Garry Kasparov: Chess, Deep Blue, AI, and Putin | Lex Fridman Podcast #46

The following is a conversation with Garry Kasparov. He is considered by many to be the greatest chess player of all time. From 1986 until his retirement in 2005, he dominated the chess world, ranking world number one for most of those 19 years. While he has many historical matches against human chess players, in the long arc of history, he may be remembered for his match against the machine, IBM's Deep Blue. His initial victories and eventual loss to Deep Blue captivated the imagination of the world, of what role artificial intelligence systems may play in our civilization's future. That excitement inspired an entire generation of AI researchers, including myself, to get into the field. Garry is also a pro-democracy political thinker and leader, a fearless human rights activist, and author of several books, including How Life Imitates Chess, which is a book on strategy and decision making, Winter is Coming, which is a book articulating his opposition to the Putin regime, and Deep Thinking, which is a book on the role of both artificial intelligence and human intelligence in defining our future. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Garry Kasparov. As perhaps the greatest chess player of all time, when you look introspectively at your psychology throughout your career, what was the bigger motivator, the love of winning or the hatred of losing? Tough question. I have to confess, I never heard it before, which is, again, congratulations, it's quite an accomplishment. Losing was always painful. For me, it was almost like a physical pain because I knew that if I lost the game, it's just because I made a mistake. I always believed that the result of the game had to be decided by the quality of my play. Okay, you may say it sounds arrogant, but it helped me to move forward because I always knew that there was room for improvement. Was there the fear of the mistake? Actually, fear of mistake guarantees mistakes. And the difference between top players and the very top is that it's the ability to make a decision without predictable consequences. You don't know what's happening. It's just intuitively, I can go this way or that way. And there are always hesitations. People are like, you are just at the crossroad. You can go right, you can go left, you can go straight, you can turn and go back. And the consequences are just very uncertain. You have certain ideas what happens on the right or on the left, or just if you go straight, but it's not enough to make well-calculated choice. And when you play chess at the very top, it's about your inner strength. So I can make this decision, I will stand firm, and I'm not going to waste my time because I have full confidence that I will go through. Now, going back to the original question is, I would say neither. It's just it's love for winning, hate for losing. They were important elements, psychological elements. But the key element, it's the, I would say the driving force was always my passion for making a difference. It's just, I can move forward and I can always enjoy not just playing, but creating something new. Creating something new. How do you think about that? It's just finding new ideas in the openings, some original plan in the middle game. Actually, that helped me to make the transition from the game of chess where I was on the very top to another life where I knew I would not be number one. I would not be necessarily on the top, but I could still be very active and productive by my ability to make the difference by influencing people, say, joining the democratic movement in Russia or talking to people about human-machine relations. There's so many things where I knew my influence may not be as decisive as in chess, but still strong enough to help people to make their choices. So you can still create something new that makes a difference in the world outside of chess. But wait, you've kind of painted a beautiful picture of your motivations to chess, to create something new, to look for those moments of some brilliant new ideas. But were you haunted by something? So you make it seem like to be at the level you're at, you can get away without having demons, without having fears, without being driven by some of the darker forces. I mean, you sound almost religious, you know, darker forces, spiritual demons. I mean, do you have a call for a priest? That's what I'm guessing. Yeah. Now, let's go back to these crucial chess moments where I had to make big decisions. As I said, it was all about my belief from very early days that I can make all the difference by playing well or by making mistakes. So yes, I always had an opponent across the chessboard, opposite me. But no matter how strong the opponent was, whether just an ordinary player or another world champion like Anatoly Karpov, having all respect for my opponent, I still believe that it's up to me to make the difference. And I knew I was not invincible. I made mistakes. I made some blunders. And with age, I made more blunders. So I knew it. But it's still very much for me to be decisive factor in the game. I mean, even now, look, my latest chess experience was horrible. I mean, I played Fabio Caruana, this number two, number two, number three player in the world these days. We play this 960 with the so-called Fischer random chess, reshuffling pieces. Yeah, I lost very badly, but it's because I made mistakes. I mean, I had so many winning positions. I mean, 15 years ago, I would have crushed him. And while I lost, I was not so much upset. I mean, I know, as I said in the interview, I can fight any opponent, but not my biological clock. So it's fighting time is always a losing proposition. But even today at age 56, I knew that I could play great game. I couldn't finish it because I didn't have enough energy or just I couldn't have the same level of concentration. But in a number of games where I completely outplayed one of the top players in the world, I mean, it gave me a certain amount of pleasure. That is, even today, I haven't lost my touch. Not the same, you know, okay, the jaws are not as strong and the teeth are not as sharp, but I could get him just, you know, almost, you know, on the ropes. You still got it. Still got it. And it's, you know, and it's, I think it's my wife said it well. I mean, she said, look, Gary, it's somehow, it's not you just fighting your biological clock. It's just, you know, maybe it's a signal because, you know, the goddess of chess, since you spoke, right? Yeah. The goddess of chess, Keisha, maybe she didn't want you to win because, you know, if you could beat number two, number three player in the world, I mean, that's one of the top players who just recently played a world championship match. If you could beat him, that would be really bad for the game of chess. But just what people will say, oh, look, the game of chess, you know, it's not making any progress. The game is just, you know, it's totally devalued because, look, the guy coming out of retirement, you know, just, you know, winning games. Maybe that was good for chess, not good for you, but it's, look, I've been following your logic. We should always look for, you know, demons, you know, superior forces and other things that could, you know, if not dominate our lives, but somehow, you know, play a significant role in the outcome. Yeah. So the goddess of chess had to send a message. Yeah. Okay. So Gary, you should do something else. Time. Now for a question that you have heard before, but give me a chance. You've dominated the chess world for 20 years, even still got it. Is there a moment you said you always look to create something new? Is there games or moments where you're especially proud of in terms of your brilliance of a new creative move? You've talked about Mikhail Tal as somebody who was aggressive and creative chess player in your own game. Look, you mentioned Mikhail Tal. It's very aggressive, very sharp player, famous for his combinations and sacrifices, even called magician from Riga. So for his very unique style, but any world champion, you know, it's, yeah, was a creator. Some of them were so flamboyant and flash like Tal. Some of them were, you know, just, you know, less discerned at the chess board like Tigran Petrosyan, but every world champion, every top player brought something into the game of chess. And each contribution was priceless because it's not just about sacrifices. Of course, amateurs, they enjoy, you know, the brilliant games where pieces being sacrificed. It's all just, you know, it's all piece of hanging. And it's all of a sudden, you know, being material down, rook down or just, you know, queen down, the weaker side delivers the final blow and just, you know, mating opponent's king. But there are other kinds of beauty. I mean, it's a slow positional maneuvering, you know, looking for weaknesses and just gradually strangling your opponent and eventually delivering sort of a positional masterpiece. Yeah. So I think I made more difference in the game of chess than I could have imagined when I started playing. And the reason I thought it was time for me to leave was just, I mean, I knew that I was no longer in the position to bring the same kind of contribution, the same kind of new knowledge into the game. So, and going back, I could immediately look at my games against Anatoly Karpov. It's not just I won the match in 1985 and became world champion at age 22, but there were at least two games in that match. Of course, the last one, game 24, that was decisive game of the match, I won and became world champion. But also the way I won, it was a very sharp game and I found a unique maneuver that was absolutely new and it became some sort of just a typical now. Though just when the move was made on the board and put on display, a lot of people thought it was ugly. And another game, game 16 in the match, where I just also managed to outplay Karpov completely with black pieces, just paralyzing his entire army in its own camp. Technically or psychologically, it was a mix of both in game 16. Yeah, I think it was a big blow to Karpov. I think it was a big psychological victory for a number of reasons. One, the score was equal at a time and the world champion, by the rules, could retain his title in case of a tie. So, before game 16, we have nine games to go. And also it was some sort of a bluff because neither me nor Karpov saw the refutation of this opening idea. And I think it's just for Karpov, it was double blow because not that he lost the game, it was a triple blow. He lost the game, it was a brilliant game and I played impeccably after just this opening bluff. And then they discovered that it was a bluff. So, again, I didn't know, I was not bluffing. So, that's why it happens very often. Some ideas could be refuted. And it's just what I found out, and this is, again, going back to your spiritual theme is that you could spend a lot of time working. And when I say you could, it's in the 80s, in the 90s. It doesn't happen these days because everybody has a computer. You could immediately see if it works or it doesn't work. Machine shows your refutation in a split of a second. But many of our analysis in the 80s or in the 90s, they were not perfect simply because we're humans and you analyze the game, you look for some fresh ideas. And then just it happens that there was something that you missed because the level of concentration at the chessboard is different from one that when you analyze the game, just moving the pieces around. But somehow, if you spend a lot of time at the chessboard preparing, so in your studies, with your coaches, hours and hours and hours, and nothing of what you found had materialized on the chessboard. Somehow, these hours helped. I don't know why, always helped you. It's as if the amount of work you did