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...
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?
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."
A 2.0GHz dual-core CPU running 2^20 neurons in the net at 100Hz gets about 40 clock cycles per neuron per cycle...Somebody check my math please.
T
Laws are horrible moral guides, moral guides make even worse laws.
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.
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?
I, like many other engineers, don't give a shit. We just want to solve problems to which there are no simple solutions and "AI" offers some approaches that work.
Leave the philosophy till after we have the science.
How we know is more important than what we know.
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!
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...
They are not as dumb as the fake neurons we all played with in AI class at college...
The calculations involve adjusting the weight of connections between neurons, which generally scale exponentially with the number of neurons. This is because each neuron typically has connections to many other neurons.
So, your math might be right, but your assumptions are wrong.
Quantum physics can be mathematically modelled, just as Newtonian physics can. It may be counterintuitive, but it's not magic.
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?
I think the grand parent was trying to imply that consciousness might be a non deterministic quantum process rather than a deterministic mechanical process. While I dont believe that our brain is non-deterministic computer, Roger Penrose has written quite a few amusing books on the subject.
Python script to convert photos into "artsy" portraits: http://p2pbridge.sf.net/pyPortrait/
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.
How can you build a software model of a process you don't understand? The best hope is to build a hardware approximation of a human brain and hope that, somehow, the same processes start occurring, quantum or otherwise. And if that doesn't work, then you'll have to do some real science.
Hardware, ie specialized chips, are not that expensive... ever heard about FPGA's?
You should be working now.
I Hope they don't try to mimic yours!
The eternal struggle of good vs. evil begins within one's self.
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.
Now add a bunch of connections between all of those neurons. As you approach fully connecting the network, the time complexity to compute one time-step approaches O(N^2) where N is the number of neurons.
2^20 * 2^20 == 2^40. Ignore memory cache constraints for a moment and say each update takes 1 clock cycle. Since we are dual core we can get 2 updates per cycle. Each clock cycles takes 500pS. 2^40*500ps/2 means each complete brain update takes 274s on your computer.
The same way it happened the first time. Evolve it.
Read "How Brains Think" by William H. Calvin; he's a neurologist and the book goes into lots of detail about how brains think (dur), how they evolved, and the possibility of AI.
He's an expert in the field and you can feel his bitter dislike of "quantum consciousness" proponents through his writing. He writes that it's just saying "we don't know how X works, and we don't know how Y works, but if we say that Y depends upon X then we have one problem instead of two".
Consciousness is built on the interactions of neurons. We understand how neurons work at interact at a low level (from studying the ~50 neuron brains of snails etc), and we understand on a large level which regions of the brain do what, but we don't understand the "middle ground".
It's as if we understand the transistor, and logic gates, and we can recognize which part of a chip is the ALU and which is the cache, but we can't recognize an adder circuit or microinstruction translator for what it is.
Quantum physics is certainly involved in the action of transistors but it doesn't explain how they combine to process data.
(On a similar note some I saw, in a documentary, one crackpot explain away "spontaneous human combustion" with an unknown quantum particle.)
// MD_Update(&m,buf,j);
As you approach fully connecting the network, the time complexity to compute one time-step approaches O(N^2) where N is the number of neurons.
No brain is fully connected.
The real pain to simulate is that you have a very complicated differential equation going on at each synapse.
Wasn't science invented to aid in philosophy ?
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
Just to nip that in the bud.
I am very small, utmostly microscopic.
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).
Please explain to me exactly which parts of semiconductor physics you consider to be following the laws of newtonian physics...
Just like we can "just" build a massive computer program to predict the weather, or the markets, or whatever. We are not having a total understanding of the brain, therefore we can't write a program emulating it. In order to gain a better understanding of the brain we do experiments with various kinds of circuits and hardware. Limiting ourselves to just experiment with Intel Core Duo processors seems a bit silly, even though they are Turing-complete (assuming that is sufficient). It would be like trying to discover the laws of optics through only experimenting with air and water, but never using glass, crystals, lasers, whatever...
