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>But Nicolelis is in a camp that thinks that human consciousness (and if you believe in it, the soul) simply can’t be replicated in silicon. That’s because its

by rm999 14y ago

>But Nicolelis is in a camp that thinks that human consciousness (and if you believe in it, the soul) simply can’t be replicated in silicon. That’s because its most important features are the result of unpredictable, non-linear interactions amongst billions of cells, Nicolelis says. This is a fringe opinion, and I really wish the title reflected that. Ignoring the absurd 'linear' part of the article, I don't believe predictability is important to the brain. While it's possible quantum effects could explain unpredictability in the physical universe, there is no scientific evidence this is relevant to the brain; the brain operates at a much higher, more macro level than quantum mechanics. Besides, randomness can be introduced into silicon if it's that important. I hope the article is misrepresenting his opinion, but they seem dangerously close to 'the brain is more complex than I can comprehend, so it must be magic'. I and many cognitive and neuroscientists I've spoken to consider this whole line of reasoning to be anti-scientific philosophy (although I may be biased because I studied AI, which rests on the idea that silicon can recreate intelligence).

zepolud 14y ago
Even a quantum system could be simulated on classical Turing machine so I fail to see how that relates to computability. The whole article boils down to a metaphysical, a-wizard-did-it, type of argument as usual.
bascule 14y ago
According to Max Tegmark's calculations, the importance of quantum mechanical effects on brain processes is negligible: http://arxiv.org/abs/quant-ph/9907009 http://arxiv.org/abs/quant-ph/9907009 This paper posits the brain can be modeled as a classical (e.g. Newtonian, "billiard ball"-style) physical system
- api 14y ago
  This is based on the idea that the sum total of what the brain does can be explained by and represented by neural network type models. The conventional neural network model neglects the interior of the neuron. Gene regulatory networks for complex eukaryotes are on the order of neural networks in complexity and involve quantum-scale interactions, which opens the possibility of quantum effects being significant. Gene regulation within the neuron affects neural firing behavior and, more importantly, profoundly affects neural growth patterns and thus learning and longer term forms of cognition. This also neglects the possibility (now considered probable) that more cell types than just neurons are involved in brain activity: http://en.wikipedia.org/wiki/Gliotransmitter http://en.wikipedia.org/wiki/Gliotransmitter In short: the brain is not a neural network. Rather, those mathematical connectionist models are just that: models of aspects of the brain. We do not yet know to what extent these other mechanisms play a role, and what their role is. Given their nature it seems in both cases that their role might be more long-term, affecting long duration learning, planning, etc. It really seems to me as if the most ardent and enthusiastic adherents of the Kurzweilian vision are computer scientists who don't really respect the domain of biology and like to hand-wave away its complexity as "background noise." You can't do that. I say this as a lifelong computer programmer who has studied biology. Studying biology really blew away any notions I had of simple, classical computer programs becoming movie-style AI. The author is not making an anti-scientific "magic" argument. He is simply pointing out that biological systems are analog, embodied, electrochemical (and thus physical and possibly quantum), nonlinear complex systems, and he is being skeptical about the idea that such a system is going to yield readily to digital computer simulation. I agree with his skepticism. Prediction: brain simulations will simulate superficial brain behavior but they will not become sentient. More specific prediction: they will get stuck in closed cycle loops. They will not exhibit the higher order motivation, creativity, or learning behavior seen in brains, which is probably because these behaviors emerge from all the real embodied biophysical stuff the CS people are ignoring.
  - bascule 14y ago
    This paper specifically addresses microtubules and is definitely not neglecting the interior of neurons. I suggest you read the paper instead of just the abstract before you give feedback.
    - api 14y ago
      Microtubules, maybe, but that's only one of a billion things going on in there. Here's a pretty decent article: http://www.nature.com/news/2011/110615/pdf/474272a.pdf http://www.nature.com/news/2011/110615/pdf/474272a.pdf My point is that a neuron is not an equation in a connection model. It's a cell. You can't hand-wave away its identity as such or all the things that happen in cells. Even if nothing quantum is involved (and I didn't say it was... we don't know), including significant aspects of intra-cellular activity and including other cell types (glia, etc.) and other types of interactions adds exponentially to the classical computation requirements. I didn't mean that I dismissed the idea of classical computers simulating the brain or the implications. I just meant that I'm skeptical. Even if it is possible I'm very skeptical of it happening soon due to the absolutely insane computational requirements. My intuition is that it would require a leap on the order of vacuum tube ENIAC -> Intel Core i7. Meanwhile consumer demand for faster and faster chips is giving way to demand for slower but more energy efficient chips for mobile devices, which is subtracting from the economic incentive to continue Moore's Law. (AMD just bowed out of the x86 race for instance, leaving us with an Intel monopoly at the high end. Monopolies get lazy and stagnate.) Personally I'm much more optimistic about "wet" transhumanism-- life extension, augmentation, brain hacking, etc., than I am about "real" AI in the near term or mind uploading. I also see computers stagnating a little for a while the way aerospace did from the Apollo era until about now... entirely for economic rather than physical reasons.
