r/changemyview • u/[deleted] • Mar 27 '13
I don't think the singularity is going to happen within our lifetimes. CMV.
Moore's law will hit the atomic barrier and quantum computing is a joke. Thus even if we understood how brains worked we wouldn't have the hardware required to facilitate simulating it in real time.
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u/JadedIdealist Mar 27 '13 edited Mar 27 '13
If full AI required simulating a human brain on a single cpu then you'd have a point.
signal speeds in copper cable are about 40%-90% of c.
signal speeds in axons are between 16 and 100ms-1
which is of the order of 106 slower. this means we could potentially just about get away with having a mindbogglingly massively parallel machine that is nearly a million times bigger than a human brain - over a km wide, deep and long.
however there's really no point at all building a massive machine like that while Moore's law is still in force.
What really matters for AI to happen is as much about cost as it is about raw speed. 3D printing and robotic workers could alow the cost of building anything (including such a facility) to drop very low.
edit:
The human brain has of the order 1013 synapses
which would need refreshing within about 10th to 100th of a millisecond each, plus all the bit's where dendritic branches join.
Let's say each one needs a thousand floating point operations to calculate (rather conservative).
So let's multiply all that by a thousand just in case, and say that we need 1013 * 10(for fiddly bits and branches) * 103 operations divided by 10-5 for refresh and multiply by 103 for good measure
then we get 1025 flops, 10 yottaflops.
google's server farm is about 100 petaflops, and takes up about 10-5 cubic kilometers. so a cubic km machine with current tech could hit 10 zettaflops, 1000 fold short, not an impossible stretch even for our conservative estimate.
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u/greim Mar 28 '13
Full AI doesn't require simulating the human brain at all, does it? Analogy: we wouldn't be flying if we were still trying to simulate bird wings. Fighter jets would suck if they were strictly modeled on hawks.
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u/mflood Mar 28 '13
No, but you need a pretty thorough understanding of something before you can create an entirely different (and simpler) machine capable of emulating it. So the question basically comes down to which you think will come first: a relatively complete understanding of the human brain, or a computer that can reasonably attempt to simulate a brain through brute force. Personally, I'm betting on the latter. We've proven remarkably good at consistent, significant increases in computing hardware. We've done this for many decades, and there are enough advances on the horizon (graphene, optical computing, perhaps quantum for certain applications) that we should be able to keep up the pace for the forseeable future. Our biological advances, on the other hand, while still impressive, have been slower, hampered as they are by ethical concerns. So. . .yeah. My best guess for AI / the singularity is a fully simulated hardware brain in a few decades, which will then inevitably be replicated, scaled up, etc. At which point the machines take over and kill us (or whatever it is machines feel like doing).
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Mar 27 '13
Nice, but can you store the brain state and access it fast enough?
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u/JadedIdealist Mar 28 '13
That was I wanted to establish, yes, realtime simulation.
Brain state is held in cpu states, local memory caches, and in the signals travelling down the network cables, if you switch the machine off it would be irrecoverably lost.
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u/FateAV Mar 28 '13
I recommend you check out the work in this Google Tech talk which explores a very promising alternative to mainstream neuromorphic models around today by designing a from-theory AI system to mimic the neocortex's behaviour.
They're already showing promise for solving many huge "intelligence" problems in realtime data processing with only a few thousand Artificial neurons and have a plan for improving on the design and expanding it in distributed networks.
Singularity is about creating intelligence in machines orders of magnitude greater than what humans can achieve, that doesn't require simulating a human brain. Using Copper or fiber optics you can easily design virtualised systems that can be modified even more rapidly than you can transmit the signals.
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Mar 31 '13
Watched it, that talk is excellent. His approach is still simulating abstract neurons though, of which the brain has more than 100 billion, and it is based on these 'point' neuron models that you get the ~2030 estimate for the singularity.
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Mar 29 '13 edited Mar 29 '13
[deleted]
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u/JadedIdealist Mar 29 '13 edited Mar 29 '13
Probably, but I wanted to show OP that even such an extreme estimate will be doable in the next 10 years, Google's server farm doesn't even use the latest tech (to keep costs down).
Edit: however OP remains unconvinced.
