5 ms·

Getting close would take an advancement in computer technology of the magnitude of the transition from vacuum tubes in individual boxes to a 32nm Core i7. ...s

Getting close would take an advancement in computer technology of the magnitude of the transition from vacuum tubes in individual boxes to a 32nm Core i7. ...so about 35 years? ;)

clistctrl 16y ago
well, if you're going to use that as a baseline you should also factor in that the rate of advancement is exponential. so maybe 10?
- jonhendry 16y ago
  That probably helps more if the problem complexity is increasing linearly. If it's going up exponentially with problem size, especially if complexity increases at a faster rate than technology, then you're not going to make much progress. ie, if emulating a human brain is only N times as hard as emulating a flatworm, Moore's Law might do the trick. But if emulating a human brain is more like (flatworm complexity)^(number of cells in human brain - number of cells in flatworm brain) then Moore's Law is unlikely to help for a very long time indeed.
api 16y ago
Maybe, though I am concerned about processing power stagnating. Advancement is governed by economics as well as technical capability. There must be demand for new technology, or a field stagnates. Witness aviation as an example... utterly stagnant outside of military niche applications. People seem to no longer want faster and faster computers, and the market seems to be moving toward lighter-weight lower-power portable devices like netbooks, the iPad, etc. Those have slower CPUs than current-generation desktops. I suppose the extreme gamer and server/datacenter markets are still driving performance, but for how long? One problem is that programmers are not using the capabilities of current-generation processors, partly because the dominant OS (cough Windows cough) makes it horrifically painful to deploy desktop apps. This drives all development to the web and turns desktops into thin clients. In the end this kills demand for performance outside the datacenter market.
- troystribling 16y ago
  You are correct for consumer electronics. But commercial and scientific computing are driving increases computational power and density that do not seem to be letting up. In the 4 years I have worked in hosting the amount of server you can get in a 4u box has gone from 8 2.5GHz cores to 24 2.5GHz cores and from 32GB to 256GB. The storage requirements and compute requirements for applications are also increasing substantially.
- werrett 16y ago
  You're confounding peoples preference for usability (including portability) with a preference for applications with low computational demands. If you could pack the "extreme gamer" capabilities of a Playstation or an Xbox into a format as "usable"[1] as an iPad... Then you would of engineered the next iPad. The iPad was able to come into existence because we've finally hit the point where we can cram that much computation into a small factor form (along with all the other engineering advances like wireless networking, reducing power consumption, improving display and improving battery life). Most of those advances are directly descended from the pushing of the bleeding edge. Companies / people are not simply going to go "oh we've got iPads now. So no need to make anything faster / better / bigger". [1] By usable I'm not talking about some magical Jobsian property of the device. I'm not even talking about the software interface. I'm talking about being able to surf the web / post to your blog / whatever while on the toilet. Try doing THAT in 1995.
jacquesm 16y ago
Or 500, or 10,000, who is to know. The problem is that the way the brain seems to be organized is around very simple (at face value) processing components that operate at a ridiculously low frequency in a massive parallel manner that we programmers can only dream of, at a power budget that would make Ebenhaezer Scrooge look very happy indeed. If 35 years (according to Henry Makram, linked below it's only a decade) was all it took then we could simulate the brain today at a reduced speed and get meaningful output, after all, all you'd have to do is slow down the inputs accordingly. We're as far away from having a universally teachable computer (not programmable!) as we were in the early 70's when true AI was only about a decade away. Some interesting reading about the 'state of the art': http://spectrum.ieee.org/tech-talk/semiconductors/devices/blue-brain-project-leader-angry-about-cat-brain http://spectrum.ieee.org/tech-talk/semiconductors/devices/bl... http://bluebrain.epfl.ch/ http://bluebrain.epfl.ch/ http://www.technologyreview.com/biotech/19767/ http://www.technologyreview.com/biotech/19767/
- 10ren 16y ago
  The "simulate at reduced speed" theory appeals to me, but I think the actual numbers make it implausible. Assuming Moore's Law, 30 years is a 1,000,000 speed up, plus let's say 4.5 years for 3 more doublings, giving us 8,000,000. To simulate 1 second would take 3 months. Debugging would be frustrating. (assuming 35 years from now; seems an arbitrary figure.)
  - jacquesm 16y ago
    > Assuming Moore's Law That alone may already be a mistake, it's an observation, not a law after all. Besides, compared the 35 years ago we can now do things 1,000,000 times faster than back then, but computers are not 1,000,000 times 'smarter' they just give the same answers that you could compute back then but faster and on fewer computers. The future is parallel anyway, so it isn't Moores law (increase in density of transistors on-chip) per-se that will drive this, more likely there will be a switch to increasing chip packing density with smaller chips (bigger yield) and better communications between the chips (think computing fabric). We need a huge advance in programming languages before we can really contemplate building an AI by taking advantage of such a structure though, simply simulating the organic soup that forms a brain is going to be a much harder problem computationally and may simulate a dead or an insane brain much more easily than it will simulate a live and thinking one.
barmstrong 16y ago
This is exactly what I was thinking. Actually, if that last shift took 35 years, the next one of that magnitude will be even faster. This is Kurtzweil's fundamental insight: exponential growth is faster than people realize. We consistently underestimate it because our brains are pre-disposed to think linearly. If it takes you 1 year to solve 1% of a problem, your brain feels like you're 99 years away. In reality, you're only 7 doublings from completion.
- api 16y ago
  Where that falls down is that it fails to consider limits. Exponential growth cannot continue forever. At some point, something will limit it. It may be a physical limit, a supply-side resource limit, or an economic demand limit, but there will be a limit somewhere. Without limits, a single bacterium could fill the entire universe in a few years. Sometimes things do grow like that for a while, but Kurzweil's attempt to turn this into a universal law and neglect limits is hand-wavey and silly.
  - btilly 16y ago
    True. However decades long periods of exponential improvement in technology is the norm, not the exception. The most spectacular example is Moore's law, but it is hardly alone. If you read The Innovator's Dilemma you will find plenty of other examples, ranging from the maximum range of a steam ship to the volume of dirt a backhoe can scoop per hour. The interesting questions are how much computing power you need to perform equivalent tasks to a human brain, and whether current technology will reach that before it plateau's out.
    - joe_the_user 16y ago
      The idea of "things leveling out" evoke a metaphor of there being some finite amount of resources that can be gotten out of somewhere. Exponential growth of tools opens up an exponential number of different avenues of exploration - if computers didn't advance at all for ten years, we'd still come up with many more ways to use them. With them advancing exponentially, we can not only find different ways of using them but new fields where different forms of exponential growth can happen. And so-forth. There's no fixed frontier but a moving process. This isn't saying it's all wonderful but it's all likely to be a bit beyond our ability to encompass it - to draw a circle around it.
bh42 16y ago
Intel predicted the end of Moore's Law would come with 16 nanometer manufacturing processes and 5 nanometer gates, due to quantum tunnelling.

