Comments on: Getting machines to think like us
newsmaker AI pioneer John McCarthy discusses early goals, recent gains and how "artificial intelligence" got its name.
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think better than we do. That wouldn't seem hard.
Next, they could program unmanned aerial vehicles to see and
avoid other air traffic, just like a live pilot does. So far, they are
dumb and blind, and so a danger to all other air traffic.
think better than we do. That wouldn't seem hard.
Next, they could program unmanned aerial vehicles to see and
avoid other air traffic, just like a live pilot does. So far, they are
dumb and blind, and so a danger to all other air traffic.
think better than we do. That wouldn't seem hard.
Next, they could program unmanned aerial vehicles to see and
avoid other air traffic, just like a live pilot does. So far, they are
dumb and blind, and so a danger to all other air traffic.
The only way that we are ever going to create an intelligent machine that approaches the level of thought found in the human mind is through pulse coded neural networks used to implement positive feedback cortical planes. Current Von-Neuman machines don't have the power to emulate a neural network containing billions of neurons with trillions of interconnectsion - maybe they never will.
The problem is that current AI research still revolves around how to get Von Neuman machines to act intelligently. This is moronic! Its like looking for your eyeglasses out by the streetlight when you lost them in a dark alley because the light is better there. It just ain't going to happen! Of course, I am not saying that such research is useless - that would also be moronic. It just won't lead to a concious machine.
If you want a concious machine, there is no alternative, but to create specialized hardware to emulate the neural network. Three dimensional circuitry implemented with proximity field effect gates might work. However, this is a chicken and egg problem because there will be little motivation to develop the proper circuitry since you get so much bang for the buck with von neuman machines.
Of course if you had enough Von Neuman machines that could handle trillions of interconnections maybe it would be possible to make a concious machine. However, this would be prohibitively expensive --- wait, what about the internet....
The problem is that even if we had the specialized hardware you propose, we wouldn't know what to do with it. We understand too little about the problem. We don't even uderstand what questions to ask. Technology normally evolves in small incremental steps, but we still don't know what the incremental steps to get from "Elisa" to "HAL". It is today just a big step from Simulated Intelligence to Artificial Intelligence.
Since Von Newman machines have proven to be so good at emulating anything they allow us to emulate massively parallel systems in a cheap lab. There's nothing, NOTHING, a neural net or parallel machine can do that a Von Newman cannot do slowly. Maybe they are orders of magnitude too slow to do any practical AI, buit that doesn't matter. For research purposes slow AI is the same as AI, so if we can use the VN machines to emulate a machine that can, in a few months of computation, deduce something simple that requires actual intelligence, it would be a great step.
If we'd rather concentrated on creating specialized machines we would instead be spending millions and probably some of the best brains on earth in building thousands of generations of machines that don't work and that are probably trying to solve problems we don't understand, machines that could have been emulated, even if slowly, by other machines we already have.
Once we get Von Newman machines to do some intelligent things we would have achieved something: understanding some of the fundamental questions and mechanisms. And then, only then, investing in designing a platform to do that at a bigger and faster scale, is worth the effort.
Why waste billions on designing hundreds of generations of machines to do tasks we don't even understand?
It is better to rely on emulation until we understand the questions, until we can say "this is what I want the machine to do", and then we can move our efforts into building efficient and scalable machines.
Speed is not of the essence. Slow AI is still AI.
Today we don't know how to go from Elisa to Hal. We don't have a roadmap or a path, we have no incremental steps to go by. Building extremely capable hardware such as your proposed neural nets is not going to help us get there.
Once we've built emulations that can show some signs of being on that path it is worth to concentrate on building specialized hardware to do practical implementations.
The only way that we are ever going to create an intelligent machine that approaches the level of thought found in the human mind is through pulse coded neural networks used to implement positive feedback cortical planes. Current Von-Neuman machines don't have the power to emulate a neural network containing billions of neurons with trillions of interconnectsion - maybe they never will.
The problem is that current AI research still revolves around how to get Von Neuman machines to act intelligently. This is moronic! Its like looking for your eyeglasses out by the streetlight when you lost them in a dark alley because the light is better there. It just ain't going to happen! Of course, I am not saying that such research is useless - that would also be moronic. It just won't lead to a concious machine.
If you want a concious machine, there is no alternative, but to create specialized hardware to emulate the neural network. Three dimensional circuitry implemented with proximity field effect gates might work. However, this is a chicken and egg problem because there will be little motivation to develop the proper circuitry since you get so much bang for the buck with von neuman machines.
Of course if you had enough Von Neuman machines that could handle trillions of interconnections maybe it would be possible to make a concious machine. However, this would be prohibitively expensive --- wait, what about the internet....
The problem is that even if we had the specialized hardware you propose, we wouldn't know what to do with it. We understand too little about the problem. We don't even uderstand what questions to ask. Technology normally evolves in small incremental steps, but we still don't know what the incremental steps to get from "Elisa" to "HAL". It is today just a big step from Simulated Intelligence to Artificial Intelligence.