      - simonster 14y ago
        > My point is that a neuron is not an equation in a connection model. It's a cell. You can't hand-wave away its identity as such or all the things that happen in cells. There's a huge philosophical difference between the idea that there is something going on in a brain that can't be computed (what the article suggests, and what you seem to suggest here) and the idea that a brain is hard to simulate (which is what you suggest in the next paragraph). As the posters above you have pointed out, the former is a fringe opinion unsupported by current evidence. The latter is a skeptical viewpoint to which many neuroscientists subscribe. Personally, I'm in the "I want to believe" camp. > My intuition is that it would require a leap on the order of vacuum tube ENIAC -> Intel Core i7. Meanwhile consumer demand for faster and faster chips is giving way to demand for slower but more energy efficient chips for mobile devices, which is subtracting from the economic incentive to continue Moore's Law. To a first approximation, speed, power consumption, and performance per dollar are all linear functions of transistor size. If you can make smaller transistors, you can make a more power-efficient chip with the same performance, or you can make a more powerful chip with the same energy consumption. I don't think people will stop innovating on this front until we hit a physical wall. There may only be one major desktop CPU maker, but there are plenty of competing fabrication plants. Since the brain is embarrassingly parallel, we only need to get within a few orders of magnitude of simulating a brain on a single chip, at which point we can just string a bunch of processors together. > Personally I'm much more optimistic about "wet" transhumanism-- life extension, augmentation, brain hacking, etc., than I am about "real" AI in the near term or mind uploading. If by "near term" you mean within the next 20 years or so, I agree. Beyond that, it's really hard to tell. If faster computers actually let us make scientific discoveries faster, the singularity people may well be right.
Justsignedup 14y ago
Also we're not trying to reproduce someone's brain and predict what that someone will think... Instead we are trying to reproduce human thought and intellect. That's like saying we can't re-create the stock market somewhere (that has the same basic rules/behaviors, but not the exact same data)...
anigbrowl 14y ago
Well...I'm a believer in strong AI, and I think a brain in silicon (or whatever substrate you prefer) is definitely possible. Downloads of human brains to silicon, maybe not so much because you'd have to accurately record the state and topology of ~10^11 neurons, which is rather difficult. So I'm not that optimistic about my brain being freely copyable the way people's brains are in Iain Banks' SF novels (although I'd like to be wrong about this).
amalag 14y ago
How are you conflating randomness with unpredictability?
- rm999 14y ago
  I'm giving him the benefit of the doubt; unpredictable is as nonsensical as nonlinear in the context of the debate.
  - amalag 14y ago
    Anything one cannot find the order to one assigns as random or nonsensical? If someone doesn't have the understanding to see higher order patterns, how is calling it random a useful way to understand the higher order pattern?
pradocchia 14y ago
While it's possible quantum effects could explain unpredictability in the physical universe, there is no scientific evidence this is relevant to the brain; the brain operates at a much higher, more macro level than quantum mechanics. The brain evolved in the physical world. It seems an odd economy to categorically exclude quantum effects because they are "too small", hard to measure, and/or poorly understood.
vorg 14y ago
> the brain operates at a much higher, more macro level than quantum mechanics I didn't realize anyone had worked out the level at which quantum mechanics decoheres to Newtonian mechanics.
- lutusp 14y ago
  > I didn't realize anyone had worked out the level at which quantum mechanics decoheres to Newtonian mechanics. Well, yes, of course -- the Heisenberg Uncertainty principle is the border between them: http://en.wikipedia.org/wiki/Uncertainty_principle http://en.wikipedia.org/wiki/Uncertainty_principle Equation: 𝝈x 𝝈p >= ℏ/2 I emphasize the "border" isn't a like a solid barrier, it's more a statement about probability. Also, everyone should realize that the relationship between human brain function and QM is very speculative. It might be true, it might just be someone's pet idea. There's no real evidence for or against a role for QM in brain function, and a number of persuasive suggestions that it's not involved.
  - vorg 14y ago
    I was thinking about Schrodinger's cat. Quantum Decoherence and Consciousness are two phenomena not yet(?) explained by science, so it's natural to wonder if they're related to each other.
    - lutusp 14y ago
      > Quantum Decoherence and Consciousness are two phenomena not yet(?) explained by science, so it's natural to wonder if they're related to each other. I would credit the argument only if they had an association, not solely because they're both unexplained. Otherwise we could assume a connection between Bigfoot and the Loch Ness Monster, on the dubious ground that they're both asserted to exist but with no evidence. :) > I was thinking about Schrodinger's cat. It's important to say that the Schrodinger's cat experiment is a useful thought experiment, but it can't actually be carried out -- too many ways for the system to decohere.
    - thedufer 14y ago
      To clear things up, "Schrodinger's cat" was an attempt to show the absurdity of the current best interpretation of quantum mechanics (it _is_ absurd, but it still models reality to the best of our knowledge). It was never intended to be an actual experiment, nor would it actually work.

