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

Lex Fridman and Garry Kasparov on kasparov on genius, machines, dictatorship, and the limits of AI.

Lex FridmanhostGarry Kasparovguest
Oct 27, 201955mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:00 – 1:30

    Intro

    1. LF

      The following is a conversation with Garry Kasparov. He's 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 a 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 @lexfridman, spelled F-R-I-D-M-A-N. And now, here's my conversation

  2. 1:30 – 3:44

    Kasparov’s competitive psychology: losing, mistakes, and decisive intuition

    1. LF

      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?

    2. GK

      Tough question. I have to confess, I never heard it before, which is ... again, congratulations. It's quite an accomplishment. (laughs)

    3. LF

      (laughs)

    4. GK

      Um, losing was always painful. For me, it was almost like a physical pain, because I knew that if I lost a game it's just because I made a mistake. So it ... I always believed that the r- the result of the game, uh, had to be decided by the quality of my play. Okay, you may say it s- sounds arrogant, but it helped me to move forward because I always knew that there was room for improvement, so it's the ...

    5. LF

      Was there the fear of the mistake?

    6. GK

      Actually, fear of mistake guarantees mistakes. And the difference between, uh, top players, the very top, is that it's the ability to make a decision-

    7. LF

      Yeah.

    8. GK

      ... without predictable consequences. You don't know what's happening. It starts intuitively. I could go this way or that way and, uh, there are always hesitations. You know, people are like, "You're, you are just, you know, at a crossroad. You can go right, you can go left, you can go straight. You can turn and go back, and the consequences are just un- uh, very uncertain." Just, you have certain ideas what happens on the right or on the left or on the just, you know, if you go straight, but it's not enough to make well-calculated choice, and, uh, when you play chess at the very top, it's, it's, it's, 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. Um, going back to your original question is I would say neither. It's just it's the, it's lo- love for winning, hate for losing, they were important elements, psychological elements, but the key element, it's the,

  3. 3:44 – 6:29

    “Making a difference” as the core drive—creative chess and life beyond the board

    1. GK

      I would say the, the driving force was always my passion for, for making a di- making a difference. It's just I can move forward and I can always, it's, I can always enjoy not just playing but creating something new.

    2. LF

      Creating something new. How do you think about that?

    3. GK

      It's just, uh-

    4. LF

      You-

    5. GK

      ... finding new ideas in the openings, you know, some original plan in the middle game. It's ... actually, that helped me to make the transition from the game of chess, where I was on the very top to, 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 a difference, by influencing people, say, joining the democratic movement in Russia or talking to people about, uh, 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.

    6. LF

      So you can still create something new that makes a difference, uh, uh, 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? See, you make it seem like to be at the level you are at, you can get away f- without having demons, without, without having fears, without being driven in- f- by some of the darker forces.

    7. GK

      (exhales sharply) I mean, you sound almost religious, you know, darker forces, spiritual, uh-

    8. LF

      No.

    9. GK

      ... demons. I mean, do you have a call for a priest? (laughs)

    10. LF

      (laughs) That's why I'm dressing.

    11. GK

      Uh, yeah. No, uh, uh, just let's go back to, to, to these crucial chess moments where I had to make big decisions.

    12. LF

      Yes.

    13. GK

      As I said, it's, it's, you know, 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 the-

    14. LF

      Right.

    15. GK

      ... yes, I, I, I always had an opponent across the chess board opposite me, but no matter how strong that opponent was, whether they just were ordinary player or another world champion like Anatoly Karpov-... I, having all respect for my opponent, I still believe that it's, it's up to me to make the difference. Uh, and, um, uh, I, you know, (exhales) I knew I, I was not invincible. I made mistakes. I made some blunders, and, you know, with age, they all... I, I made more blunders. Okay, good.

    16. LF

      (laughs)

  4. 6:29 – 9:04

    Aging, decline, and the “biological clock” (Caruana, Fischer Random, and pride in still outplaying elites)

    1. GK

      I knew it. But it's, it's still, you know, it's, it's very much for me to be decisive factor in the game. I mean, even now, look, I just... You know, my latest chess experience was horrible. I mean, I g-... I played Caruana, Caruana, Fabi Caruana, uh, this number two, number two, number three player in the world these days. We played this 960 with s-... a Fisher, so-called Fisher random chess where you're shuffling 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. So, and it's, it's... You know, while I lost, I, I wasn't so much upset. I mean, I know, as I, as I said in my in-... in the interview, I can fight any opponent, but not my biological clock. So it's-

    2. LF

      (laughs)

    3. GK

      Um, it's... Fighting time is, is, is, is, is always a losing proposition. But even today, at age 56, you know, I, I knew that, you know, I could play great game. I couldn't finish it because I didn't have enough energy or just, you know, I couldn't have the same level of concentration, but, you know, in num-... number of games where I completely outplayed one of the top players in the world, I mean, gave me certain amount of, of, uh, pleasure. That is, even today, I haven't lost my touch.

    4. LF

      Yeah.

    5. GK

      Not the same, you know, uh... Okay, the jaws are not as, as strong and the teeth are not as sharp, but I could get him just, you know, almost, you know, to... on the ropes. Uh-

    6. LF

      You still got it.