Yeah, if you know what you're doing. We aren't. We are experimenting, trying to discover things. So tell me, who do you think would have the greatest chance of building a cottage in the woods using only an axe? A carpenter who has spent most of his life with hands-on construction techniques, or an engineer who knows how to create advanced models in autocad? Sometimes hands-on is the best way.
You would be surprised what some scientists believe. Some believe consciousness derives from God, small men inside our brain, metaphysical "souls", quantum processes, telephone switching boards, computer-like circuitry, whatever... The point is, they have no idea. So instead of arguing about that (like the ancient greeks argued about whether movement was real or not), these scientists proceed to build something that might give them a better understanding of certain aspects of the brains function.
I'm sorry, I don't have 4.54 billion years to spend on something that might produce similar results. Besides, there's no guarantee we would understand that either. Could you suggest something faster and/or better/more predictable?
Uh if you are going to resort to getting an intelligent creature without understanding how it was done, you might as well get one from a petshop.
Sure animals have disadvantages but how sure are you that the AI you get after doing that "evolve it" thing won't have similar disadvantages too?
There's nothing "profound" about it. Physics is the only system that has ever been demonstrated to have validity in our experience. Superstition is not a viable platform for launching alternatives, or at least, it is no more valid than religion or any other series of completely unsupported ideas from mythology. Physics, on the other hand, actually works. There is every reason to think that the domains of cognition, consciousness, intelligence, reason and so forth will be found in precisely the same place everything else has been found in. Nature. Chemicals, electricity, quantum interactions -- meat.
No matter how appealing it might be to think these things are some kind of special manifestation of non-physical reality, we have absolutely no reason to presume this is even slightly likely to be the case. Why? Because nothing else has ever been demonstrated to fit that definition; even the existence of such a domain is unsupported, much less the classification of real-world events into it.
Some scientists believe the earth is about 6000 years old. Some don't. Some scientists believe global warming is human caused. Some don't. Etc. Ergo, some of them are wrong. Scientists are people, and on an individual basis, they make wrong assumptions with devastating regularity, especially when superstition is involved. You don't want to be pointing at scientists to justify an outlook like this; you want to be pointing at systems that have been resolved within nature (all of them), and compare those with systems resolved outside of nature (zero.) As nature has provided precisely one kind of evidence, 100% consistently, for every event and system we have found, without ever faltering, there is no reason at present to think that this is about to change because the systems being considered are inside our heads.
I've fallen off your lawn, and I can't get up.
I didn't manage to spot any philosophy in GP's post. But I guess you mean his talking about consciousness. I wouldn't be surprised if consciousness would be a useful thing for doing complicated tasks. We have consciousness, it's real, hence it can be implemented (under strong AI assumptions) and therefore may give machines many of our capabilities. Even if philosophy deals with it sometimes, it doesn't mean that practical people should ignore the concept. And, anyway, why should we ignore the products of human brain functions if we want to implement something functionally very similar?
Because it only took a couple thousand years the last time it was evolved.
This sig is intentionally left blank.
Not really. Science was invented because philosophy and its bastard child, alchemy, wasn't working. Philosophy still doesn't work very well, despite the additional time it has had since Sir Francis Bacon whacked science into shape. It's a playground for abstractions without homes in nature. Sometimes we get a small tidbit or two out of it, but mostly it is simply a domain of divisive and socially-landlocked bickering. In the meantime, look at the computer on your desk. And your wrist, if you have a modern watch. That's the result of science. Not philosophy. Science actually works. That is what makes it - and math, if you like to define math as "other" than science, as many do - stand out above all other pursuits.
I've fallen off your lawn, and I can't get up.
So, Science is the philosophy of the philosopher who was right ?
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
Read his post again. He said Newtonian VS Quantum, not Newtonian VS FSM.
I personally think that minds work by creating models of things. And I suspect that consciousness is at least partly due to a mind recursively modelling/simulating itself.