by rm999 14y ago

zepolud 14y ago

Even a quantum system could be simulated on classical Turing machine so I fail to see how that relates to computability. The whole article boils down to a metaphysical, a-wizard-did-it, type of argument as usual.

bascule 14y ago

According to Max Tegmark's calculations, the importance of quantum mechanical effects on brain processes is negligible: http://arxiv.org/abs/quant-ph/9907009 http://arxiv.org/abs/quant-ph/9907009 This paper posits the brain can be modeled as a classical (e.g. Newtonian, "billiard ball"-style) physical system

api 14y ago
This is based on the idea that the sum total of what the brain does can be explained by and represented by neural network type models. The conventional neural network model neglects the interior of the neuron. Gene regulatory networks for complex eukaryotes are on the order of neural networks in complexity and involve quantum-scale interactions, which opens the possibility of quantum effects being significant. Gene regulation within the neuron affects neural firing behavior and, more importantly, profoundly affects neural growth patterns and thus learning and longer term forms of cognition. This also neglects the possibility (now considered probable) that more cell types than just neurons are involved in brain activity: http://en.wikipedia.org/wiki/Gliotransmitter http://en.wikipedia.org/wiki/Gliotransmitter In short: the brain is not a neural network. Rather, those mathematical connectionist models are just that: models of aspects of the brain. We do not yet know to what extent these other mechanisms play a role, and what their role is. Given their nature it seems in both cases that their role might be more long-term, affecting long duration learning, planning, etc. It really seems to me as if the most ardent and enthusiastic adherents of the Kurzweilian vision are computer scientists who don't really respect the domain of biology and like to hand-wave away its complexity as "background noise." You can't do that. I say this as a lifelong computer programmer who has studied biology. Studying biology really blew away any notions I had of simple, classical computer programs becoming movie-style AI. The author is not making an anti-scientific "magic" argument. He is simply pointing out that biological systems are analog, embodied, electrochemical (and thus physical and possibly quantum), nonlinear complex systems, and he is being skeptical about the idea that such a system is going to yield readily to digital computer simulation. I agree with his skepticism. Prediction: brain simulations will simulate superficial brain behavior but they will not become sentient. More specific prediction: they will get stuck in closed cycle loops. They will not exhibit the higher order motivation, creativity, or learning behavior seen in brains, which is probably because these behaviors emerge from all the real embodied biophysical stuff the CS people are ignoring.
- bascule 14y ago
  This paper specifically addresses microtubules and is definitely not neglecting the interior of neurons. I suggest you read the paper instead of just the abstract before you give feedback.
  - api 14y ago
    Microtubules, maybe, but that's only one of a billion things going on in there. Here's a pretty decent article: http://www.nature.com/news/2011/110615/pdf/474272a.pdf http://www.nature.com/news/2011/110615/pdf/474272a.pdf My point is that a neuron is not an equation in a connection model. It's a cell. You can't hand-wave away its identity as such or all the things that happen in cells. Even if nothing quantum is involved (and I didn't say it was... we don't know), including significant aspects of intra-cellular activity and including other cell types (glia, etc.) and other types of interactions adds exponentially to the classical computation requirements. I didn't mean that I dismissed the idea of classical computers simulating the brain or the implications. I just meant that I'm skeptical. Even if it is possible I'm very skeptical of it happening soon due to the absolutely insane computational requirements. My intuition is that it would require a leap on the order of vacuum tube ENIAC -> Intel Core i7. Meanwhile consumer demand for faster and faster chips is giving way to demand for slower but more energy efficient chips for mobile devices, which is subtracting from the economic incentive to continue Moore's Law. (AMD just bowed out of the x86 race for instance, leaving us with an Intel monopoly at the high end. Monopolies get lazy and stagnate.) Personally I'm much more optimistic about "wet" transhumanism-- life extension, augmentation, brain hacking, etc., than I am about "real" AI in the near term or mind uploading. I also see computers stagnating a little for a while the way aerospace did from the Apollo era until about now... entirely for economic rather than physical reasons.
    - simonster 14y ago
      > My point is that a neuron is not an equation in a connection model. It's a cell. You can't hand-wave away its identity as such or all the things that happen in cells. There's a huge philosophical difference between the idea that there is something going on in a brain that can't be computed (what the article suggests, and what you seem to suggest here) and the idea that a brain is hard to simulate (which is what you suggest in the next paragraph). As the posters above you have pointed out, the former is a fringe opinion unsupported by current evidence. The latter is a skeptical viewpoint to which many neuroscientists subscribe. Personally, I'm in the "I want to believe" camp. > My intuition is that it would require a leap on the order of vacuum tube ENIAC -> Intel Core i7. Meanwhile consumer demand for faster and faster chips is giving way to demand for slower but more energy efficient chips for mobile devices, which is subtracting from the economic incentive to continue Moore's Law. To a first approximation, speed, power consumption, and performance per dollar are all linear functions of transistor size. If you can make smaller transistors, you can make a more power-efficient chip with the same performance, or you can make a more powerful chip with the same energy consumption. I don't think people will stop innovating on this front until we hit a physical wall. There may only be one major desktop CPU maker, but there are plenty of competing fabrication plants. Since the brain is embarrassingly parallel, we only need to get within a few orders of magnitude of simulating a brain on a single chip, at which point we can just string a bunch of processors together. > Personally I'm much more optimistic about "wet" transhumanism-- life extension, augmentation, brain hacking, etc., than I am about "real" AI in the near term or mind uploading. If by "near term" you mean within the next 20 years or so, I agree. Beyond that, it's really hard to tell. If faster computers actually let us make scientific discoveries faster, the singularity people may well be right.