could be transformed into some sort of spiritual energy that helped you to come up with other great ideas during the board. Again, even if there was no direct connection between your preparation and your victory in the game, there was always some sort of invisible connection between the amount of work you did, your dedication to actually to, and your passion to discover new ideas, and your ability during the game at the chessboard when the clock was ticking, we still had ticking clock, not digital, not digital clock at the time. So to come up with some brilliance. And I also can mention many games from the 90s. So obviously, all amateurs would pick up my game against Veselin Topalov in 1999 and V. Gonzay, again, because it was a brilliant game. The Black King traveled from its own camp to into White's camp across the entire board. It doesn't happen often, trust me, as you know, in the games of professional players, top professional players. So that's why visually, it was one of the most impressive victories. But I could bring to our attention many other games that were not so impressive for amateurs, not so beautiful, just sacrifice always beautiful, you sacrifice pieces. And then eventually you have so very few resources left, and you use them just to crush your opponent, basically, you have to make the king because you have almost nothing left at your disposal. But I, you know, I, up to the very end, get less and less, but still up to the very end, I always had games with some sort of, you know, interesting ideas and games that gave me great satisfaction. But I think it's what happened from 2005 up to these days was also a very, very big accomplishment, since, you know, I had to find myself to sort of relocate myself. Yeah, rechannel the creative energies. Exactly. And to find something where I feel comfortable, even confident that my participation still makes the difference. Beautifully put. So let me ask perhaps a silly question, but sticking on chess for just a little longer. Where do you put Magnus Carlsen, the current world champion in the list of all-time greats? In terms of style, moments of brilliance, consistency? It's a tricky question. You know, the moment you start ranking world champions, Yeah, you lose something? It's the, I think it's not fair because it's the, any new generation knows much more about the game than the previous one. So when people say, oh, Gary was the greatest, Fischer was the greatest, Magnus was the greatest, it disregards the fact that the great players of the past, whether Lasky or Capelplanc, Alokian, I mean, they knew so little about chess by today's standards. I mean, today, just any kid, you know, that spent a few years, you know, with his or her chess computer knows much more about the game simply just because you have access to this information. And it has been discovered generation after generation. We added more and more knowledge to the game of chess. It's about the gap between the world champion and the rest of the field. So it's the, now, if you look at the gap, then probably Fischer, you know, could be on top, but very short period of time, then you should also add a time factor. Yeah. I was on top, not as big as Fischer, but much longer. So, and also, unlike Fischer, I succeeded in beating next generation. Yeah. Here's the question. Yeah. Let's see if you still got the fire, speaking of the next generation, because you did succeed beating the next generation. Next, it's close. Okay. Anand, short, Anand, the sheer of, Kramnik is already 12 years younger. So that's a neck, that's, but still yet I, I competed with them and I just, I beat most of them and I was still dominant when I left at age 41. So back to Magnus. Magnus, I mean, consistency is phenomenal. The reason Magnus is, is on top and it's, seems unbeatable today. Magnus is, is a lethal combination of Fischer and Karpov, which is very, it's very unusual because Fischer style was very dynamic, just fighting to the last point, I mean, just using every resource available. Karpov was very different. It's just, he had an unparalleled ability to use the, every piece with a maximum effect, just its minimal resources always produce maximum effect. So now imagine that you merge these two styles. So it is, it's, it's like, you know, it's squeezing every stone for a drop of water, but, but doing it, you know, just, you know, for 50, 60, 70, 80 moves. I mean, Magnus could go on as long as Fischer with all his passion and energy, and at the same time being as meticulous and, and, and, and, and deadly as, as, as Karpov by just, you know, using every little advantage. So, and he has good, you know, very good health. It's important. I mean, physical conditions are, by the way, very important. So a lot of people don't recognize it. There are later studies shows that chess players burn thousands of calories during the game. So that puts him on the top of this field of the world champions. But again, it's, it's the discussion that is, I saw recently in internet, whether Garry Kasparov of his peak, let's say late eighties, could beat Magnus Carlsen today. I mean, it's totally irrelevant because Garry Kasparov in 1989, okay, played great chess, but still I knew very little about chess compared to Magnus Carlsen in 2019, who, by the way, learned from me as well. So that's why, yeah, I'm extremely cautious in making any judgment that involves, you know, time gaps. You ask, you know, soccer fans. So who is your favorite, Pelé, Maradona or Messi? Yeah. Who's your favorite? Messi. Messi. Why? Because... Maybe Maradona, maybe. No, because you're younger, but that's simple. Your instinctive answer is correct because you saw, you didn't see Maradona in action. I saw all of them in action. So that's why, but since, you know, when I was, you know, just following it, you know, just it's Pelé and Maradona, they were just, you know, they were big stars and it's Messi's already just, I was gradually losing interest in other things. So I remember Pelé in 1970, the final match, Brazil-Italy. So that's the first World Cup soccer I watched. So that's the, and actually my answer when I just, you know, because I was asked this question as well. So I say that it's just, while it's impossible to make a choice, I would still probably go with Maradona for a simple reason. The Brazilian team in 1970 could have won without Pelé. It was absolutely great. Still could have won, maybe, but it is, the Argentinian team in 1986 without Maradona would not be unified. So this is, and Messi, he still hasn't won a title. That's, that's, could argue for that for an hour, but you could say, if you ask Maradona, if you look in his eyes, especially let's say Garry Kasparov in 1989, he would have said, I was sure as hell would beat Magnus Carlsen. Yeah, just simply because- The confidence, the fire. Simply because, again, it's just, they saw me in action. So this, again, it's the age factor is important. Therefore, with the passion and energy and being equipped with all modern ideas, but again, then you make a very just important assumption that you could empower Garry Kasparov in 89 with all ideas that have been accumulated over 30 years. That would not be Garry Kasparov, that would be someone else. Because again, I belong to 1989. I was way ahead of the field and I beat Karpov several times in the world championship matches and I crossed 2,800, which by the way, if you look at the, in rating, which is just, it's, even today, so this is the rating that I retire. So this is, it's still, it's just, it's a top two, two, three. So that's, that's Karwan and Dink, it's about the same rating now. And I crossed 2,800 in 1990. We're just, you look at the inflation. When I crossed 2,800 in 1990, there was only one player in 2,700 category, Anatoly Karpov. Now we had more than 50. So just, when you see this, so if you add inflation, so I think my 2,851, it could probably, could be more valuable as Magnus 2,882, which was his highest rating. But anyway, again, too many hypotheticals. You're lost to IBM DBlue in 1997. In my eyes, that is one of the most seminal moments in the history. Again, I apologize for being romanticizing the notion, but in the history of our civilization, because humans, as a civilization, for centuries saw chess as, you know, the peak of what man can accomplish, of intellectual mastery, right? And that moment when a machine could beat a human being was inspiring to just an entire, anyone who cares about science, innovation, an entire generation of AI researchers. And yet, to you that loss, at least if reading your face, seemed like a tragedy, extremely painful, like you said, physically painful, why? When you look back at your psychology of that loss, why was it so painful? Were you not able to see the seminal nature of that moment? Or was that exactly why it was that painful? As I already said, losing was painful, physically painful. And the match I lost in 1997 was not the first match I lost to a machine. It was the first match I lost, period. That's... Oh, wow. Oh, wow. Right. That makes all the difference to me. First time I lost. Now, I lost, and the reason I was so angry that I just, I had suspicions that my loss was not just the result of my bad play. So, though I played quite poorly, just when you started looking at the games today, I made tons of mistakes. But I had all reasons to believe that there were other factors that had nothing to do with the game of chess. And that's why I was angry. But look, it was 22 years ago. It's more than the bridge. We can analyze this match and this is with everything you said. I agree with probably one exception. Is that considering chess as the sort of, as a pinnacle of intellectual activities, was our mistake. Because we just thought, oh, it's a game of the highest intellect. And it's just, you have to be so intelligent. And you could see things that the ordinary mortals could not see. It's a game. And all machines had to do in this game is just to make fewer mistakes, not to solve the game. Because the game cannot be solved. I mean, according to Koval Shannan, the number of legal moves is 10 to the 46th power. Too many zeros, just for any computer to finish the job, you know, in the next few billion years. But it doesn't have to. It's all about making fewer mistakes. And I think that's this match actually. And what's happened afterwards with other games, with Go, with Shogi, with video games. It's a demonstration that it's the machines will always beat humans in what I call closed systems. The moment you build a closed system, no matter how the system is called, chess, Go, Shogi, Dota, machines will prevail simply because they will bring down number of mistakes. Machines don't have to solve it. They just have to, the way they outplay us, it's not by just being more intelligent. It's just by doing something else. But eventually, it's just, it's capitalizing on our mistakes. And I think that's the way it's capitalizing on our mistakes. When you look at the chess machines ratings today, and compare this to Magnus Carlsen, it's the same as comparing Ferrari to Usain Bolt. The gap is, I mean, by chess standards is insane. 