YouSaid · the spoken record

Peter Norvig

lines on the record: 74
first: 2019-09-30
most recent: 2019-09-30
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“Just in general, as a programmer, I'm interested in programming tools, both in terms of the current systems we have today with TensorFlow and so on. Can we make them much easier to use for broader class of people? And also can we apply machine learning to the more traditional type of programming? So when you go to Google and you type in a query and you spell something wrong, it says, did you mean? And the reason we're able to do that is because lots of other people made a similar error and then they corrected it. We should be able to go into our code bases and our bug fix spaces. And when I type a line of code, it should be able to say, did you mean such and such? If you type this today, you're probably going to type in this bug fix tomorrow.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So we talked about these assistance in conversation. I think that's a great area. I think combining Common sense reasoning with the power of data is a great area.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“I don't know. Again, it's hard to predict the future. As a society so far, we've survived nuclear bombs and other things. Of course, only societies that have survived are having this conversation. So maybe that's survivorship bias there.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I certainly think about threats. I think about dangers, and I think any new technology has positives and negatives. And if it's a powerful technology, it can be used for bad as well as for good So I'm certainly not worried about the robot apocalypse and the Terminator type scenarios. I am worried about In employment, and are we going to be able to react fast enough to deal with that? We're already seeing it today where a lot of people are disgruntled about the way income inequality is working. And automation could help accelerate those kinds of problems. I see powerful technologies can always be used as weapons, whether they're robots or drones or whatever. Some of that we're seeing due to AI. A lot of it needs AI. And I don't know what's a worse threat.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And I think conversation is important. I think we sometimes have these tests where it's easy to fool the system, where you can have a chatbot that can have a conversation, but you never, it never gets into a situation where it has to be deep enough that it really reveals itself as being intelligent or not. I think Turing suggested that, but I think if he were alive, he'd say, you know, I didn't really mean that seriously, right? And I think this is just my opinion. But I think Turing's point was not that this test of conversation is a good test. I think his point was having a test is the right thing. So rather than having the philosopher say, oh no, AI is impossible. You should say, well, we'll just have a test. And then the result of that will tell us the answer. And it doesn't necessarily have to be a conversation test.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“I get impressed all the time. But like really impressive, you know, go playing StarCraft playing. Those are all pretty cool.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“It's just in the other end. Yeah, and certainly, you know, if you can get to dog level, a lot of people have invested a lot of love in their pets.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. So, I mean, I think that's just the way we are. We want to trust. We want to believe. We want to fall in love. And it doesn't necessarily take that much, right? So, you know, my kids fell in love with their teddy bear. And the teddy bear was not very interactive, right? So that's all us. Pushing our feelings onto our devices and our things. And I think that that's what we like to do. So we'll continue to do that.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think as people, that's what we love to do. And I was at a showing of her where we had a panel discussion and somebody asked me what other movie do you think her is similar to? And my answer was Life O'Brien, which is not a science fiction movie But both movies are about wanting to believe in something that's not necessarily real.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So, as you say, I like to focus on what's a useful tool. And in some cases, being at human level is an important part of crossing that threshold to make the tool useful. So we see in things like these personal assistants now that you get either on your phone or on a speaker that sits on the table, you want to be able to have a conversation with those. And I think as an industry, we haven't quite figured out what the right model is for what these things can do. And we're aiming towards, well, you just have a conversation with them the way you can with a person. But we haven't delivered on that model yet, right? So you can ask it, what's the weather? You can ask it, play some nice songs, and five or six other things, and then you run out of stuff that it can do.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. So certainly I don't think human level intelligence is one thing, right? So I think there's lots of different tasks, lots of different capabilities. I also don't think that should be the goal, right? So I wouldn't want to create a calculator that could do multiplication at human level. That would be a step backwards. And so for many things, we should be aiming far beyond human level. For other things, maybe human level is a good level to aim at. And for others, we'd say, well, let's not bother doing this because we already have humans can take on those tasks.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“We had the ARPANET. And then there was this proposal to. Have this internet, and this crazy senator Gore. Thought that might be a good idea. And I remember thinking, oh, come on, you can't expect a commercial company to understand this technology. They'll never be able to do it. Yeah, okay, we can have this.com domain, but it won't go anywhere. So I was wrong. Al Gore was right.