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My real concern about AI is that generalised Moore’s law means we only have a relatively short time to plan. Assuming that computers continue to double in proce

My real concern about AI is that generalised Moore’s law means we only have a relatively short time to plan. Assuming that computers continue to double in processing power every 18 months or so, then we only have 10 years where we go from 1% human level to human level. This really is not a long time to make good decisions.

kumarski 11y ago
Limitless exponential growth doesn't happen in the physical world. Technological advance happens on s-curves.
- dnautics 11y ago
  As S-curve may even be optimistic. https://en.wikipedia.org/wiki/Bacterial_growth#/media/File:Bacterial_growth_en.svg https://en.wikipedia.org/wiki/Bacterial_growth#/media/File:B...
  - kumarski 11y ago
    That's the natural world, I'm talking about technology.
daveguy 11y ago
A few things about AI that the singularity crowd either doesn't get or doesn't want to get: 1) Growth rates in nature are never exponential. They are sigmoidal. Sigmoids look very exponential when you're in the middle of them, but we are starting to see the level of moore's law (yeah yeah, it's technology not ICs, still sigmoidal) 2) Even if we had a computer that was 1,000 times faster than the ones we have today and used 1/1,000 of the computing power we STILL don't have the algorithms to produce a human intelligence and that is one hell of an algorithm. 3) The focus for a long time has been moore's law and the associated increase in FLOPS. I think what is more important and more limiting is the bandwidth and bandwidth is a couple orders of magnitude lower than FLOPS where FLOP=Byte and an extra order of magnitude lower when FLOP=Word.
- CardenB 11y ago
  Do you happen to have a source for your point about sigmoidal growth? I'd like to read more about that.
  - mhandley 11y ago
    It's more correctly known as a logistic curve. The Wikipedia page has quite a few references: https://en.wikipedia.org/wiki/Logistic_function https://en.wikipedia.org/wiki/Logistic_function
- lolyololol 11y ago
  It isn't too hard to be off an order or two of magnitude when dealing with exponential increases, no reason advances could or couldn't level off at 1% or 1000% of human capacity.
  - danieltillett 11y ago
    I am not sure that just hoping computation growth will level off at some threshold below human level is wise planning.It is like assuming that a singularity level intelligence will be nice and so saying we don’t need to think about the consequences.
  - deleted 11y ago
    [deleted]
- joe_the_user 11y ago
  Growth rates in nature are never exponential. They are sigmoidal. - For whatever his other flaws, Kurweil deals with this by pointing out that Moore's law has effectively been a series of sigmoidal curves - but these series constitutes a trend. Even if we had a computer that was 1,000 times faster than the ones we have today and used 1/1,000 of the computing power we STILL don't have the algorithms to produce a human intelligence and that is one hell of an algorithm. - One has to put such an algorithm as in the realm of "unknown unknowns". Anyone who says they know for sure that a human-capability-equivalent algorithm is complex would have to know a least a lot about such an algorithm. No one can yet make that claim. So the non-existence of such an algorithm isn't a certainty but just a trend. And the "unknown unknown" things might a long time out, might be just around the corner or might be utterly impossible.
deleted 11y ago
[deleted]
bennyg 11y ago
Limited by a lot of things that processors are already getting awfully close to - quantum interference and the size of the architecture. It really can't get that much smaller.
- danieltillett 11y ago
  We know that we are not going to get anywhere near human level intelligence using current technology so it really doesn’t matter. What is important is there anyway of building the computational power of human level intelligence other than making a baby.
karmacondon 11y ago
I've yet to see any evidence that human-like intelligence and computation speed are related in any way. There's a lot more to general intelligence than how fast numbers can be multiplied together.
- danieltillett 11y ago
  Actually in humans raw computational speed (nerve impulse speed) and intelligence (g) are quite correlated. We have a rough idea of how much processing the human brain is capable of by looking at the eye and optic nerve. Our most powerful computers are many orders of magnitude below human level processing.
  - vl 11y ago
    >Our most powerful computers are many orders of magnitude below human level processing. How can this be true? Human brain consumes just so much energy, our chips are already running close to single-electron level switching, and consume comparable amounts of energy (not even talking about computer clusters/supercomputers). May be layouts/programming are not good enough, but bare computing power is there.
    - danieltillett 11y ago
      Human brains are far more efficient than computers. We tend to forget how efficient human brains are. You might find this post interesting [1]. 1. http://chrisfwestbury.blogspot.co.il/2014/06/on-processing-speed-of-human-brain.html http://chrisfwestbury.blogspot.co.il/2014/06/on-processing-s...
      - vl 11y ago
        This post lost me at last * 1000 - number of connection should not be counted. I.e. number of units x frequency gives you FLOPS. With this correction it's just 20 gigaflops for the human brain. Modern deep neutral network demonstrate that they do comparable decisions with relatively little power. (i.e. modern speech and image recognition running on laptops, for example). So I say for modern computers it's all about correct programming.

