Lex Fridman plays Red Dead Redemption 2

We're playing Red Dead Redemption 2, a game that my good friend Ng has recommended. We met in Austin, but she's now in Boston, Cambridge, working on exoskeletons. And robotic limbs. And robotic limbs, which in the future I guess would be cyborgs. We started playing it a little bit ago, and it's way better than I imagined. So the dialogue is great. But just even the dynamics of horses, because I thought it was just going to be grand theft auto on a horse, but there's so much more to this game. Well right now we're in story mode. If we played free play, we could find a random horse and train it. Yeah, but it's cool that the horse gets tired, you have to take care of it. Just the harsh conditions of snow as a start of the story is incredible. You ever ridden a horse? Yeah. You're laughing because there's a picture of me on the internet on a horse. Okay, I'm not sure this is going to be a lot of shooting. Is it Y to take out the gun? I don't think we have a gun. I picked up where you left off. No, why did I get off the horse? Okay, check your pockets. Oh, you've got your binoculars. I know you have in your pocket. But the gun, I don't know. I don't know if you have any weapons. What happened? What happened to our weapon? I don't know. I wasn't here for that. All I did is I played it for like five more minutes and I shot the wolves that were attacking. Oh, the wolves? What happened with the wolves? That's how you wasted all of your ammo? With the wolves? Yeah, there's like five of them. It was as difficult as you don't. How long did it take? You said it took you five minutes? No, I did. Yeah, it was five minutes because it was just one little chase, but it took me like three attempts because I was trying to get better at aiming because I kept killing the other guy. Oh, there's a bit of a fight. It's like we're about to go into combat. Anyway, I mentioned Austin. Do you remember how we met? How long ago was this? It was like a year and a half ago, I think. In the summer, right? I came to visit some friends and that was at a coffee shop and we ran into each other. Yeah. And that was, and since then, when did you go to MIT? That was recent, right? Very recent. That was in September. It's been fun. The winter is very cold, though. So this is your first cold place, right? Yeah. And I love the heat. Like the Texas heat was great. 96 degrees, walking on the trail. Yeah, it's nice. I love it. How do I pull out a gun? I don't know if you have a gun. Hold LB. Oh, you have a gun. Nice. Okay, so how do you do the, you know, like you can swap through the different guns you have. How do you think you could flip through it? No. I don't need guns. I use fists, bro. Okay, but the revolver might be enough. Okay. Approach our horse. I think it's more entertaining when you play this. Because I'm so bad at it. It's just so great. It's just an incredibly gorgeous game. Just like the snow, the sound of it. I also put it on cinematic mode. Which does what? Which does what? Just the views of it. It's not really first person. It's not as pleasant for playing the game, but it's pleasant for watching someone else play. Okay, is this not my horse? Just for the record, we're both noobs at this game, but it's more fun this way. Yeah. Okay, horse weapons. I saw that you can skin animals. There's a lot of really interesting stuff. R key to cycle. Oh, there we go. Yeah, there you go. I told you. How do you swipe? How do you? R key to cycle? R key. R key. Cool. Okay. Why do I need to go? Why do I still need to do this? I remember like it was yesterday. All the wolves I killed were there. Our needs right now are supplies. Nice twirl. Everything else, including comb, can wait. Okay. This guy walks really slow.... to deal with as it is. But come on. I don't think these guys are in touch with their feminine side. Why don't you think that? Just everything they're doing is like the most masculine. Their coats are pretty long. That's true. It's pretty feminine. Look, three-year kilt. Probably no, or a skirt. I guess a kilt isn't. What do you think about kilts? Um, I think they're pretty awesome. I mean, it's pretty aggressive. Could take. Buy one, but... Yeah, if you're not Scottish. Just in general. Just sport a kilt. It's just like an aggressive move. Walk around Boston in a kilt. A giant coat in a kilt. I mean, I don't wear a skirt in the winter. You think I can go to the gym in a kilt? Just work out. Just do curls. Might be kind of stinky. Would I get kicked out