YouSaid · the spoken record

Douglas Lenat

lines on the record: 176
first: 2021-09-15
most recent: 2021-09-15
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

“But no, no, so what you bring up is this really important point of like well, how do you handle Exceptions and inconsistencies, and so on. And one of the hardest lessons for us to learn, it took us about five years to really grit our teeth and learn to love it is we had to give up global consistency. So the knowledge base can no longer be consistent. So this is a kind of scary thought. I grew up watching Star Trek.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Police the system to make sure that we're saying things as generally as we possibly can. So you don't want to say things like no mouse is also a moose because if you said things like that, then you'd have to add another one or two or three zeros onto the number of assertions you'd actually have to have. So at some point, we generalize things more and more and we get to a point where we say, oh yeah, for any two biological taxons, if we don't know explicitly that one is a generalization of another, then almost certainly they're disjoint. A member of one is not going to be a member of the other and so on.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Something like that. Or another thing we look for are contradictions, things which can't both be true. And we say to like, what is it that we know that causes us to know that both of these can't be true at the same time? For instance, in one of the weekly world news editions, in one article it talked about how Elvis was cited, you know, even though he was getting on in years and so on. And another article in the same one talked about people seeing Elvis' ghost. So it's like, why do we believe that at least one of these articles, you know, must be wrong and so on. So we have a series of techniques like that that enable our people. And by now, we have about 50 people working full-time on this and have for decades. So we've put in the thousands of person years of effort. We've built up these tens of millions of rules. We constantly”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Thing we sometimes look at is sort of like fake news or sort of humorous onion headlines or headlines in The Weekly World News, if you know what that is, or the National Inquirer, where it's like, oh, we don't believe this, then we introspect on why don't we believe it. So there are things like B17 lands on the moon. You know, it's like, why don't we, what do we know about the world that causes us to believe that that's just silly?”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Between one sentence and the next one. What are all the things that the writer expected you to fill in and infer occurred between the end of one sentence and the beginning of the other? So like if the sentence says Fred Smith robbed the third national bank period, he was sentenced to 20 years in prison period. Well, between the first sentence and the second, you're expected to infer things like Fred got caught, Fred got arrested, Fred went to jail, Fred had a trial, Fred was found guilty, and so on. If my next sentence starts out with something like the judge dot dot dot, then you assume it's the judge at his trial. If my next sentence starts out something like the arresting officer dot dot dot, you assume that it was the police officer who arrested him after he committed the crime and so on. So those are two techniques for getting that knowledge.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“That basically covered the resources needed. And then we had to devise a method to actually figure out Well, what are the tens of millions of things that we need to tell the system? And for that, we've found a few techniques which worked really well. One is to take any piece of text almost. It could be an advertisement, could be a transcript, it could be a novel, it could be an article. And don't pay attention to the actual type that's there, the black space on the white page. Pay attention to the complement of that, the white space, if you will. So what did the writer of this sentence assume that the reader already knew about the world? For instance, if they used a pronoun, how did they figure out that why did they think that you would be able to understand what the intended referent of that pronoun was? If they used an ambiguous word, how did they think that you would be able to figure out what they meant by that word? The other thing we look at is the gap.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“And being brittle, they're now resting on this massive pyramid, if you will, this massive lattice of common sense knowledge so that when things go wrong, when something unexpected happens, they can fall back on more and more and more general principles, eventually bottoming out in things like, for instance, if we have a problem with the microphone, one of the things you'll do is unplug it, plug it in again and hope for the best, right? Because that's one of the general pieces of knowledge you have in dealing with electronic equipment or software systems or Things like that”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Sort of not all of human knowledge, but the things that you assume other people know, the things you count on other people knowing. And so by now we've done that. And the good news is since you've waited 38 years just about to talk to me, we're about at the end of that process. So most of what we're doing now is not putting in even what you would consider common sense, but more putting in domain specific application specific knowledge about Healthcare in a certain hospital or about oil pipes getting clogged up or whatever the applications happen to be. So we've almost come full circle and we're doing things very much like the expert systems of the 1970s and the 1980s except instead of resting on nothing.