any meaningful results..
certainly it has certain charateristics like that, but to say the only possible usuable system is constrained only to that design is to miss the point...
we aren't trying to reduplicate the human mind anymore then a car is trying to reduplicate a horse, and there are several variations on 'intelligent' that don't even come close to the exact way a human mind works. Perhaps you should meditate on what it means to be 'useful'..
CS majors know the time/space tradeoff, but they never get taught the 3rd, crucial, tradeoff of the set: comprehension!
Two out of the three replies to my comment thought that I meant 40 cycles was enough per neuron. I guess I was not clear enough.
40 cycles is nowhere near enough. 40 inputs for a real neuron is small, and 40 cycles would barely let you sum the inputs. To heck with adjusting weights, you can't even run the thing in real-time. The AC I was replying to said that this could be simulated in software at break-neck speed. He is wrong.
T
Laws are horrible moral guides, moral guides make even worse laws.
...to accurately model most American thought processes.if this could only be a typical american problem, duh. stupidity is really world-wide. try locking it up in some nation-state, anyone?
Look at the rubbish the human brain generates. Ideology. Irrationality. Depression. Religion. Politics. Reality TV.
You really want processors that need weekly visits from an Eliza program and iZoloft patches?
"Sorry, Bob. I can't run those projections now. The supercomputing cluster is in a funk over the American Idol results."
Y'all think AI is going to be so great and a bag of chips, too.
Right way are ofcourse to create a software program that mimics the inner workings of the brain.
Having been a fan of neuromorphic engineering for several years now(Note I'm not an active researcher but I pretend somedays :) ) one of the major advantages of neuromorphic functionality isn't necessarily it's ability to model biological systems but the fact that the devices are extremely low power. When modeling neurons in silicon(at least back in the day of Carver Mead's work and for cochlea and retina stuff and I'm doubting it's changed too bunch but I could be wrong) the transistors would run in sub threshhold mode(basically leakage currents so OFF) since the power curves modeled the expected neuro response curves. One of Boahen's stated goals(at least on his website when he was at Penn) was to reduce power consumption and improve processing power for problem solving via these techniques. His lab has been in Scientific America a couple times in the last few years for work in accurately modeling Neuronal spiking in hardware too. I have them but not at hand so I can't cite them at the moment but they were fun reads.
So in summary, it's more than just modeling the brain. It's about letting biology inspire us to make better and more efficient computing systems.
I don't care what you say, all I need is my Wumpabet soup.
Let's hope this model isn't affected by the radiation around Ragnar Anchorage.
Just to nip that in the bud.
I am very small, utmostly microscopic.
But will it make the blondes smarter?
but the US is represented by their presidant. enough said!
The human brain generates so much rubbish because it does not use mathematical logic, but pattern matching.
In many cases, mathematical logic can not be used to prove the absolute truth of a proposition; therefore the brain uses pattern matching to 'prove' the 'truth' of a proposition to the degree that is useful for the survival of the entity that carries it.
Take, for example, the proposition that 'prime numbers are infinite'. We all think they are infinite, but there is no mathematical proof for it yet. When we are asked the question if 'prime numbers are infinite', then our first answer is 'yes'...that's pattern matching at work: since we have found a pretty large number of prime numbers, there must be infinite, just like in other cases (the decimal digits of PI, for example).
well, that's actually it - nothing more to see here, move along
Why would you want to model a human brain? I understand the reasoning of figuring out how the brain works, but if your going to make a intelligent system with the flexibility and ability to learn on the scale of a human being, I would think you don't have to emulate a human brain. Just emulate some of what seem to be the most important characteristics of the brain, and somehow take full advantage of the fact that most of the physical and biological restraints that apply to a brain do not apply to a software system.
Nuff Said.
I apologise if someone else has raised this point..
Why are some people intent on making Homo Sapiens obsolete?
1 Build humanoid robot
2 build silicon-based superbrain
3 ??????
4 Extinction!
Idiots.
Travelling forward in time at a rate of 1 second per second.
