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

“Yes, so let me first give you an anecdote, and then I'll answer your question. So there's a search engine you've probably never heard of called Northern Light. It went out of business, but the way it worked, it was a kind of vampiric search engine. And what it did was it didn't index. The internet at all. All it did was it negotiated and got access to data from the big search engine companies about what query was typed in. And where the user ended up being happy and actually then they type in a completely different query unrelated query and so on. So it just went from query to the web page that seemed to satisfy them eventually.”
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 you're able to represent and reason with these much, much, much more complicated expressions that go way, way beyond what simple three word or forward English sentences are, which is really what the semantic web can represent and really what knowledge graphs can represent.”
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
“Very nicely using these kinds of graph structures or using something like the semantic web and so on. But the problem is that Very often, what you want to be able to express. Takes a lot more than three words and a lot more than simple graph structures like that to represent. So for instance, if you've read or seen Romeo and Juliet, I could say to you something like, Remember when Juliet drank the potion that put her into a kind of suspended animation, when Juliet drank that potion, what did she think that Romeo would think when he heard from someone that she was dead? And you could basically understand what I'm saying. You could understand the question. You could probably remember the answer was, well, she thought that this friar would have gotten a message to Romeo saying that she was going to do this, but the friar didn't”
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, think of the semantic web as a kind of knowledge graph, and Google already has something they call knowledge graph, for example, which is sort of like a node and link diagram. So you have these nodes that represent concepts or words or terms, and then there are some arcs that connect them that might be labeled. And so you might have a node with like one person that represents one person. Let's say a husband link that then points to that person's husband. And so there'd be then another link that went from that person labeled wife that went back to the first node and so on. So having this kind of representation is really good if you want to represent binary relations, essentially relations between two things. And so if you have the equivalent of like three word sentences or something like that, you can represent 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
“Works and why things are the way they are, they weren't able to give explanations of their answer. It's one thing to use a machine learning system that says this is what you should, you know, I think you should get this operation and you say why. And it says, you know, 0.83. And you say, no, in more detail, why? And it says 0.831. That's not really very compelling and that's not really very helpful”
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 so we got hold of her chart and we put in her case, and it came up with exactly the same diagnoses and exactly the same therapy recommendations, but the difference was because it was a knowledge-based system, a rule-based system, it was able to tell us step by step, by step why this was the diagnosis. And step by step why this was the best therapy and the best procedure to do for her and so on. And there was a real epiphany because that made all the difference in the world. Instead of blindly having to trust in authority, we were able to understand what was actually going on. So at that time, I realized that that really is what was missing in computer programs was that even if they got things right, because they didn't really understand the way the world”
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
“If you know nothing, you can really learn nothing. You can appear to learn. So I'll also anecdotes, I could go back and give you about why I feel so strongly about this personally. Was in 1980-81. My daughter Nicole was born and she's actually doing fine now. But when she was a baby, she was diagnosed as having meningitis. And doctors wanted to do all these scary things. And my wife and I were very worried and we could not get a meaningful answer from her doctors about exactly why they believed this, what the alternatives were, and so on. And fortunately, a friend of mine, Ted Shortliff, was another assistant professor in computer science at Stanford at the time, and he'd been building a program called Meissen, which was a medical diagnosis program that happened to specialize in blood infections like meningitis. And so he had privileges at Stanford Hospital because he was also an M.”
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 know, it's one of these things where, yes, it may be helpful most of the time. It may even be correct most of the time, but if it doesn't really understand what it's saying and if it doesn't really understand why things are true and doesn't really understand how the world works, then some fraction of the time it's going to be wrong. Now, if your only goal is to sort of find relevant information, like search engines do, then being right 90% of the time is fantastic. That's unbelievably great. Okay, however, if your goal is to save the life of your child who has some medical problem or your goal is to be able to drive for the next 10,000 hours of driving without getting into a fatal accident and so on, then error rates down at the 10% level or even the 1% level are not really acceptable.”
