Post by dubyakayel on Mar 19, 2011 13:09:14 GMT -5
What do you say to that, Dave? Are you guys building a machine that will take over using intelligence from humans?
Ferrucci: No. I think what this challenge helps us appreciate, frankly, is how incredible the human brain is. And it helps illuminate what's really hard for computers and what humans find natural and what we're looking for in terms of the right sort of human-machine interface. Wouldn't it be great to be able to communicate with the computer like Captain Picard or Captain Kirk does on "Star Trek," where you can fluently dialogue with an information-seeking computer that can understand what you're asking, ask follow up questions, and get exactly at the information that you need? That would be incredible. That's kind of this motivating vision, and whether Watson loses or not in this big game is really not the point. The point is we were able to take a step forward in that direction, and I think that's what we're most excited about.
A SELF-CONFIDENT COMPUTER
Playing successfully on Jeopardy! often involves ego and the confidence to gamble. Did you program self-confidence into Watson? How close are computers to breaking that barrier of human-like emotions?
Ferrucci: That's a great question. It's a fascinating one really. And one of the big challenges—and this is where we exploited machine learning in a big way—was computing that confidence and figuring out how to use that confidence to manage risk during a game.
So, for example, sometimes the computer is really sure it knows the answer and wants to be very aggressive with the buzzer. Other times it's not so sure, and it actually weighs how good its competitors are. Other times it feels its way ahead and doesn't want to take a risk, so it needs to be a lot more confident to buzz in. Sometimes it's desperate and actually wants to take a risk, even if it's not as sure. All that's in there, believe it or not. And you want to call those emotions. They're really not emotions. They're complex mathematical equations that we've trained into Watson over many, many simulations. It makes it a very fascinating challenge.
The other thing I'll mention about emotions, though, is Watson doesn't sweat! I sweat, but Watson doesn't. So we've seen games where Watson lost a big daily double and went down to zero and just kept right on going. Personally I would have fainted. [laughter]
Brooks: Interestingly, when Garry Kasparov was beaten by Deep Blue many years ago, he said, "Well, at least it didn't enjoy beating me." [laughter]
So we, as humans, like to hold onto what we've still got that the computers don't have. And what's happened here is there's an extra piece. You know, wordplay and puns and stuff like that used to be something that people could have but computers could never understand. Dave and his team now have them understanding it.
Ferrucci: I don't think you should worry. I mean, think about it this way: A computer is understanding language the way you might understand another language you don't know. Pick a language you don't know and then think about it. The only way you could understand it is by reading dictionaries in that language. You don't really connect those words to your experiences. They're not connected to your emotions. They're just connected to one another. The computer is using statistics. It doesn't actually enjoy or love or appreciate any of what those words represent.
Brooks: Yet. [laughter]
WHERE WE STAND
Yeah, are we on the verge of "Skynet," the artificially intelligent system in the Terminator movies?
Brooks: We knew Skynet was going to come up! [laughter] You know, one of the things people worry about is, as computers get smarter, are they going to replace us? Well, you are still here. Computers didn't replace you. You use them as tools. And this is getting better tools. And I suspect that's IBM's agenda here—they want to build better tools for people. I don't think we need to worry anytime soon about the machines taking over. I work in robotics, and the robots we build haven't gotten rid of people. They just make them more productive. We can relax for a few hundred years, is my guess.
"There are simple things that three-year-olds can do that computers cannot yet do."
Von Ahn: I think a few hundred years is a good answer. There are the very, very simple things that computers still cannot do. Even determining who somebody is from an image or whether something is a cat or a dog from an image is something that computers cannot do very well. So there are simple things that three-year-olds can do that computers cannot yet do.
So we don't have to worry about HAL from 2001...
Von Ahn: We don't have to worry about HAL just yet. Maybe in a hundred years or so. But that's okay; we'll be dead. [laughter]
One last question for Dave: What's the silliest answer you ever heard from Watson?