34, 3,500 to 2,800, 2,850 on Magnus. It's like difference between Magnus and an ordinary player from an open international tournament. It's not because machine understanding is better than Magnus Carlsen, but simply because it's steady. Machine has steady hand. And I think that is what we have to learn from 1997 experience, and from further encounters with computers and sort of the current state of affairs with AlphaZero, beating other machines. The idea that we can compete with computers in computers in so-called intellectual fields, it was wrong from the very beginning. By the way, the 1997 match was not the first victory of machines over- Over grandmasters. Over grandmasters. No, actually, I played against first decent chess computers from late 80s. So, I played with the prototype of Deep Blue called Deep Thought in 1989, two rapid chess games in New York. I won handily both games. We played against new chess engines like Fritz and other programs. And then it was Israeli program Junior that appeared in 1995. Right, right, right. I remember. Yeah. So, there were several programs. I lost a few games in Blitz. I lost one match against the computer chess engine in 1994, rapid chess. So, I lost one game to Deep Blue in 1996 match, the match I won. Some people tend to forget about it that I won the first match. Yes. But we made a very important psychological mistake thinking that the reason we lost Blitz matches, five minutes games, the reason we lost some of the rapid chess matches, 25 minutes chess, because we didn't have enough time. If you play a longer match, we will not make the same mistake. Nonsense. So, yeah, we had more time, but we still make mistakes. And machine also has more time. And machines will always be steady and consistent compared to humans' instabilities and inconsistencies. And today we are at the point where, yes, nobody talks about humans playing against machines. Now, machines can offer handicap to top players and still you know, will be favored. I think we're just learning that it's no longer human versus machines. It's about human working with machines. That's what I recognized in 1998, just after leaking my wounds and spending one year and just, you know, ruminating so what's happened in this match. And I knew that though we still could play against the machines. I had two more matches in 2003, playing both deep free and deep junior. Both matches ended as a tie. Though these machines were not weaker, at least, probably stronger than deep blue. And by the way, today, chess app on your mobile phone is probably stronger than deep blue. I'm not speaking about chess engines that are so much superior. And by the way, when you analyze games we played against deep blue in 1997 on your chess engine, they'll be laughing. And it also shows that's how chess changed because chess commentators, they'll look at some of our games like game four, game five, brilliant idea. Now you ask Stockfish, you ask Houdini, you ask Commodore, all the leading chess engines. Within 30 seconds, they will show you how many mistakes both Gary and deep blue made in the game that was trumpeted as a great chess match in 1997. Well, okay. So you've made an interesting, if you can untangle that comment. So now in retrospect, it was a mistake to see chess as the peak of human intellect. Nevertheless, that was done for centuries. So- By the way, in Europe, because you move to the far East, they will go, they had- Right, but games, games. Again, some of the games like board games. Yeah, I agree. So if I push back a little bit, so now you say that, okay, but it was a mistake to see chess as the epitome. And then now there's other things maybe like language, like conversation, like some of the things that in your view is still way out of reach of computers, but inside humans. Do you think, can you talk about what those things might be? And do you think just like chess that might fall soon with the same set of approaches, if you look at alpha zero, the same kind of learning approaches as the machines grow in size? No, no, it's not about growing in size. It's about, again, it's about understanding the difference between closed system and open-ended system. So you think that key difference, so the board games are closed in terms of the rules, the actions, the state space, everything is just constrained. You think once you open it, the machines are lost? Not lost, but again, the effectiveness is very different because machine does not understand the moment it's reaching territory of diminishing returns. To put it in a different way, machine doesn't know how to ask right questions. It can ask questions, but it will never tell you which questions are relevant. So it's like about the, it's a direction. So I think it's in human-machine relations we have to consider our role. And many people feel uncomfortable that the territory that belongs to us is shrinking. I'm saying, so what? Eventually we'll belong to the last few decimal points, but it's like having a very powerful gun and all you can do there is slightly alter the direction of the bullet, maybe 0.1 degree of this angle. But that means a mile away, 10 meters of target. So that's, we have to recognize that is a certain unique human qualities that machines in a foreseeable future will not be able to reproduce. And the effectiveness of this cooperation, collaboration depends on our understanding what exactly we can bring into the game. So the greatest danger is when we try to interfere with machine superior knowledge. So that's why I always say that sometimes you'd rather have, by reading this pictures in radiology, you may probably prefer an experienced nurse than, rather than having top professor, because she will not try to interfere with machines understanding. So it's very important to know that if machines knows how to do better things in 95%, 96% of territory, we should not touch it because it's happened. It's like in chess, recognize, they do it better. See where we can make the difference. You mentioned AlphaZero. I mean, AlphaZero, it's actually a first step into what you may call AI, because everything that's being called AI today, it's just, it's one or another variation of what Claude Shannon characterized as a brute force. It's a type A machine, whether it's Deep Blue, whether it's Watson, and all these things, the modern technologies that are being trumpeted as AI, it's still brute force. It's the, all they do, it's they do optimization. It's this, they are, they keep improving the way to process human generated data. Now, AlphaZero is the first step towards machine produced knowledge, which is, by the way, it's quite ironic that the first company that championed that was IBM. Oh, it's in backgammon. Interesting. Yes. You just, you should, you should, you should look at IBM. It's a new gammon. It's the, it's the scientist, he's still working at IBM. They had an early nineties. It's the, it's the, it's the program that played in all the AlphaZero types. So just trying to come up with own strategies, but because of success of Deep Blue, this project had been not abandoned, but just, it wasn't, it was put on calls. And now we just, it's, it's, it's, it's, it's, everybody talks about, about this, the machines generated knowledge. So as revolutionary, and it is, but there's still, you know, many open-ended questions. Yes. AlphaZero generates its own data. Many ideas that AlphaZero generated in chess were quite intriguing. So I, I, I looked at these games with, not just with interest, but with, you know, it's, it was quite exciting to learn how machine could actually, you know, juggle all the pieces and just play positions with a broken material balance, sacrificing material, always being ahead of other programs, you know, one or two moves ahead by, by foreseeing the consequences, not over calculating because machines, other machines were at least as powerful in calculating, but it's having this unique knowledge based on discovered patterns. After playing 60 million games. Almost something that feels like intuition. Exactly. But there's one problem. Now, a simple question. If, if AlphaZero faces superior point, let's say another powerful computer accompanied by a human who could help just to discover certain problems, because I already, I look at many AlphaZero games. I visited their lab, you know, spoke to Demis Kasabis at his team. And I, I know there's certain weaknesses there. Now, if these weaknesses are exposed, then the question is how many games will it take for AlphaZero to correct it? The answer is hundreds of thousands. Even if it keeps losing, it's this, because the whole system is based. So it's now, imagine, so this is, you can have a human by just making a few tweaks. So humans are still more flexible. And, and as long as we recognize what is, what is our role, where we can play sort of, so the most valuable part in this collaboration. So it's, it will help us to understand what are the next steps in human machine collaboration. Beautifully put. So let's talk about the thing that machines certainly don't know how to do yet, which is morality. Machines and morality. It's another question that, you know, just it's, it's, it's being asked all the time these days. And I, I think it's another phantom that is haunting a general public because it's just being fed with this, you know, illusions is that how can we avoid machines, you know, having bias, being prejudices. You cannot, because it's like looking in the mirror and complaining about what you see. If you have certain bias in the society, machine will, will just follow it. It's just, it's, it's, you know, you look at the mirror, you don't like what you see there. You can, you know, you can break it, you can try to distort it, or you can try to actually change something. Just by yourself. By yourself. Yes. So it's, it's very important to understand is this, is that you cannot expect machines to, to improve the yields of our society. And moreover, machines will simply, you know, just, you know, amplify. Yes. Yeah. But the thing is, people are more comfortable with other people doing injustice, with, with being biased. We're not comfortable with machines having the same kind of bias. So that's a, that's an interesting standard that we play some machines with autonomous vehicles. They have to be much safer with automated systems. Of course, of course, they're much safer. Statistically, they're much safer than, than. It's not of course. Why would they, it's not of course. It's, it's not given. Autonomous vehicles, you have to work really hard to make them safer. I, I, I think it just, it goes without saying, is the, the outcome of the, of this, I wouldn't call it competition, but comparison is very clear. But the problem is not about being, you know, safer. It's the 40,000 people or so every year died in car accidents in the United States. And it's, it's statistics. One accident with, with autonomous vehicle and it's front page of a newspaper. Yes. So it's, it's, again, it's about psychological. So it's, while people, you know, kill each other in car accidents because they make mistakes, they make more mistakes. For me, it's, it's, it's not a question. Of course, we make more mistakes because we're human. Yes. Machines also, and by the way, no machine will ever reach a hundred percent perfection. That's another, that's another important fake story that, that, that, that is being fed to the public. If machine doesn't reach a hundred percent performance is not safe. No. All you can ask any computer, whether it's, you know, playing chess or, or doing the stock market calculations or driving your autonomous vehicle, it's to make fewer mistakes. And yes, I know it's not, you know, it's not easy for us to accept because, ah, if, you know, if you have two humans, you know, colliding in their cars, okay, it's like, if one of, one of these cars is autonomous vehicle. And by the way, even if it's human's fault, terrible. How could you allow a machine to, to, to, to run without a driver at the wheel? So, you know, let's linger that for a second, that double standard, the way you felt with your first loss against Deep Blue, were you treating the machine differently than you would have a human? So what do you think about that difference between the way we see machines and humans? No, it's the, at that time, you know, for me, it was a match and that's why I was angry because I believe that the match was not, you know, fairly organized. So it's, it's, ah, definitely there weren't fair advantages for, for IBM and I want to play there another match, like