of Planet Fitness if I wore a kilt? I mean, well, you have to think about it this way. Like, would I get kicked out of Planet Fitness if I wore a skirt to the gym? I don't think they think of it that way. They'll just see me in a kilt. It's like, excuse me, sir. You're scaring. You're scaring everyone. And you're making all kinds of sounds. You would make sounds while you're wearing a kilt? Yeah, you have to. You have to make the sounds? Like William Wallace. I'll paint my face blue, whatever, and stripes. Like Braveheart? Wow. Wow. It's cheesy as hell, but it's epic. It's a great speech. Is it? It's a good monologue? No, he does a speech where they're the underdogs and they have to fight the British. He basically says, like, we can run and keep our lives, or we can stand here and fight for our freedom. And the question is, you have to imagine years from now, when you're in your deathbed and you're looking back, would you come back here for just one more chance to fight instead of fleeing? It's a good speech. Gotta be brave. Yeah. Sometimes you have to put your life on the line. Bravery is important. I was talking to my nephew about this recently. So he plays, I think it's called Minecraft. Yeah. And there's zombies in the game, and he knows a way of, like, escaping whatever conflict he's in so that he doesn't have to face it. And I told him that in life, it's really important to be brave because you can't always run away from your problems. So I think bravery is super important. What are they saying? Should I take the lead or should I send the gang? What do you mean? You have those options? I have those options. No, take the lead, send the gang, send the gang. Oh, lead from the back. All right. Oh, shoot. Where is, where are the people? Oh, that's right. I didn't see the dot. The screen is humongous. Yeah, it's ridiculous. Should I bring the thing closer? No, it's good. Oh, shoot. I keep on getting shot. How do I hide? Oh, this is getting real. Hold on. How do I crouch again? Sometimes you have to put, just like you said, you have to put your life on the line. It's worth it. It was worth it at the end. Retry checkpoint. Don't restart the mission. Is that an A? A. Oh, you have to hold it. Yeah, because restarting the mission, we're going to go through that whole walking thing. So what is it? Is it Y to shoot? No. To take out the gun? This is really hard. I know. It's hard to like chat and do this. Yeah. You try it. Okay. Oh, shit. That was me. That wasn't you. That was me. Yeah, that was you, me, and me. That was me. It was animating your death shot. Yeah, I did so good. Nice. Oh, there's someone there. All right, where are the people? Oh, nice. Oh, where are the... Who is it? I don't think there's anybody behind you. I think you're imagining things. Nice. Oh, no. But I figured it out now. Okay. What are we doing, Dutch? I mean, by the minute, becoming more and more of a cowboy. Thank God we're in Texas. Where's the set? Do you know? I don't know. I could look it up. Oh, my phone's trying to charge. Oh, there's a guy. Oh, there's a guy. Oh, there's a guy. Oh, there's a guy. Oh, my phone's charging somewhere over there. Did you hear what he said? I don't go down that easy. You just shot him twice. Just to prove a point. Sounds like your claim was false. You need to eat. Oh, oh, oh. I need to eat. Oh, wait. Yeah, all right, cool. Hold on. What am I eating? Apples? You need to hold on. I think that's salt. Let's get. How do I switch over? Oh, I see. Okay. That thing. LB to use. Okay. Did that help? Let me see. I want to eat. Oh, shoot. No, no, no, no, no. Everything is fine. All right. I'm just keep dying. Oh, what? I restarted the mission. Yeah, just restarting the mission. We're going to go through that whole walking thing. That's good. Gives us a chance to relive the incredible graphics of this video game. Going faster. Were you pressing a while you were on the horse? Yeah, but not enough. I haven't figured out if you can just hold it or if you have to keep pressing it. It's complicated. I don't think I'm controlling it anymore. Yeah. This is gorgeous. Yeah, it's really beautiful. Have you ridden horses? Yeah, I used to go to a horseback riding camp. You like it? Loved it. I like horses a lot. They're very gentle. They're kind of like, well, they're better than dogs in a way. Like they're more loyal and they don't realize how large they are. Yeah. And they're really just sweet. I love horses. There's so many cliche things and this is great. This is like a mix