The title statement is almost meaningless. It would be better just to say "simulating reality takes a LONG time".
My research is in molecular dynamics. I simulate systems up to 1 billion atoms on Kraken & Titan. HUGE approximations are made in simulating these systems, but depending on what exactly it is you're studying, these simulations still provide useful results. That is the key to all these studies: how well does your approximation reproduce whatever it is that you're attempting to model? In some cases, very well. For instance, I'm not going to get exact energy levels of a large system, but the system will qualitatively evolve in the same fashion that the experimental system does (which then guides the experimental counterpart to the research). I don't know the details of this brain simulation, but there is certainly some aspect of it that is not being reproduced anywhere close to real-life, and hopefully this isn't what they're interested in (and I'm sure they know that, but I don't think the article author does).
The very best simulations of reality that we can perform handle at most just a few H/He/C atoms. And an issue called the fermion-sign problem means that the computational power necessary to simulate larger systems scales exponentially with the number of particles. Unfortunately what that means is -- short of developing quantum computers (which are polynomial order for the sign problem) -- we aren't ever going to simulate more than a few atoms with near-perfect accuracy, and certainly nothing like a human brain.
EDIT: Didn't mean for my comment to sound so negative. Obviously, the researchers know exactly what they're doing. I was just trying to dispel the impression that we're close to simulating the human brain.
Generally, the people doing brain simulations like to claim that they can use a massively reduced representation (little more than a graph model that pushes signals around with some constants) and yet, somehow, the simulation is inherently capable of reproducing something complex about thought. I'm not sure how they get to this conclusion, but it's a massive reductionism. It would be nice if it were true- it would mean that for a reasonable expenditure, we could build a machine that, basically, "thought" and had a "mind" and we could convince ourselves that it was "living" much like we think of other humans.
To date nobody has come up with a really compelling disproof that they are more or less correct- thought and mind seem to be best explained as "emergent behavior of a complex system".
Now, whether can we bootstrap a thinking mind by running complex simulations on computers remains to be seen. I'd like to believe there is some interesting physics going on in brains we can't simulate with straightforward physical models, but there really isn't any good evidence for that.
For all the reasons you listed, if we’re going to crack the problem of strong AI in the next century, we’re not going to be doing it by simulating the brain at the atomic or molecular level. However the lower level simulations are important because we still don’t have deep understanding of how neurons work.
An overwhelming amount of neuroscience research data points to the neocortex reusing the same functional unit composed of 100's-1000's of neurons called a cortical column. For example one patient was able to regain her balance by rerouting the signal from her vestibular system to her tongue. So the cortical column is the layer of abstraction we should be shooting for.
Hopefully we'll move away from the 1950’s style perceptron, whose mathematical simplicity has attracted researchers but has been a major distraction to AI as they share almost nothing in common with their biological counterparts. If we don’t want to see a 3rd AI winter, we need to move to more biologically inspired approaches.
If we have a reliable model for how synapses fire, we can simulate the brain. Whatever problems quantum mechanics impose on molecular simulation is not relevant, the same way that you don't need to simulate the nucleons on your molecules even if you need precise energy measurements.
To put this claim in perspective, we are still unable to simulate a single cell by modeling everything we know from biochemistry, even if we ignore molecular dynamics. Mostly this is because we don't know what many genes and the proteins they encode do.
This matters, for example, if we want to simulate neuronal plasticity or the effect of antidepressants. We're an incredibly long way from a full simulation, which would also require integration with the rest of the nervous system.
> To put this claim in perspective, we are still unable to simulate a single cell by modeling everything we know from biochemistry, even if we ignore molecular dynamics. Mostly this is because we don't know what many genes and the proteins they encode do.
To me, this mostly shows that naive beliefs about difficulty aren't really accurate ('but it should it harder to simulate a brain than a cell, because it's bigger right!').
To correctly model a cell you would need to simulate every atom and there are about 10^11 to 10^14 (!) of them in a single cell.
I think an interesting number would be how many atoms does it take to simulate one atom reasonably well. Then you could get correct results for some ( really ) small biological functions.
If Moore's law were to continue to hold, this would mean the same simulation could operate in real-time on an 83K processor cluster in approximately 25 years or on one processor in about 50 years. Of course, this simulation is 1% of the neurons that a human brain has, and I don't know if scaling up to a full-brain would be linear (This probably depends on the average length of axons in the brain.). This completely unrealistic estimate also assumes no improvements in algorithms, etc..