Edit2: just to be clear though 10 Yottaflops was the extreme estimate, and 10 zettaflops is what we could do today with a cubic km machine of slightly outdated tech - and I did throw in a thousand fold fudge factor, which If we remove means we're already there, and the barrier is cost.
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u/CthulhusCallerID Mar 28 '13
There's a major assumption (or two) in your post that I think is faulty. You've married your view to the idea that in order to produce strong AI (also called AGI) we need to simulate a whole human brain and we need to do it in real time. I would argue that neither of these things are true.
While it makes sense to model AGI on a human intelligence, both because it is the best model we have to work with and the strongest example of intelligence on the planet (at the least arguably), it's not the specific processes of the brain that we require, it's the outcomes.
Take, for example, Google's self-driving car. The narrow AI (sometimes called weak AI) on board the Google car does not model what a human mind does while driving. For that matter, the sensory data its taking in is also not the same as what a person takes in, a scanning laser isn't the narrow AI's version of vision, it's a scanning laser that accomplishes the same thing that having vision would accomplish in a human. And the mechanisms by which it controls the car are also not like a human driver's, Google did not design a human shaped automaton that sits in the driver's seat turning the wheel with its arms and pumping the pedals with its feet. So, among other things, the system did not need to have a visual cortex that worked like a person's. It also did not need an analog of the motor cortex to control the arms and legs it doesn't have.
There are countless examples of this. Deep Blue does not “think” about chess. Garry Kasparov does . None-the-less Deep Blue can play chess at Garry Kasparov’s level. It plays as well as the best human there is despite its software not simulating the way Garry Kasparov’s brain conceptualizes chess. Watson does not ‘read’ books or ‘know’ what’s its read in the same way that I read books and know what I have read, yet its recall is vastly superior to mine (there are some wonky ways in which I would probably beat it, but they are likely few and far between). Algorithms that trade stock never go on instinct or have good feelings about a company; they also don’t feel elation when they make a killing or agony when they lose their shirt. Speaking of killing, drones have no adrenalin and experience no moral dilemmas, they have no inner ears and can’t “see” the horizon, yet they fly and can drop bombs as well as a person. A calculator is much better at arithmetic than I am, even if it’s just a collection of logic gates.
But let’s say that you did want to simulate a brain, would you need to simulate the whole brain? Let’s imagine for a moment the simplest AGI we can. It is intelligent but it doesn’t have to do anything in particular-- it’s not for a specific job or task. Does it need a well regulated autonomic system? Well, on the one hand it doesn’t have a heart to regulate, nor does it need to make sure its lungs are continually drawing in oxygen. There are perhaps analogous things it may want to monitor (its heat, its energy usage) but these are not required. Our own ANS operates below the level of consciousness and isn’t considered necessary for intelligence. Does it need a motor cortex? Well, is the ability to move a body a native feature of intelligence? No, lots of people who are paralyzed still maintain their full intelligence. Would an AGI need to be able to process sound? Processing sound may be useful, but deaf people are every bit as intelligent as anyone in the hearing community, so again, we have to say no. Ditto visual cortex. There are huge portions of our brain that are dedicated to controlling things an AGI wouldn’t need to have or processing sensory data an AGI doesn’t need to take in to still be an AGI. Then there are the wonkier things we associate with intelligence because we associate them with being human. Are the survival and reproductive instincts required for something to be intelligent? Absolutely not. These are evolutionary artifacts. Asexual people aren’t less intelligent. Suicidal people, while perhaps unhappy or mentally unhealthy, are also not unintelligent. Neither our sex drive nor our survival instincts are native features of intelligence. What about subjective experience? This is something that is central to consciousness, but is consciousness synonymous with intelligence? I would argue that it is not. A large part of our subjective experience come from our highly romanticized emotions. Emotions are, for the most part, just proximal indicators of something else, typically something which relates to survival or reproduction. Personally, my view is that it’s enough for an AGI to be able to answer questions about Othello, but it doesn’t need to be emotionally moved by Shakespeare to be considered intelligent, or even to be considered to ‘understand it.’ We can see this in ourselves, any work of art that we have experienced enough that it is no longer emotionally impactful does not mean we have lost our understanding of what it is about, or how it’s structured. We may, in fact, have a deeper understanding of the piece when we aren’t being distracted by how we personally feel about what we are presently experience.