a rubber match. So your anger or displeasure was aimed more like at the humans behind IBM versus the actual pure algorithm. Yes, absolutely, absolutely. Look, I mean, I, I knew at the time, and by the way, I was, objectively speaking, I was stronger at that time. So that's, that probably added to my anger because I knew I could beat the machine. Yeah. Yeah, so that's, and that's the, and that's, I lost, and I knew I was not well prepared. So, because they, I have to give them credit, they did some good work, ah, from 1996 and I, but I still could beat the, beat the machine. So I made too many mistakes. Also, this is the whole, it's this, the publicity around the match. So I, I underestimated the effect, you know, just it's, and, and being called the, you know, the, the, the brain's last stand, you know, it's okay. No, no, no pressure. Okay. Well, let me ask. Ah, so I was born also in the Soviet Union. What lessons do you draw from the rise and fall of the Soviet Union in the 20th century? When you just look at this nation that is now look, pushing forward into what Russia is. If you look at the long arc of history of the 20th century, what do we take away? What do we take away from that? I think the lesson of history is clear. Ah, undemocratic systems, totalitarian regimes, systems that are based on controlling their citizens and just, ah, every aspect of their life, not offering opportunities to, for private initiative, central planning systems, they doomed. They just, you know, they, they cannot be driving force for innovation. So they, in, in the history timeline, I mean, they could cause certain, you know, distortion of, of, of, ah, the concept of progress. Ah, they, by the way, they may call themselves progressive, but we know that is this, the damage that they caused to, to humanity is just, it's, it's, it's yet to be measured. But at the end of the day, they fail. They fail and it's, ah, and the end of the Cold War was a great triumph of the free world. It's not that the free world is perfect. It's very important to recognize the fact that, I always like to mention, you know, one of my favorite books, The Lord of the Rings, that the, there's no, there's no absolute good, but there is an absolute evil. Good, you know, comes in many forms, but we all, you know, it's being humans or being even, you know, humans from fairy tales or just some sort of mythical creatures. It's the, eh, you can always find, ah, spots on the sun. So this is, you're conducting war and just, and, and, and fighting for justice. There are always things that, you know, can be easily criticized and human history is the, is a never ending quest for perfection. Ah, but we know that there is absolute evil. We know it's, for me, it's now clear that it's, I mean, it's, nobody argues about Hitler being absolute evil, but I think it's very important to recognize Stalin was absolute evil. Communism caused more damage than any other ideology, ah, in the 20th century. And unfortunately, while we all know that fascism was condemned, but there was no Nuremberg for common communism. And that's why we could see, you know, still is the, ah, the successors of Stalin are feeling far more comfortable. And you, you as one of them. You highlight a few interesting connections actually between Stalin and Hitler. I mean, they're, they're in, in terms of the, ah, adjusting or clarifying the, the history of World War II, which is very interesting. Of course, we don't have time. So let me ask. You can ask it. I just, I just recently delivered a speech in Toronto, ah, at 80th anniversary of Molotov-Ribbentrop Pact. It's something that I believe, you know, just, you know, has must, must be taught in the schools that the World War II, ah, ah, had been started by two dictators by signing these, these, ah, criminal, criminal treaty collusion of two tyrants in August 1939 that led to the beginning of the World, World War II. And the fact is that eventually Stalin had no choice but to join allies because Hitler attacked him. So it just doesn't, you know, ah, ah, eliminate the fact that Stalin helped Hitler to start World War II. And he was one of the beneficiaries at early, at early stage by, ah, annexing, ah, part of Eastern Europe. And as a result of the World War II, he annexed almost entire Eastern Europe. And for many Eastern European nations, the end of the World War II was the beginning of, of communist occupation. So Putin, you've talked about as a man who stands between Russia and democracy, essentially today, you've been a strong opponent and critic of Putin. Let me ask again, how much does fear enter your mind and heart? So in 2007, there's this interesting comment from Oleg Kalugin, KGB general. He said that, I do not talk details. People who knew them are all dead now because they were vocal. I'm quiet. There's only one man who's vocal and he may be in trouble. World chess champion Kasparov. He has been very outspoken in his attacks on Putin. And I believe he's probably next on the list. So clearly your life has been, and perhaps continues to be in danger. How do you think about having the views you have, the ideas you have, being in opposition as you are in this kind of context when your life could be in danger? Ah, that's the reason I live in New York. So it's the, was not my first choice, but I knew I had to leave Russia at one point. And among other places, New York is the safest. Is it safe? No. I mean, it's just, it's the, I know what happens, what happened, what is happening with many of Putin's enemies. But at the end of the day, I mean, what can I do? I mean, it's, I, I could be very proactive by trying to change things I can influence, but here are a way of facts. I, I cannot stop doing what I've been doing for a long time. It's the right thing to do. I grew up, you know, with my family teaching me sort of the wisdom of Soviet dissidents, do what you must and so be it. I could try to be cautious by not traveling to certain places where, you know, my security could be at risk. There's so many invitations to speak at different locations in the world. And I have to say that many countries are just now, are not destinations that I can afford to travel. My mother still lives in Moscow. I meet her a few times a year. She was devastated when I had to leave Russia because since my father died in 1971, so she was 33 and she dedicated her entire life to her only son. But she recognized in just a year or so since I left Russia that it was the only chance for me to continue my normal life. So just to, I mean, to be relatively safe and to, to do what she taught me to do, to make the difference. Do you think you will ever return to Russia or let me ask a different way, when? Oh, I'm sure. It will be sooner than many people think because I think Putin's regime is facing insurmountable difficulties. And again, I read enough historical books to know that dictatorships, they, they end suddenly. It's just on Sunday, dictator feels comfortable. He believes he's popular on Monday morning. He's bust. The good news and bad news. I mean, the bad news is that I don't know when and how Putin rule ends. The good news, he also doesn't know. Okay. Well put. Let me ask a question that seems to preoccupy the American mind from the perspective of Russia. One, did Russia interfere in the 2016 US election government sanction and future to will Russia interfere in the 2020 US election? And what does that interference look like? It's very old. You know, we had such an intelligent conversation and, and you are ruining everything by asking such a stupid question. It's been going downhill the entire way. Yeah, but it's, it's, it's, it's, it's insulting for my intellect. Okay. Of course they did interfere. Of course they did absolutely everything to elect Trump. I mean, they said it many times. It is just, you know, I met enough KGB colonels in my life to tell you that, you know, just the way Putin looks at Trump. This is the way, looks, and I don't have to hear what he says, what Trump says, you know, just, I don't need to go through congressional investigations. The way Putin looks at Trump is the way the KGB officers looked at the assets. It's just, and following to 2020, of course they will do absolutely everything to help Trump to survive because I think the damage that Trump's reelections could cause to America and to the free world, it's just, it's beyond one's imagination. I think basically if Trump is reelected, he will ruin NATO because he's already heading in this direction, but now he's just, he's still limited by the reelection hurdles. If he's still in the office after November, 2020, okay, January, 2021, I don't want to think about it. My problem is not just Trump because Trump is basically, it's a symptom, but the problem is that I don't see, it's just, it's the, in American political horizon, politicians who could take on Trump for all damage that he's doing for the free world, not just things that happened, that went wrong in America. So there's the, it seems to me that the campaign, political campaign on the democratic side is fixed on certain important, but still secondary issues. Because when you have the foundation of the Republic in jeopardy, I mean, you cannot talk about healthcare. I mean, understand how important it is, but it's still secondary because the entire framework of American political life is at risk. And you have Vladimir Putin just, it's having, unfortunately, free hands by attacking America and other free countries. And by the way, we have so much evidence about Russia interfering in Brexit, in elections in almost every European country. And thinking that they will be shy of attacking America in 2020, now with Trump in the office, yeah, I think it's, yeah, it definitely diminishes the intellectual quality of our conversation. I do what I can. Last question. If you can go back, just look at the entirety of your life, you accomplished more than most humans will ever do. If you could go back and relive a single moment in your life, what would that moment be? There are moments in my life when I think about what could be done differently, but- No, experience happiness and joy and pride, just to touch once again. I know, I know, but it's the, look, I made many mistakes in my life. So I just, it's the, I know that at the end of the day, it's, I believe in the butterfly effect. So it's the, I knew moments where I could, moments where I could, now, if I'm there at that point in 89, in 93, pick up a year, I could improve my actions by not doing this stupid thing. But then how do you know that I will have all other accomplishments? Yeah, I just, I'm afraid that we just have to just follow this, if you may call wisdom before it's gump, it's the life is this, it's a box of chocolate and you don't know what's inside, but you have to go one by one. So it's the, I'm happy with who I am and where I am today. And I'm very proud, not only with my chess accomplishments, but that I made this transition. And since I left chess, I built my own reputation that had some influence on the game of chess, but it's not directly derived from the game. I'm grateful for my wife, who helped me to build this life. We actually married in 2005. It was my third marriage. That's why I said I made mistakes in my life. And by the way, I'm close with two kids from my previous marriages. So that's the, I managed to sort of to balance my life. And here, I live in New York. So we have our two kids born here in New York. It's new life and it's busy. Sometimes I wish I could, I could limit my engagement in many other things that are still taking time and energy, but life is exciting. And as long as I can feel that I have energy, I have strengths, I have passion to make the difference, I'm happy. I think that's a beautiful moment to end on. Gary, spasibo, thank you very much for talking today. Thank you.