of Grand Theft Auto and Skyrim. Because the nature scenes are beautiful. It's not always winter, right? Well, I think that I remember a version where it was winter. I'm sure the seasons change in the game. Winter is brutal. It's crazy. So you're not enjoying the craziness of it? At least a little bit? I mean, I think it's bonding for the people that live there. Because you get to complain? Yeah, because they get to complain together. And you get to appreciate it deeper when it's actually warmer. When it's like a different season. Yeah. When the seasons change. It is beautiful when it snows. We recently, it was a weekend where it was like negative 11 degrees or something. It's crazy. You ever build a snowman? Once, but when I was younger. Have you? Yeah, all the time. All the time? Yeah. I used to really enjoy eating snow and then people would tell me you shouldn't do that. And I said, I would still do it. Why did you keep doing it? Just a rebellion and you couldn't live with it. Yeah, it tastes good. I see. It tastes good. I don't know. Do you chew on ice too? No. No, it's like, it's refreshing, but I think it's probably horrible for you. Because all kinds of stuff can be in the snow. I don't think I was so much concerned about my health or immune system when I was young. Probably made it stronger. Yeah, probably. Kids these days. They're not eating enough snow. They don't know what it was like. What's the scariest thing you've ever done? Scariest? Skydiving. Did you skydive? I've gone skydiving. I think probably scuba diving. Because I didn't take a class or anything and I was scuba diving. We went under the water and there were stingrays. And it was like this really weird feeling of like, this may go very wrong, but I feel like the people around me are very competent, so they'll take care of me if something happens. Yeah, the same thing for skydiving for me. Yeah. Have you ever killed a man? No, have you? Yeah. Lost count. I'm really taking this game in. The spirit of this game. Just killed many cows. Just killed many cowboys in my day. If you had the opportunity to live in this time for like a year, would you? Oh yeah, probably. Like a vacation, but the opposite of a vacation. Could I come back? Yeah, yeah, yeah. But you know, you have to stay for a whole year though. Whole year I would do it. Okay. Yeah. My lab, they do this thing where they go to Africa and they help people and you stay for a month. But it's like these really harsh conditions. I think two of the girls that recently went, they got really sick while they were there. But you're helping these people who don't have access to these limbs. Yeah, probably also helps you appreciate. Yeah, everything that you have access to readily. You guys are suspiciously close together. I know. We're like, hey. Hey. What are you thinking about, Jan? All right, let's go. Wait, wait, wait. Why isn't it letting me? All right. Oh, that's what it was. I only had my fist. Oh, shoot. Nice. I really want to get this guy. Okay. All right, come on. Obviously, we're not very good at this game. Oh. It's kind of fun. We just keep. We just keep dying the same. But. Hey, how about this? What? Yeah. A, restart checkpoint. Okay. Hey. I'm the one that pointed that out. I pushed the restart mission by accident. That's true. What do you think about cyborgs? Do you think in 100 years, we'll all be partially robot? Yeah, I think we have to merge with technology in order to. In order to evolve with it, because it's evolving so quickly. If we don't evolve with it, it's like we lose a step in evolution. Yeah. Like it's the logical next step. Including brain. Yeah. BCIs and BMIs are the future. So you like the New York link stuff? Love it. Love it. There's a lot of awesome New York link people here in Austin. Are there? They were saying they want to give me a tour and meet them and stuff. I really want to meet them. And the surgeon. I talked to a few surgeons. They're just incredible people. I love it. Yeah. And the cool thing about New York link is they have all these different... How do I stop crouching? I don't know. Oh. Okay. That's fine. Crouching is good. It's a good look. I feel like you should be crouching. You're definitely safer. Yeah. But you look less gangster, but it's fine. The cool thing is they got all kinds of... They got materials, engineering people. They got electrical, robotics. Obviously, software engineering. They have to take care of the animals. That's a whole thing. Yeah. That's tough. I mean, I deal with a lot