kumarski 11y ago

Limitless exponential growth doesn't happen in the physical world. Technological advance happens on s-curves.

dnautics 11y ago
As S-curve may even be optimistic. https://en.wikipedia.org/wiki/Bacterial_growth#/media/File:Bacterial_growth_en.svg https://en.wikipedia.org/wiki/Bacterial_growth#/media/File:B...
- kumarski 11y ago
  That's the natural world, I'm talking about technology.

daveguy 11y ago

A few things about AI that the singularity crowd either doesn't get or doesn't want to get: 1) Growth rates in nature are never exponential. They are sigmoidal. Sigmoids look very exponential when you're in the middle of them, but we are starting to see the level of moore's law (yeah yeah, it's technology not ICs, still sigmoidal) 2) Even if we had a computer that was 1,000 times faster than the ones we have today and used 1/1,000 of the computing power we STILL don't have the algorithms to produce a human intelligence and that is one hell of an algorithm. 3) The focus for a long time has been moore's law and the associated increase in FLOPS. I think what is more important and more limiting is the bandwidth and bandwidth is a couple orders of magnitude lower than FLOPS where FLOP=Byte and an extra order of magnitude lower when FLOP=Word.

CardenB 11y ago
Do you happen to have a source for your point about sigmoidal growth? I'd like to read more about that.
- mhandley 11y ago
  It's more correctly known as a logistic curve. The Wikipedia page has quite a few references: https://en.wikipedia.org/wiki/Logistic_function https://en.wikipedia.org/wiki/Logistic_function
lolyololol 11y ago
It isn't too hard to be off an order or two of magnitude when dealing with exponential increases, no reason advances could or couldn't level off at 1% or 1000% of human capacity.
- danieltillett 11y ago
  I am not sure that just hoping computation growth will level off at some threshold below human level is wise planning.It is like assuming that a singularity level intelligence will be nice and so saying we don’t need to think about the consequences.
- deleted 11y ago
  [deleted]
joe_the_user 11y ago
Growth rates in nature are never exponential. They are sigmoidal. - For whatever his other flaws, Kurweil deals with this by pointing out that Moore's law has effectively been a series of sigmoidal curves - but these series constitutes a trend. Even if we had a computer that was 1,000 times faster than the ones we have today and used 1/1,000 of the computing power we STILL don't have the algorithms to produce a human intelligence and that is one hell of an algorithm. - One has to put such an algorithm as in the realm of "unknown unknowns". Anyone who says they know for sure that a human-capability-equivalent algorithm is complex would have to know a least a lot about such an algorithm. No one can yet make that claim. So the non-existence of such an algorithm isn't a certainty but just a trend. And the "unknown unknown" things might a long time out, might be just around the corner or might be utterly impossible.

deleted 11y ago

[deleted]

bennyg 11y ago

Limited by a lot of things that processors are already getting awfully close to - quantum interference and the size of the architecture. It really can't get that much smaller.

danieltillett 11y ago
We know that we are not going to get anywhere near human level intelligence using current technology so it really doesn’t matter. What is important is there anyway of building the computational power of human level intelligence other than making a baby.

karmacondon 11y ago

I've yet to see any evidence that human-like intelligence and computation speed are related in any way. There's a lot more to general intelligence than how fast numbers can be multiplied together.

danieltillett 11y ago
Actually in humans raw computational speed (nerve impulse speed) and intelligence (g) are quite correlated. We have a rough idea of how much processing the human brain is capable of by looking at the eye and optic nerve. Our most powerful computers are many orders of magnitude below human level processing.
- vl 11y ago
  >Our most powerful computers are many orders of magnitude below human level processing. How can this be true? Human brain consumes just so much energy, our chips are already running close to single-electron level switching, and consume comparable amounts of energy (not even talking about computer clusters/supercomputers). May be layouts/programming are not good enough, but bare computing power is there.
  - danieltillett 11y ago
    Human brains are far more efficient than computers. We tend to forget how efficient human brains are. You might find this post interesting [1]. 1. http://chrisfwestbury.blogspot.co.il/2014/06/on-processing-speed-of-human-brain.html http://chrisfwestbury.blogspot.co.il/2014/06/on-processing-s...
    - vl 11y ago
      This post lost me at last * 1000 - number of connection should not be counted. I.e. number of units x frequency gives you FLOPS. With this correction it's just 20 gigaflops for the human brain. Modern deep neutral network demonstrate that they do comparable decisions with relatively little power. (i.e. modern speech and image recognition running on laptops, for example). So I say for modern computers it's all about correct programming.