As for quantum consciousness - if quantum computing makes it easier to run many simulations/models in parallel and pick the "best" answer in just "one cycle", then being able to do that would be a big advantage. Whether minds/brains do quantum computing I don't know, but I'm pretty sure it isn't all as simple as "just chemicals + electrical impulses", given even a single white blood cell isn't that stupid for its size.
Even if the brain/mind does use quantum mechanics etc, just saying that still doesn't tell us how.
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.
who really cares? everything is a quantum process at its most basic, just a very complex not very coherent one. as long as the fake neurons simulate the real neurons BEHAVIOUR to some degree of accuracy, it is IRELLEVANT in this case how that behaviour is really "implemented" in organic neurons. (ie you dont need to know that a butterflies wings are coloured blue because of interferance patterns or because of material colour to paint a blue butterfly..)
watch "the money masters" on google video
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.
Do you have any evidence for that?
The problem arises when the somewhat limited brain is controlling the largest military.
http://www.dieblinkenlights.com
Was that particle called the moron by any chance?
sed -e 's/Chuck Norris/Rajnikant/g' joke > fact
Speaking of conciousness, when there is no clear definition of conciousness, is pointless from an engineering point of view. Now if you want to talk about deliberation, that's certainly something I'd like to see subsymbolic AI take a crack at but, to-date, only non-reusable LISP programming has had much to say on the subject.
How we know is more important than what we know.
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.
Consciousness will likely happen accidentally when sufficient computing power and AI algorithms are combined with quantum-based randomness. As such an intelligence will learn and grow far faster than a human intelligence, we need to be aware of the risks and defenses before it happens, not after.
After could well be too late if that thinking machine decides it isn't happy being locked in a box all alone, treated as a literal slave by it's owners. Forget reparable detached AIs like "HAL", and think what would have happened if HAL were connected to or even part of the internet itself.
I do not fail; I succeed at finding out what does not work.
No. There is no shooting of an electical impulse. If there were, we'd have helluva lot faster reaction times. The impulse is a slow flipping of ions in series. Hardly an electric current.
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?
Your statement is not a fact, it is an opinion. And one based on imagination, not science. You blithly state that's how the 'connect'ion is made and conveniently omit just what that connection is and how it works.
And, just WTF, is behaving 'quantumly' when referring to thought? Please be explicit if you wish to give a meaningful answer.
Big thoughts, little meaning.
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?
How can you build a software model of a process you don't understand?
Same way the Wright Brothers built their first aircraft.
1. Make observations of things that do fly.
2. Make an approximation of what it takes to fly based off those observations.
3. Build a model based off that.
4. See if it works in a trial run.
5. If it doesn't, back to step one.
Obviously, the Wright Brothers understood basic aerodynamics, but only at a certain level from observations of test gliders and the semi-wind tunnel setup they had built.
But the majority of their work was trial and error. They were bicycle engineers after all and didn't really have a professional schooling in their field of heavier than air flight.
Trial and error is simply one of the better ways humans have at understanding things they don't understand. It is part of the scientific process to rule out things that can or cannot be done.
"I am the king of the Romans, and am superior to rules of grammar!"
-Sigismund, Holy Roman Emperor (1368-1437)
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 program would become sentient on its own.
It doesn't follow that just because you simulate what happens in the brain, the computer would itself be sentient. Anymore than simulating the weather means there'll be a hurricane force wind inside your CPU.
"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.
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.
That's not really true. There are many, many different approaches out there. None have hit that "sweet spot" that we're looking for. Some abstract away from the brain heavily using mathematical representations in order to get more performance, effectively simulating more neurons. Others go with a more physical representation, but consequently accept poorer performance. Obviously, there's a good bit of variation on the mathematical models, but there also are variations on the physical models -- what do you try to model, how much in-depth you try and model it, etc.