of animal stuff in our lab too. Like with the rats. The rats are a lot nicer than the mice. But I think they're dealing with monkeys, right? Yeah. No, they're doing everything. They do mice too, I think. But they're monkeys. And they make them super happy. And pigs too. Oh, that's wonderful. Yeah. I did gig a factory opening. There's an animal zoo you can rent. You can rent folks that... They'll bring a bunch of animals and you get to play with them. They're petting. It's a cool thing for a party. That's so cute. You just order a bunch of animals and you get to pet them. Like a goat and a bunny. You're talking about petting zoos? Yeah. But they're portable. You can bring it to your party. Yeah. Those exist. They usually come to children's parties. Yeah, it was hard. Yeah, they're great. I will forever be a child. Do you see any bad guys? No, but I hear someone shooting. Where? I don't know. They're shooting at someone. I feel like they're just shooting... They're just shooting at some of the things. Is it aiming at them? They're trying to look cool. They're shooting for the gram. I don't know. It's like you're going to the gun range. Okay. It's like me wearing the... The kilt. At the gym. I think I might eat the protein bar that's in your fridge. It's not... Can I just have a bite of it? Because I feel like my blood sugar is really low. It's not that good. Is it? Does this have sugar in it? No. Sadly not. Maybe it'll help me. I killed the last of them. The last of what? Of the powerade things? No, the last guy. You did? Yeah. I think the AI in this game is pretty shitty. It didn't pick up? They were just shooting around. They couldn't figure out what the enemy is. And the enemy couldn't figure out what the good guys are. And kill without thought. You're in. Whoa. Why did you buy that one? What do you mean? The protein bar. Because I went out yesterday and it was past midnight and I wasn't sure where to get food. So that's what you decided to eat? Yeah. I was ambitious. I got a different flavor and it was pretty good. What are they shooting at? Oh, there you go. Am I still shooting at somebody? Oh. Advance or defend? Advance. I think you should mount a horse. I don't live. You should mount a horse. I think it would be more fun and quicker. But you don't look as cool. Look how I'm walking. No cover. Not crouching anymore. Not crouching. Yeah. You made me angry. When I get angry, I don't crouch. Do you ever play shooters? Like Call of Duty? I'm not as into it. I like when there's a story. No. With Call of Duty, I think there's a story mode. Like single player. There is. But it's more like... It's a lot of this, but not as scenic. Yeah. It's also a little bit more military. So if you're into that kind of thing. I don't know which direction I'm being shot from. It doesn't show you on the map. Oh. I guess not. They're running away. There. I took care of everything. Thank you. What would I do without you? I don't know. I need to just chill with the guys, I think. Oh, we're going into different buildings. I'm not sure if I'm going to be able to shoot these guys. Nice. Okay. I like that we're delegating duties here. That's great. I mean, if there's anything I love to do in a game, it is forge. Forge something? That's great. You can do all of the fighting. I'm not good at fighting in this either. We're learning. I like the we in that. It feels like a team. This is great. I really thought this game would be way worse. Well, you didn't like Zelda. So I think that's why. Yeah, we should mention we played Zelda for a little bit before. And it was too fun. It was too adventure. It was too shallow. You like the accents in this game better? Yeah, this game is gritty. It's like... It feels like a movie I'd want to watch. Do you think you were a cowboy in a past life? What made you decide to live in Texas? What guy would answer no to that? No, I was... I was more of a carrot farmer. Like some very insignificant vegetable. Of course I was... No, you know what? Not a cowboy. Because the cowboys are the good guys usually, right? I think so. I mean... I was a bank robber. Bank robber? Do you... So you think that being a criminal would be a lot of fun? Yeah, I like the challenge of it. Yeah. I don't like the murder, but sometimes you have to do what you have to do to get the job done. It's like a puzzle? No, I'm just speaking like a cowboy. No. No, I think it's actually... would be, in this context, super challenging to... without hurting anybody to steal money. But you're going to