Since Von Newman machines have proven to be so good at emulating anything they allow us to emulate massively parallel systems in a cheap lab. There's nothing, NOTHING, a neural net or parallel machine can do that a Von Newman cannot do slowly. Maybe they are orders of magnitude too slow to do any practical AI, buit that doesn't matter. For research purposes slow AI is the same as AI, so if we can use the VN machines to emulate a machine that can, in a few months of computation, deduce something simple that requires actual intelligence, it would be a great step.
If we'd rather concentrated on creating specialized machines we would instead be spending millions and probably some of the best brains on earth in building thousands of generations of machines that don't work and that are probably trying to solve problems we don't understand, machines that could have been emulated, even if slowly, by other machines we already have.
Once we get Von Newman machines to do some intelligent things we would have achieved something: understanding some of the fundamental questions and mechanisms. And then, only then, investing in designing a platform to do that at a bigger and faster scale, is worth the effort.
Why waste billions on designing hundreds of generations of machines to do tasks we don't even understand?
It is better to rely on emulation until we understand the questions, until we can say "this is what I want the machine to do", and then we can move our efforts into building efficient and scalable machines.
Speed is not of the essence. Slow AI is still AI.
Today we don't know how to go from Elisa to Hal. We don't have a roadmap or a path, we have no incremental steps to go by. Building extremely capable hardware such as your proposed neural nets is not going to help us get there.
Once we've built emulations that can show some signs of being on that path it is worth to concentrate on building specialized hardware to do practical implementations.
The only way that we are ever going to create an intelligent machine that approaches the level of thought found in the human mind is through pulse coded neural networks used to implement positive feedback cortical planes. Current Von-Neuman machines don't have the power to emulate a neural network containing billions of neurons with trillions of interconnectsion - maybe they never will.
The problem is that current AI research still revolves around how to get Von Neuman machines to act intelligently. This is moronic! Its like looking for your eyeglasses out by the streetlight when you lost them in a dark alley because the light is better there. It just ain't going to happen! Of course, I am not saying that such research is useless - that would also be moronic. It just won't lead to a concious machine.
If you want a concious machine, there is no alternative, but to create specialized hardware to emulate the neural network. Three dimensional circuitry implemented with proximity field effect gates might work. However, this is a chicken and egg problem because there will be little motivation to develop the proper circuitry since you get so much bang for the buck with von neuman machines.
Of course if you had enough Von Neuman machines that could handle trillions of interconnections maybe it would be possible to make a concious machine. However, this would be prohibitively expensive --- wait, what about the internet....
The problem is that even if we had the specialized hardware you propose, we wouldn't know what to do with it. We understand too little about the problem. We don't even uderstand what questions to ask. Technology normally evolves in small incremental steps, but we still don't know what the incremental steps to get from "Elisa" to "HAL". It is today just a big step from Simulated Intelligence to Artificial Intelligence.
Since Von Newman machines have proven to be so good at emulating anything they allow us to emulate massively parallel systems in a cheap lab. There's nothing, NOTHING, a neural net or parallel machine can do that a Von Newman cannot do slowly. Maybe they are orders of magnitude too slow to do any practical AI, buit that doesn't matter. For research purposes slow AI is the same as AI, so if we can use the VN machines to emulate a machine that can, in a few months of computation, deduce something simple that requires actual intelligence, it would be a great step.
If we'd rather concentrated on creating specialized machines we would instead be spending millions and probably some of the best brains on earth in building thousands of generations of machines that don't work and that are probably trying to solve problems we don't understand, machines that could have been emulated, even if slowly, by other machines we already have.
Once we get Von Newman machines to do some intelligent things we would have achieved something: understanding some of the fundamental questions and mechanisms. And then, only then, investing in designing a platform to do that at a bigger and faster scale, is worth the effort.
Why waste billions on designing hundreds of generations of machines to do tasks we don't even understand?
It is better to rely on emulation until we understand the questions, until we can say "this is what I want the machine to do", and then we can move our efforts into building efficient and scalable machines.
Speed is not of the essence. Slow AI is still AI.
Today we don't know how to go from Elisa to Hal. We don't have a roadmap or a path, we have no incremental steps to go by. Building extremely capable hardware such as your proposed neural nets is not going to help us get there.
Once we've built emulations that can show some signs of being on that path it is worth to concentrate on building specialized hardware to do practical implementations.
one) first requires understanding our own evolved intelligence. To
do that we need to start over. See "Wholly holistic evolution, Mr.
Darwin" at http://we.karleklund.net.
one) first requires understanding our own evolved intelligence. To
do that we need to start over. See "Wholly holistic evolution, Mr.
Darwin" at http://we.karleklund.net.
- Designed Intelligence
- by karlek76 July 5, 2006 1:21 PM PDT
- Creating a stable designed intelligence (as opposed to an evolved
- Like this Reply to this comment
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- designed intelligence?
- by newcreation July 6, 2006 11:50 AM PDT
- no wonder why he said it he rejected "conventional christianity "at an early age" so he would see darwin like that..nice in theory if you buy all the loop wholes in thinking
- Like this
-
(33 Comments)one) first requires understanding our own evolved intelligence. To
do that we need to start over. See "Wholly holistic evolution, Mr.
Darwin" at http://we.karleklund.net.