    7. GK

      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, Garry. It's... Somehow, it's not even just fighting biolo-... your biological clock. It just, you know... Maybe it's a signal." Because, you know, (sighs) the goddess of chess, since you spoke great about demon-

    8. LF

      Yeah, religiously.

    9. GK

      The goodness of chess, Kaicia, 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, that's, that's one of the be-... top players who just recently played World Championship match. If you could beat him, it... that would be really bad for the game of chess.

    10. LF

      (laughs)

    11. GK

      I mean, just, just what people would say, "Oh, look, the game of chess, you know, it's, it's, it's, it's not make any progress. The game is just... You know, it's, it's totally devalued because, look, the, 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, uh, it... I mean, following your logic, we should always look for, you know, demons, you know-

    12. LF

      (laughs)

    13. GK

      ... superior forces and other things that could-

    14. LF

      Yes.

    15. GK

      ... you know, if not dominate our lives, but somehow, you know, play a significant role in, in, uh, the outcome.

    16. LF

      Yeah, so the goddess of chess had to send a message.

    17. GK

      Yeah. That's okay.

    18. LF

      I got it.

    19. GK

      Okay. So Garry, you should do something else. (laughs) Time.

  5. 9:04 – 12:17

    What makes a masterpiece: Kasparov’s proudest games, Tal’s legacy, and beauty beyond sacrifices

    1. LF

      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, 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 a aggressive and creative chess player. In, in your own games.

    2. GK

      Uh, uh, look, you mentioned Mikhail Tal. W-... It's very aggressive, very sharp player, uh, famous for his combinations and sacrifices. Even called Magician from Riga, so for his, uh, uh, very unique style. But, uh, any, any world champion, you know, it's... Yeah, was a creator. Some of them were so, um, flamboyant and flashy like Tal. Some of them were, no, just, you know, less, uh, uh, discerned, uh, at the chessboard, like Tigran Petrosian. But every world champion, every top player brought something into the game of chess. And, uh, 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 are hanging and, and, and it's all of a sudden, you know, being material down, a rook down or just, you know, queen down, the, uh, the, the, um, weaker side, uh, uh, delivers the, uh, the final blow and just, you know, mating opponent's king. But, uh, there's... there are other kinds of beauty. I mean, there's s-... slow positional maneuvering, you know, looking for weaknesses and just... and, and gradually, you know, strangling, uh, uh, your opponent and eventually delivering sort of a positional masterpiece. Yeah. So I think I, I made more difference in the game of chess than I could, I could have imagined when I started playing. And, uh, the reason I thought it was time for me to, to leave is that, I mean, I knew that I was not... uh, I was not... no longer in the position to, uh, um, bring ba-... bring the same kind of contribution, the same kind of, uh, new knowledge in-... into the game. Yeah.

    3. LF

      So, um, and, uh, going back, I could immediately look at my games against Anatoly Karpov.

    4. GK

      Correct.

    5. LF

      It's not just I won the match in 1985 and became, uh, world champion at age 22, but, uh, there were at least two games in that match. Uh, 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... it was a very, um, sharp game, and I found a unique maneuver that was absolutely new and it became some sort of a-... just typical now. Though this... when the move was made, was made at the... o- on the board and put on display, a lot of people thought it was ugly, so this- Mm-hmm.

    6. GK

      And another game, game 16 in the match where I just also managed to outplay Karpov completely with s-... black pieces, just, you know, paralyzing his entire army in, in, in, in its own... its own camp.

    7. LF

      Technically or psychologically, or was that a mix of both in game 16?

  6. 12:17 – 16:41

    Preparation, intuition, and the pre-computer era: why hard work “transforms” into over-the-board ideas

    1. GK

      Yeah, it, 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 the time, and, uh, uh, the world champion, you know, by the rules, could re- retain his title in case of a tie. So we still have, you know, uh, before game 16, we have nine games to go. Uh, and also it was some sort of a bluff because n- n- n- n- neither me nor Karpov saw the refutation of this opening idea. And, uh, um... And I think it's as 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, you know, just this, this, this opening bluff. And then, you know, they discovered that it was a bluff.

    2. LF

      Mm-hmm.

    3. GK

      So it's the, uh... Again, I didn't know, i- I was not bluffing. So that's why I, it's, it happens very often. It's when, you know, some ideas could be refuted and it's just... What I found out, and this is, again, going back to your, you know, spiritual theme-

    4. LF

      (laughs)

    5. GK

      ... is that it's, it's you could spend a lot of time working. And when I say you could, it's just, it's, it's in the '80s and the '90s. It doesn't happen these days because everybody has a computer. You could immediately see if, if it works or it doesn't work. Machine shows you a refutation in the split of a second. But many of the, our analysis in the '80s or in the '90s, they were not perfect simply because we're humans and they don't just... You, you, you analyze the game, you look for some fresh ideas, and then just it happens that, yeah, there, there was something that you missed. Because the level of concentration at the chess board is different from when the, when you analyze the game-

    6. LF

      You can analyze.

    7. GK

      ... just moving the pieces around.

    8. LF

      Interesting.

