YouSaid · the spoken record

Melanie Mitchell

lines on the record: 102
first: 2019-12-28
most recent: 2019-12-28
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

“What you're saying? Don't know if Turing computation is going to be sufficient. Probably I would guess it will. I don't see any reason why we need anything else. So, in that sense, we have invented the hardware we need, but we just need to make it faster and bigger. And we need to figure out the right algorithms and the right sort of architecture.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I'm a college professor for one thing, so I don't have a lot of extra funds to invest, but also no one knows what's going to work in AI, right? That's the problem”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I knew that, you know, one of my talks, one of the people in the audience was a public lecture, one of the people in the audience said, what AI companies are you investing in?”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“That's what we need. All this expert system stuff is not going to get you to AI. You need common sense. And he basically gave up his whole. Academic career to go pursue that. And I totally admire that. But I think that the approach itself. Will not in 2020 or wherever what do you think is wrong with it?”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it's still going, and it's the idea was to try and. Encode all of common sense knowledge, including all this invisible knowledge in some kind of logical representation. And it just never... I think could do any of the things that he was hoping it could do because that's just the wrong approach.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly right, yeah. That's a hard question because how do you represent that knowledge is the question, right? I can certainly write down f equals ma and Newton's laws and a lot of physics can be deduced from that. But that's probably not the best representation of that knowledge for doing the kinds of reasoning we want a machine to do. So I don't know. It's impossible to say now. And people, you know, the projects like there's a famous. The famous psych project.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Sure. And I think people have made some progress along those lines. I mean, people have been working on this for a long time. But the problem is, and this I think is the problem of common sense. Like people have been trying to get these common sense networks here at MIT. There's this concept net project, right? But the problem is that, as I said, most of the... Knowledge that we have is invisible to us. It's not in Wikipedia. It's very basic things about Know intuitive physics, intuitive psychology. Intuitive metaphysics, all that stuff.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“But we have, you know, it's really hard to know. 100 billion neurons or something? I don't know. And they're connected via trillions of synapses. And there's all this chemical processing going on. There's just a lot of capacity for. And their information's encoded in different ways in the brain. It's encoded in chemical interactions. It's encoded in electric firing and firing rates. And nobody really knows how it's encoded. But it just seems like there's a huge amount of capacity. So I think it's huge. It's just enormous. And it's amazing how much stuff we know.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“We need to understand better, I think, how How we do it, how humans do it. And it comes down to internal models, I think. You know, people talk a lot about mental models. Concepts are mental models that I can. In my head, I can do a simulation. A situation like walking a dog. And that there's some work in psychology that Promotes this idea that all of concepts are really mental simulations, that whenever you encounter a concept or situation in the world or you read about it or whatever, you do some kind of mental simulation that allows you to predict what's going to happen, to develop expectations of what's going to happen. So that's the kind of structure I think we need is that kind of mental model that And in our brains somehow these mental models are very much interconnected.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So it can be argued that all of this Generalization we do of concepts. And recognizing concepts in different situations. Is done by analogy. Every time I'm recognizing that, say, You're a person. That's by analogy because I have this concept of what a person is and I'm applying it to you. And every time I recognize a new situation, like one of the things I talked about in the book was the concept of walking a dog. That's actually making an analogy because all that, you know, the details are very different.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“We don't even say that, right? Yeah, and the view that kind of went into, say, Copycat, that whole thing is that. That act of saying the same thing happened to me is making an analogy. And in some sense, that's what underlies all of our concepts.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Sure. And if I go and tell a friend of mine about this podcast interview, my friend might say, oh, the same thing happened to me. You know, let's say, you know, you ask me some really hard question And I have trouble answering it. My friend could say, the same thing happened to me, but it was like, it wasn't a podcast interview. It wasn't. Was a completely different situation. And yet my friend is seen essentially the same thing. You know, we say that very fluidly, the same thing happened to me.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I never had that concept before this year, essentially. I mean, and I can make an analogy with it like being interviewed for a news article in a newspaper. And I can say, well, you kind of play the same role that the newspaper reporter played. It's not exactly the same because maybe they actually emailed me some written questions rather than talking. And the writing, the written questions are analogous to your spoken questions. There's just all kinds of similarities.