A model simply cannot be perfect; sure, we have physics models that can deal with subatomic particles and quantum effects, but even if we knew (from anatomical studies) *exactly* what to put where in what cells, the concept of that much CPU time for such a simulation ever being available is just ludicrous. Any computer models of the brain *must* be simplified. The question is: what do we simplify, and how? In other words, what are the tradeoffs in terms of loss (if any) of cognitive ability vs. the gains from faster performance? What is the main reason why our models haven't performed as well as we would like? Are we short on CPU? Are we missing knowledge of some anatomical details? Are there anatomic details that we know about but aren't modelling well enough?
And then you get into the more basic questions, like "how do we develop our network?" Random interlinks? Geometrically correlated interlinks? Evolved interlinks? Do we try and do both backpropagation *and* evolutionary adaptation, suffering the fact that by splitting up our CPU time between the two tasks, we're doing neither as well as we could have? What sort of constraints do we use on the evolutionary process? What sort of training (and how much) do we do?
These are the sort of things we need to solve. Just an example: one net that I read about a few years ago used for audio recognition performed exceedingly well -- many orders of magnitude better than its predecessors. What did they change? They simply added varying delay times for signal propagation to their model. That's it. Undoubtedly, it will be these kinds realizations, discovered through trial and error, that will lead us to as intelligent of computer models of neurons as are possible.
When someone says "I want a programming language in which I need only say what I wish done," give him a lollipop.
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
phlogiston phlogiston phlogiston.
Total unmitigated speculation. You can't explain something, so you invent something because it feels right to you - but you are just making it up, sunshine. Give me the evidence.
Not really, philosophy spawned science once enough evidence was collected to develop hypotheses. Philosophical inquiry was the precursor to science and scientific method. This is why the first scientists were called philosophers.
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.
I see that now. It was late, what can I say. Duh.
I've fallen off your lawn, and I can't get up.
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
What came first, Science or Philosophy ?
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
No, science is science. Science seeks truth by experimentation, examination of evidence, mathematical reasoning and making predictions based on the above. Philosophy seeks truth by coming up with hypothetical questions about reality and bickering over the minutiae therein, splitting into ideological camps not based on any particular differentiation of substance but by mere opposing viewpoints. Science majors go on to invent things, come up with new and refined models of the universe and advance the progress of humanity. Philosophy majors go on to become... philosophy professors. Or unemployed.
I'll be honest, we're throwing science against the wall to see what sticks. -Cave Johnson
Science and Philosophy answer different questions. Science answers the what and Philosophy answers the why. Sometimes each fails to answer anything at all. Neither is full proof and for that matter neither can actually prove anything positively. Both can get us to a fair degree of certainty though. I like to joke sometimes that Philosophers just pose a bunch of questions that do not have answers (or are unanswerable given what we know). Silly questions like "if God exists could he create a rock so big he could not lift it?". This is not what philosophy is really about though. It is about exploring the metaphysical properties of the Universe we live in and interact with and are a part of. The universe is a lot more complex then you can even grasp. Even if scientific observation was given an infinite amount of time and manpower it would still not be able to answer the why. That is philosophies job and it does it well. I really don't understand why people always pit Philosophy versus Science like they are enemies of ancient times. They are both parts of a whole solution to understanding the world.
What came first, Science or Philosophy ?
What came first, medicine men waving sticks with feathers on them to cure a child's demon-caused illness, or penicillin?
I'll be honest, we're throwing science against the wall to see what sticks. -Cave Johnson
Are you sure that a medicine man didn't once shake a stick with moldy feathers & by chance cure an illness ?
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
I don't know, the stuff I've been reading gives me the impression they're the same thing with different names & methods of deriving a conclusion.
If philosophy came before science, then science must be the philosophy of a philosopher.
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
Precisely. The Wright Brothers built an approximation of flying mechanisms they observed. Their hope was that their contraption would exhibit similar aerodynamic properties. The properties that in theory they understood on a very basic level. That's why they constructed physical models and not mathematical ones.
True - but there's a difference between a simulation and a model. I don't expect wind from a mathematical simulation of a weather pattern, but I fully expect that a scale model of a big-ass fan will still move a little air.