Leonard Susskind: Quantum Mechanics, String Theory and Black Holes | Lex Fridman Podcast #41

The following is a conversation with Leonard Susskind. He's a professor of theoretical physics at Stanford University and founding director of Stanford Institute of Theoretical Physics. He is widely regarded as one of the fathers of string theory and in general, as one of the greatest physicists of our time, both as a researcher and an educator. This is the Artificial Intelligence Podcast. Perhaps you noticed that the people I've been speaking with are not just computer scientists, but philosophers, mathematicians, writers, psychologists, physicists, and soon other disciplines. To me, AI is much bigger than deep learning, bigger than computing. It is our civilization's journey into understanding the human mind and creating echoes of it in the machine. If you enjoy the podcast, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Leonard Susskind. You worked and were friends with Richard Feynman. How has he influenced you, changed you as a physicist and thinker? What I saw, I think what I saw was somebody who could do physics in this deeply intuitive way. His style was almost to close his eyes and visualize the phenomena that he was thinking about and through visualization, outflank the mathematical, the highly mathematical and very, very sophisticated technical arguments that people would use. I think that was also natural to me, but I saw somebody who was actually successful at it, who could do physics in a way that I regarded as simpler, more direct, more intuitive. And while I don't think he changed my way of thinking, I do think he validated it. He made me look at it and say, yeah, that's something you can do and get away with. Practically, he didn't get away with it. So, do you find yourself, whether you're thinking about quantum mechanics or black holes or string theory, using intuition as a first step or a step throughout using visualization? Yeah, very much so, very much so. I tend not to think about the equations. I tend not to think about the symbols. I tend to try to visualize the phenomena themselves. And then when I get an insight that I think is valid, I might try to convert it to mathematics, but I'm not a natural mathematician. I'm good enough at it. I'm good enough at it, but I'm not a great mathematician. So for me, the way of thinking about physics is first intuitive, first visualization, scribble a few equations maybe, but then try to convert it to mathematics. Experience says that other people are better at converting it to mathematics than I am. And yet, you've worked with very counterintuitive ideas. So how do you- No, that's true, that's true. How do you visualize something counterintuitive? How do you dare? By rewiring your brain in new ways. Yeah, quantum mechanics is not intuitive. Very little of modern physics is intuitive. Intuitive, what does intuitive mean? It means the ability to think about it with basic classical physics, the physics that we evolved with throwing stones, or throwing stones, splashing water, or whatever it happens to be. Quantum physics, general relativity, quantum field theory are deeply unintuitive in that way. But after time and getting familiar with these things, you develop new intuitions. I always said you rewire. And it's to the point where me and many of my friends, I and many of my friends, can think more easily quantum mechanically than we can classically. We've gotten so used to it. I mean, yes, our neural wiring in our brain is such that we understand rocks and stones and water and so on. We sort of evolved for that. Evolved for it. Do you think it's possible to create a wiring of neuron-like state devices that more naturally understand quantum mechanics, understand wave function, understand these weird things? Well, I'm not sure. I think many of us have evolved the ability to think quantum mechanically to some extent. But that doesn't mean you can think like an electron. That doesn't mean, another example, forget for a minute quantum mechanics, just visualizing four-dimensional space or five-dimensional space or six-dimensional space, I think we're fundamentally wired to visualize three dimensions. I can't even visualize two dimensions or one dimension without thinking about it as embedded in three dimensions. If I want to visualize a line, I think of the line as being a line in three dimensions. Or I think of the line as being a line on a piece of paper with a piece of paper being in three dimensions. I never seem to be able to, in some abstract and pure way, visualize in my head the one dimension, the two dimension, the four dimension, the five dimensions, and I don't think that's ever gonna happen. The reason is, I think, our neural wiring is just set up for that. On the other hand, we do learn ways to think about five, six, seven dimensions. We learn ways, we learn mathematical ways, and we learn ways to visualize them, but they're different. And so, yeah, I think we do rewire ourselves. Whether we can ever completely rewire ourselves to be completely comfortable with these concepts, I doubt. So that it's completely natural. To a degree, it's completely natural. So I'm sure there's somewhat, you could argue, creatures that live in a two-dimensional space. Yeah, maybe there are. And, well, it's romanticizing the notion, of course, we're all living, as far as we know, in three-dimensional space, but how do those creatures imagine 3D space? Well, probably the way we imagine 4D, by using some mathematics and some equations and some tricks. Okay, so jumping back to Feynman just for a second, he had a little bit of an ego. Yes. Yes. Well, do you think ego is powerful or dangerous in science? I think both, both, both. I think you have to have both arrogance and humility. You have to have the arrogance to say, I can do this. Nature is difficult, nature is very, very hard. I'm smart enough, I can do it. I can win the battle with nature. On the other hand, I think you also have to have the humility to know that you're very likely to be wrong on any given occasion. Everything you're thinking could suddenly change. Young people can come along and say things you won't understand, and you'll be lost and flabbergasted. So I think it's a combination of both. You better recognize that you're very limited, and you better be able to say to yourself, I'm not so limited that I can't win this battle with nature. It takes a special kind of person who can manage both of those, I would say. And I would say there's echoes of that in your own work, a little bit of ego, a little bit of outside of the box, humble thinking. I hope so. So was there a time where you felt, you looked at yourself and asked, am I completely wrong about this? Oh yeah, about the whole thing or about specific things? The whole thing. What do you mean? Wait, which whole thing? Me and me and my ability to do this thing. Oh, those kinds of doubts. First of all, did you have those kinds of doubts? No, I had different kind of doubts. I came from a very working class background, and I was uncomfortable in academia for a long time. But there weren't doubts about my ability or my, they were, just the discomfort in being in an environment that my family hadn't participated in, I knew nothing about as a young person. I didn't learn that there was such a thing called physics until I was almost 20 years old. So I did have certain kind of doubts, but not about my ability. I don't think I was too worried about whether I would succeed or not. I never felt this insecurity, am I ever gonna get a job? That had never occurred to me that I wouldn't. Maybe you could speak a little bit to this sense of what is academia, because I too feel a bit uncomfortable in it. There's something I can't put quite into words what you have that's not, doesn't, if we call it music, you play a different kind of music than a lot of academia. How have you joined this orchestra? How do you think about it? I don't know that I thought about it as much as I just felt it. Thinking is one thing, feeling is another thing. I felt like an outsider until a certain age when I suddenly found myself the ultimate insider in academic physics. And that was a sharp transition, and I wasn't a young man, I was probably 50 years old. So you were never quite, it was a phase transition, you were never quite in the middle. Yeah, that's right, I wasn't. I always felt a little bit of an outsider. In the beginning, a lot an outsider. My way of thinking was different, my approach to mathematics was different, but also my social background that I came from was different. Now these days, half the young people I meet they're parents or professors. Right. Right, that was not my case. So yeah, but then all of a sudden at some point I found myself at the very much the center of, maybe not the only one at the center, but certainly one of the people in the center of a certain kind of physics. And all that went away, I mean it went away in a flash. So maybe a little bit with Feynman, but in general, how do you develop ideas? Do you work through ideas alone? Do you brainstorm with others? Oh, both, both, very definitely both. The younger time I spent more time with myself. Now, because I'm at Stanford, because I have a lot of ex-students and people who are interested in the same thing I am, I spend a good deal of time, almost on a daily basis, interacting, brainstorming as you said. It's a very important part. I spend less time probably completely self-focused and with a piece of paper and just sitting there staring at it. What are your hopes for quantum computers? So machines that are based on, that have some elements of leveraged quantum mechanical ideas. Yeah, it's not just leveraging quantum mechanical ideas. You can simulate quantum systems on a classical computer. Simulate them means solve the Schrodinger equation for them or solve the equations of quantum mechanics on a computer, on a classical computer. But the classical computer is not doing, is not a quantum mechanical system itself. Of course it is. Everything's made of quantum mechanics, but it's not functioning. It's not functioning as a quantum system. It's just solving equations. The quantum computer is truly a quantum system, which is actually doing the things that you're programming it to do. You want to program a quantum field theory. If you do it in classical physics, that program is not actually functioning in the computer as a quantum field theory. It's just solving some equations. Physically, it's not doing the things that the quantum system would do. The quantum computer is really a quantum mechanical system, which is actually carrying out the quantum operations. You can measure it at the end. It intrinsically satisfies the uncertainty principle. It is limited in the same way that quantum systems are limited by uncertainty and so forth. And it really is a quantum system. That means that what you're doing when you program something for a quantum system is you're actually building a real version of the system. The limits of a classical computer, classical computers are enormously limited when it comes to quantum systems. They're enormously limited because you probably heard this before, but in order to store the amount of information that's in a quantum state of 400 spins, that's not very many, 400 I can put in my pocket, 400 pennies in my pocket. To be able to simulate the quantum state of 400 elementary quantum systems, qubits we call them, to do that would take more information than can possibly be stored in the entire universe if it were packed so tightly that you couldn't pack any more in. 400 qubits. On the other hand, if your quantum computer is composed of 400 