Justsignedup 14y ago

Also we're not trying to reproduce someone's brain and predict what that someone will think... Instead we are trying to reproduce human thought and intellect. That's like saying we can't re-create the stock market somewhere (that has the same basic rules/behaviors, but not the exact same data)...

anigbrowl 14y ago

Well...I'm a believer in strong AI, and I think a brain in silicon (or whatever substrate you prefer) is definitely possible. Downloads of human brains to silicon, maybe not so much because you'd have to accurately record the state and topology of ~10^11 neurons, which is rather difficult. So I'm not that optimistic about my brain being freely copyable the way people's brains are in Iain Banks' SF novels (although I'd like to be wrong about this).

amalag 14y ago

How are you conflating randomness with unpredictability?

rm999 14y ago
I'm giving him the benefit of the doubt; unpredictable is as nonsensical as nonlinear in the context of the debate.
- amalag 14y ago
  Anything one cannot find the order to one assigns as random or nonsensical? If someone doesn't have the understanding to see higher order patterns, how is calling it random a useful way to understand the higher order pattern?

pradocchia 14y ago

While it's possible quantum effects could explain unpredictability in the physical universe, there is no scientific evidence this is relevant to the brain; the brain operates at a much higher, more macro level than quantum mechanics. The brain evolved in the physical world. It seems an odd economy to categorically exclude quantum effects because they are "too small", hard to measure, and/or poorly understood.

vorg 14y ago

> the brain operates at a much higher, more macro level than quantum mechanics I didn't realize anyone had worked out the level at which quantum mechanics decoheres to Newtonian mechanics.

lutusp 14y ago
> I didn't realize anyone had worked out the level at which quantum mechanics decoheres to Newtonian mechanics. Well, yes, of course -- the Heisenberg Uncertainty principle is the border between them: http://en.wikipedia.org/wiki/Uncertainty_principle http://en.wikipedia.org/wiki/Uncertainty_principle Equation: 𝝈x 𝝈p >= ℏ/2 I emphasize the "border" isn't a like a solid barrier, it's more a statement about probability. Also, everyone should realize that the relationship between human brain function and QM is very speculative. It might be true, it might just be someone's pet idea. There's no real evidence for or against a role for QM in brain function, and a number of persuasive suggestions that it's not involved.
- vorg 14y ago
  I was thinking about Schrodinger's cat. Quantum Decoherence and Consciousness are two phenomena not yet(?) explained by science, so it's natural to wonder if they're related to each other.
  - lutusp 14y ago
    > Quantum Decoherence and Consciousness are two phenomena not yet(?) explained by science, so it's natural to wonder if they're related to each other. I would credit the argument only if they had an association, not solely because they're both unexplained. Otherwise we could assume a connection between Bigfoot and the Loch Ness Monster, on the dubious ground that they're both asserted to exist but with no evidence. :) > I was thinking about Schrodinger's cat. It's important to say that the Schrodinger's cat experiment is a useful thought experiment, but it can't actually be carried out -- too many ways for the system to decohere.
  - thedufer 14y ago
    To clear things up, "Schrodinger's cat" was an attempt to show the absurdity of the current best interpretation of quantum mechanics (it _is_ absurd, but it still models reality to the best of our knowledge). It was never intended to be an actual experiment, nor would it actually work.