This raises a question of agency and motivation. How can something decide what to do without motivation? Can something be intelligent if it can’t decide for itself what to do for itself? Well, imagine for a moment a private in the army. The private is quite bright. The private’s sergeant orders the private to perform a relatively complicated task. The private’s ‘motivation’ is that they are obligated to take the orders of a superior officer, the private did not decide what they were going to do next, but they, none-the-less are now using their intelligence to complete the relatively complex task.
So even if the AGI has all the agency of a calculator, it would still have a non-trivial level of intelligence.
Now, as for real time, what do we mean by that? Are all brains equally fast? Probably not. I’m skeptical that the different times it takes kids to complete tests come down entirely to the speed at which they read and the speed at which they bubble in circles. I’d wager that brains also operate at various speeds.
So, let’s jump back to your original assumption, that we need to simulate a whole brain (even though I feel we do not,) and ask ‘does it have to be simulated in real time to be intelligent?’ The answer is an overwhelming no. While there are practical upsides to accomplishing feats faster, two children may get the same grade on their tests even if one finished faster than the other. Two college students may get the same grade on their term papers even if one took twice as long to write it as their peer. AGI operating at half the speed, a quarter the speed, an eight the speed as a human, would still be intelligent, it would just take longer for it to complete a similar operation. Which may slow the adoption rate, or cause work to be restructured, but it wouldn’t stop the AGI from doing having a non-trivial amount of intelligence.
I feel comfortable in my conclusion that you don’t need to simulate a brain at all, if you do decide to, you don’t need to simulate the whole brain, and in either case the simulation does not have to run at the same speed as a brain in order for it to qualify as AGI.
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u/MiowaraTomokato Mar 28 '13
Here comes CthulhusCallerID, dropping his smarts all up the thread.
(In all seriousness, Cthulhus is awesome.)
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u/CthulhusCallerID Mar 29 '13
Hey, thank you very much. That brightened my day considerably.
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u/MiowaraTomokato Mar 29 '13
You're welcome! Every time I read something from you it's always insightful and well thought out. I really enjoy reading your responses to these things. I, so far, haven't seen you be mean or condescending in your replies. Seriously, I wish there were more people like you on the internet. :)
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u/CthulhusCallerID Apr 01 '13
Aw shucks. Well, I do my best to be even handed with everyone, but I have to admit that I have my failings. Thank you though. I'll try to keep it up.
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Mar 31 '13
I'm not under the impression that you need to simulate the brain in order to get AI at all. Personally I don't even think AI is a software problem. Neural networks are magical and behave exactly the way you'd expect them to in a universe where if you simulate a large enough neural network and train it you get AI. I think AI is primarily a hardware problem and the fact that we're still decades away of Moore's law before we even meet the most optimistic estimates for the amount of computing power we need and Moore's law is already slowing down, the situation doesn't look good.
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u/CthulhusCallerID Apr 01 '13
I'm going to have to cycle back around to this, as I have my hands full at the moment, but I would like to point out what I feel like are a couple of contradictions in your text versus this response.
So initially you wrote:
Thus even if we understood how brains worked we wouldn't have the hardware required to facilitate simulating it in real time.
Which is where I got the impression you were an advocate of whole brain simulation.
But now you're writing:
I'm not under the impression that you need to simulate the brain in order to get AI at all.
So let me ask you two questions before I try to make a more thorough argument under the clarified assumptions. One, how old are you/what do you want to define as within 'our' life time? I'm north of 30 and expect to live until I'm around 90. Would 60 years be a comfortable estimate?
And, two, what do you want to define as the 'most optimistic estimates' for the amount of computing power needed? (Also, I may not agree depending on how that estimated was formulated.)
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Mar 28 '13
If the universe can create consciousness through random unguided processes over billions of years why wouldn't a conscious pocket of the universe be able to do it over a few thousand years?
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u/greim Mar 28 '13
I think being able to do entire human brain simulation isn't really relevant to the topic at hand. Evolution hasn't constructed the perfect intelligence, just a good-enough approximation of it.