Getting close would take an advancement in computer technology of the magnitude of the transition from vacuum tubes in individual boxes to a 32nm Core i7. ...so about 35 years? ;)

clistctrl 16y ago

well, if you're going to use that as a baseline you should also factor in that the rate of advancement is exponential. so maybe 10?

jonhendry 16y ago
That probably helps more if the problem complexity is increasing linearly. If it's going up exponentially with problem size, especially if complexity increases at a faster rate than technology, then you're not going to make much progress. ie, if emulating a human brain is only N times as hard as emulating a flatworm, Moore's Law might do the trick. But if emulating a human brain is more like (flatworm complexity)^(number of cells in human brain - number of cells in flatworm brain) then Moore's Law is unlikely to help for a very long time indeed.

api 16y ago

Maybe, though I am concerned about processing power stagnating. Advancement is governed by economics as well as technical capability. There must be demand for new technology, or a field stagnates. Witness aviation as an example... utterly stagnant outside of military niche applications. People seem to no longer want faster and faster computers, and the market seems to be moving toward lighter-weight lower-power portable devices like netbooks, the iPad, etc. Those have slower CPUs than current-generation desktops. I suppose the extreme gamer and server/datacenter markets are still driving performance, but for how long? One problem is that programmers are not using the capabilities of current-generation processors, partly because the dominant OS (cough Windows cough) makes it horrifically painful to deploy desktop apps. This drives all development to the web and turns desktops into thin clients. In the end this kills demand for performance outside the datacenter market.

troystribling 16y ago
You are correct for consumer electronics. But commercial and scientific computing are driving increases computational power and density that do not seem to be letting up. In the 4 years I have worked in hosting the amount of server you can get in a 4u box has gone from 8 2.5GHz cores to 24 2.5GHz cores and from 32GB to 256GB. The storage requirements and compute requirements for applications are also increasing substantially.
werrett 16y ago
You're confounding peoples preference for usability (including portability) with a preference for applications with low computational demands. If you could pack the "extreme gamer" capabilities of a Playstation or an Xbox into a format as "usable"[1] as an iPad... Then you would of engineered the next iPad. The iPad was able to come into existence because we've finally hit the point where we can cram that much computation into a small factor form (along with all the other engineering advances like wireless networking, reducing power consumption, improving display and improving battery life). Most of those advances are directly descended from the pushing of the bleeding edge. Companies / people are not simply going to go "oh we've got iPads now. So no need to make anything faster / better / bigger". [1] By usable I'm not talking about some magical Jobsian property of the device. I'm not even talking about the software interface. I'm talking about being able to surf the web / post to your blog / whatever while on the toilet. Try doing THAT in 1995.