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So, analogy is when you recognize that one situation Is essentially the same as another situation and essentially is kind of the key word there because it's not the same. So if I say. Last week I did a podcast interview actually like three days ago in Washington, D.C. And that situation was very similar to this situation, although it wasn't exactly the same. You know, it was a different person sitting across from me. We had different kinds of microphones. The questions were different. The building was different. There's all kinds of different things. Really, it was analogous. Or I can say doing a podcast interview, that's kind of a concept. It's a new concept.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“A concept is in some sense a fundamental unit of thought. So, say we have Concept of A dog okay And a concept is embedded in a whole space of concepts so that there's certain concepts that are closer to it or farther away from it.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So in this program, all the concepts of the program were innate. Because we weren't, I mean, obviously that limits it quite a bit. But what we were trying to do is say suppose you have some innate concepts. Do you flexibly apply them to new situations? And how do you make analogies?”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So there are different kinds of agents that can build connections between different things. So, just to give you a concrete example, what Copycat did was it made analogies between strings of letters. So here's an example. A, B, C changes to ABD. What does IJK change to? The program had some prior knowledge about the alphabet. It knew the sequence of the alphabet. It had a concept of letter, successor of letter. It had concepts of sameness. So it had some innate things programmed in. But then it could do things like Discover that. ABC is a group of letters in succession And then an agent can mark that.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, we called it a workspace. And the workspace is a data structure. The agents are little pieces of code that you could think of them as little detectors or little filters that say, I'm going to pick this place to look and I'm going to look for a certain thing. And is this the thing I think is important? Is it there? So it's almost like, you know, convolution in a way, except a little bit. More general and saying, and then highlighting it in the workspace.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“They interacted through this global kind of what we call the workspace. So it's actually inspired by the old Blackboard systems where you would have agents that post information on a blackboard, a common blackboard. Is like old very old fashioned AI”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Instead of having kind of a passive network in which you have input that's being processed through these feed forward layers and then there's an output at the end, that perception is really a dynamic process, you know, where our eyes are moving around and they're getting information and that information is feeding back to what we look at next influences what we look at next and how we look at it. And so copycat was trying to do that kind of simulate that kind of idea where you have these Agents is kind of an agent based system, and you have these agents that are picking things to look at and deciding whether they were interesting or not, whether they should be looked at more, and that would influence other agents.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So, the view is that analogy is not just this kind of reasoning technique where we go, you know, shoe is to foot, glove is to what? These kinds of things that we have on IQ tests or whatever, but that it's much deeper, it's much more pervasive in everything we do, in every language, our thinking, our perception. So he had a view that was a very active perception idea so the idea was that”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“It's a program that makes analogies in an idealized domain, idealized world of letter strings. So as you say, 30 years ago, wow. So I started working on it when I started grad school in 1984. Dates me. And it's based on Doug Hofsteder's ideas about that analogy is really a core aspect of thinking. Remember, he has a really nice quote in the book by himself and Emmanuel Sander called Surfaces and Essences. I don't know if you've seen that book, but it's about analogy. And he says, without concepts, there can be no thought and without analogies, there can be no concepts.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, that we don't need, there's no sort of innate stuff that has to get built in This is, you know, it's because it's a hard problem. I personally, you know, I'm very sympathetic to the cognitive science side because that's kind of where I came in to the field. I've become more and more sort of an embodiment. Adherent saying that, you know, without having a body. It's going to be very hard to learn what we need to learn about the world.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I don't know if these different views are not necessarily mutually exclusive. And I think people like Jan Lacun. Agrees with the developmental psychology. Causality intuitive physics, et cetera. But he still thinks that it's learning, like end-to-end learning is the way to go.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Can't necessarily learn that there are objects in the world So there's just a lot of pieces of the puzzle that people are promoting. With different opinions of how important they are and how close we are to being able to put them all together to create general intelligence.