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“That all of us were off by an order of magnitude. That it turns out what you need are tens of millions of these pieces of knowledge about every day, sort of like if you have a coffee cup with stuff in it and you turn it upside down, the stuff in it's going to fall out. So you need tens of millions of pieces of knowledge like that, even if you take trouble to make each one as general as it possibly could be. But the good news was that thanks to initially the fifth generation effort and then later US government agency funding and so on, we were able to get enough funding not for a couple person centuries of time, but for a couple person millennia of time, which is what we've spent since 1984 getting Psych to contain the tens of millions of rules that it needs in order to really capture and span”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“And I got the opportunity thanks to my friend Woody Bledsoe, who was one of the people who founded that to come and be its principal scientist. And he said, you know, and he sent Admiral Bob Inman, who was the person running MCC, came and talked to me and said, look, Professor, you know, you're talking about doing this project. It's going to involve person centuries of effort. You've only got a handful of graduate students. You do the math. It's going to take you like longer than the rest of your life to finish this project. But if you move to the wilds of Austin, Texas, we'll put 10 times as many people on it. And, you know, you'll be done in a few years. And so that was pretty exciting. And so I did that. I took my leave from Stanford. I came to Austin. I worked for MCC. And the good news and bad news, the bad news is...”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“And what it said was, Hey, all you big American companies, that's also how you know it was a long time ago, because they were American companies rather than multinational companies. Hey, all you big American companies, normally it would be an antitrust violation if you colluded on R&D, but we promise for the next 10 years we won't prosecute any of you if you do that to help combat this threat. And so overnight the first two consortia, research consortia in America sprang up. Both of them coincidentally in Austin, Texas, one called Semitech focusing on hardware chips and so on, and then one called MCC, the Microelectronics and Computer Technology Corporation, focusing on more on software, on databases and AI and natural language understanding and things like that.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“1980s, there was something called the Japanese fifth generation computing effort. Japan had threatened to do in computing and AI and hardware what they had just finished doing in consumer electronics on the automotive industry, namely resting control away from the United States and more generally away from the West. And so America was scared and Congress did something, that's how you know it was a long time ago because Congress did something. Congress passed something called the National Cooperative Research Act, NCRA.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Another person said, Well, let's actually look at one single short one-volume desk encyclopedia article. And so we'll look at what was like a four paragraph article or something. I think about Greeb's. Grebes are a type of waterfowl. And if we were going to sit there and represent every single thing that was there, how many assertions or rules or statements would we have to write in this logical language and so on and then multiply that by all of the number of articles that there were and so on? So all of these estimates came out with a million. And so if you do the math, it turns out that like, oh, well, then maybe in something like a hundred person years in one or two person centuries, we could actually get this written down by hand. And a marvelous coincidence, opportunity existed right at that point in time.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“And one person got the answer by saying, well, look, you can only burn into human long-term memory a certain number of things per unit time, like maybe one every 30 seconds or something. Other than that, it's just short term memory and it flows away like water and so on. So by the time you're, say, 10 years old or so, how many things could you possibly have burned into your long-term memory? And it's like about a million. Another person went in a completely different direction and said, well, if you look at the number of words in a dictionary, not a whole dictionary, but for someone to essentially be considered to be fluent in a language, how many words would they need to know and then about how many things about each word would you have to tell it? And so they got to a million that way.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I think Ed Feigenmum was there. I think Josh Litterberg was there. So we have all these different smart people and we came together to address the question that you raised, which is if it's important to represent common sense knowledge and world knowledge in order for AIs to not be brittle, in order for AIs not to just have the veneer of intelligence, well, how many pieces of common sense, how many if-then rules, for instance, would we have to actually write in order to essentially cover what people expect perfect strangers to already know about the world? And I expected there would be an enormous divergence of opinion and computation. But amazingly, everyone got an answer which was around a million.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So let's leave the efficiency question aside for now. So how does all this information get represented in logical form so that these algorithms, resolution theorem proving and other algorithms can actually grind through all the logical consequences of what you said? And that ties into your question about how many of these things do you need? Because if the answer is small enough, then by hand you could write them out one at a time. So in the 1984, I held a meeting at Stanford, where I was a faculty member there, where we assembled about half a dozen of the smartest people I know, people like Alan Newell and Marvin Minsky and Alan Kay and a few others.