The problem arises when the somewhat limited brain is controlling the largest military.
http://www.dieblinkenlights.com
The article says that the chip will work at 300 teraflops. The human brain might be rated at 100,000 teraflops http://www.setiai.com/archives/000035.html so there is still quite a lot of speed to make up. However, it seems to me that through state saving (paging) one could simulate the connections between many more that a million neurons using this device. If you virtualize as a cube 3000 deep and track connections between these layers in software then processing over the virtual layers can proceed sequentially. So, it seems as though it won't take all that much more hardware development to get to simulations on the human scale owing to the higher frequency of individual operations.s -selling-solar.html
--
Solar, a bright idea http://mdsolar.blogspot.com/2007/01/slashdot-user
..this quantum based brain that we have. I was thinking independently of this, then while searching for this, i found many other people which incline to think that the brain might have an ability to harness the quantum properties of ..matter. Many Many things can be explained with this theory, including our massive "pattern matching/risk calculation" power. The "parallelism" of the brain might not be because of 100 billion neurons, but because of the quantum possibilities. However, this is just a theory.
don't forget, the brain also operates on a much lower voltage than most CPUs. Think of the battery life we could in laptops if they operated on a 70 (well a total change of 30(!)) millivolt potential.
The first type of back-propagation is the term as it is used by computer scientists using neural networks. (This is what you're thinking of.) The second type of back-propagation is the term as it is used by neuroscientists. Unfortunately, they are two completely different things. As a computer scientist who does brain modeling, this greatly irritates me.
Ben Hocking
Need a professional organizer?
I've been doing a lot of simulations with Izhikevich-based neurons (combined with RC filtered dendrites), and really appreciate his work. Have you read his 2007 book? (I have it, but have not yet read much of it.)
Ben Hocking
Need a professional organizer?
Having hardware that duplicates human thought is an excellent corner stone to help me with my many woes. With Hard Drives approaching the Pico byte range, we will be able to backup our memories; And access vitally important past events. Obviously, there will be many more steps to take before I will be able to access things like my wifes birthday, our first date, and so on. Personally, I will be very grateful for less arguments about past events that I have for some reason or another, considered to trivial to remember.
"Come back Dear! I'm good with True-False!" - Larry, the Cable Guy
If you're trying to understand a fruit-fly, then the current project is great. However, without using large numbers of neurons, you're going to miss out on important details. For example, when a signal travels down the axon, there's a certain probability that the signal will "fail" to cross the synaptic cleft. This is called a synaptic failure. It turns out that in simulations our lab did that such failures actually improve cognitive performance in a hippocampal model (and presumably in other regions of the brain as well). This was only true for models that had more than 2,000 neurons. Additionally, increasing the number of neurons increases the "optimal" synaptic failure rate. At 100,000 neurons the optimal failure rate was about 50-60%. (We actually simulate just the CA3 region of the hippocampus. For comparison, the rat CA3 has about 250,000 neurons in this region, and humans have about 2,300,000.) In the human brain, the actual failure rate is between 55-85% (depending partly on the part of the brain we're talking about). This is only one example out of many where the size of the network is very important in determining "why" nature made certain choices.
Ben Hocking
Need a professional organizer?
Every day, hundreds of millions of people have their energy sucked away by computers, in work places and living rooms equipped with game boxes. By the use of bank cards which give the government the ability to 'turn off' our money 'privileges' on an individual basis should they choose. Everybody seems now to have a cell phone. Aside from the mental health concerns associated with having your brain cells randomly stimulated by modulated microwave signals, having your time and attention on a telephone leash is enormously limiting. The only good of it all is the internet.
Humanity has been subverted, and it continues. The very saddest part is that EA sports games appear to be one of the primary culprits.
Sports games! I mean. . . For goodness sake.
I am glad that I don't understand the appeal of hefting foot balls as it renders me largely immune to the siren call of silicon.
-FL
"The first-generation design will be composed of a circuit board with 16 chips, each containing a 256-by-256 array of silicon neurons."
This already exceeds the connections in the cortex of your average political talk show host.
It is by the juice of the coffee bean that thoughts acquire speed, the teeth acquire stains. The stains become a warning
There have has been a proof for it for a long time. Gettin' wiki wit it.