Perhaps a more interesting question is whether or not the brain can really be simulated by a classical computer at all. If quantum mechanics plays a role in the function of the brain we will need a quantum computer to do the job. A classical simulation of a quantum brain would be a very odd beast indeed! It might exhibit behavior that seems like intelligence but somehow falls short.
Maybe the simulation algorithm is the thing that needs improvement. Some day one finds a way to reduce the complexity an order of magnitude, then the era of human brain is over.
Roger Penrose has theorized the brain relies on quantum effects, but it seems to have been as discredited as something currently unfalsifiable can be discredited.
At what point does this become unethical (if ever)?
Before you answer, please consider how certain you are that you are not a simulation.
Edit: I don't know the answer, and there probably is a large gray area. But I do know this starts to make me uncomfortable the more accurate it gets. Time to go reread Egan's Axiomatic again, I guess.
Even if you are a simulation, would you prefer not to exist? What, really, is the difference between reality and a perfectly-executed simulation? It's hard to condemn one without condemning the other.
I think it becomes unethical once we see strong evidence that the system could be self-aware. Before that, it's just a simulation. Simulating storm activity doesn't make it rain.
Without having an abortion debate, what's actually happening in the simulation is just a random interconnection of very primitive nodes at this point. The network has no refined architecture and, at best, some kind of spontaneous activity. In the number of nodes, it could be (generously) compared to flipping on a cat for one second. But a cat's brain obviously has extremely fine architecture, so the better analogy would be that they're flipping on a completely scrambled cat for one second.
Unfortunately, that's only for a number of cells equivalent to 1% of a human brain. A full brain's worth of simulation would take 2.5 days....although that much is probably not necessary. It will fall soon enough, though.
I'm not certain if that extrapolation you made of the time it takes to simulate a brain at the same abstraction level is valid. You're assuming the computation cycles needed will scale linearly, which might not be true considering that the brain is a network of neurons, where each neuron has a high number of in/out links to many other neurons. Consider the case where you take n seconds to simulate n neurons. Now add another neuron with connections to perhaps n/2 existing neurons. You'll have to iterate over each in/out edge of that neuron. Since adding just one neuron increases the time by a non-constant factor, the resources needed would increase more than just linearly. All this of course depends on the abstraction model, and I admit I know nothing about it.
The thought that we are maybe two decades away from having the computing power to simulate a human brain in realtime (and much more than that subsequently) is astounding, even in this age of technological wonder.
So it will take about 26.6 years before we can simulate a brain in real time, only considering Moore's Law. (Calculated this without pen and paper using my iPhone calculator, so somebody should check this ;) )
Does anyone know what it means to simulate brain activity? Is the brain being emulated in any meaningful way? Or is it just modeling the physical behavior of neurons?
Yes we are very far away from the human brain on many levels. However, I don't like this kind of article because it doesn't make sense on the software level.
Mathematically, we could figure out how much computing power we would need to match the human brain (24 bytes per synapse * number of synapse, etc).
I think I would be more interested in what was the specific of their experiment.
Recent research has shown glial cells, the uncelebrated insulator of the axon, in fact provide significant chemical signaling and modulation to the process of neural activity. Only phenotypical changes have been observed, it's not understood yet. Suffice to say that computational limits aside, we still couldn't simulate a brain because we wouldn't know what to make.
These attempts at brain simulation perplex me to no end.
Simulating a lump of tissue is definitely useful, it's when they start talking about simulating a complete brain that I get lost.
A brain doesn't happen overnight. It is the result of a long developmental process encompassing embryology, learning and experience acquisition.
How do they plan to wire the whole thing?
Micro- and macroscopic connections are well understood, it is the so-called meso-scale (in between) that is troublesome.
There will never be a non-destructive way to do extract the information of a live brain, and I'm not sure there will ever be a way to extract it at all. The current methods[0] allow to extract either the wiring or the genes expression.
Yup...people thought the Wright brothers should stick to building bicycles too. I mean how can a bicycle repairman replicate a mechanism that nature took a million years to develop in a bird? It was ridiculous. Couple years later they were watching them fly around in the air.
