YouSaid · the spoken record

Gary Marcus

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109
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2019-10-03
most recent
2019-10-03
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1
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podcast

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  1. “Think some parts of it are and some aren't. So, my company that I recently founded with Rod Brooks from MIT for many years and so forth, we're interested in both. We're interested in physical reasoning and psychological reasoning, among many other things. There are pieces of each of these that are accessible. So if you want a robot to figure out whether it can fit under a table, that's a relatively accessible piece of physical reasoning. You know, if you know the height of the table and you know the height of the robot, it's not that hard. If you wanted to do physical reasoning about Jenga, it gets a little bit more complicated and you have to have higher resolution data in order to do it. With psychological reasoning, it's not that hard to know, for example, that people have goals and they like to act on those goals, but it's really hard to know exactly what those goals are.”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  2. “I think that you're right, for example, that Facebook does a lot of experimentation in psychological reasoning. In fact, Zuckerberg talked about AI at a talk that he gave NIPS. I wasn't there, but the conference has been renamed NERPS. But he used to be called NIPS when he gave the talk. And he talked about Facebook basically having a gigantic theory of mind. So I think it is certainly possible. I mean, Facebook does some of that. I think they have a really good idea of how to addict people to things. They understand what draws people back to things. And I think they exploit it in ways that I'm not very comfortable with. But even so, I think that there are only some slices of human experience that they can access through kind of interface they have. And of course, they're doing all kinds of VR stuff, and maybe that'll change and they'll expand their data. And, you know, I'm sure that that's part of their goal. So it is an interesting question.”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  3. “So, I can sort of guess how you might react to something based on how I think I would react to it. And robots don't have that intuition, and they also can't do experiments on people in the same way, or we'll probably shut them down. So, you know, if we wanted to have robots figure out how I respond to pain by pinching me in different ways, like that's probably, you know, it's not going to make it past the human subjects board and companies are going to get sued or whatever. So there's certain kinds of practical experience that are limited or off limits to robots”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  4. “Yeah, physical versus psychological. And the argument I was making is physical knowledge might be more accessible because you could have a robot, for example, lift a bottle, try putting on a bottle cap on it, see that it falls off if it does this, and see that it could turn it upside down. And so the robot could do some experimentation. We do some of our psychological reasoning by looking at our own minds.”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  5. “Would say that common sense knowledge includes both physical knowledge and psychological knowledge and the argument I was making.”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  6. “And so there are lots of places where if we had a good machine interpretable set of common sense, many things would accelerate relatively quickly, but I don't think even that is like a single point. There's many different aspects of knowledge. And we might, for example, find that we make a lot of progress on physical reason and getting machines to understand, for example, how keys fit into locks or that kind of stuff, or how this gadget here works and so forth and so on. Machines might do that long before they do really good psychological reasoning because it's easier to get kind of labeled data or to do direct experimentation on a microphone stand than it is to do direct experimentation on human beings to understand the levers that guide them.”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  7. “How to flexibly approach some kind of novel MacGyver problem solving kind of situation. And I don't know that all of these things will come once. I think there are certain vital prerequisites that we're missing now. So for example, machines don't really have common sense now. So they don't understand that bottles contain water and that people drink water to quench their thirst and that they don't want to dehydrate. They don't know these basic facts about human beings. And I think that that's a rate limiting step for many things. It's a rate limiting step for reading, for example, because stories depend on things like, oh my God, that person's running out of water. That's why they did this thing. Or if they have water, they could put out the fire. So, you know, you watch a movie and your knowledge about how things work matter. And so a computer can't understand that movie if it doesn't have that background knowledge. Same thing if you read a book.”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  8. “I think that it will be somewhere in between, and I guess it depends what you mean by gradual and sudden. I don't think it's going to be one day. I think it's important to realize that intelligence is a multidimensional variable. So people sort of write this stuff as if IQ was one number. And, you know, the day that you hit 262 or whatever, you displaced the human beings. And really, there's lots of facets to intelligence. So there's verbal intelligence and there's motor intelligence and there's mathematical intelligence and so forth. Machines in their mathematical intelligence far exceed most people already and their ability to play games. They far exceed most people already in their ability to understand language. They lag behind my five-year-old, far behind my five-year-old. So there are some facets of intelligence in the machines of grasp and some that they haven't. And we have a lot of work left to do to get them to, say, understand natural language or to understand”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source

  9. “I think our place in the food chain has already changed. So there are lots of things people used to do by hand that they do with machine. If you think of a singularity as like one single moment, which is I guess what it suggests, I don't know if it'll be like that. But I think that there's a lot of gradual change and AI is getting better and better. I mean, I'm here to tell you why I think it's not nearly as good as people think, but the overall trend is clear. Maybe Ray Kurzweil thinks it's an exponential and I think it's linear in some cases it's close to zero right now, but it's all going to happen. I mean, we are going to get to human-level intelligence or whatever artificial general intelligence at some point. And that's certainly going to change our place in the food chain because a lot of the tedious things that we do now, we're going to have machines do and a lot of the dangerous things that we do now, we're going to have machines do. I think our whole lives are going to change from people finding their meaning through their work through”

    2019-10-03 · Lex Fridman Podcast · Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI · IDENTIFIED FROM THE TRANSCRIPT · source