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so that's certainly true, right? So we definitely changed the structure of the network, right? So if you think back in the very early days, Larry and Sergei had the page rank paper, and John Kleinberg had this Hubson authorities model, which says the web is made out of these hubs which will be My page of cool links about dogs or whatever and people would just list links and then there'd be authorities which were the ones, the page about dogs that most people link to. That doesn't happen anymore. People don't bother to say my page of cool links. Because we took over that function. So we changed the way that wor”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's game theoretic, and so we had to think not only is this the right move for us to make now, but also if we make this move, what's the counter move going to be? Is that going to get us into a worse place, in which case we won't make that move? We'll make a different move.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. One of the metrics we had was focused on the first thing. Some of it was focused on the whole page. Some of it was focused on the top three or so. So we looked at a lot of different metrics for how well we were doing, and we broke it down into subclasses of maybe here's a type of query that we're not doing well on, then we try to fix that. Early on, we started to realize that we were in an adversarial position, right? So we started thinking, well, we're kind of like the card catalog in the library. So the books are here, and we're off to the side, and we're just reflecting what's there. And then we realized every time we make a change, the webmasters make a change.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Definitely was an exciting time, and as you say, we were doubling in size every year. And the challenges were we wanted to get the right answers. And we had to figure out what that meant. We had to implement that and we had to make it all efficient and To keep on testing and seeing if we were delivering good answers.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Wondering what the. Yeah, so the class came first. Some of the stuff that's in Pi Tudes was write ups of what was in the class, and then some of it was just continuing to work on new problems.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Observatory with puzzles and X. Yeah, just it seemed like fun. I like doing puzzles and I like being an educator. I did a class with Udacity, Udacity 212, I think it was, that was basically problem solving using Python and looking at different problems”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Way and so that was the point at which I said okay can't have only Lisp as a language Because I don't want to, you know, you only got 10 or 12 or 15 weeks or whatever it is to teach AI. And I don't want to waste two weeks of that teaching Lisp. So I say, I got to have another language. Java was the most popular language at the time. I started doing that. And then I said, it's really hard to have a one-one correspondence between the pseudocode and the Java because Java is so verbose. So then I said, I'm going to do a survey and find the language that's most like my pseudocode. And it turned out Python basically was my pseudocode. Somehow, I had channeled Guido. Designed a pseudocode that was the same as Python, although I hadn't heard of Python at that point. And from then on, that's what I've been using because it's been a good match.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Saying all you need is parentheses in atoms. But I remember, you know, as we had the AI textbook and because we did it in the 90s, we had pseudocode in the book, but then we said, well, we'll have Lisp online because that's the language of AI at the time. And I remember some of the students complaining because they hadn't had lists before and they didn't quite understand what was going on. And I remember one student complained, I don't understand how this pseudocode corresponds to this lisp. And there was a one-to-one correspondence between the symbols in the code and the pseudocode. And the only thing difference was the parentheses. So I said, it must be that for some people, a certain number of left parentheses shuts off their brain.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“At all the parentheses, yeah. So I think a couple things. So, one was, I think it was designed for a single programmer or a small team. And skilled programmer who had the good taste to say, well, I am doing language design, and I have to make good choices. And if you make good choices, that's great. If you make bad choices, you can hurt yourself, and it can be hard for other people on the team to understand it. So I think there was a limit to the scale of the size of a project in terms of number of people that Lisp was good for. And as an industry, we kind of grew beyond that. I think it is in part the parentheses. One of the jokes is the acronym for Lisp is lots of irritating, silly parentheses. My acronym was Lisp is syntactically pure.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And that allows a better match between your problem and your eventual code. And I think Lisp had done that better than other languages.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I think the beautiful part is the simplicity that in half a page you can define the whole language. And other languages don't have that. So you feel like you can hold everything in your head. Then a lot of people say, well, then that's too simple. Here's all these things I want to do. And my Java or Python or whatever has a hundred or two hundred or three hundred different syntax rules. And don't I need all those? And Lisp's answer was, no, we're only going to give you eight or so syntax rules, but we're going to allow you to define your own. And so that was a very powerful idea. And I think this idea of saying, I can start with my problem and with my data, and then I can build the language I want for that problem and for that data. And then I can make lists, define that language. You're mixing levels and saying I'm simultaneously a programmer in a language and a language designer.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So, if you're a little bit less efficient, but it makes it easier to understand and modify, then that's the right trade-off.