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(I'll assume that, here, performance means speed of memory access and calculation.)If all that memristors offer is performance, and you propose memristors will

by diiq 16y ago

(I'll assume that, here, performance means speed of memory access and calculation.)If all that memristors offer is performance, and you propose memristors will lead to AI, you are suggesting that what is currently preventing an artificial intelligence from succeeding is speed of calculation, and further that the particular kind of calculation needed is the same kind potentially improved by memristors.I can't completely demonstrate that to be untrue without referencing every attempt at AI ever made, because you're asking for a negative proof --- that NO current AI research fulfills those two requirements. I haven't read all the AI papers ever, let alone talked to researchers that haven't published. But I've read what I can, and I... I guess I just don't feel like the evidence suggests that current research is hindered solely by speed, NOR that "moving memory and processing power closer together" has much to do with any somewhat-successful attempts machine intelligence.

Benjo 16y ago
So what DO you think is holding us back? My understanding is the memristor is a much closer model of a synapse. So if the problem isn't raw computing power and it's not the synapse model then what do you think it is? What's holding us back from simulating a brain? Do we just not know enough about the design of a brain? Or do we need to understand something about consciousness itself? For what it's worth, this project seems to think we are only 10-20 years away from simulating it with conventional computing: http://en.wikipedia.org/wiki/Blue_Brain_Project http://en.wikipedia.org/wiki/Blue_Brain_Project
- Fargren 16y ago
  What's holding us back in our attempts to simulate a brain is that we don't know how the brain works. That's a much more important hurdle to overcome than performance, I believe.
  - Benjo 16y ago
    Do we understand the building blocks? What's the smallest system we can't model?
    - possibilistic 16y ago
      Helium.
      - gnosis 16y ago
        I'm not even sure that a single helium atom can be accurately modeled, if you take in to account all of the subatomic particles and processes involved (which are still in the process of being discovered and understood).
- jerf 16y ago
  If we knew precisely what was holding us back, it wouldn't be holding us back. You're asking a question you can always just move the goalposts for. (I'm not saying you will, but you can.)
  - Benjo 16y ago
    I'm just asking for a guess.
    - possibilistic 16y ago
      I'm a computational molecular biologist, and I don't understand the cell or the brain. Nobody does. What's holding us back? The proteome, interactome, connectome, etc. etc. You'll see biologically-inspired AI after we solve a MUCH simpler set of problems: cancer, aging, and viruses. I doubt you'll still be young when that happens. (Not that I don't hope for this to happen as soon as possible.) I wouldn't concern myself AI anyway. With the rate at which our machines are becoming more parallel and gaining in throughput, I might expect to see an accurate model of a single neuron in a few decades. Get over the Kurzweil fantasy and live each day as best as you can. If we don't get to live forever it isn't the end of the world. (And if you believe it is then maybe you should be working on this problem instead.)
      - joe_the_user 16y ago
        I think that Kurzweil has already answered arguments such as this. My rendition of that argument would be that... <argument> Scientists who study these things are absolutely correct in saying that we won't achieve quick progress with walls they can see and the tools that they have. Yes, the thing is that we won't see notable progress in the experimental biological realm but rather we will first see super-quick progress from something like a very crude, biologically inspired AI that indeed doesn't require us to understand the brain but works well-enough at the exe-scale. From that, we'll have far more powerful tools to actually start to understand the brain. </argument> I'm not qualified to say whether Kurzweil's answer here is correct. However, I don't think anyone is going to be able to make final judgment until a "singularity" happens or until computing progress definitively hits a wall we can't go around. The living-forever question, of course, is a whole, other discussion. The world is changing very rapidly. Given this, any extrapolation thirty years into the future is fantasy. Things may be very much nicer, very much more unpleasant or in-between. My argument is for uncertainty, not certainty. The idea that things will remain about the same seems like at least as much of a "fantasy" as the idea that the singularity will come and solve all of our problems.
joe_the_user 16y ago
Well... you've upped the ante a lot from my earlier post. I only asked for the reason why people didn't think memrisors wouldn't lead to a break through when various people argued that it would. I'm not certain it will but I'm also not certain it won't. Still.. Maybe, maybe, just by being slightly optimistic about this development, I deserve to be tagged as "propos[ing] memristors will lead to AI" Fine, tag me as claiming that memristors will jump us to the singularity fifteen years earlier than Ray Kurzweil claims, with ponies for everyone! But seriously... Neural networks have been pretty standard AI model for a while now. Memristors claim to be able to simulate them on a chip rather than forcing them to go back-and-forth between disk and chip. Why would that lead to some level of advance? I'm waiting for the argument...