    9. GK

      And... But somehow, if you spend a lot of time at the chess board preparing, so in your studies, with your, uh, coaches, it's hours and hours and hours, and nothing of what you found could, you know, had materialized on the, on, on, on chess, on the chess board. Somehow these hours help... I don't know why. Always helped you. It's, it's as if, you know, the amount of work you did, uh, could be transformed into some sort of, yeah, spiritual energy that helped-

    10. LF

      (laughs)

    11. GK

      ... you to come up with other great ideas during the board. Again, even if it's, it was, 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, uh, your dedication to actually to... and your passion to, uh, discover new ideas, and your ability during the game at the chess board when the clock was ticking, we still had ticking clock, not digital clock at the time.

    12. LF

      (laughs)

    13. GK

      So to come up with some, some, some brilliancy. And, um... And I also can mention many games, you know, from the '90s. So it's the... Obviously, all amateurs would pick up my game against Veselin Topalov in 1999 in Again, because it was a brilliant game, uh, the black king traveled from, uh, from, uh, its own camp to, into the, uh, into m- into white's camp across the entire board. It doesn't happen often, trust me, (laughs) as you know-

    14. LF

      Mm-hmm.

    15. GK

      ... in, in, in, in the games with professional players, top professional players. So that's why visually it was one of the most impressive victories. But I could bring to, to your attention many other games that were not so impressive, uh, for, for amateurs, not so, not so, uh, um, beautiful-

    16. LF

      Mm-hmm.

    17. GK

      ... just 'cause it's... Sacrifice is always beautiful. You sacrifice pieces-

    18. LF

      Yeah.

    19. GK

      ... and then, and then eventually, you have so... you have very few resources left, and you, you, you use them just to, to, to, to crush your opp- uh, your, your opponent basically, to... It's a... You have to mate the king because you have al- almost, almost, uh, nothing, nothing, nothing left, uh, at your disposal. But, uh, I... You know, I... Up to the very end, again, less and less, but still up to the very end, I always had games with some sort of, you know, interesting ideas and, uh, and games that gave me great satisfaction. But I think it's what happened from 2005 up to these days was also very big, very big accomplishment since, you know, I had to find myself, to sort of relocate myself. Uh-

    20. LF

      Yeah, rechannel the creative energies to do other pursuits.

    21. GK

      Exactly, and, and to, to find something where I f- feel comfortable, even confident that my participation still makes the difference.

  7. 16:41 – 23:07

    Ranking greatness across eras: Magnus Carlsen, time gaps, and the problem of comparisons

    1. LF

      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.

    2. GK

      It's a tricky question. You know, uh, the moment you start ranking-

    3. LF

      Yeah.

    4. GK

      ... a world champion-

    5. LF

      You lose something.

    6. GK

      It's the... I think it's, it's, it's not fair because it's the... any new generation knows much more about the game than-

    7. LF

      Yes.

    8. GK

      ... the previous one. So when people say, "Oh, Garry was the greatest, Fischer was the greatest, Magnus was the greatest," it disregard the fact that the great players of the past, whether Alaskair, Kapablanca, Alekhine, I mean, they knew so little about chess by today's standards. I mean, today, just any kid, you know, that spent few years, you know, in, w- uh, uh, uh... with his or her chess computer when... knows much more about the games, simply just because you ac- have access to this information. And it ha- 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.

    9. LF

      Yeah.

    10. GK

      I was on top, not as big as Fischer-

    11. LF

      Very long time.

    12. GK

      ... but, but much longer.

    13. LF

      Yes.

    14. GK

      So that's... So, and also, unlike Fischer, I was succee- I succeeded in beating next generation.

    15. LF

      Yes. Here's the question.

    16. GK

      Yeah.

    17. LF

      Let's see if you still got the fire, speaking of the next generation, because you did succeed beating the next generation.

    18. GK

      The next, it's close.

    19. LF

      What?

    20. GK

      Okay, Anand short, Anand, uh, uh, the... Sherukh... Kramnik is already 12 years younger. So that's the ne-

    21. LF

      Yeah.

    22. GK

      That's... But still, yet I, I competed with them and I just outbeat most of them and, and I was still dominant when I left at age, uh, um, 41. So-... back to Magnus. Magnus, I mean, consistency is phenomenal. The reason Magnus is, is on top and, uh, it's, seems unbeatable today, Magnus is, is a lethal combination of Fischer and Karpov, which is very, it's very unusual because Fischer's style was very dynamic, just fighting to the last point, just using every resource available. Karpov was very different, as just he had an unparalleled ability to use the... Every piece was a maximum effect, which is this minimal resources always produce maximum effect, just... So, now imagine that you merge these two styles. So it's, it's, it's like, you know, it's a squeezing every stone for a drop of water.

    23. LF

      (laughs)

    24. GK

      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 this passion and energy, and at the same time being as meticulous and, and, and, and deadly as, as, as, as Karpov by just, you know, using every little advantage. So, and, um, 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.

    25. LF

      I didn't know that, yeah.

    26. GK

      There are latest studies shows that chess players burn thousands of calories, uh, uh, uh, during the game. So, that puts him on the top of this field of, o- 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 '80s-

    27. LF

      Yeah.

    28. GK

      ... could beat Magnus Carlsen today, I mean, it's totally irrelevant because Garry Kasparov in 1989, okay, played, uh, great chess but, still, I knew very little about chess compared to Magnus Carlsen 2019.

    29. LF

      Yeah.