jacquesm 16y ago

Or 500, or 10,000, who is to know. The problem is that the way the brain seems to be organized is around very simple (at face value) processing components that operate at a ridiculously low frequency in a massive parallel manner that we programmers can only dream of, at a power budget that would make Ebenhaezer Scrooge look very happy indeed. If 35 years (according to Henry Makram, linked below it's only a decade) was all it took then we could simulate the brain today at a reduced speed and get meaningful output, after all, all you'd have to do is slow down the inputs accordingly. We're as far away from having a universally teachable computer (not programmable!) as we were in the early 70's when true AI was only about a decade away. Some interesting reading about the 'state of the art': http://spectrum.ieee.org/tech-talk/semiconductors/devices/blue-brain-project-leader-angry-about-cat-brain http://spectrum.ieee.org/tech-talk/semiconductors/devices/bl... http://bluebrain.epfl.ch/ http://bluebrain.epfl.ch/ http://www.technologyreview.com/biotech/19767/ http://www.technologyreview.com/biotech/19767/

10ren 16y ago
The "simulate at reduced speed" theory appeals to me, but I think the actual numbers make it implausible. Assuming Moore's Law, 30 years is a 1,000,000 speed up, plus let's say 4.5 years for 3 more doublings, giving us 8,000,000. To simulate 1 second would take 3 months. Debugging would be frustrating. (assuming 35 years from now; seems an arbitrary figure.)
- jacquesm 16y ago
  > Assuming Moore's Law That alone may already be a mistake, it's an observation, not a law after all. Besides, compared the 35 years ago we can now do things 1,000,000 times faster than back then, but computers are not 1,000,000 times 'smarter' they just give the same answers that you could compute back then but faster and on fewer computers. The future is parallel anyway, so it isn't Moores law (increase in density of transistors on-chip) per-se that will drive this, more likely there will be a switch to increasing chip packing density with smaller chips (bigger yield) and better communications between the chips (think computing fabric). We need a huge advance in programming languages before we can really contemplate building an AI by taking advantage of such a structure though, simply simulating the organic soup that forms a brain is going to be a much harder problem computationally and may simulate a dead or an insane brain much more easily than it will simulate a live and thinking one.

barmstrong 16y ago

This is exactly what I was thinking. Actually, if that last shift took 35 years, the next one of that magnitude will be even faster. This is Kurtzweil's fundamental insight: exponential growth is faster than people realize. We consistently underestimate it because our brains are pre-disposed to think linearly. If it takes you 1 year to solve 1% of a problem, your brain feels like you're 99 years away. In reality, you're only 7 doublings from completion.

api 16y ago
Where that falls down is that it fails to consider limits. Exponential growth cannot continue forever. At some point, something will limit it. It may be a physical limit, a supply-side resource limit, or an economic demand limit, but there will be a limit somewhere. Without limits, a single bacterium could fill the entire universe in a few years. Sometimes things do grow like that for a while, but Kurzweil's attempt to turn this into a universal law and neglect limits is hand-wavey and silly.
- btilly 16y ago
  True. However decades long periods of exponential improvement in technology is the norm, not the exception. The most spectacular example is Moore's law, but it is hardly alone. If you read The Innovator's Dilemma you will find plenty of other examples, ranging from the maximum range of a steam ship to the volume of dirt a backhoe can scoop per hour. The interesting questions are how much computing power you need to perform equivalent tasks to a human brain, and whether current technology will reach that before it plateau's out.
  - joe_the_user 16y ago
    The idea of "things leveling out" evoke a metaphor of there being some finite amount of resources that can be gotten out of somewhere. Exponential growth of tools opens up an exponential number of different avenues of exploration - if computers didn't advance at all for ten years, we'd still come up with many more ways to use them. With them advancing exponentially, we can not only find different ways of using them but new fields where different forms of exponential growth can happen. And so-forth. There's no fixed frontier but a moving process. This isn't saying it's all wonderful but it's all likely to be a bit beyond our ability to encompass it - to draw a circle around it.

bh42 16y ago

Intel predicted the end of Moore's Law would come with 16 nanometer manufacturing processes and 5 nanometer gates, due to quantum tunnelling.