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
“If you go to Siri, and I think I have, you know, where can I go for help with my alcohol problem or something? It'll come back and say, I found seven liquor stores near you 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
“Sort of a core to start this process, it never really takes off. And so that's why I view this as a pump priming exercise to get a big enough, manually produced, even though that's kind of ugly duckling technique Put in the elbow grease to produce a large enough core that you will be able to do all the kinds of things you're imagining without sort of ending up with the kind of wacky brittlenesses that we see, for example, in GPT-3 where you'll tell it a story about someone putting a poison, plotting to poison someone and so on. And then GPT-3 says, you say, what's the very next sentence? The next sentence is, oh, yeah, that person then drank the poison they just put together. It's like that's probably not what happened for someone.”
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, that is, in fact, one of our goals is how can we harness machine learning? How can we harness natural language processing to increasingly automate the knowledge acquisition process, the growth of Psych. And that's what I meant by priming the pump That if you sort of learn things at the fringe of what you know already. You learn this new thing is similar to what you know already, and here are the differences and the new things you had to learn about it, and so on. So the more you know, the more and more easily you can learn new things. But unfortunately, inversely, if you don't really know anything, and it's really hard to learn anything. And so if you're not careful, if you start out with two.”
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
“About that, and not like think about why that might have been the case, and what else would be the case if that were true, and so on, and then suggest things back to the right brain to quickly check out again. So it's that kind of synergy back and forth, which I think is really what's going to lead to general AI not narrow brittle machine learning systems and not just something like Psych.”
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
“Say, by the way, did they have slightly elevated levels of bioactive vitamin D in their blood and so on? And if the answer is no, that strongly disconfirms your whole causal chain. And if the answer is yes, that's somewhat confirms that causal chain. And so using that, we were able to take these correlations from this GOAS database and we were able to essentially focus the doctors, focus the researchers' attention on the very small percentage of correlations that had some explanation and even better some explanation that also made some independent prediction that they could confirm or disconfirm by looking at the data. So think of it like this kind of synergy where you want the right brain machine learning to quickly come up with possible answers. You want the left brain cyclic AI to think”
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
“Exactly. The important thing, even more than that, is you shouldn't really trust that 20-step Rube Goldberg chain any more than you trust that initial A to Z correlation, except two things. One, if you can't even think of one causal chain to explain this, then that correlation probably was just noise to begin with. And secondly, and even more powerfully, along the way that causal chain will make predictions like the one about having more bioactive vitamin D in your blood. So you can now go back to the data about these patients.”
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 we say, okay, let's use all this public knowledge and common sense knowledge about what reactions occur where in the human body, what polymerizes what, what catalyzes what reactions, and so on. And let's try to put together a 10 or 20 or 30-step causal explanation of why that mutation might have caused that medical condition. And so Psych would put together, in some sense, some Rube Goldberg-like chain. Would say, Oh, yeah, that mutation, if it got expressed, would be this altered protein, which because of that, if it got to this part of the body, would catalyze this reaction. And by the way, that would cause more bioactive vitamin D in the person's blood. And anyway, 10 steps later, that screws up bone resorption, and that's why this person got osteoporosis early in life 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
“To bring them into the hospital. So now you can do correlation studies, machine learning studies of which mutations are associated with and led to which physiological problems and diseases and so on, like getting arthritis and so on. And the problem is that those correlations turned out to be very spurious. They turned out to be very noisy. Very many of them have led doctors onto wild goose chases and so on. And so they wanted a way of eliminating or the bad ones or focusing on the good ones. And so this is where psych comes in, which is psych takes those sort of A to Z correlations between point mutations and medical condition that needs treatment.”
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
“Machine learning to think quickly, but you want the ability to think deeply even if it's a little slower. So I'll give you an example of a project we did recently with NIH involving the Cleveland Clinic and a couple other institutions that we ran project for. And what it did was it took Guas's genome-wide association studies. Those are sort of big databases of patients that came into a hospital. They got their DNA sequenced because the cost of doing that has gone from infinity to billions of dollars to hundreds of dollars or so. And so now patients routinely get their DNA sequenced. So you have these big databases of the SNPs, the single nucleotide polymorphisms, the point mutations in a patient's DNA, and the disease that 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
“I think of machine learning work as more or less what our right brain hemispheres do. So being able to take a bunch of data and recognize patterns, being able to statistically infer things and so on. I certainly wouldn't want to not have a right brain hemisphere. But I'm also glad that I have a left-frain hemisphere as well, something that can metaphorically sit back and puff on its pipe and think about this thing over here. It's like, why might this have been true? What are the implications of it? How should I feel about that and why and so on? Thinking more deeply and slowly, what Kahneman called thinking slowly versus thinking quickly, whereas you want”
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
“Exactly. And it makes more or less anyone able to be a teacher in that way. So that's part of the answer. And then the other is that the system on its own will be able to, through reading, through conversations with other people and so on, learn the same way that you or I or other humans do.”