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Yes. Okay. So now we have three things to talk about. We'll keep adding more. Although it's okay. The first and the third are related.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“And secondly, how can you then efficiently run these algorithms to actually get the information you need in the case of the case? 10 hours or 10,000 years of computation. And those are both really important questions.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So, how can you do it at all is something that philosophers have grappled with, and fortunately philosophers a hundred years ago and even earlier developed a kind of formal language like English. It's called predicate logic or first order logic or something like predicate calculus and so on. So there's a way of representing things in this formal language, which Enables a mechanical procedure to sort of brind through and algorithmically produce all of the same logical entailments, all the same logical conclusions that you or I would from that same set of pieces of information that are represented that way. So that sort of raises a couple questions. One is how do you get all this information from say observations and English and so on into this logical form?”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“So let's tease apart two different tasks, really, both of which are incredibly important and even necessary if you're going to have this in a usable, usable fashion as opposed to, say, like library books sitting on a shelf and so on, where the knowledge might be there, but if a fire comes, the books are going to burn because they don't know what's in them and they're just going to sit there while they burn. So there are two aspects of using the knowledge. One is a kind of a theoretical, how is it possible at all? And then the second aspect of what you said is how can you do it quickly enough?”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“But the point is that there's almost no telling what little bits of knowledge about the world you might actually need in some situations which were unforeseen.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“You really need to draw on common sense. For instance, my wife and I were driving recently and there was a trash truck in front of us. And I guess they had packed it too full and the back exploded and trash bags went everywhere. And we had to make a split second decision. Are we going to slam on our brakes? Are we going to swerve into another lane? Are we going to just run it over because there are cars all around us? And in front of us was a large trash bag and we know what we throw away in trash bags. It's probably not a safe thing to run over on the left was a bunch of fast food restaurant trash bags. And it's like, oh, well, those things are just like styrofoam and leftover food. We'll run over that. And so that was a safe thing for us too. Now that's the kind of thing that's going to happen maybe once in your life.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Human, you could also say things like why, or how might you be wrong about this, or something like that. And the person would answer you. And it might be a little annoying if you have a small child and they keep asking why questions in series. Eventually you get to the point where you throw up your hands and say, I don't know, it's just the way the world is. But for many layers, you actually have that layered solid foundation of support so that when you need it, you can count on it. And when do you need it? Well, when things are unexpected, when you come up against a situation which is novel, for instance, when you're driving, it may be fine to have a small program, a small set of rules that cover 99% of the cases, but that 1% of the time when something strange happens.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“Think of understanding more like a think of it more like the ground you stand on, which could be very shaky, could be very unsafe, but most of the time is not because underneath it is more ground. And eventually rock and other things. But layer after layer after layer, that solid foundation is there. And you rarely need to think about it. You rarely need to count on it, but occasionally you do. And I've never used this analogy before, so bear with me. But I think the same thing is true in terms of getting computers to understand things, which is you ask a computer question, for instance, Alexa or some robot or something, and maybe it gets the right answer. But if you were asking that of a”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“We're doing sort of like when you get a dog to fetch your morning newspaper, the dog might do that successfully, but the dog has no idea what a newspaper is or what it says or anything like that”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source
“I was a faculty member in the computer science department at Stanford. My colleagues and I did research in all sorts of artificial intelligence. Programs. So natural language understanding programs, robots, expert systems, and so on. And we kept hitting the very same brick wall. Our systems would have impressive early successes. And so if your only goal was academic, namely to get enough material to write a journal article, that might actually suffice. But if you're really trying to get AI, then you have to somehow get past the brick wall. On the brick wall was the programs didn't have what we would call common sense. They didn't have general world knowledge. They didn't really understand what they were doing, what they were doing. What they were saying, what they were being asked. And so very much like a clever dog performing tricks, we could get them to do tricks, but they never really understood what they were doing.”
2021-09-15 · Lex Fridman Podcast · #221 – Douglas Lenat: Cyc and the Quest to Solve Common Sense Reasoning in AI · IDENTIFIED FROM THE TRANSCRIPT · source