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, to say, you know, what really matters is the total time it takes to get the project done. And most of that's going to be the programmer time.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And said objects are just dictionaries. And yeah, they have a few little tricks as well. But mostly, you know, the thing that would have been a hundred times too slow in the 80s is now plenty fast for most everything.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Guess one thing is you don't have to worry about the small details of efficiency as much as you used to, right? So like I remember I did my list book in the 90s and one of the things I wanted to do was say here's how you do an object system. And basically, we're going to make it so each object is a hash table and you look up the methods, and here's how it works. And then I said, of course, the real common Lisp object system is much more complicated. It's got all these efficiency type issues. And this is just a toy. Nobody would do this in real life. And it turns out Python pretty much did exactly. What I said”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it is how you feel, right? And so, yeah, documentation is good, but it's more a design question, right? If you get the design right, then people will figure it out whether the documentation is good or not. And if the design's wrong, then it'll be harder to use.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, that's a great question. Sometimes I try to look at flexibility of design. Yes, this API solves this problem, but where is it going to go in the future? Who else is going to want to call this? And are you making it easier for them to do that?”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Then, as a company grows, you say, well, we don't want everybody to be the same, to have the same skill set. And so now we're hiring biologists in our health areas, and we're hiring physicists, and we're hiring mechanical engineers, and we're hiring social scientists and ethnographers and people with different backgrounds who bring different skills.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. And I think as a company grows, you get more expansive in the types of people you're looking for, right? So I think, you know, in the early days, we'd interview people and the question we were trying to ask is, how close are they to Jeff Dean? And most people were pretty far away, but we take the ones that were not that far away. And so we got kind of a homogeneous group of people who are really great programmers.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And then we built up an ecosystem where a lot of times you can download a lot of stuff that does a big part of what you need. And so now it's more a question of assembly rather than manufacturing. And that's a different way of looking at problems.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think that's true. You know, we never really should have focused on programmer, right? Because it's still a skill. And what we really want to focus on is the result. So we built this ecosystem where the way you can get stuff done is by programming it yourself Least when I started library functions meant you had square root, and that was about it. Everything else you built from scratch”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“I downloaded the package, I installed it, I tried calling some things. The first one didn't work, the second one didn't work. Now I'm done. And I say, but I have 100 questions about how does this work and how does that work? And they say, who cares? Right? I don't need to understand the whole thing. I answered my question. It's a big, complicated package. I don't understand the rest of it, but I got the right answer. And I'm just, it's hard for me to get into that mindset. I want to understand the whole thing. And, you know, if they wrote a manual, I should probably read it. But that's not necessarily the right way. And I think I have to get used to. Dealing with being more comfortable with uncertainty and not knowing everything.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And I see myself being stuck sometimes in kind of the old ways. Right, so you know be working on a project, maybe with a younger employee and we say, oh, well, here's this new package that could help solve this problem. And I'll go and I'll start reading the manuals. And, you know, I'll be. Two hours into reading the manuals. And then my colleague comes back and says, I'm done.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“But I wish they would change the message a little bit, right? So I think code isn't the main thing. I don't really care if you know the syntax of JavaScript or if you can connect these blocks together in this visual language. But what I do care about is that you can analyze a problem. You can think of a solution. You can carry out, you know, make a model, run that model, test the model, see the results, verify that they're reasonable, ask questions and answer them. So it's more modeling and problem solving. And you use coding in order to do that, but it's not just learning coding for its own sake.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Think there's lots of different ways, and I think programming means more things now. And I guess, you know, when I wrote that article, I was thinking more about Becoming a professional software engineer. And I thought that's sort of a career long field of study. But I think there's lots of things now that people can do where programming is a part of solving what they want to solve without achieving that professional level status. So I'm not going to be going and writing a million lines of code, but I'm a biologist or a physicist or something or a even a historian. And I've got some data and I want to ask a question of that data. And I think for that, you don't need 10 years, right? So there are many shortcuts to being able to answer those kinds of questions. And, you know, you see today a lot of emphasis on learning to code, teaching kids how to code. I think that's great.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And then there are certain things that just hard to do virtually, right? So, you know, we're in a field where if you have your own computer and your own paper and so on, you can do the work anywhere. But if you're in a biology lab or something, you don't have all the right stuff at home.