qubits, it can do everything 400 qubits can do. What kind of space, if you just intuitively think about the space of algorithms, that that unlocks for us. So there's a whole complexity theory around classical computers measuring the running time of things, and P, so on. What kind of algorithms, just intuitively, do you think it unlocks for us? Okay, so we know that there are a handful of algorithms that can seriously beat classical computers and which can have exponentially more power. This is a mathematical statement. Nobody's exhibited this in the laboratory. It's a mathematical statement. We know that's true, but it also seems more and more that the number of such things is very limited. Only very, very special problems exhibit that much advantage for a quantum computer, of standard problems. To my mind, as far as I can tell, the great power of quantum computers will actually be to simulate quantum systems. If you're interested in a certain quantum system and it's too hard to simulate classically, you simply build a version of the same system. You build a version of it, you build a model of it that's actually functioning as the system, you run it, and then you do the same thing you would do to the quantum system, you make measurements on it, quantum measurements on it. The advantage is you can run it much slower. You could say, why bother? Why not just use the real system? Why not just do experiments on the real system? Well, real systems are kind of limited. You can't change them, you can't manipulate them, you can't slow them down so that you can poke into them. You can't modify them in arbitrary kinds of ways to see what would happen if I change the system a little bit. I think that quantum computers will be extremely valuable in understanding quantum systems. At the lowest level, the fundamental laws. They're actually satisfying the same laws as the systems that they're simulating. That's right. Okay, so on the one hand, you have things like factoring. Factoring is the great thing of quantum computers, factoring large numbers. That doesn't seem that much to do with quantum mechanics. It seems to be almost a fluke that a quantum computer can solve the factoring problem in a short time. And those problems seem to be extremely special, rare, and it's not clear to me that there's gonna be a lot of them. On the other hand, there are a lot of quantum systems. Chemistry, there's solid state physics, there's material science, there's quantum gravity, there's all kinds of quantum field theory. And some of these are actually turning out to be applied sciences as well as very fundamental sciences. So we probably will run out of the ability to solve equations for these things. You know, solve equations by the standard methods of pencil and paper, solve the equations by the method of classical computers. And so what we'll do is we'll build versions of these systems, run them, and run them under controlled circumstances where we can change them, manipulate them, make measurements on them, and find out all the things we wanna know. So in finding out the things we wanna know about very small systems, right, is there something we can also find out about the macro level? About something about the function, forgive me, of our brain, biological systems? The stuff that's about one meter in size versus much, much smaller. Well, all the excitement is about, among the people that I interact with, is understanding black holes. Black holes. Black holes are big things. They are many, many degrees of freedom. There is another kind of quantum system that is big. It's a large quantum computer. And one of the things we've learned is that the physics of large quantum computers is in some ways similar to the physics of large quantum black holes. And we're using that relationship. Now you asked, you didn't ask about quantum computers, the systems, you didn't ask about black holes, you asked about brains. Yeah, about stuff that's in the middle of the two. It's different. So black holes are, there's something fundamental about black holes that feels to be very different than brains. Yes. And they also function in a very quantum mechanical way. Right. Okay. It is, first of all, unclear to me, but of course it's unclear to me. I'm not a neuroscientist. I have, I don't even have very many friends who are neuroscientists. I would like to have more friends who are neuroscientists. I just don't run into them very often. Among the few neuroscientists I've ever talked about about this, they are pretty convinced that the brain functions classically. That it is not intrinsically a quantum mechanical system or doesn't make use of the special features, entanglement, coherent superposition. Are they right? I don't know. I sort of hope they're wrong, just because I like the romantic idea that the brain is a quantum system. Yeah. But I think probably not. The other thing, big systems can be composed of lots of little systems, okay? Materials, the materials that we work with and so forth are, can be large systems, a large piece of material, but they're made out of quantum systems. Now, one of the things that's been happening over the last good number of years is we're discovering materials and quantum systems which function much more quantum mechanically than we imagine. Topological insulators, this kind of thing, that kind of thing. Those are macroscopic systems, but they, just superconductors, superconductors, have a lot of quantum mechanics in them. You can have a large chunk of superconductor, so it's a big piece of material. On the other hand, it's functioning and its properties depend very, very strongly on quantum mechanics. And to analyze them, you need the tools of quantum mechanics. If we can go on to black holes, and looking at the universe as an information processing system, as a computer, as a giant computer. It's a giant computer. What's the power of thinking of the universe as an information processing system? Or what is, perhaps its use, besides the mathematical use of discussing black holes and your famous debates and ideas around that, to human beings, or life in general, as information processing systems? So all systems are information processing systems. You poke them, they change a little bit, they evolve. All systems are information processing systems. So there's no extra magic to us humans? It certainly feels, consciousness, intelligence feels like magic. It sure does. Where does it emerge from? If we look at information processing, what are the emerging phenomena that come from viewing the world as an information processing system? Here is what I think. My thoughts are not worth much in this. If you ask me about physics, my thoughts may be worth something. If you ask me about this, I'm not sure my thoughts are worth anything. But as I said earlier, I think when we do introspection, when we imagine doing introspection and try to figure out what it is when we do, and we're thinking, I think we get it wrong. I'm pretty sure we get it wrong. Everything I've heard about the way the brain functions is so counterintuitive. For example, you have neurons which detect vertical lines. You have different neurons which detect lines at 45 degrees. You have different neurons. I never imagined that there were whole circuits which were devoted to vertical lines in the brain. Doesn't seem to be the way my brain works. My brain seems to work if I put my finger up vertically, or if I put it horizontally, or if I put it this way or that way. It seems to me it's the same circuits that are, it's not the way it works. The way the brain is compartmentalized seems to be very, very different than what I would have imagined if I were just doing psychological introspection about how things work. My conclusion is that we won't get it right that way. That, how will we get it right? I think maybe computer scientists will get it right. Eventually, I don't think they're anywhere near it. I don't even think they're thinking about it. But by computer, eventually we will build machines, perhaps, which are complicated enough, and partly engineered, partly evolved, maybe evolved by machine learning and so forth. This machine learning is very interesting. By machine learning, we will evolve systems, and we may start to discover mechanisms that have implications for how we think and for what this consciousness thing is all about. And we'll be able to do experiments on them and perhaps answer questions that we can't possibly answer by introspection. So that's a really interesting point. In many cases, if you look at even the string theory, when you first think about a system, it seems really complicated, like the human brain. And through some basic reasoning, in trying to discover fundamental, low-level behavior of the system, you find out that it's actually much simpler. Is that generally the process? And two, do you have that also hope for biological systems as well, for all the kinds of stuff we're studying at the human level? Of course, physics always begins by trying to find the simplest version of something and analyze it. Yeah, I mean, there are lots of examples where physics has taken very complicated systems, analyzed them, and found simplicity in them for sure. I said superconductors before. It's an obvious one. A superconductor seems like a monstrously complicated thing with all sorts of crazy electrical properties, magnetic properties, and so forth. And when it finally is boiled down to its simplest elements, it's a very simple quantum mechanical phenomenon called spontaneous symmetry breaking, which we, in other contexts, we learned about and we're very familiar with. So yeah, I mean, yes, we do take complicated things, make them simple, but what we don't wanna do is take things which are intrinsically complicated and fool ourselves into thinking that we can make them simple. We don't wanna make, I don't know who said this, but we don't wanna make them simpler than they really are, okay? Is the brain a thing which ultimately functions by some simple rules, or is it just complicated? In terms of artificial intelligence, nobody really knows what are the limits of our current approaches. You mentioned machine learning. How do we create human-level intelligence? It seems that there's a lot of very smart physicists who perhaps oversimplify the nature of intelligence and think of it as information processing, and therefore there doesn't seem to be any theoretical reason why we can't artificially create human-level or superhuman-level intelligence. In fact, the reasoning goes, if you create human-level intelligence, the same approach you just used to create human-level intelligence should allow you to create superhuman-level intelligence very easily, exponentially. So what do you think that way of thinking that comes from physicists is all about? I wish I knew, but there's a particular reason why I wish I knew. I have a second job. I consult for Google. Not for Google, for Google X. I am the senior academic advisor to a group of machine-learning physicists. Now, that sounds crazy because I know nothing about the subject. I know very little about the subject. On the other hand, I'm good at giving advice, so I give them advice on things. Anyway, I see these young physicists who are approaching the machine-learning problem. There is a real machine-learning problem, namely, why does it work as well as it does? Nobody really seems to understand why it is capable of doing the kind of generalizations that it does and so forth. And there are three groups of people who have thought about this. There are the engineers. The engineers are incredibly smart, but they tend not to think as hard about why the thing is working as much as