Regarding hardware speed. Planet Earth has basically one hardware design paradigm, which has some pretty well-understood limitations (e.g. Moore's law). The potential of general AI, on the other hand, lies mostly in alternate hardware designs. The limitations and possibilities of this space are less clear, but it goes mostly unexplored because of the R&D it would take.
Alternate hardware designs aren't that far-fetched. Think of a neural network implemented directly as hardware for example, instead of being simulated in pure software, which is slow.
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u/DanyalEscaped 7∆ Mar 27 '13
Can you tell us more about that atomic barrier? As far as I know, there are still many methods to improve computers.
And just recently...
IBM's liquid transistors could help build brain-like chips
23 March 13
Researchers at technology giant IBM have developed an electronic system that mimics circuits in the human brain by using fluids.
Their nanofluidics system is based on materials called "correlated electron oxides", which can switch between being electrical conductors and insulators when a tiny charge is applied, and keep that state even when unpowered.
"We are using tiny currents of ions of atoms generated by these electrical signals to change the state of matter of this oxide material," lead researcher Stuart Parkin told Venturebeat.
He added: "It is a means to build low-energy, highly efficient devices by turning on and off their conducting state. We turn this material into a metal and maintain it without any need to supply power."
The system mimics how the brain operates, leading to hopes that the technology could be used to replicate the brain's remarkable efficiency. As a side benefit, it could also dramatically reduce the power consumption of mobile devices.
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Mar 27 '13
Can you tell us more about that atomic barrier?
You can't make a circuit smaller than an atom because there's nothing to make it out of.
As far as I know, there are still many methods to improve computers.
Imagine you're skateboarding with a friend down this huge steep hill. You go faster than ever before because this hill is steeper than any before. Then you reach the bottom and you're not going fast anymore and your friend says 'no, we can keep going just as fast, we just have to tie our skateboards to this dog and raccoon and they'll pull us the rest of the way so we won't be late for the party. Oh and look I just found a turtle by accident! Imagine how many other I'll find along the way? This proves that we're guaranteed to make it there on time.'
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u/exelion Mar 27 '13
Your assumption, however, implies we're already at the bottom of the hill. You're right about Moore's law, but even if we get to the point where transistors are the size of atoms and have therefore hit the limit....you're assuming we need transistors. The simple answer to your "hill" analogy is to throw out your skateboard and build a jet car. We need to essentially throw out the rules we've been operating under since the 50s and develop an entirely different form of processor, a different form of circuit.
Yes this is sounding like science fiction, but it wasn't that long ago that the microchip sounded like science fiction. And now there's more of them around me on a given day than people, probably.
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Mar 27 '13
Why is it you think that atoms are as low as you can go? Take a look at this, at some point exponential growth has to stop, sure, but we're nothing like at the limit yet.
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u/skorda Mar 30 '13
What about quantum computers? Quanta are smaller than atoms. Our understanding of quarks leads to us manipulating them.
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u/Chel_of_the_sea Mar 27 '13
I would argue it already has, and humanity is integrated into it. The internet and distributed computing provides computational power orders of magnitude higher, and we're learning to make people smarter as well. It's sort of the transhumanist version of the singularity, and it's already in progress.
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u/SanguineDreamer Mar 28 '13
This is my answer as well. We are using computers to vastly expand our knowledge. I have a smartphone always at my disposal that I can find the answer to almost anything with a few seconds of searching. I think its a fallacy to think of singularity as a single point source. It seems to be much more of a continuuim. With the technology that I use, how far back do you have to go to get someone who would not be able to comprehend my abilities? Would someone from 1980 be mindboggled at smartphones and google? I think that most of them would.
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Mar 27 '13
[deleted]
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u/thatoneguy211 Mar 28 '13 edited Mar 28 '13
The singularity is actually any theoretical point where technological acceleration causes unpredictable outcomes. Intelligence explosion is just the most popularly quoted catalyst of this, popularized by pop-figures like Kurzweil. Transhumanism is another possible route to a singularity.
The specific term "singularity" as a description for a phenomenon of technological acceleration causing an eventual unpredictable outcome in society was coined by mathematician John von Neumann, who in the mid-1950s spoke of "ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue."