They use it to understand brain. So they wire it like the brain is wired.
If they simulate cortex, they wire arrange it into cortical columns (size of each column is between 50,000 and 100,000 neurons and there is over two million of them). Those columns have many different layers and neuron types. Understanding how cortical columns and minicolumns work is very important.
This has been done before with a full human brain scale model in 2005. It took 50 days on 27 processor for that simulation. It's always good to have more research being produced, but this linked article is a bit short on information.
I would imagine that the analogue nature of the brain is going to always entail a lot of approximation on simulation. I am not sure you could even accurately simulate even 1 neuron.
Disclaimer: this is completely out of my field - just a layman speculating.
How many Moore law doublings before it is real time? Seems like ~23 generations or ~35 years. Of course, if you leave out the bits constantly thinking about sex, we might get there a lot faster :)
[+] [-] Xcelerate|12 years ago|reply
My research is in molecular dynamics. I simulate systems up to 1 billion atoms on Kraken & Titan. HUGE approximations are made in simulating these systems, but depending on what exactly it is you're studying, these simulations still provide useful results. That is the key to all these studies: how well does your approximation reproduce whatever it is that you're attempting to model? In some cases, very well. For instance, I'm not going to get exact energy levels of a large system, but the system will qualitatively evolve in the same fashion that the experimental system does (which then guides the experimental counterpart to the research). I don't know the details of this brain simulation, but there is certainly some aspect of it that is not being reproduced anywhere close to real-life, and hopefully this isn't what they're interested in (and I'm sure they know that, but I don't think the article author does).
The very best simulations of reality that we can perform handle at most just a few H/He/C atoms. And an issue called the fermion-sign problem means that the computational power necessary to simulate larger systems scales exponentially with the number of particles. Unfortunately what that means is -- short of developing quantum computers (which are polynomial order for the sign problem) -- we aren't ever going to simulate more than a few atoms with near-perfect accuracy, and certainly nothing like a human brain.
EDIT: Didn't mean for my comment to sound so negative. Obviously, the researchers know exactly what they're doing. I was just trying to dispel the impression that we're close to simulating the human brain.
[+] [-] dekhn|12 years ago|reply
To date nobody has come up with a really compelling disproof that they are more or less correct- thought and mind seem to be best explained as "emergent behavior of a complex system".
Now, whether can we bootstrap a thinking mind by running complex simulations on computers remains to be seen. I'd like to believe there is some interesting physics going on in brains we can't simulate with straightforward physical models, but there really isn't any good evidence for that.
[+] [-] shardling|12 years ago|reply
On a deeper level, we still have trouble simulating even a single proton.
http://en.wikipedia.org/wiki/Lattice_gauge_theory
[+] [-] slacka|12 years ago|reply
An overwhelming amount of neuroscience research data points to the neocortex reusing the same functional unit composed of 100's-1000's of neurons called a cortical column. For example one patient was able to regain her balance by rerouting the signal from her vestibular system to her tongue. So the cortical column is the layer of abstraction we should be shooting for.
Hopefully we'll move away from the 1950’s style perceptron, whose mathematical simplicity has attracted researchers but has been a major distraction to AI as they share almost nothing in common with their biological counterparts. If we don’t want to see a 3rd AI winter, we need to move to more biologically inspired approaches.
[+] [-] marcosdumay|12 years ago|reply
[+] [-] foobarbazqux|12 years ago|reply
This matters, for example, if we want to simulate neuronal plasticity or the effect of antidepressants. We're an incredibly long way from a full simulation, which would also require integration with the rest of the nervous system.
[+] [-] gwern|12 years ago|reply
To me, this mostly shows that naive beliefs about difficulty aren't really accurate ('but it should it harder to simulate a brain than a cell, because it's bigger right!').
But of course, progress is being made on simulating cells: http://lesswrong.com/lw/drk/paper_simulation_of_a_complete_c... It's a high-level enough model that you can do it with only 1 core per cell.
[+] [-] deletes|12 years ago|reply
I think an interesting number would be how many atoms does it take to simulate one atom reasonably well. Then you could get correct results for some ( really ) small biological functions.