Quoting from the link:
William of Ockham had no beard. The most likely explanation is that it was chewed off by squirrels every morning.
Precise immitation is not the best route to success.
Gives a whole new meaning to the name Rockhead.
Let's just say for arguments sake that scientists eventually perfect artificial intelligence in a computer or network of computers .at the conclusion of the experiment they pull the plug, would that be in effect the murder of a sentient being? Would legislation be enacted to protect intelligences in "virtual worlds"??
Damn No more setting fire to the Sims characters.
Biologists thought DNA sequencing of the human genome would take eons, too. Doing it by hand was horrible.
Then some engineers got interested.
Now we have gene sequencing machines.
People are clever when motivated. There's not much of a commercial need for generic AI yet.
..don't panic
I think this is how 'The Terminator' started isn't it?
....besides human stupidity, but much better yet, posttramatic stress disorder effects.
Imagine having an artificial cortex kick in when the real cortex is shutdown by PTSD stimuli.
and hardly a model.
There are analog processes involved in the brain. There are electrical fields around neurons that affect neurons that are not directly connected. The proposed device can't do these, or rather it could, but in such a device the result would be noise and error. In the brain the result is heuristic processing and global information storage.
Read "Brain and Perception" by Karl Pribram. It'd help to have a neuroscientist and a physicist available when you do so. It's not an easy read. I studied it under Karl, and sat in on sessions with him and two of the physicists who helped with the appendices, and it took me a year.
It's about some things we know, and most ignore, and so leads to the fact of how little we actually know of reality, substituting selective support for abstractions from psychology.
Simulators do remarkable things, often with fewer parts and processes than that which they model. However, they can only tell us things about the results from the abstracted model, and nothing about the thing being modeled.
"I may be synthetic, but I'm not stupid." -- Bishop 341-B
FTA: "We want to be able to explore different ideas, different connectivity patterns, different operations in these areas..." Building this system of interconnected processors is not 'building a brain' or even 'building the cortex.' The scientists/engineers are buidling a scaled down, highly abstracted implementation of a certain subset of subsystems of the brain, none of which are well understood. This is good exploratory science, laudable in its goals, but it is a laughable proposition that this system will be even a rudimentary modeling of the real world. A [human] brain is a highly integrated set of systems, whose most interesting attribute is [arguably] that it allows humans to think. Whatever this silicon system [or any subsequent system, no matter how advanced] achieves, 'thinking' [as in the common-sense definition] will not be one of its abilities; that is, unless you wish to engage in a semantics game... Turing knew this... see Chomsky's "Language and Thought: Some Reflections on Venerable Themes"... relevant excerpts here http://www.zmag.org/CHOMSKY/pp/#C1
Last time this was on slashdot, they mentioned it was a very very very slow model. The intriguing thing is, eventually it's going to be possible to transfer the complete memory of a living brain to a computer. A machine like this would then be able to perpetuate the life of the person indefinitely. To the person being simulated, the outside world would appear to go by very fast but time to that person would pass at the same rate as it did in their biological brain. 25 seconds would feel like 25 seconds regardless of the world spinning by super fate.
The question is, after the memory transfer, would the human begin experiencing what the silicon copy was experiencing after death in some kind of seemless transfer? Would the human just die forever and the silicon brain follow an entirely different path, like a twin? Although the knowledge gained by the human was perpetuated, is the human hopelessly destined to end their personal experience at death?
or more? or did you mean 256 dimensions with 16 ? editors? backup systems? spell checkers?
Hasn't anyone seen the terminator?!
...to replace Slashdot Editors?
This article tells us absolutely nothing about the design other than that the
total number of neurons emulated is very small. And no, this is not the "most
ambitious project yet" by a landslide. It is dwarfed by IBM's own Blue brain project, as well
as CCortex.
http://en.wikipedia.org/wiki/Blue_Brain
The only novelty I see here is that they fabricated artificial neurons on a chip, which greatly
speeds up the whole thing.
Non sequitur: Your facts are uncoordinated.
Does Major Motoko Kusanagi know about this ?
Ugh, already used my last mod point above funny