hurt a lot of people. It's also very stressful. If you rob a bank in a small town at that time, you're probably hurting a lot of people. You think so? You think you have to kill someone? No, I mean like financially. Oh, yeah. That town is probably dependent on the bank. Although like... It's a really good show, Yellowstone. Oh, that's a great show. It's a great show. I've seen it. You've seen it? Yeah. Good job. It's more like a modern... I mean... You know... Without going into cowboy sounding cliches, there's a certain kind of ethic and value system you live under that I think is in part admirable. Oh, I clicked the wrong thing. What happened? Oh, we didn't get there in time. I'm sorry. We were chatting too much. I got distracted. Yeah. It's just beautiful. I like kind of chilling and walking around this world. Does it make you sad that we'll have cyborgs and robots and AI? No, I think if we merge with it, we have a really optimistic looking future. But you're going to lose some of the... this kind of cowboy humanness, you know? Well, I think that your humanness will be enhanced. Like the same way that, you know, money makes you rich, sure. But it just amplifies whatever type of person you are. I think it'll be the same thing with AI. Like it's just a current... It's amplifying whatever interests you have. So if you're very interested in, I don't know, art, you're going to be able to download all of art history and have access to it at any time that you need it. Yeah. Was that the guy that I was supposed to shoot? No. Oh. Oh, I think so. Don't hurt me. Is don't hurt me... Is he dying? Is that like a... reverse psychology or what? I think he has to die. Was I not supposed to kill him? Oh. Damn it. Oh no. We weren't supposed to kill him. Oh no. I think we're not paying attention to the mission and I think it's better that way. I think it's more entertaining. Yeah. I thought for sure he was trying to trick you. Yeah, I'm definitely excited about AI. But you have to be... You definitely have to be cautious. Especially about which companies get the control of it. I like the more companies, the more people have control. The more people have control of AI systems, the better. The distributed. That's the cool thing about ChadGBT is like, it's pretty easy to build. Relatively speaking. So a lot of companies will be doing it. How'd you know that? Wait, did you do that? Yeah, I did. Wait. What did I do? Hold on. Why is it going this way? Okay, that started so nice. I know, that really went well. Don't hurt me. Okay, hold on. Why is the horse... LT ready to lasso. Throw the lasso. RT. Cool. Alright. Now you're just flirting with him. And then dismount. How'd you kill him? I think you killed him. Press B near... Oh, hog tying him. Oh, nice. He's really playing dead for you. Yeah. Nice. He's done. Hold X and you just gotta pick him up. Alright. Are we kidnapping him? I think so. Approach the back of your horse and hold X to stow him? Yeah. I don't really think it's kidnapping. He's like broken, dying in the middle of the wilderness. I think you're saving him, honestly. Alright, let's get back on the horse, I guess. Wow, this winter is brutal. Do you think people will have relationships with AI systems? Yeah. Because the AI system will be able to, I think, guess your needs very quickly. But I think it'll get boring. I think it'll be... It'll be too perfect? Yeah. Would you date a robot? Um, maybe. Maybe for a little bit. I don't think it would be as fun as dating a human, though. Especially if humans merge with technology. Sure. Well... Fun. That's an interesting word. Yeah, I suspect that robots would be too perfect. But if it's... I think the human merging with the AI would be a very interesting combo. Yeah, I agree. Because then you wouldn't have this laggy brain that's like forgetting things. You would have more interesting conversations, and you would have like all of your passions. You would be able to dive in deep to them and then come up with really great ideas on how to explore those ideas and research would become more intuitive, I think. Yeah, it's a tricky thing, because you want some... Like, life should still have some challenge. It feels like a lot of our development happens in the face of challenge. Or we just find new challenges with the... Even though we gain extra abilities, we'll still find stuff that's challenging. This guy does not sound nice. Is that how you dress in Boston? Pretty much. Pretty much. It's too cold. I would always underdress. Did you? Were