they do how to use it, obviously. They've provided a lot of data. And it is they who demonstrated that machine-learning can work much better than you had any right to expect. The machine-learning systems are systems, the systems not too different than the kind of systems that physicists study. There's not all that much difference between quantum, in the structure of the mathematics, physically, yes, but in the structure of the mathematics, between a tensor network designed to describe a quantum system on the one hand and the kind of networks that are used in machine-learning. So there are more and more, I think, young physicists are being drawn to this field of machine-learning. Some very, very good ones. I work with a number of very good ones, not on machine-learning, but on having lunch. On having lunch? Right. Yeah. And I can tell you they are super smart. They don't seem to be so arrogant about their physics backgrounds that they think they can do things that nobody else can do. But the physics way of thinking, I think, will add great value to, or will bring value to the machine-learning. I believe it will. And I think it already has. At what time scale do you think predicting the future becomes useless? In your long experience in being surprised at new discoveries. Sometimes a day, sometimes 20 years. There are things which I thought we were very far from understanding, which practically in a snap of the fingers or a blink of the eye suddenly became understood, completely surprising to me. There are other things which I looked at and I said, we're not gonna understand these things for 500 years, in particular quantum gravity. The scale for that was 20 years, 25 years. And we understand a lot, and we don't understand it completely now by any means, but I thought it was 500 years to make any progress. It turned out to be very, very far from that. It turned out to be more like 20 or 25 years from the time when I thought it was 500 years. So if we may, can we jump around quantum gravity, some basic ideas in physics? What is the dream of string theory, mathematically? What is the hope? Where does it come from? What problem is it trying to solve? I don't think the dream of string theory is any different than the dream of fundamental theoretical physics altogether. Understanding a unified theory of everything. I don't like thinking of string theory as a subject unto itself, with people called string theorists who are the practitioners of this thing called string theory. I much prefer to think of them as theoretical physicists trying to answer deep fundamental questions about nature, in particular gravity, in particular gravity and its connection with quantum mechanics, and who at the present time find string theory a useful tool, rather than saying there's this subject called string theorists. I don't like being referred to as a string theorist. Yes, but as a tool, is it useful to think about our nature in multiple dimensions, the strings vibrating? I believe it is useful. I'll tell you what the main use of it has been up till now. Well, it has had a number of main uses. Originally, string theory was invented, and I know that I was there, I was right at the spot where it was being invented, literally, and it was being invented to understand hadrons. Hadrons are subnuclear particles, protons, neutrons, mesons, and at that time, the late 60s, early 70s, it was clear from experiment that these particles called hadrons could vibrate, could rotate, could do all the things that a little closed string can do, and it was and is a valid and correct theory of these hadrons. It's been experimentally tested, and that is a done deal. It had a second life as a theory of gravity, the same basic mathematics, except on a very, very much smaller distance scale. The objects of gravitation are 19 orders of magnitude smaller than a proton, but the same mathematics turned up, the same mathematics turned up. What has been its value? Its value is that it's mathematically rigorous in many ways and enabled us to find mathematical structures, mathematical structures which have both quantum mechanics and gravity. With rigor, we can test out ideas. We can test out ideas. We can't test them in the laboratory, that they're 19 orders of magnitude too small, the things that we're interested in, but we can test them out mathematically and analyze their internal consistency. By now, 40 years ago, 35 years ago, and so forth, people very, very much questioned the consistency between gravity and quantum mechanics. Stephen Hawking was very famous for it, rightly so. Now, nobody questions that consistency anymore. They don't because we have mathematically precise string theories which contain both gravity and quantum mechanics in a consistent way. So it's provided that certainty that quantum mechanics and gravity can coexist. That's not a small thing. It's a very big thing. It's a huge thing. Einstein would be proud. Einstein, he might be appalled. I don't know. He didn't like quantum mechanics very much, but he would certainly be struck by it. I think that may be, at this time, its biggest contribution to physics in illustrating almost definitively that quantum mechanics and gravity are very closely related and not inconsistent with each other. Is there a possibility of something deeper, more profound, that still is consistent with string theory but is deeper that is to be found? Well, you could ask the same thing about quantum mechanics. Is there something? Exactly. Yeah, yeah. I think string theory is just an example of a quantum mechanical system that contains both gravitation and quantum mechanics. So is there something underlying quantum mechanics? Perhaps something deterministic. Perhaps something deterministic. My friend, Gerard Etoft, whose name you may know, he's a very famous physicist. Dutch, not as famous as he should be, but. Hard to spell his name. It's hard to say his name. No, it's easy to spell his name. Apostrophe, he's the only person I know whose name begins with an apostrophe. And he's one of my heroes in physics. He's a little younger than me, but he's nevertheless one of my heroes. Etoft believes that there is some sub-structure to the world which is classical in character, deterministic in character, which somehow, by some mechanism that he has a hard time spelling out, emerges as quantum mechanics. I don't. The wave function is somehow emergent. The wave function, not just the wave function, but the whole mechan, the whole thing that goes with quantum mechanics, uncertainty, entanglement, all these things are emergent. So you think quantum mechanics is the bottom of the well? Is the... Here, I think, is where you have to be humble. Here's where humility comes. I don't think anybody should say anything is the bottom of the well at this time. I think we can reasonably say, or I can reasonably say, when I look into the well, I can't see past quantum mechanics. I don't see any reason for there to be anything beyond quantum mechanics. I think Etoft has asked very interesting and deep questions I don't like his answers. Well, again, let me ask, if we look at the deepest nature of reality, whether it's deterministic or, when observed, as probabilistic, what does that mean for our human level of ideas of free will? Is there any connection whatsoever from this perception, perhaps illusion of free will that we have, and the fundamental nature of reality? The only thing I can say is I am puzzled by that as much as you are. The illusion of it, the... The illusion of consciousness, the illusion of free will, the illusion of self. Does that connect to... How can a physical system do that? And I am as puzzled as anybody. There's echoes of it in the observer effect. Yeah. So do you understand what it means to be an observer? I understand it at a technical level. An observer is a system with enough degrees of freedom that it can record information, and which can become entangled with the thing that it's measuring. Entanglement is the key. When a system, which we call an apparatus or an observer, same thing, interacts with the system that it's observing, it doesn't just look at it, it becomes physically entangled with it. And it's that entanglement which we call an observation or a measurement. Now does that satisfy me personally as an observer? Yes and no. I find it very satisfying that we have a mathematical representation of what it means to observe a system. You are observing stuff right now. Yeah. At the conscious level. Right. Do you think there's echoes of that kind of entanglement in our macro scale? Yes, absolutely, for sure. We're entangled with everything, quantum mechanically entangled with everything in this room. If we weren't, then we would just, well, we wouldn't be observing it. But on the other hand, you can ask, do I really, am I really comfortable with it? And I'm uncomfortable with it in the same way that I can never get comfortable with five dimensions. My brain isn't wired for it. Are you comfortable with four dimensions? A little bit more because I can always imagine the fourth dimension is time. So the arrow of time, are you comfortable with that arrow? Do you think time is an emergent phenomena or is it fundamental to nature? That is a big question in physics right now. All the physics that we do, or at least that the people that I am comfortable with talking to, my friends, my friends. My friends, we all ask the same question that you just asked. Space, we have a pretty good idea is emergent and it emerges out of entanglement and other things. Time always seems to be built into our equations as just what Newton pretty much would have thought. Newton modified a little bit by Einstein would have called time. And mostly in our equations it is not emergent. Time in physics is completely symmetric, forward and backward. Right, symmetric. So you don't really need to think about the arrow of time for most physical phenomena. Most microscopic phenomena, no. It's only when the phenomena involve systems which are big enough for thermodynamics to become important, for entropy to become important. For a small system, entropy is not a good concept. And entropy is something which emerges out of large numbers. It's a probabilistic idea, it's a statistical idea, and it's a thermodynamic idea. Thermodynamics requires lots and lots and lots of little substructures. So it's not until you emerge at the thermodynamic level that there's an arrow of time. Do we understand it? Yeah, I think we understand better than most people think they understand. Most people say they think we understand it. Yeah, I think we understand it. It's a statistical idea. You mean like second law thermodynamics, entropy and so on? Yeah, yeah. Pick a pack of cards and you fling it in the air and you look what happens to it. It gets random. We understand it. It doesn't go from random to simple. It goes from simple to random. But do you think it ever breaks down? What I think you can do is in a laboratory setting, you can take a system which is somewhere intermediate between being small and being large and make it go backward. A thing which looks like it only wants to go forward because of statistical mechanical reasons, because of the second law. You can very, very carefully manipulate it to make it run backward. I don't think you can take an egg, a Humpty Dumpty who fell on the floor and reverse that. But you can, in a very controlled situation, you can take systems which appear to be evolving statistically toward randomness, stop them, reverse them and make them go back. What's the intuition behind that? How do we do that? How do we reverse it? You're saying a closed system. Yeah, pretty much closed system, yes. Did