    30. GK

      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, uh, "Who is your favorite? Pele, Maradona or Messi?"

  8. 23:07 – 27:31

    Deep Blue 1997: first true match loss, anger, and reframing chess as a ‘closed system’

    1. LF

      Your loss to IBM Deep Blue 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 the civilizations 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, and the entire generation of AI researchers. And yet, to you that loss, at least if reading your face, was... 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?

    2. GK

      Uh-

    3. LF

      Or, or was that exactly why it was that painful?

    4. GK

      Oh. Ugh. As I already said, losing was painful, physically painful.

    5. LF

      Physically.

    6. GK

      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.

    7. LF

      Yeah.

    8. GK

      Uh, that's... Yeah. Uh-

    9. LF

      Oh, wow.

    10. GK

      (laughs)

    11. LF

      Oh, wow.

    12. GK

      Yeah, it's-

    13. LF

      Right.

    14. GK

      Yeah, uh, that, that makes all the difference to me.

    15. LF

      Yes.

    16. GK

      First time I lost. It's just... Now, I lost and, uh, the reason I was so angry that I just, you know... I had-... uh, suspicions that my loss was not just the result of my bad play.

    17. LF

      Yes.

    18. GK

      So, though I played quite poorly, you know, just when you start looking at the games today, I made tons of mistakes. But, you know, I, I had all reasons to believe that, you know, there were other, 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 water under the bridge. We can analyze this match, and this is, with everything you said, I, I agree, with probably one exception. Is that, uh, considering chess, you know, as the sort of, uh, as a pinnacle of intellectual activities was our mistake. Because, you know, we just thought, "Oh, it's, uh, it's a game of the highest intellect and it's just, you know, you have to be so, you know, intelligent, and that you could see things that, you know, the, uh, the ordin- the, the, uh, ordinary mortals could not see."

    19. LF

      Mm-hmm.

    20. GK

      It's a game. And, uh, uh, 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 Claude Shannon, the number of legal moves is 10 to the 46th power.

    21. LF

      Mm-hmm.

    22. GK

      Too many zeros. So, just for-

    23. LF

      (laughs)

    24. GK

      ... any computer to finish the job, you know, uh, uh, in, in, in, in next few billion years.

    25. LF

      Yeah.

    26. GK

      Uh, but it doesn't have to. It's all about making fewer mistakes. And I think that's the ... This match actually, and what's happened afterwards with other games, with, with Go, with shogi, uh, with, uh, video games, it's a demonstration that it's the machines will always beat humans in what I call closed systems.

    27. LF

      Mm-hmm.

    28. GK

      The moment you build a closed system, no matter how the system's called, Chess, Go, shogi, Dota, uh, machines will prevail simply because they will bring down number of mistakes. Um, machines don't have to solve it, they just have to, uh, it's... The way they outplay us, it's not by just being more intelligent. It's just by, by doing something else, but eventually, it's just-

    29. LF

      (laughs)

    30. GK

      ... it's capitalizing on our mistakes. When you look at the chess machines ratings today, and compare it, compare this to Magnus Carlsen, it's the same as comparing Ferrari to Usain Bolt.

  9. 27:31 – 31:22

    From human-vs-machine to human-with-machine: engines, ties in 2003, and how computers changed chess forever

    1. GK

      further encounters with computers, and sort of the, the current state, state of affairs with AlphaZero, uh, beating other machines. The idea that we can compete with computers in so-called intellectual fields, it's, uh, it was wrong from the very beginning. It's just, it's... By the way, the 1997 match was not the first victory of machines over-

    2. LF

      Over grandmasters. Over che-

    3. GK

      ... over grandmasters.

    4. LF

      Yeah.

    5. GK

      No. Actually, it's, I played against first decent chess computers from late, from late '80s. So, I played with a prototype of Deep, uh, Blue called Deep Thought in 1989, two rapid chess games in New York. I won handily, b- both games. We played against, uh, new, um, chess engines, like Fritz and other programs. And then, it's the, was Israeli program, Junior, that appeared in 1995.

    6. LF

      Right, right, right, I remember.

    7. GK

      Yeah. So there, there were, there were several programs. I, you know, I lost few games in blitz. I lost one match against a computer, a chess engine in 1994, rapid chess. So, I lost one game to Deep Blue in 1996 match, the man I, the match I, I won. Some people, you know, tend to forget about it that I won the first match. (laughs)

    8. LF

      Yes.

    9. GK

      But it's, it's, we m-... We made a very important psychological mistake, thinking that the reason we lost blitz matches, five, 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 mistakes. Nonsense. So there's, yeah, we had more time, but we still made mistakes. And machine also has more time. And machines, machine will always, you know, uh, uh, will always be steady and consistent compared to humans' instabilities and inconsistencies. And, um, today, we are at a point where, yes, nobody talks about, you know, uh, humans playing against machines. Now, machines can offer handicap to, to, to top players, and still, you know, uh, uh, will, will, will be favored. I think we're just learning that it's, it's, it's no longer human versus machines. It's about human working with machines. That's what I recognized in 1998, just after licking my wounds and spending one year and just, you know, ruminating so the, so what's happened at, i- in this match. And I knew that though we're still good playing against the machines, I, I had two more matches in, uh, in 2003 playing both, uh, Deep Fritz and Deep Junior. Both matches ended as a tie.