by diiq 16y ago

Benjo 16y ago

So what DO you think is holding us back? My understanding is the memristor is a much closer model of a synapse. So if the problem isn't raw computing power and it's not the synapse model then what do you think it is? What's holding us back from simulating a brain? Do we just not know enough about the design of a brain? Or do we need to understand something about consciousness itself? For what it's worth, this project seems to think we are only 10-20 years away from simulating it with conventional computing: http://en.wikipedia.org/wiki/Blue_Brain_Project http://en.wikipedia.org/wiki/Blue_Brain_Project

Fargren 16y ago
What's holding us back in our attempts to simulate a brain is that we don't know how the brain works. That's a much more important hurdle to overcome than performance, I believe.
- Benjo 16y ago
  Do we understand the building blocks? What's the smallest system we can't model?
  - possibilistic 16y ago
    Helium.
    - gnosis 16y ago
      I'm not even sure that a single helium atom can be accurately modeled, if you take in to account all of the subatomic particles and processes involved (which are still in the process of being discovered and understood).
jerf 16y ago
If we knew precisely what was holding us back, it wouldn't be holding us back. You're asking a question you can always just move the goalposts for. (I'm not saying you will, but you can.)
- Benjo 16y ago
  I'm just asking for a guess.
  - possibilistic 16y ago
    I'm a computational molecular biologist, and I don't understand the cell or the brain. Nobody does. What's holding us back? The proteome, interactome, connectome, etc. etc. You'll see biologically-inspired AI after we solve a MUCH simpler set of problems: cancer, aging, and viruses. I doubt you'll still be young when that happens. (Not that I don't hope for this to happen as soon as possible.) I wouldn't concern myself AI anyway. With the rate at which our machines are becoming more parallel and gaining in throughput, I might expect to see an accurate model of a single neuron in a few decades. Get over the Kurzweil fantasy and live each day as best as you can. If we don't get to live forever it isn't the end of the world. (And if you believe it is then maybe you should be working on this problem instead.)
    - joe_the_user 16y ago
      I think that Kurzweil has already answered arguments such as this. My rendition of that argument would be that... <argument> Scientists who study these things are absolutely correct in saying that we won't achieve quick progress with walls they can see and the tools that they have. Yes, the thing is that we won't see notable progress in the experimental biological realm but rather we will first see super-quick progress from something like a very crude, biologically inspired AI that indeed doesn't require us to understand the brain but works well-enough at the exe-scale. From that, we'll have far more powerful tools to actually start to understand the brain. </argument> I'm not qualified to say whether Kurzweil's answer here is correct. However, I don't think anyone is going to be able to make final judgment until a "singularity" happens or until computing progress definitively hits a wall we can't go around. The living-forever question, of course, is a whole, other discussion. The world is changing very rapidly. Given this, any extrapolation thirty years into the future is fantasy. Things may be very much nicer, very much more unpleasant or in-between. My argument is for uncertainty, not certainty. The idea that things will remain about the same seems like at least as much of a "fantasy" as the idea that the singularity will come and solve all of our problems.

joe_the_user 16y ago

Well... you've upped the ante a lot from my earlier post. I only asked for the reason why people didn't think memrisors wouldn't lead to a break through when various people argued that it would. I'm not certain it will but I'm also not certain it won't. Still.. Maybe, maybe, just by being slightly optimistic about this development, I deserve to be tagged as "propos[ing] memristors will lead to AI" Fine, tag me as claiming that memristors will jump us to the singularity fifteen years earlier than Ray Kurzweil claims, with ponies for everyone! But seriously... Neural networks have been pretty standard AI model for a while now. Memristors claim to be able to simulate them on a chip rather than forcing them to go back-and-forth between disk and chip. Why would that lead to some level of advance? I'm waiting for the argument...