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. Then there's people pushing different things, or there's the people, the causality people who say, you know, deep learning as it's formulated today, completely lacks any notion of causality. And that's dooms it. And therefore, we have to somehow give it some kind of notion of causality. Lot of Push from the more cognitive science crowd sane. We have to look at developmental learning. We have to look at how babies learn. We have to look at intuitive physics. All these things we know about physics. And as somebody kind of quipped, we also have to teach machines intuitive metaphysics, which means like objects exist. Causality exists These things that maybe we're born with. I don't know. That they don't have, the machines don't have any of that. You know, they look at a group of pixels and maybe they get 10 million examples, but they”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Right. So I think from what I understand, Jan Lacun is. Rightly saying supervised learning is not sustainable. We have to figure out how to do unsupervised learning, that that's going to be the key. I think that's probably true. I think unsupervised learning is going to be harder than people think. I mean, the way that we humans do it. Then there's the opposing view, you know, the Gary Marcus kind of hybrid view where deep learning is one part, but we need to bring back kind of these symbolic approaches and combine them. Of course, no one knows how to do that very well.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Sort of almost at the hugely accelerating part of the exponential. And by in the next 30 years, we're going to see super intelligent AI and all that. And we'll be able to upload our brains and that. So there's that kind of extreme view that most, I think most people who work in AI don't have. Disagree with that. But there are people who are. Maybe aren't singularity people, but they do think that the current approach of deep learning is going to scale and is going to kind of go all the way, basically. Take us to true AI or human level AI or whatever you want to call it. And there's quite a few of them. And a lot of them A lot of the people I met who work at. Big tech companies in AI groups kind of have this view that we're really not that far, you know.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, they're all over the place. So there's kind of the singularity, transhumanism group. I don't know exactly how to characterize that approach. Yeah, the sort of exponential progress we're on”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Certainly possible. One thing that surprised me when I was writing the book was how far apart different people are in the field are on this thing. Their opinion of how far the field has come and what is accomplished and what's going to happen next.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Would be my guess. I think that in The sort of going along in the narrow AI that these current, the current approaches will get better I think there's some fundamental limits to how far they're going to get. I might be wrong, but that's what I think. And there's some fundamental weaknesses that they have that I talk about in the book that just comes from this approach of supervised learning. Requiring Sort of feed forward networks and so on It's just, I don't think it's a sustainable approach to understanding the world.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“A nice unit for predict And it's like that many Fantastic discoveries have to be made. And of course, there's no Nobel Prize in. Not yet.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“And I quoted somebody in my book who said that human level intelligence is 100 Nobel Prizes away. Which I like because it's a nice way to sort of”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, and I don't know how far they really expected to get But I think that, and they're really, you know, Marvin Minsky's super smart guy and very sophisticated thinker. But I think that no one really understands or understood, still doesn't understand. How complicated, how complex. The things that we do are because they're so invisible to us. You know, to us, vision, being able to look out at the world and describe what we see, that's just immediate. It feels like it's no work at all. So it didn't seem like it would be that hard. But there's so much going on unconsciously sort of invisible to us that Think we overestimate It will be to get computers to do it.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I believe as the field matures we will be better, and I think the reason that we've had so much trouble is that we have so little understanding of our own intelligence. So there's the famous story about Marvin Minsky. Assigning computer vision as a summer project to his undergrad students. And I believe that's actually a true story.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, to me it is the most interesting because it's the most complex, I think. It's the most self-aware. It's the only system, at least that I know of, that reflects on its own intelligence.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I think that it's a fantastic time to be in the field because there's so many questions and so much we don't understand. There's so much work to do.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I don't know. I mean, I think intelligence is a continuum. And I think that the ability to, in some sense, have intention, have a goal, have a... Some kind of self awareness is part of it. So I'm not sure if, you know, it's hard to know where to draw that line. I think that's kind of a mystery. But I wouldn't say that, say, that, you know. The planets orbiting the Sun is an intelligent system. I would find that maybe not the right term to describe that. And this is, you know, there's all this debate in the field of like, what's the right way to define intelligence? What's the right way to model intelligence? Should we think about computation? Should we think about dynamics? Should we think about free energy and all of that stuff?”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I don't know if I would say any system like that has intelligence. But I guess what I want to, I don't have a good enough definition of intelligence to say that.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think that's what drives me particularly. I'm Really interested in human intelligence. But I'm also interested in the sort of the phenomenon of intelligence more generally. And I don't think humans are the only thing with intelligence. Or even animals. But I think intelligence. Concept that encompasses a lot of complex systems. And if you think of things like insect colonies or cellular processes or the immune system or all kinds of different biological or even societal processes have as an emergent property some aspects of what we would call intelligence. You know, they have memory, they process information, they have goals, they accomplish their goals, et cetera. To me, the question of what is this thing? Was really fascinating to me and exploring it using computers seemed to be a good way to approach the question.