    10. LF

      Mm-hmm.

    11. GK

      Uh, though these machines were not weaker, at least, actually probably stronger than Deep Blue, um... And by the way, today, uh, chess app on your mobile phone-

    12. LF

      (laughs)

    13. GK

      ... is probably stronger than Deep Blue.

    14. LF

      Than Deep Blue, right?

    15. GK

      I'm not speaking of any- about chess engines that are so much superior. And by the way, when you analyze games we played against Deep Blue 1997 on your chess engine, they'll be laughing.

    16. LF

      Yeah.

    17. GK

      So this is, and it's also shows that's how chess changed, because, uh, chess commentators that look at some of our games, like game four, game five, "Brilliant idea!" Now, you ask, uh, um-

    18. LF

      (laughs)

    19. GK

      ... Stockfish, you ask-

    20. LF

      Yeah.

    21. GK

      ... Houdini, uh, you ask Commodore, all the leading chess engines.

    22. LF

      Yeah.

    23. GK

      Within 30 seconds, they will show you how many mistakes both Gary and Deep Blue made- (laughs)

    24. LF

      (laughs)

    25. GK

      ... (laughs) in the game that was, uh, uh-... uh, uh, trumpeted as the, as a great, uh, uh, chess match in 1997.

    26. LF

      Well, okay. So, y- 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, I mean-

    27. GK

      In, by the way, in Europe.

    28. LF

      Yeah.

    29. GK

      Because, you know, you move to the Far East, they will go... They, they, they had shown-

    30. LF

      Right. Games, games.

  10. 31:22 – 33:57

    Open-ended vs closed systems: what humans still contribute and why ‘asking the right questions’ matters

    1. LF

      So if I push back a little bit, so now y- you say that... Okay, but it was a mistake to see chess as the epitome. And now... 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, can you talk about what those things might be? And do you think, just like chess, they might fall-

    2. GK

      Um-

    3. LF

      ... soon, with the same set of approaches, if you look at AlphaZero, the same kind of learning approaches as the machines grow in size?

    4. GK

      No, no, it's not about growing in size. It's about, again, it's about, uh, understanding the difference between closed system and open-ended system.

    5. LF

      So you think that key difference... So the board games are closed in terms of the, uh, the rules-

    6. GK

      Rules, rules.

    7. LF

      ... set, the actions-

    8. GK

      Simple rules.

    9. LF

      ... the state space. Everything is just constrained. You think once you open it, the machines are lost?

    10. GK

      Uh, not lost, but again, the effectiveness is very different because machine does not understand the moment it's reaching territory of diminishing returns.

    11. LF

      Hm.

    12. GK

      It's the... Sim- to put it in, in, in, in, in, 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 there's the... It's like about the... It's the, it's a direction. So these... It's... I think it's in human-machine relations we have to consider so, uh, our role. And people, many people feel uncomfortable that this, the territory that, that belongs to us is, is shrinking. Uh, I'm saying, so what, you know? This is... Eventually we'll belong to the last few decimal points. But it's like having... So a very powerful gun, that's... And, and, and all you can do there is slightly, you know, alter direction of the bullet. Maybe, you know, .1 de-, uh, uh, degree of, of this angle. But that means a mile away, 10 meters of target. (laughs)

    13. LF

      Yes.

    14. GK

      So, so that's... We have to recognize that there's a certain unique human qualities that machines, in a foreseeable future, will not be able to reproduce. And, uh, and the effectiveness of this cooperation, collaboration depends on our understanding what exactly we can bring into the game. So, uh, the greatest danger is when we try to interfere with machine's superior knowledge. So that's why I always say that sometimes you'd rather have... By reading this as, as pictures in radiology, uh, you may probably prefer an experienced nurse than, rather than having top professor.

    15. LF

      Mm-hmm.

  11. 33:57 – 37:40

    AlphaZero and ‘machine-produced knowledge’: intuition-like patterns and the flexibility gap

    1. GK

      Because she will not try to interfere with machine's understanding. So this... 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, it's, it happened. We... It's like in chess. Recognize they do it better. See where we can make the difference. Y- you mentioned AlphaZero. I mean, AlphaZero is, it's, it's a... It's actually a first step into what you may call AI.

    2. LF

      Right.

    3. GK

      Because everything that's being called AI today is just... It's, uh, it's, it's one or another variation of what Claude Shannon characterized as a brute force.

    4. LF

      Yeah.

    5. GK

      It's a type A machine, whether it's Deep Blue, whether it's, uh, Watson, it's... And all these, these systems, the modern technologies that are being trumpeted as, as AI, it's still brute force. It's the... All they do, it's they do optimization.

    6. LF

      Mm-hmm.

    7. GK

      It's this... They are, you know... They, uh, they keep, you know, improving the way to process human-generated data.

    8. LF

      Mm-hmm.

    9. GK

      Now, AlphaZero is the first step towards, you know, machine-produced knowledge.

    10. LF

      Yes.

    11. GK

      Which is, by the way, by the way, it's quite ironic that the first company that championed that was IBM.

    12. LF

      (laughs)

    13. GK

      Oh, it's, it's... In backgammon.

    14. LF

      Interesting.

    15. GK

      In backgammon.

    16. LF

      Backgammon.

