What makes you think that doing things in parallel is the key to consciousness?
There's also the point that, as far as running an algorithm is concerned, there is no difference whether things are run in parallel or not - a single core machine can always do the same thing as one doing it in parallel, it's just a question of performance. If consciousness is something that can be developed on a computer (as we know it today, i.e., simply a matter of running the right software), then it can be run on any computer, although it might be very slow.
As far as algorithms are concerned, what you suggest is nothing new - e.g., neural networks are used in AI, and they model a process that occurs in parallel. But it doesn't matter whether you run it on hardware with multiple cores or only one.
You also seem to be unaware of anything to do with multiple cores, SMP and so on? - Yes, writing things to run in parallel is a difficult area, but this is not specific to AI, and is something that is already done today on most computers.
In summary: (a) running things in parallel isn't inherently necessary, it's just a question of whether you'd get better performance, (b) the industry already realised years ago that running things in parallel is a way to get better performance, and this transition became standard even on bog standard PCs in the last decade - even phones have multiple cores these days. (Of course, it's true that we're still a long way from solving the problem of scaling most software to say thousands or millions of cores, but again, it's not like no one's thought of this.)
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#1mdwh
Posted 08 October 2012 - 07:16 AM
What makes you think that doing things in parallel is the key to consciousness?
There's also the point that, as far as running an algorithm is concerned, there is no difference whether things are run in parallel or not - a single core machine can always do the same thing as one doing it in parallel, it's just a question of performance. If consciousness is something that can be developed on a computer (as we know it today, i.e., simply a matter of running the right software), then it can be run on any computer, although it might be very slow.
As far as algorithms are concerned, what you suggest is nothing new - e.g., neural networks are used in AI, and they model a process that occurs in parallel. But it doesn't matter whether you run it on hardware with multiple cores or only one.
You also seem to be unaware of anything to do with multiple cores, SMP and so on? - Yes, writing things to run in parallel is a difficult area, but this is not specific to AI, and is something that is already done today on most computers.
In summary: (a) running things in parallel isn't inherently necessary, it's just a question of whether you'd get better performance, (b) the industry already realised years ago that running things in parallel is a way to get better performance, and this transition became standard even on bog standard PCs in the last decade - even phones have multiple CPUs these days. (Of course, it's true that we're still a long way from solving the problem of scaling most software to say thousands or millions of cores, but again, it's not like no one's thought of this.)
There's also the point that, as far as running an algorithm is concerned, there is no difference whether things are run in parallel or not - a single core machine can always do the same thing as one doing it in parallel, it's just a question of performance. If consciousness is something that can be developed on a computer (as we know it today, i.e., simply a matter of running the right software), then it can be run on any computer, although it might be very slow.
As far as algorithms are concerned, what you suggest is nothing new - e.g., neural networks are used in AI, and they model a process that occurs in parallel. But it doesn't matter whether you run it on hardware with multiple cores or only one.
You also seem to be unaware of anything to do with multiple cores, SMP and so on? - Yes, writing things to run in parallel is a difficult area, but this is not specific to AI, and is something that is already done today on most computers.
In summary: (a) running things in parallel isn't inherently necessary, it's just a question of whether you'd get better performance, (b) the industry already realised years ago that running things in parallel is a way to get better performance, and this transition became standard even on bog standard PCs in the last decade - even phones have multiple CPUs these days. (Of course, it's true that we're still a long way from solving the problem of scaling most software to say thousands or millions of cores, but again, it's not like no one's thought of this.)