Ferrucci: Well, as Watson's developed over the years, it's had a lot of silly answers; there's quite a variety of them. I guess one of my favorites is we asked it "What do grasshoppers eat?" and its answer was "kosher." [laughter]
Ferrucci: No. I think what this challenge helps us appreciate, frankly, is how incredible the human brain is. And it helps illuminate what's really hard for computers and what humans find natural and what we're looking for in terms of the right sort of human-machine interface. Wouldn't it be great to be able to communicate with the computer like Captain Picard or Captain Kirk does on "Star Trek," where you can fluently dialogue with an information-seeking computer that can understand what you're asking, ask follow up questions, and get exactly at the information that you need? That would be incredible. That's kind of this motivating vision, and whether Watson loses or not in this big game is really not the point. The point is we were able to take a step forward in that direction, and I think that's what we're most excited about.
A SELF-CONFIDENT COMPUTER
Playing successfully on Jeopardy! often involves ego and the confidence to gamble. Did you program self-confidence into Watson? How close are computers to breaking that barrier of human-like emotions?
Ferrucci: That's a great question. It's a fascinating one really. And one of the big challenges—and this is where we exploited machine learning in a big way—was computing that confidence and figuring out how to use that confidence to manage risk during a game.
So, for example, sometimes the computer is really sure it knows the answer and wants to be very aggressive with the buzzer. Other times it's not so sure, and it actually weighs how good its competitors are. Other times it feels its way ahead and doesn't want to take a risk, so it needs to be a lot more confident to buzz in. Sometimes it's desperate and actually wants to take a risk, even if it's not as sure. All that's in there, believe it or not. And you want to call those emotions. They're really not emotions. They're complex mathematical equations that we've trained into Watson over many, many simulations. It makes it a very fascinating challenge.
The other thing I'll mention about emotions, though, is Watson doesn't sweat! I sweat, but Watson doesn't. So we've seen games where Watson lost a big daily double and went down to zero and just kept right on going. Personally I would have fainted. [laughter]
Brooks: Interestingly, when Garry Kasparov was beaten by Deep Blue many years ago, he said, "Well, at least it didn't enjoy beating me." [laughter]
So we, as humans, like to hold onto what we've still got that the computers don't have. And what's happened here is there's an extra piece. You know, wordplay and puns and stuff like that used to be something that people could have but computers could never understand. Dave and his team now have them understanding it.
Ferrucci: I don't think you should worry. I mean, think about it this way: A computer is understanding language the way you might understand another language you don't know. Pick a language you don't know and then think about it. The only way you could understand it is by reading dictionaries in that language. You don't really connect those words to your experiences. They're not connected to your emotions. They're just connected to one another. The computer is using statistics. It doesn't actually enjoy or love or appreciate any of what those words represent.
Brooks: Yet. [laughter]
WHERE WE STAND
Yeah, are we on the verge of "Skynet," the artificially intelligent system in the Terminator movies?
Brooks: We knew Skynet was going to come up! [laughter] You know, one of the things people worry about is, as computers get smarter, are they going to replace us? Well, you are still here. Computers didn't replace you. You use them as tools. And this is getting better tools. And I suspect that's IBM's agenda here—they want to build better tools for people. I don't think we need to worry anytime soon about the machines taking over. I work in robotics, and the robots we build haven't gotten rid of people. They just make them more productive. We can relax for a few hundred years, is my guess.
"There are simple things that three-year-olds can do that computers cannot yet do."
Von Ahn: I think a few hundred years is a good answer. There are the very, very simple things that computers still cannot do. Even determining who somebody is from an image or whether something is a cat or a dog from an image is something that computers cannot do very well. So there are simple things that three-year-olds can do that computers cannot yet do.
So we don't have to worry about HAL from 2001...
Von Ahn: We don't have to worry about HAL just yet. Maybe in a hundred years or so. But that's okay; we'll be dead. [laughter]
One last question for Dave: What's the silliest answer you ever heard from Watson?
Ferrucci: Well, as Watson's developed over the years, it's had a lot of silly answers; there's quite a variety of them. I guess one of my favorites is we asked it "What do grasshoppers eat?" and its answer was "kosher." [laughter]
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www.pbs.org/wgbh/nova/tech/will-watson-win-jeopardy.html
Not the entire interview, but thought the ending was the most important parts.
www.pbs.org/wgbh/nova/tech/will-watson-win-jeopardy.html
Not the entire interview, but thought the ending was the most important parts.