    17. GK

      Yes. You just... You should, you should, you should look at IBM as this. It's in Eurogammon. It's the, it's the scientist called Tesaro.

    18. LF

      (laughs) So interesting.

    19. GK

      He's still working at IBM. They had it in early '90s. It's just... It's the, it's the, you know, the program that played, you know, the AlphaZero type. So just trying to come up with own strategies. But because of success of Deep Blue, this project, uh, had been... Not abandoned, but just, you know... It's, it's, it wasn't... It was put on hold. And now, it just, you know... It's, it's, it's, uh, you know... It's everybody talks about, about these, the, 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 e- data. Many ideas that AlphaZero generate in chess were quite intriguing. So I, I, I looked at these games with... Not just with interest, but with, you know... It was quite exciting to-

    20. LF

      Mm-hmm.

    21. GK

      ... learn how machine could actually, you know, juggle all the pieces and just, uh, uh, play positions with the broken material balance, sacrificing material, always being ahead of other programs, you know, one or two moves ahead by, by foreseeing the consequence. Not over-calculating, because machines, other machines were at least as powerful in calculating.

    22. LF

      Mm-hmm.

    23. GK

      But it's having this unique knowledge based on discovered patterns after playing 60 million games.

    24. LF

      Almost something that feels like intuition.

    25. GK

      Exactly. But there's one problem.

    26. LF

      Yeah.

    27. GK

      Now, uh, the simple question. If, if AlphaZero faces superior opponent, let's say another powerful computer-... accompanied by a human, who could help just to discover certain problems. Because I already, I looked at many AlphaZero games. I visited their lab, you know, spoke to Demis Hassabis and his team, and I, I know there's certain weaknesses there. Now, if these weaknesses are exposed, the next 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 can... It's just because the whole system is based.

    28. LF

      Yeah.

    29. GK

      So, it's... Now, imagine so that says 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, uh, um, so the, uh, uh, most valuable part in this collaboration. So, it's... It will help us to understand what are the next steps in human-machine collaboration.

  12. 37:40 – 38:41

    Machines, morality, and bias: AI as a mirror that amplifies society’s flaws

    1. LF

      Beautifully put. So, let's talk about the thing that machines certainly don't know how to do yet, which is morality.

    2. GK

      Machines and morality. That's another question that, you know, just it's, it's, uh, is being asked all the time these days, and it's... I think it's another phantom that is haunting, uh, our general public because it's just being fed with these, you know, illusions is that how can we avoid machines, you know, uh, having bias-

    3. LF

      Yeah.

    4. GK

      ... being prejudiced?

    5. LF

      Yeah.

    6. GK

      You cannot, because it's like looking in the mirror-

    7. LF

      Yes.

    8. GK

      ... and complaining about what you see. If you have certain bias in the society, machine will, will just follow it.

    9. LF

      Yeah.

    10. GK

      It's just... It's, it's... You know, y- you look at the mirror, you don't like what you see there, you can, you know, uh, you can break it, you can try to distort it-

    11. LF

      Yeah.

    12. GK

      ... or you can try to actually change something just-

    13. LF

      By yourself. So, they show-

    14. GK

      By, by yourself, yes. So, it's, it's very important to understand is this, is that you cannot expect machines to, to improve-

    15. LF

      Yes.

    16. GK

      ... the ills of our society. And moreover, machines will simply, you know, just, you know, amplify it.

  13. 38:41 – 40:42

    Safety, autonomy, and the double standard: why we demand more perfection from machines than humans

    1. LF

      Yes. Yeah, but the thing is, people are, uh, more comfortable with other people doing injustice with, with being biased. We're not comfortable with machines having the same kind of bias. So, uh, that's a, that's an interesting standard that we place on machines. With autonomous vehicles, they have to be much safer. With, uh, automated systems-

    2. GK

      Of course, of course, they're much safer. Statistically, they're much safer than, than-

    3. LF

      That's not an "of course." Why would they... It's not an "of course." It's, it's not given. Autonomous vehicles, you have to work really hard to make them-

    4. GK

      No, but it's the, it's, it's-

    5. LF

      ... safer.

    6. GK

      Uh, I, 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, uh, 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 v- vehicle and it's front page of the newspaper.

    7. LF

      Yes. So, yes.

    8. GK

      So, it's the... It's again, it's about psycho... (laughs) 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 100% perfection. That's another, that's another important fake story that, that, that is being fed to the public. If machine doesn't reach 100% performance, it's not safe. No. All you can ask any computer, whether it's, you know, playing chess or, or doing the stock market calculations or, uh, driving your autonomous vehicle, it's to make fewer mistakes.

    9. LF

      Mm-hmm.

    10. GK

      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? Yeah, okay, it's life. If one of, one of these cars is autonomous v- vehicle... And by the way, even if it's h- it's human's fault, terrible. How could you allow a machine to-

    11. LF

      (laughs)

    12. GK

      ... uh, to, to, to run without a driver at, at, at the wheel?

  14. 40:42 – 42:00

    Deep Blue revisited: anger aimed at IBM’s humans, match politics, and the ‘Brain’s Last Stand’ pressure

    1. LF

      So, you know, let's linger that for a second, that double standard. The way you felt with your first loss against, uh, DeepBlue, were you treating the machine differently than you would have a human? Or, so, what do you think about that difference between the way we see machines and humans?