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
“Given everything I already know, and if any of these seven things were true, I would have come up with the answer you just gave me instead of the wrong answer I came up with. Is one of these seven things true. And then you, the expert, will look at those seven things and say, oh, yeah, number five is actually true. And so, without actually having to tinker down at the level of logical assertions and so on, you'll be able to educate the system in the same way that you would help educate another person who you were trying to apprentice or something 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
“But if someone were to walk into the room right now and they were dripping wet, we would immediately look outside to say, oh, did it start to rain or something like that? Why did we say maybe it started to rain? That's not a sound logical inference, but it's certainly a reasonable abductive leap to say, well, one of the most common ways that a person would have gotten dripping wet is if they had gotten caught out in the rain or something like that. So what does that have to do with what we were talking about? So suppose you're building one of these applications and the system gets some answer wrong and you say, oh, yeah, the answer to this question is this one, not the one you came up with. Then what the system can do is it can use everything it already knows about common sense, general knowledge, the domain you've already been telling it about and context, like we talked about and so on and say, well, here are seven alternatives, each of which I believe 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
“Capture tools, knowledge, testing tools, and so on. Think of them as like user interface suite of software tools if you want, something that will help people to more or less automatically expand and extend the system in areas where, for instance, they want to build some app, have it do some application or something like that. So I'll give you an example of one, which is something called abduction. So you've probably heard of deduction and induction and so on, but abduction is unlike those. Abduction is not sound. It's just useful. So for instance, Deductively, if someone is out in the rain and they're going to get all wet and when they enter a room, they might be all wet and so on. That's deduction”
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 we have, in fact, two directions we're pushing on very, very heavily currently at SciCore, and one involves natural language understanding and the ability to read what people have explicitly written down and to pull knowledge in that way. But the other is to build a series of knowledge editing tools, knowledge entry tools, 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
“Perform this by definition because Because those pieces of elided, of omitted information, of those missing steps, as it were, are pieces of common sense. If you actually included all of them, it would almost be offensive or confusing to the reader. It's like, why are they telling me all these stuff? Of course I know that all these things. And so it's one of these things which almost by its very nature. Has almost never been explicitly written down anywhere because by the time you're old enough to talk to other people and so on, if you survived to that age, presumably you already got pieces of common sense. Like, you know, if something causes you pain whenever you do it, probably not a good idea to keep doing it.”
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
“Everyone can have their own Alexa or Siri or Google Assistant or whatever. Everyone will have this sort of cradle to grave assistant, which will get to know you, which you'll get to trust. It'll model you. You'll model it. And it'll call to your attention things which will, in some sense, make your life better, easier, less mistake ridden, and so on, less regret ridden if you listen to it.”
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
“Agree. I think that The main thing that AI prostheses, AI amplifiers will do for people is make it easier, maybe even unavoidable for them to do good, critical thinking. So pointing out logical fallacies, logical contradictions, and so on in things that they otherwise would just blithely believe, pointing out essentially data which they should take into consideration if they really want to learn the truth about something and so on. So I think doing not just educating in the sense of pouring facts into people's heads, but educating in the sense of arming people with the ability to do good critical thinking is enormously powerful. The education system that we have in the US and worldwide generally don't Do a good job of that. But I believe that the AI as well. The AIs can and will in the same way 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
“The other problem with the internet is that it has enabled us to surround ourselves with an echo chamber, with a bubble of like-minded people, which means that you can have truly bizarre theories, conspiracy theories, fake news, and so on promulgate and surround yourself with people who essentially reinforce what you want to believe or what you already believe about the world. In the old days, that was much harder to do when you had, say, only three TV networks or even before when you had no TV networks and you had to actually like look at the world and make your own reasoned decisions.”
