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The most obvious thing to do in a movie, when they write about robots, is give them human-like motivations of some kind or other, so that the robot can be a character in the movie. It's very easy to assume that robots would just naturally be like humans, like in that movie "AI," where you have this sort of Pinocchio robot that gets lonely.
They create this imitation 10-year-old, and they don't even bother to think that, well, now what will happen when this woman who gets this imitation 10-year-old gets older--when she is 70 or 80--and she still has this imitation 10-year-old. From the point of view of the plot of the movie, it wasn't necessary to think about that, and so that's just sort of one more way in which people are misled by stories.
What do you think of Ray Kurzweil's notion of "the singularity"
McCarthy: I think it's nonsense. I don't think Kurzweil has any ideas that have any potential to do that. Now, it could happen in 2045, but it wouldn't happen through any effort of Kurzweil. You see, I think that most likely, the next major advance is going to be not made by one of us old guys--and I include Kurzweil among the old guys--but by some young guy.
When I was in Israel (in June), I met this young guy who likes my paper on ascribing mental qualities to machines, and well, I only got a few minutes to talk to him, but I think there is so to speak more hope from people like him than there are from people who have been in the field a long time.
And what about research into the brain--has that yielded any notions for artificial intelligence?
McCarthy: Certainly, we've gotten (to know) a lot about how the brain works. I don't think it's got very much that connects with artificial intelligence yet. Let me give you an example. The positron emission tomography (PET scan) has found a little area in the brain that uses a lot of energy when people are doing mental arithmetic. That's fine, but what goes on in that area when people are doing mental arithmetic is still beyond the present neurophysiology to determine.
I've been reading through some
writing you'd done on progress and sustainability. You seemed to be very optimistic about the future--that material progress is sustainable. But it's a very pessimistic age we live in.
McCarthy: Public moods and journalistic moods can change very fast. Let us suppose that the only really short-term practical way of maintaining automotive transportation is to use liquid hydrogen as a fuel and to produce liquid hydrogen by nuclear reactors. That may very well be the case. I think that if the public, the Congress and the journalists are suddenly faced with really not being able to use cars (unless we) adopt this new technology, then all of a sudden, the mind will be concentrated, as Samuel Johnson says.
So as the problem gets to a point where we really need to deal with it, we'll deal with it.
McCarthy: Yes, I think so. I don't think that we will let ourselves suffer a real disaster if there is a way of doing (something about it). You can look at the response of the U.S. and other countries in time of war as an example that shows that ideas can change very fast when there is a necessity.
You've also written that you think global warming can be avoided or even reversed, if it turns out to be a serious problem. You wrote that a few years ago--do you still think that's the case, given current research?
McCarthy: I think there is pretty good evidence that there is some warming. I guess there is controversy about the cause, but it can be reversed, if necessary. But it still isn't clear that it's harmful.
The way of thinking, even among the scientists, is predominantly doom-oriented. Not entirely, but predominantly. They still are not thinking of how we can fix things other than to refrain. I mean, scientists are affected by the same moods that affect the rest of the public.
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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.