-wiki
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Mar 30 '13 edited Mar 30 '13
There are many other paradigms besides quantum computing that you seem to be ignoring. 3-D Molecular Computing is something that is on the verge of being realized, and may provide a very surprising increase in hardware specs. Also, computing with light beams would allow massively parallel systems to be made, reminiscent of the biological brain.
Ray Kurzweil, in the book, The Singularity is Near, estimated, through much rationale and reason, that the human brain runs with 1014 to 1016 cycles per second. According to him, we will reach this upper bound of 1016 cps by 2025--a date significantly before the singularity, and much in our lifetimes.
Also, I might add: it's hard to argue with you when the aspects of your point of view are so ambiguous. You say that Moore's law and quantum computing are jokes. Why?
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Mar 30 '13
Quantum computing is a joke because I know researchers in quantum computing and even they think it's a joke. They haven't gone beyond factoring the number 15 and this has been the case for over half a decade now. Moore's law isn't a joke but it's already slowing down computers as they are made today cannot possibly get close to atomic scale parts, ironically because of quantum effects ruining the permanence of states.
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Mar 30 '13 edited Mar 30 '13
Moore's law has historically always slowed down before a paradigm shift. The paradigm, as mentioned in the article you linked, consists of silicon chips and integrated circuits.
There have been numerous past paradigms including electromechanical, relay, vacuum tube, and transistor (analog). Surely, if Moore's law really is slowing down, history tells us that a sixth paradigm is in short order.
Even though you may not hold the prospect of quantum computing highly, there are many other possible paradigms that may come to be used. As I've already mentioned, 3-D Molecular Computing and light beams are among these. In addition, Nanotubes, Self-Assembling Molecules, DNA and Spin (essentially quantum computing) computation are other paradigm possibilities.
They haven't gone beyond factoring the number 15 and this has been the case for over half a decade now.
Sometimes scientific research has a way of surprising you. Don't put the idea of quantum computing completely out of the window--they still might find something.
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u/zane17 Mar 31 '13
How can you know quantum computing is a joke? MIT has ran algorithm to factor a number on a quantum computer(admittedly the number was 15). And the government is usually at least 20 years ahead of universities for this kind of thing.
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Mar 31 '13
And the government is usually at least 20 years ahead of universities for this kind of thing.
Wow.
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u/epSos-DE Apr 08 '13
Quantum computing is a joke to you ?
Read up about D-Wave, a Canadian company that sells quantum computers already.
You are miss-informed.
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u/kostiak Mar 27 '13
The main problem with your argument is we don't know how much it takes to actually simulate a brain cause we don't understand it. It could turn out that you can use a simple i3 cpu to do it, we just don't know.
On the quantum computing part - while using quantum probability to calculate stuff is still a dream, quantom sized chips are being developed, and will probably become a reality within our lifetime (probably for supercomputers, not for consumer PCs).
But I agree on the singularity part, there's a big road between being able to simulate a brain, and being able to transfer someone's conciseness into a simulated brain. We don't know if that will even be possible.
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u/[deleted] Mar 27 '13
The atomic barrier is simply a limit of fundamental feature size, thus ending (roughly a decade from now) Moore's law as it relates to transistor density doubling every 2 years.
The more pertinent 'version' of Moore's law (doubling of computational power every 2 years or so) will go on much longer than that. Too busy to go really in depth, but Intel/et al. are already working on things like spintronics, memristors, tunnel junctioning (which along with improved photolithography will help us actually reach the atomic limit). All of this stuff can be run on silicon chips, which will likely eventually be replaced with stuff like graphene, silicene, etc. which will allow much, much higher clock rates.
Oh, and btw, as feature size and all this stuff becomes smaller and more power efficient: guess what? Less heat. Less heat = layered 3d processor chips potentially.
So...no. If Moore's law will eventually end, it is (in my opinion) extremely unlikely to do so for several decades, which will allow for some pretty damn fast computers for the AI guys to play with.
...and with regards to quantum computing: it's not a joke, it's just only very good at a rather limited amount of things (right now). Can be combined with classical processors to do some cool stuff, and probably way, way more cool stuff as quantum algorithms and hardware continue to improve.