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
“These sorts of dependencies on technology. And overall, I think that having smarter individuals and having smarter AI augmented human species will be one of the few ways that we'll actually be able to overcome some of the global problems we have involving poverty and starvation and global warming and overcrowding, all the other problems that are besetting the planet. We really need to be smarter. And there are really only two routes to being smarter. One is through biochemistry and genetics engineering. The other route is through having general AIs that augment our intelligence and hopefully one of those two Ways of paths to salvation will come through before it's too late.”
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's right. If you read a book about how to make butter, that's not the same as if you had to learn it and do it yourself.”
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 so on. Today, people don't really understand numbers. They don't really understand math. They don't really estimate very well at all. And so on. They don't really understand the difference between trillions and billions and millions and so on very well because calculators do that all for us. things like the internet and search engines that same kind of juvenilism is reinforced in making people essentially be able to live their whole lives not just without being able to do arithmetic and estimate but now without actually having to really know almost anything because anytime they need to know something they'll just go and look it up”
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'll give you the other side, which is that almost nothing has done more harm than something like the internet and access to that information in two ways. One is it's made people more globally ignorant in the same way that calculators made us more or less innumerate. So when I was growing up, we had to use slide rules. We had to be able to estimate.”
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 that means that humanity as a species will be smarter. And when was the last time that any invention qualitatively made a huge difference in human intelligence? You have to go back a long ways. It wasn't like the internet or the computer or mathematics or something. It was all the way back to the development of language. We sort of look back on pre-linguistic cavemen as well. They weren't really intelligent, were they? They weren't really human, were they. And I think that, as you said, 50, 100, 200 years from now, people will look back on people today right before the advent of the sort of lifelong general AI muses and say, you know, those poor people, they weren't really human, were they?”
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
“Then people will become smarter. It's not so much that it'll be us versus the AIs. It's more like us and the AIs together. We'll be able to do things that require more creativity, that would take too long right now, but we'll be able to do lots of things in parallel. We'll be able to misunderstand each other less. There's all sorts of value that effectively for an individual would mean that individual will, for all intents and purposes, be smarter.”
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
“Path upward that we get from, for instance, talking with each other. That's why humans today know so much more than humans 100,000 years ago. We're not really that much smarter than people were 100,000 years ago, but there's so much more knowledge and we have language and we can communicate. We can check things on Google and so on. So effectively we have this enormous power at our fingertips. And there's almost no limit to how much you could learn if you wanted to because you've already gotten to a certain level of understanding of the world that enables you to read all these articles and understand them, that enables you to go out and if necessary do experiments, although that's slower as a way of gathering data and so on. And I think this is really an important point, which is if we have artificial intelligence, real general artificial intelligence, human level artificial intelligence.”
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
“Even if it isn't, so to speak, everything you need, it's primed the knowledge pump enough that psyche can now itself help to learn more and more automatically on its own by reading things and understanding and occasionally asking questions like a student would or something and by doing experiments and discovering things on its own and so on. So through a combination of psych power discovery and psych-powered reading, it will be able to bootstrap itself. Maybe it's the final 2%, maybe it's the final 99%. So even if I'm wrong, all I really need to build is a system which has primed the pump enough that it can begin that cascade upward, that self-reinforcing sort of quadratically or maybe even exponentially increasing.”
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 I think I'm right enough. And let me explain what I mean by that, which is. Sometimes, like, if you have an old fashioned pump, you have to prime the pump. And then eventually it starts. So I think I'm right enough in the sense that. What we've built.”
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 for the first several years, I would have said that it was on the order of one or two million. And so it took us about five or six years to realize that we were off by a factor of 10”
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 would say assertions. Assertions or rules. Because I'm not talking about rigid rules, but rules of thumb. But assertions is a nice one that covers all of these things.”
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
“Exactly. That's what I meant about ferreting out the unstated things in text. What are all the things that were assumed? And so those are things like if you have a problem with something turning it off and on often fixes it for reasons we don't really understand and we're not happy about or people can't be both alive and dead at the same time or water flows downhill. If you search online for water flowing uphill and water flowing downhill, you'll find more references for water flowing uphill because it's used as a kind of metaphorical reference for some unlikely thing because of course everyone already knows that water flows downhill. So why would anyone bother saying 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 want to distinguish between what you think of as facts and the kind of things that we represent. So we map to and essentially make sure that psych has the ability to, as it were, read and access the kind of facts you might find, say, in Wikidata or stated in a Wikipedia article or something like that. So what we're representing, the things that we need a small number of tens of millions of, are more like rules of thumb, rules of good guessing, things which are usually true and which help you to make sense of the facts that are sort of sitting off in some database or some other more static story.”