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And certainly it is important to have that kind of informal, you know, I meet people outside of class, we talk together because we're all in it together. I think that's really important both in keeping your motivation and also that's where some of the most important learning goes on. So you want to have that maybe especially now we start getting into higher bandwidths and augmented reality and virtual reality. You might be able to get that without being in the same physical place.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“And so those are two separate things. I mean, you could certainly imagine I pay a huge amount of tuition and everybody signed up and says, yes, you're doing this. But then I'm in my room and my classmates are in different rooms, right? We could have things set up that way. So it's not just the online versus offline. I think what's more important is the commitment that you've made.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“The same way you were, but also because you were enrolled, you had paid tuition, sort of everybody was expecting you to stick with it.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I think there's two issues. One is Whether it's in person or online, so it's sort of the physical location. And then the other is kind of the affiliation, right? So Stuck with it in part because you were in the classroom and you saw”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“That's really just the top tier of people that are ready to do that. The rest of the people just don't see or don't have their motivation and don't see how if they push through and were able to do it, what advantage that would get them. So I think we got a long way to go before we were able to do that. And I think it'll be some of it is based on technology, but more of it's based on the idea of community. You've got to actually get people together. Of the getting together can be done online. I think some of it really has to be done in person in order to build that type of community and trust.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“Really excited to be part of a new thing. And so the students brought their own motivation. And so I think this is great because there's lots of people around the world who have never had this before, would never have the opportunity to go to Stanford and take a class or go to MIT or go to one of the other schools. But now we can bring that to them. And if they bring their own motivation, they can be successful in a way they couldn't be for.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I guess the main thing I learned is when I came in, I thought the challenge was information, saying if I'm just take the stuff I want you to know and I'm very clear and explain it well, then my job is done and good things are going to happen. And then in doing the course, I learned, well, yeah, you got to have the information. But really, the motivation is the most important thing. If students don't stick with it, it doesn't matter how good the content is. And I think being one of the first classes, we were helped by sort of exterior motivation. So we tried to do a good job of making it enticing and setting up ways for the community to work with each other, to make it more motivating, but really a lot of it was, hey, this is a new thing.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“It was great fun doing it, particularly being right at the start. Because it was exciting and new, but it also meant that we had less competition. So one of the things you hear about, well, the problem with MOOCs is the completion rates are so low, so it must be a failure. And I got to admit I'm a prime contributor. I probably started 50 different courses that I haven't finished, but I got exactly what I wanted out of them because I had never intended to finish them. I just wanted to dabble in a little bit either to see the topic matter or just to see the pedagogy of how are they doing this class.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“For the most part, we still go to war. We still do terrible things, but for the most part, we've learned to trust each other and live together. So that's going to be important for our AI systems as well. Also, I think a lot of the emphasis is on AI, but in many cases, AI is part of the technology, but isn't really the main thing. So a lot of what we've seen is more due to communications technology than AI technology. AI, you want to make these good decisions, but the reason we're able to have any kind of system at all is we've got the communication so that we're collecting the data and so that we can reach lots of people around the world. I think that's a bigger change that we're dealing with.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“I think that's right. I think that's a big issue. Just listening, my friend Mark Moffat is a naturalist, and he says, the most amazing thing about humans is that you can walk into a coffee shop or a busy street in a city. And there's lots of people around you that you've never met before and you don't kill each other.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“It's a million dimension space, and CAT is this string that goes out in this crazy bath. And if you step a little bit off the path in any direction, you're in nowhere's land and you don't know what's going to happen. And so I think that's where we are. And now we've got to deal with that. So it wasn't so much an explanation, but it was an understanding of what the models are and what they're doing, and now we can start exploring how do you fix that.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source
“You look in a textbook and you say, okay, now we've mapped out the space. And Cat is here and dog is here. And maybe there's a tiny little spot in the middle where you can't tell the difference, but mostly we've got it all covered. And if you believe that metaphor, then you say, well, we're nearly there. And there's only going to be a couple adversarial images. But I think that's the wrong metaphor. And what you should really say is it's not a 2D.”
2019-09-30 · Lex Fridman Podcast · Peter Norvig: Artificial Intelligence: A Modern Approach · IDENTIFIED FROM THE TRANSCRIPT · source