    2. GK

      No, it's the... At that time, you know, for me, it was a match, and that's why I was angry because I believed that-

    3. LF

      You lost.

    4. GK

      ... the match was not, you know, fairly organized. So, it's the, it's, uh, uh, definitely there were unfair advantages for, for IBM and I went to play their... Another match. It's like a rubber match.

    5. LF

      S- so your a- a- anger or, uh, displeasure was aimed more, like, at the humans behind IBM versus the actual pure-

    6. GK

      Yes, absolutely.

    7. LF

      ... algorithm?

    8. GK

      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.

    9. LF

      Yeah.

    10. GK

      Yeah, so this... And that's the... And it'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, uh, from 1996. And I... But I still could beat them up with the machine, so I made too many mistakes. Also, this is the whole, it's this, the publicity around the match.

    11. LF

      Yeah.

    12. GK

      So, I, I underestimated the effect, you know, just it's... And the... And being called the, you know, the, the, the Brain's Last Stand, you know, it's okay.

    13. LF

      (laughs)

    14. GK

      N- no, no pressure.

  15. 42:00 – 45:50

    From Soviet history to Putin: totalitarianism’s failure, moral clarity, and the unfinished reckoning with communism

    1. LF

      (laughs) Okay, well, let me ask. Uh, 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?

    2. GK

      I think the lesson of history is clear. Uh, undemocratic systems, totalitarian regimes, systems that are based on controlling their citizens and just, uh, every aspect of their life, not offering opportunities to... for private initiative, central planning systems, they're doomed. They just, you know, they, uh, they cannot...... the driving force for innovation. So they, in, in history timeline... I mean, they could cause certain, you know, distortion of, of, uh, of, uh, the concept of progress. Uh, they, by the way, they call themselves progressive, but we know that is this... The damage that they caused to, to humanity is just... It's, it's yet to be measured. But at the end of the day, they fail. They fail and it's, uh... 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 because the fact is... I always like to mention, you know, one of my favorite books, The Lord of the Rings.

    3. LF

      (laughs)

    4. GK

      That the... There's no, there's no absolute good.

    5. LF

      Yeah.

    6. GK

      But there's an absolute evil.

    7. LF

      Yeah.

    8. GK

      Good, you know, comes in many forms but, eh, we all, you know, it's... Being humans or being even, you know, humans from fairy tales or just some sort of, uh, mythical creatures, it's the... You can always find a spot on the sun. So this is w- conducting war and just... And, and fighting for justice. There are always things that, you know, can be easily criticized.

    9. LF

      Mm-hmm.

    10. GK

      And human history is the... is a never-ending quest for perfection. Uh, but we know that there's absolute evil. We know it's... For me, it's now clear that it's... I mean, nobody argues about Hitler being absolutely evil, but I think it's very important to recognize Stalin was absolutely evil. Communism caused more damage than any other ideology, uh, uh, in the 20th century. And unfortunately, while we all know that fascism was condemned, there was no Nuremberg for commun- communism. And that's why we could see, you know, still this... The, uh, this, the successors of Stalin are feeling, uh, far more comfortable.

    11. LF

      So, you, you-

    12. GK

      And Putin is one of them.

    13. LF

      You highlight a few di- interesting connections actually between Stalin and Hitler. I mean, that there... The... In, in terms of the, uh, 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-

    14. GK

      Well, you can ask it. I just, I just recently delivered a speech in Toronto-

    15. LF

      Yeah.

    16. GK

      ... uh, at 80th anniversary of Molotov-Ribbentrop Pact.

    17. LF

      Yes.

    18. GK

      It's something that I believe, you know, just, you know, has... Must, must be taught in the schools. That the World War II, uh, uh, had been started by two dictators-

    19. LF

      Yes.

    20. GK

      ... by signing these, these, uh, 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 a- attacked him. So it just doesn't, you know, uh, um, eliminate the fact that Stalin helped Hitler to start World War II and he was one of the beneficiaries at early e- at early stage by, uh, annexing, uh, part of Eastern Europe. And as a result of 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.

  16. 45:50 – 49:17

    Personal risk and political resolve: exile in New York, fear management, and prediction of sudden regime collapse

    1. LF

      Mm-hmm. 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, in 2007, there's this interesting comment from Oleg Kalugin, KGB general. Uh, 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 is 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 th- in this kind of context when your life could be in danger?

    2. GK

      Uh, that's the reason I live in New York.

    3. LF

      (laughs)

    4. GK

      So it's the... Was not my first choice, but I knew I had to leave Russia at one point and, uh, 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, and what is happening with many of Putin enemies. But at the end of the day, I mean, what can I do? I mean, it's... I, uh, I could be very proactive by trying to change things I can influence, but here are where facts. I, uh, 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. Uh, there's so many invitations to speak at different locations in the world and I have to say that, uh, many countries are just now... Are not destinations that I can afford to travel. Uh, 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, uh, 1971, so she was 33 and she dedicated her entire life to her only son. But she recognized, you know, just year or so since I left Russia, that it was the only chance for me to continue my normal life. So just is to... I mean, to be relatively safe and to, to do what she taught me to do, to make a difference.