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“That's a really good question, and I have wondered about that. I myself was driven by curiosity about my own thought processes and thought it would be fantastic to be able to get a computer to mimic some of my thought processes. I'm not sure why we're so driven. I think. We want to Understand ourselves better And we also want machines to do things for us. But I don't know, there's something more to it because it's so deep in the kind of mythology or the ethos of our species. And I don't think other species have this drive. So I don't know.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“They feel would usurp their humanity. And I think maybe it's a generational thing also. Maybe our children or our children's children will be adapted. They'll adapt to these new devices that can do all these tasks and say, yes, this thing is smarter than me in all these areas, but that's great because it helps me.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So, in the book, I talk about my former PhD advisor, Douglas Hofstadter, who encountered a music generation program. And that was really the line for him, that if a machine could create beautiful music, that would be. Terrifying for him because that is something he feels is really at the core of what it is to be human, creating beautiful music, art, literature. I don't think He doesn't like the fact that Machines can Recognize spoken language really well. Like he doesn't, he personally doesn't like using speech recognition, but I don't think it bothers him to his core because it's like, okay, that's not at the core of humanity. But it may be different for every person what really...”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, I'm not sure we can define intelligence that way because smarter than is. With respect to what computers are already smarter than us in some areas. They can multiply much better than we can. They can figure out Driving routes to take much faster and better than we can. They have a lot more information to draw on. They know about traffic conditions and all that stuff. So for any given particular task, sometimes computers are much better than we are. And we're totally happy with that, right? I'm totally happy with that. I don't bother me at all. I guess the question is which things about our intelligence would we Feel very sad or upset that machines had been able to recreate.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“If I had to bet on it, I would say, no, we do have to understand our own minds, at least to some significant extent. But I think that's a really big open question. I've been very surprised at how far kind of brute force approaches based on, say, big data and huge networks can take us. I wouldn't have expected that. they have nothing to do with the way our minds work. So that's been surprising to me, so I could be wrong.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Hard to predict, but I don't see any reason why we couldn't, in principle Create something that we would consider intelligent. I don't know how we will know for sure. Maybe our own view of what intelligence is will be refined more and more until we finally figure out what we mean when we talk about it. But I think eventually we will create machines in a sense that have intelligence. They may not be the kinds of machines we have now. And one of the things that that's going to produce is making us sort of understand our own machine-like qualities that we, in a sense, Are mechanical in the sense that like cells, cells are kind of mechanical. They have algorithms, they process information by. And somehow out of this mass of cells, we get this emergent property that we call intelligence. But underlying it is...”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yes, I think we're closer to having a better. Idea of what that line is. Early on, for example, a lot of people thought that playing chess would be Couldn't play chess if you didn't have sort of general human level intelligence. And of course, once computers were able to play chess better than humans, that revised that view. And people said, okay, well, maybe now we have to revise what we think of intelligence as. And so that's kind of been a Theme throughout the history of the field is that once a machine can do some task. We then have to look back and say, oh, well, that changes my understanding of what intelligence is because I don't think that machine is intelligent. At least that's not what I want to call intelligence.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“People have been struggling with this for the whole history of the field. Defining exactly what it is that we're talking about. You know, John Searle had this distinction between strong AI and weak AI. And weak AI could be general AI, but his idea was strong AI was the view that a machine is actually thinking. That as opposed to Simulating thinking or Carrying out Processes that we would call intelligent.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think it's hard to draw lines like that When I was coming out of grad school in 1990, which is when I graduated, that was during one of the AI winters. I was advised to not put AI, artificial intelligence on my CV, but instead call it intelligence systems. So that was kind of a euphemism, I guess.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, cognitive has certain associations with it and people like to separate things like cognition and perception, which I don't actually think are separate, but often people talk about cognition as being different from sort of other aspects of intelligence. It's sort of higher level.”
2019-12-28 · Lex Fridman Podcast · Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI · IDENTIFIED FROM THE TRANSCRIPT · source