[+] [-] beloch|12 years ago|reply
Perhaps a more interesting question is whether or not the brain can really be simulated by a classical computer at all. If quantum mechanics plays a role in the function of the brain we will need a quantum computer to do the job. A classical simulation of a quantum brain would be a very odd beast indeed! It might exhibit behavior that seems like intelligence but somehow falls short.
[+] [-] 4ad|12 years ago|reply
Not at all. A classical computer can accurately simulate a quantum computer, albeit slowly.
[+] [-] luikore|12 years ago|reply
Maybe the simulation algorithm is the thing that needs improvement. Some day one finds a way to reduce the complexity an order of magnitude, then the era of human brain is over.
[+] [-] ck2|12 years ago|reply
Massive array at 8nm and there's your positronic brain.
[+] [-] wikiburner|12 years ago|reply
http://en.wikipedia.org/wiki/Quantum_mind
[+] [-] IvyMike|12 years ago|reply
Before you answer, please consider how certain you are that you are not a simulation.
Edit: I don't know the answer, and there probably is a large gray area. But I do know this starts to make me uncomfortable the more accurate it gets. Time to go reread Egan's Axiomatic again, I guess.
[+] [-] csallen|12 years ago|reply
[+] [-] cmapes|12 years ago|reply
[+] [-] Volpe|12 years ago|reply
I find it difficult to see how this could ever be unethical (given the status quo).
[+] [-] lvs|12 years ago|reply
[+] [-] moocowduckquack|12 years ago|reply
[+] [-] bhitov|12 years ago|reply
From the press release (emphasis mine):
"The nerve cells were randomly connected and the simulation itself was not supposed to provide new insight into the brain"
[+] [-] anigbrowl|12 years ago|reply
[+] [-] oh_teh_meows|12 years ago|reply
[+] [-] pervycreeper|12 years ago|reply
[+] [-] visionscaper|12 years ago|reply
[+] [-] ibudiallo|12 years ago|reply
How many gears from a mechanical computer does it take to simulate a micro processor?
If we were to one day to closely simulate the brain, I am sure the method will not involve computers as we know them today.
[+] [-] cLeEOGPw|12 years ago|reply
Imo brains themselves are like mechanical gears compared to the potential of processor.
[+] [-] jjjeffrey|12 years ago|reply
[+] [-] marcosdumay|12 years ago|reply
[+] [-] pothibo|12 years ago|reply
Mathematically, we could figure out how much computing power we would need to match the human brain (24 bytes per synapse * number of synapse, etc).
I think I would be more interested in what was the specific of their experiment.
- What kind of software were they running?
- Was the software bug-free(yeah right)?
- Was the software optimized?
- Caching?
[+] [-] kingkawn|12 years ago|reply
[+] [-] pygy_|12 years ago|reply
Simulating a lump of tissue is definitely useful, it's when they start talking about simulating a complete brain that I get lost.
A brain doesn't happen overnight. It is the result of a long developmental process encompassing embryology, learning and experience acquisition.
How do they plan to wire the whole thing?
Micro- and macroscopic connections are well understood, it is the so-called meso-scale (in between) that is troublesome.
There will never be a non-destructive way to do extract the information of a live brain, and I'm not sure there will ever be a way to extract it at all. The current methods[0] allow to extract either the wiring or the genes expression.
[0] http://www.brain-map.org/
[+] [-] Sven7|12 years ago|reply
[+] [-] hannibal5|12 years ago|reply
If they simulate cortex, they wire arrange it into cortical columns (size of each column is between 50,000 and 100,000 neurons and there is over two million of them). Those columns have many different layers and neuron types. Understanding how cortical columns and minicolumns work is very important.
[+] [-] unknown|12 years ago|reply
[deleted]
[+] [-] npatrick04|12 years ago|reply
http://izhikevich.org/human_brain_simulation/Blue_Brain.htm
[+] [-] unknown|12 years ago|reply
[deleted]
[+] [-] SeanDav|12 years ago|reply
Disclaimer: this is completely out of my field - just a layman speculating.
[+] [-] psadri|12 years ago|reply
[+] [-] mentos|12 years ago|reply
Is there any research on what other chemical/electrical interactions might be necessary to simulate the brain?
[+] [-] omarchowdhury|12 years ago|reply
[+] [-] Tloewald|12 years ago|reply
[+] [-] frozenport|12 years ago|reply
[+] [-] nfoz|12 years ago|reply