    5. LF

      Do you think you will ever return to Russia? Or let me ask a different way-

    6. GK

      Oh, sure.

    7. LF

      When will you return to Russia?

    8. GK

      Even sooner than many people think, because I think Putin's regime is facing insurmountable diff- uh, d- difficulties. And, uh, 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-... his, his bust. There's good news and bad news. I mean, the, the bad new is that I don't know when and how Putin rule ends. The good news, he also doesn't know.

  17. 49:17 – 52:23

    Russian interference and the Trump era: ‘asset’ framing, NATO risk, and Western political blind spots

    1. LF

      (laughs) Okay, well put. Let me ask, um, a question that seems to preoccupy the American mind from the perspective of Russia. One, did Russia interfere in the 2016 US election, government sanctioned? And future, two, will Russia interfere in the 2020 US election? And what does that interference look like?

    2. GK

      It's very odd, you know. We had such an intelligent conversation.

    3. LF

      (laughs)

    4. GK

      And, and you are ruining everything by asking such a stupid question.

    5. LF

      (laughs)

    6. GK

      It's just-

    7. LF

      It's been going downhill the entire way.

    8. GK

      ... it almost, it's, it's, yeah, but it's, it's, it's, it's insulting for my intellect.

    9. LF

      Okay.

    10. GK

      Of course, they did interfere.

    11. LF

      (laughs)

    12. GK

      Of course they did absolu- everything to elect Trump. I mean, they said it many times. It is just, you know-

    13. LF

      Yeah.

    14. GK

      ... I met enough KGB colonels in my life to tell you that, you know, just the way Putin looks at Trump.

    15. LF

      Yeah.

    16. GK

      This is the way, looks, and I don't have to hear what he says, what Trump says, you know, just is, I don't need to go through con- congressional investigations. The way Putin looks at Trump is the way the KGB officers looked at their assets. It's just, and falling to 2020, of course they will do absolutely everything to help Trump to survive because I think the damage that Trump's reelection 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, uh, uh, hurdles. Uh, if he's still in the office after, uh, November 2020, okay, January 2021, um, I don't want to think about it. My problem is not just Trump, because Trump is basically a symptom. But the problem is that I don't see, it's just, it's the (laughs) in American political horizon, uh, politicians who could take on Trump, uh, um, for, for all damage that he's doing for the free world, not just things that just happened that went wrong in America. So there's the, it seems to me that the campaign, political campaign on the Democratic side is, is fixed on certain important but still secondary issues.

    17. LF

      Mm.

    18. GK

      Because when you have the foundation of the republic in jeopardy, I mean, you cannot talk about healthcare. I mean, I understand how important it is, but it's still secondary because the entire framework of American political life is at risk.

    19. LF

      Yeah.

    20. GK

      And you have Vladimir Putin just, you know, just, uh, it's having virtually free hands by, by his, by attacking America and other free countries. And by the way, we have so much evidence about Russia interference in Brexit, in elections in almost every European country. And thinking that they will be shy of attacking America in 2020 now with, with Trump in the office, yeah, uh, I think it's, um, again, it definitely diminishes the intellectual quality of our conversation (laughs) .

  18. 52:23 – 55:08

    No single moment to relive: butterfly effects, life balance, family, and sustained purpose

    1. LF

      (laughs) Uh, 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?

    2. GK

      Uh, um, uh, there are moments in my life when I think about what could be done differently. But...

    3. LF

      No, experience happiness and joy and pride. Just, just to, just to touch once again.

    4. GK

      I know, I know, but it's the, it's the, it's, look, I made many mistakes in my life. So I just, it's the, uh, I, I know that. At the end of the day, it's just, I believe in the butterfly effect. So it's the, it's the I knew 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 won't have all other accomplishments?

    5. LF

      (laughs)

    6. GK

      Yeah, I just, I'm, I'm afraid that, you know, we just have to just follow this, if, if you may call wisdom a Forrest Gump, you know.

    7. LF

      (laughs)

    8. GK

      It's the life is this, you know, it's, this is, it's, it's a box of, of, of, of-

    9. LF

      Yeah.

    10. GK

      ... of chocolate and you don't know what's inside but you have to go one by one. So it's the, I'm, I'm happy with who I am and where I am today. And I am very proud not only with my chess accomplishments but that I made this transition. And since I left chess, you know, I built my own reputation that had some influence on the game of chess but not, it's not, you know, directly derived from, from, from the game. Uh, I'm grateful for my wife, so 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.

    11. LF

      (laughs)

    12. GK

      But, uh, uh, and by the way, I'm close with two kids from my previous marriages.

    13. LF

      Nice.

    14. GK

      So that's, that's the, I'm, you know, I managed to sort of to balance my life and, uh, and here, you know, I live in New York so we have our two kids born here in New York. Uh, it's, it's new life and it's, you know, it's, it's busy. Sometimes I wish I could, you know, I could limit my engagement in many other things, uh, that's, that are still, you know, um, uh, taking time and energy. But life is exciting and, um, as long as I can feel that I have energy, I have strengths, I have, uh, passion to make the difference, I'm happy.

    15. LF

      I think that's a beautiful moment to end on. Garry (Russian) . Thank you very much for talking today.

    16. GK

      Thank you (Russian) .

Episode duration: 55:23

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