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
“By the way, I should mention Marvin wouldn't do his estimate until someone brought him an envelope so that he could literally do a back of the envelope calculation to come up with his number.”
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 need to about objects in our world. And that was one of the things which they never were able to overcome. And I think that was one of the main reasons that that project failed.”
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
“Could only have one parent node. So if you had a table that was a wooden object, a black object, a flat object, and so you had to choose one, and that's the only parent it could have. When, of course, depending on what it is you need to reason about it, sometimes it's important to know that it's made out of wood. Like if we're talking about a fire, sometimes it's important to know that it's flat if we're talking about resting something on it and so on. One of the problems was that they wanted a kind of dewey decimal numbering system for all of their concepts, which meant that each node could only have at most 10 children and each node could only have one parent. And while that does enable the Dewey decimal type numbering of concepts, labeling of concepts, it prevents you from representing all the things”
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 definitely have to think of it as a graph. So we could talk about, for instance, why the Japanese fifth generation computing effort failed. There were about half a dozen different reasons. One of the reasons they failed was because they tried to represent knowledge as a tree rather than as a graph. And so each node in their representation.”
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
“of the things that are true in a broad, let's say, a century or a millennium or something like that. Things that are true in Austin, Texas are generally going to be a specialization of things that are true in Texas, which is going to be a specialization of things that are true in the United States and so on. And so you don't have to say things over and over again at all these levels. You just say things at the most general level that it applies to, and you only have to say it once, and then it essentially inherits to all these more specific contexts.”
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 it's good you asked that question because you're pointed in the right direction, which is you want contexts to be first class objects in your system's knowledge base, in particular in Sykes knowledge base. By first class object, I mean that we should be able to have psych think about and talk about and reason about one context or another context the same way it reasons about coffee cups and tables and people and fishing and so on. And so contexts are just terms in its language, just like the ones I mentioned. And so psych can reason about context. Context can arrange hierarchically and so on. And so you can say things about let's say things that are true in the modern era, things that are true in a particular year would then be a subcontext.”
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
“Things that are true in one person's belief system, but false in another person's belief system. Things that are true at one level of abstraction and false at another, for instance, at one level of abstraction, you think of this table as a solid object. But down at the atomic level, it's mostly empty space 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
“And so by the time you move, say, 20 contexts over, there could be glaring inconsistencies. So eventually you get from the normal modern real-world context that we're in right now to something like Roadrunner cartoon context where physics is very different. And in fact, life and death are very different because no matter how many times he's killed, you know, the coyote comes back in the next scene and so on. So that was a hard lesson to learn and we had to make sure that our representation language, the way that we actually encode the knowledge and represent it, was expressive enough that we could talk about things being true in one context and false in another, things that are true at one time and false in another, things that are true, let's say, in one region like one country but false in another.”
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
“When you're talking to someone in Australia, you don't think of them as being oriented upside down to you when you're planning a trip, you know, even if it's a thousand miles away, you may think a little bit about time zones, but you rarely think about the curvature of the Earth and so on. And for most purposes, you can live your whole life without really worrying about that because the Earth is locally flat. In much the same way, the psychology base is divided up into almost like tectonic plates which are individual contexts and each context is more or less consistent, but there can be small inconsistencies at the boundary between one context and the next one 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
“And anytime a computer was inconsistent, it would either freeze up or explode or take over the world or something bad would happen. Or if you come from a mathematics background, once you can prove false, you can prove anything. So that's not good and so on. That's why old knowledge-based systems were all very, very consistent. But the trouble is that by and large our models of the world the way we talk about the world and so on, there are all sorts of inconsistencies that creep in here and there that will sort of kill some attempt to build some enormous globally consistent knowledge base. And so what we had to move to was a system of local consistency. So a good analogy is you know that the surface of the earth is more or less spherical. Globally, but you live your life every day as though the surface of the earth were flat.”
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