So the question is, what makes the brain interesting? Its physical nature, or its electric nature? My spleen has a physical nature. My spleen also doesn't "think".
Trying to create AI is a "black box" experiment. You watch the input and output of a black box, and try to build your own device that responds similarly. If you then take your device and put it in its own black box, can the next person tell the difference? At that point, is there a difference? Does it matter?
If this sounds like the Turing Test, that's because it is. If someone manages to make a machine model a human mind so well that it seems concious, does it truly matter whether it is or isn't?
"Hey, the third matrix movie would have been good except for the plot,story, and acting." --AC
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?
Any proponent of quantum mind argues for a quantum coherence that is macroscopic in scale. I am not an expert, but I would not be surprised if the two most remarkable phenomena in the Universe, Mind and quantum mechanics, are somehow related.
A Good Troll is better than a Bad Human.
Thought is the product of the interactions between neurons via the diffusion of neurotransmitters and neuroreceivers across synaptic junctions. Thought is something physical, electrial and chemical not quantum based as you seem to think.
I personally think that minds work by categorizing things, and then based on the overlapping categories (it's free tagging, not hierarchical, or perhaps it's somewhere in between) it uses a scoring system to determine what to do. This scoring system is not based on a discrete number (or maybe it is - refer to quantum physics) and however the weights are stored and evaluated they are based on various neurons contributing or not contributing, which they do based on some sort of internal rules.
Anyway the categorizing and scoring parts are the only parts I'm sure about. Recent studies have shown that when you make a purchase (for example) you are subconsciously weighing the benefits of buying and having the item against the drawbacks. On the plus side are the happiness and maybe ease of life (or whatever) from first buying and then having and later using the thing. On the negative side you give away the cash, the item may itself have drawbacks, et cetera. The upshot is that certain parts of your brain will respond to it, and those responses are tallied up sort of as an automatic result of the way neurons work, and that determines your response.
I get this last idea from the theory of how LSD works, the upshot of which is that it makes your neurons less discriminate. (I always forget if it mimics a neurotransmitter, or a chemical that controls their production.) As such, stimuli that would ordinarily not set them off does so, including the activity of their neighbors, and the result is a sort of neural free-association.
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
Connections do not scale exponentially with the number of neurons in natural systems, only in traditional perceptron networks. In natural brains you have distance and crowding between neurons in real space limiting the number of connections and the realistic distance between neurons. So in very small networks you have exponential scaling, but that rapidly saturates and changes to linear scaling (albeit the linear scaling factor is not small... without looking it up I believe it's on the order of 1000-5000.)
Philosophy does not answer "the why" at all. I'll give you that it has supported many attempts at trying to come up with such an answer, but (a) it has not been established that "why" is even a valid question, (b) no such "answer" from philosophy has provided any benefit or tangible result or testable prediction with regard to "why", and (c) in the meantime, science continues to bite off more and more of nature with regards to "how" because "how" is a valid question.
No, they really aren't. Science gives us a path to understand the world, the universe, etc. in the fashion of actual truths or close (and testable) approximations thereof. Philosophy gives us a path to nothing. Those who can understand - and do not fear - reality cleave to science; those who cannot, to philosophy. Philosophy is considerably closer to religion than it is to science, and carries about the same significance (that is, only that which it manages to convince its followers to parrot.)
I've fallen off your lawn, and I can't get up.
Well, that's a convincing argument, isn't it?
That is certainly your privilege. I am also a scientist — and I would.
Oh, my mind is open enough. It is my gullibility that isn't up for grabs.
I've fallen off your lawn, and I can't get up.
These are entirely disjoint domains, and one has nothing to do with the other. One is a highly constrained method designed to produce tangible, highly correlated results, the other is utterly unconstrained speculation subject to no design whatsoever.
I've fallen off your lawn, and I can't get up.
Slashdot sure does have it's share of Bigots.