you just say that time travel is possible? No, I didn't say time travel is possible. I said you can make a system go backward. In time. You can make it go back. You can make it reverse its steps. You can make it reverse its trajectory. Yeah. How do we do it? What's the intuition there? Does it have, is it just a fluke thing that we can do at a small scale in the lab that doesn't have? What I'm saying is you can do it on a little bit better than a small scale. You can certainly do it with a simple small system. Small systems don't have any sense of the arrow of time. Atoms, atoms are, no sense of an arrow of time. They're completely reversible. It's only when you have, you know, the second law of thermodynamics is the law of large numbers. So you can break the law because it's not a deterministic law. You can break it, but it's hard. It requires great care. The bigger the system is, the more care, the more, the harder it is. You have to overcome what's called chaos. And that's hard. And it requires more and more precision. For 10 particles, you might be able to do it with some effort. For 100 particles, it's really hard. For 1,000 or a million particles, forget it. But not for any fundamental reason, just because it's technologically too hard to make the system go backward. So no time travel for engineering reasons. Oh, no, no, no, no. What is time travel? Time travel to the future, that's easy. You just close your eyes, go to sleep, and you wake up in the future. Yeah, yeah. A good nap gets you there, yeah. A good nap gets you there, right. What happens in reversing the second law of thermodynamics, the going backward in time, for anything that's human scale, is a very difficult engineering effort. I wouldn't call it time travel, because it gets too mixed up with what science fiction calls time travel. This is just the ability to reverse a system. You take the system, and you reverse the direction of motion of every molecule in it. That, you can do it with one molecule. If you find a particle moving in a certain direction, let's not say a particle, a baseball, you stop it dead, and then you simply reverse its motion. In principle, that's not too hard. And it'll go back along its trajectory in the backward direction. Just running the program backwards. Running the program backward. Yeah. If you have two baseballs colliding, well, you can do it, but you have to be very, very careful to get it just right. If you have 10 baseballs, really, really, or better yet, 10 billiard balls on an idealized frictionless billiard table. Okay, so you start the balls all on a triangle, right? And you whack them. Depending on the game you're playing, you either whack them or you're really careful, but you whack them. And they go flying off in all possible directions. Okay, try to reverse that. Try to reverse that. Imagine trying to take every billiard ball, stopping it dead at some point, and reversing its motion so that it was going in the opposite direction. If you did that with tremendous care, it would reassemble itself back into the triangle. Okay, that is a fact, and you can probably do it with two billiard balls, maybe with three billiard balls if you're really lucky. But what happens is as the system gets more and more complicated, you have to be more and more precise not to make the tiniest error, because the tiniest errors will get magnified, and you'll simply not be able to do the reversal. So yeah, but I wouldn't call that time travel. Yeah, that's something else. But if you think of it, it just made me think, if you think the unrolling of state that's happening as a program, if we look at the world, so the idea of looking at the world as a simulation, as a computer, but it's not a computer, it's just a single program. A question arises that might be useful. How hard is it to have a computer that runs the universe? Okay, so there are mathematical universes that we know about. One of them is called anti-de Sitter space, where we, and it's quantum mechanics, where I think we could simulate it in a computer, in a quantum computer. Classical computer, all you can do is solve its equations. You can't make it work like the real system. If we could build a quantum computer, a big enough one, a robust enough one, we could probably simulate a universe, a small version of an anti-de Sitter universe. Anti-de Sitter is a kind of a cosmology. So I think we know how to do that. The trouble is the universe that we live in is not the anti-de Sitter geometry, it's the de Sitter geometry. And we don't really understand its quantum mechanics at all. So at the present time, I would say we wouldn't have the vaguest idea how to simulate a universe similar to our own. You know, we could ask, could we build in the laboratory a small version, a quantum mechanical version, the collection of quantum computers entangled and coupled together, which would reproduce the phenomena that go on in the universe, even on a small scale. Yes, if it were anti-de Sitter space. No, if it's de Sitter space. Can you slightly describe de Sitter space and anti-de Sitter space? Yeah. What are the geometric properties of? They differ by the sign of a single constant called the cosmological constant. One of them is negatively curved, the other is positively curved. The anti-de Sitter space, which is the negatively curved one, you can think of as an isolated system in a box with reflecting walls. You could think of it as a system of quantum mechanical system, isolated in an isolated environment. De Sitter space is the one we really live in, and that's the one that's exponentially expanding. Exponential expansion, dark energy, whatever we want to call it. And we don't understand that mathematically. Do we understand? Not everybody would agree with me, but I don't understand. They would agree with me, they definitely would agree with me that I don't understand it. What about, is there an understanding of the birth, the origin, the Bing Bang? So, there's one thing with the other. No, no, there's theories. There are theories. My favorite is the one called eternal inflation. The infinity can be on both sides, on one of the sides and none of the sides. So, what's eternal infinity? Okay. Infinity on both sides. Oh, boy. Yeah, yeah. Why is that your favorite? Because it's the most, just mind-blowing? No. Because we want a beginning. No. Why do we want a beginning? In practice, there was a beginning, of course. In practice, there was a beginning. But could it have been a random fluctuation in an otherwise infinite time? Maybe. In any case, the eternal inflation theory, I think if correctly understood, would be infinite in both directions. How do you think about infinity? Oh, God. So, okay, of course you can think about it mathematically. I just finished this discussion with my friend, Sergey Brin. Yes. How do you think about infinity? I say, well, Sergey Brin is infinitely rich. How do you test that hypothesis? Okay. That's such a good line. Right. Yeah, so there's really no way to visualize some of these things. Like, like. Yeah, no, this is a very good question. Does physics have any, does infinity have any place in physics? Right. Right, and all I can say is, very good question. So, what do you think of the recent first image of a black hole visualized from the Event Horizon Telescope? It's an incredible triumph of science. In itself, the fact that there are black holes which collide is not a surprise. And they seem to work exactly the way they're supposed to work. Will we learn a great deal from it? I don't know, I can't, we might. But the kind of things we'll learn won't really be about black holes. Why there are black holes in nature of that particular mass scale and why they're so common may tell us something about the structure, evolution of structure in the universe. But I don't think it's gonna tell us anything new about black holes. But it's a triumph in the sense that you go back 100 years and it was a continuous development, general relativity, the discovery of black holes, LIGO, the incredible technology that went into LIGO. It is something that I never would have believed was gonna happen 30, 40 years ago. And I think it's a magnificent structure, magnificent thing, this evolution of general relativity, LIGO, high precision, ability to measure things on a scale of 10 to the minus 21. So, yeah. So you're just in awe that we, this path took us to this picture. Is it different? You know, you've thought a lot about black holes. How did you visualize them in your mind? And is the picture different than you realized it? No, it simply confirmed, you know, it's a magnificent triumph to have confirmed a direct observation that Einstein's theory of gravity at the level of black hole collisions actually works is awesome, it is really awesome. You know, I know some of the people who were involved in that. They're just ordinary people. And the idea that they could carry this out, I just, I'm shocked. Yeah, just these little homo sapiens. Yeah, just these little monkeys. Yeah, got together and took a picture of. Slightly advanced limers, I think. What kind of questions can science not currently answer but you hope might be able to soon? Well, you've already addressed them. What is consciousness, for example? You think that's within the reach of science? I think it's somewhat within the reach of science, but I think now I think it's in the hands of the computer scientists and the neuroscientists. Not a physicist. Perhaps at some point. But I think physicists will try to simplify it down to something that they can use their methods and maybe they're not appropriate. Maybe we simply need to do more machine learning on bigger scales, evolve machines. Machines not only that learn but evolve their own architecture as a process of learning, evolving architecture. Not under our control, only partially under our control, but under the control of machine learning. I'll tell you another thing that I find awesome. You know this Google thing that they taught computers how to play chess? Yeah, yeah. Okay, they taught computers how to play chess, not by teaching them how to play chess, but just having them play against each other. Against each other, self-play. Against each other. This is a form of evolution. These machines evolved. They evolved in intelligence. They evolved in intelligence without anybody telling them how to do it. They were not engineered. They just played against each other and got better and better and better. That makes me think that machines can evolve intelligence. What exact kind of intelligence, I don't know. But in understanding that better and better, maybe we'll get better clues as to what goes on in our own intelligence. Well, life and intelligence is, last question, what kind of questions can science not currently answer and may never be able to answer? Yeah. Yeah. Is there an intelligence out there that's underlies the whole thing? You can call them with a G word if you want. I can say, are we a computer simulation with a purpose? Is there an agent, an intelligent agent that underlies or is responsible for the whole thing? Does that intelligent agent satisfy the laws of physics? Does it satisfy the laws of quantum mechanics? Is it made of atoms and molecules? Yeah, there's a lot of questions. And I don't see, it seems to me a real question. It's an answerable question. Well, I don't know if it's answerable. The questions have to be answerable to be real. Some philosophers would say that a question is not a question unless it's answerable. This question doesn't seem to me answerable by any known method, but it seems to me real. There's no better place to end. Leonard, thank you so much for talking today. Okay, good.