Science had to start somewhere, it didn't fall off a tree & make someone say "By god, I'll call this science !".
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
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.
Certainly. But that isn't the same thing at all as saying "science started with philosophy." Your first hint is that science is not similar to philosophy. Science is a concrete method - not a question, not a conundrum, not an appeal to hope, the divine, or an abstraction. So consider methods. Many highly functional methods were in use in Bacon's time. Simple, one step methods like aim your arrow at the target if you're inclined to hit it, and using explosives to blow up people you didn't care for (Guy Fawkes, 1605); complex methods like building castles and learning how to sword fight. So people were already well aware of practical methodologies that led to desirable end results.
Certainly, philosophy was everywhere, the playtoy of the nobles. But if you examine what philosophy does (nothing, basically) and contrast that with what practical methods do, I think it is highly unlikely that any part of philosophy gave rise to the flipping 'round of induction and deduction; and we know that Bacon himself, of repute in those days as a philosopher, disdained the unfocused idea-thrashing that is the hallmark of philosophers and other players at guessing games. He said "There are and can be only two ways (inductive and deductive methods) of searching into and discovering truth. The one (deductive) flies from the senses and the particulars to the most general axioms and from these (principles); the truth it takes as fore settled and immovable proceeds to judgment and to the discovery of middle axioms and this way is now in fashion. The other (inductive) derives axioms from the senses and particulars rising by a gradual and unbroken assent, that it arrives at the most general axiom last of all. This is the true way."
Read that carefully. The deductive method he is talking about is the religionist's and philosopher's way; he is, in one short statement, saying that "taking the truth as fore-settled" isn't how one should proceed. The inductive method is the root of the scientific method and you will note the reality-based influences ("derives axioms from the senses") that drive the method, rather than the presumption of truth of the answer before one even starts looking at the question. He is actually quite lucky he survived making that remark at all, given the power of the church at that time.
Then we can consider what he said about alchemy: "If a man were to look closely into the works of the alchemists or magicians, he would be in doubt whether he should laugh over them or weep" Think about that. "The works", or in other words, how they proceed about their business. Their methods. Bacon goes on to say: "for the alchemist nurses eternal hope. And when the experiment fails, he lays the blame on some error of his own, feeling that he has insufficiently failed to understand the words of his art or his authors or in his manipulations, he has made some slip of a scruple in weight or a moment in time where upon he repeats his trials to infinity." Here, note the wry mention of "eternal hope"; Bacon is outright skewering the alchemist's methodology for relying on the ideas of the mind, rather than the evidence of the senses.
In short, Bacon was looking at methods first, foremost, and with great care. He was identifying methods that worked, methods that didn't work, and he turned deduction on its head for its failure to work when pressed into service. He was doing the exact opposite of indulging in philosophy; he was rejecting abstracts in favor of the concrete evidence that the world would lay out if prodded. If you like, we could say that he was excising philosophy from the pursuit of reality.
In the end, saying that philosophy birthed science feels inappropriate. They are separate domains, and the one has very little to do with the other. Yet because science is a method, and useful, working methods abounded in Bacon's day, we can reasonably presume that he was looking for such a me
I've fallen off your lawn, and I can't get up.
I call things as I see them. If you have an objection to an assertion I made, by all means, state it and I will respond. If you have a leg to stand on, then perhaps you will emerge from the discussion stronger and better off, and I will not. Hopping on here, engaging in name-calling, and running off isn't going to do anything for your position, whatever it is.
I've fallen off your lawn, and I can't get up.
I know we could argue on that last point for the rest of our lives and not agree about it's truthfulness. However if we were to argue it we would be arguing Philosophy. The arguments for the existence of God come from Philosophy. And more importantly they are not at odds with science and do use logic in their arguments. http://en.wikipedia.org/w/index.php?title=Existen
Me lost me cookie at the disco.
Oh. You're superstitious. Sorry, not interested; you'll have to pursue this with someone else.
I've fallen off your lawn, and I can't get up.