you driving a lot? No, I didn't have a car. I did do threadline and bus. I love it. I love taking the T. But I do bus much more. I would stand in the bus stop freezing. There's an intimacy. There's a romance to the bus. There is some romance to standing on the bus. There is some romance to standing outside while it's cold out. Like, you're bearing this cold, but why? What is it that you're doing that's so important that you need to be facing these elements? But you're also together with other people that are just standing there and suffering. And all pretending like we're not suffering, but we're suffering. But then we're not really suffering. It's just cold. It's just temporary, too. I never understood the romance. People would always post like, winter in Miami. And then post a picture of them on the beach. Oh, I see. They're trolling? Wait, didn't you do that? I've never done that in my life. I feel like you sent me a picture of winter in Miami. Oh, because you're now a boss. You feel like you've earned the right to. Yeah. We're going to starve to death up here, Mr. Morgan. I'm going to get you. We're going to starve to death up here, Mr. Morgan. We're okay. We have a few cans of food and a rabbit. For what, 10, 12 people? When I was in the Navy. I do not want to... You know, I was thinking about the barbecue. What about it? It was so good. Should we go back? Should. I think so. I'm very up for that. It's really good. It's so great. You take it for granted because I haven't gone in a while. It's so delicious. Where do you usually go? I just go to restaurants or just eat at home. Because it's like... I don't know why, it's almost too delicious. It's like a treat. It should be like a treat, but it's not really. It is really special though when you do have it. Because I feel like it takes a while to prepare that kind of food. They're smoking it all day, right? I like it because when visitors come, you go to Terry Black's and you do the barbecue. It's crazy. It's so good. And because there's so many... The bar is so high and then they still deliver. Yeah. It's cool. And it's consistently great. Every time you go, it's amazing. You know, one time my dad and I went. My dad used to do his residency here. And he was so excited. He was like, I can't wait to go have barbecue. I'm so excited you're going to live in Texas. All this stuff. We ate way too much and we got so sick afterwards. That's the challenge. There's a few tech folks here. They're really cool. We went out with them. But we got trashed. Like whiskey. Just so drunk. And what I didn't realize is when I'm that drunk, whatever module in my brain that says don't stop eating was off. Yeah, because your body is so relaxed. And I'm having fun and then all of a sudden it's a good idea to order like 10 pounds of meat. And then you're just... Well, not just me. Everybody together. We're just eating and eating. And it's so hard to stop because it's so freaking delicious. And then you're drunk. It's delicious. It's great while you're eating it. You know what I've noticed about unhealthy foods or like treats? It's always really fun while you're eating it. But before and after, there's always this feeling of regrets. Or like before you eat a cupcake or something, I always feel this feeling of I'm really going to regret this after I eat it but I really want it. And then while I'm eating it, I'm enjoying it. I'm like, oh, this is so good. I want another one. I have to really work on that to walk away. Walk away while you really want a thing and you say, nope, no more. God, that looks beautiful. Look at that. Do you ski? I have. I grew up cross-country skiing. Like, you know, not downhill. I don't know what that is. I was born in the mountains with the goats. No, I don't really... With goats? Why goats? Because they're really good with the mountains. Oh yeah, aren't they the ones that stand on the edges of... I have an inner goat. What's your favorite really bad meal that you shouldn't be eating? My favorite really bad meal that I shouldn't be eating? Cheap meal. Like something naughty? Probably like fried chicken. I love fried chicken. Like what kind? I don't think I've had much fried chicken. So you're talking about like KFC? No, so there's this grocery store in Miami. It's called Publix. And they have the best fried chicken. Like, it's so good. Oh, in like that little spot that keeps it warm? Yes, yep. And it's so good. And they have like thick and tender. It's super crispy and all that? Oh, it's so good. It's great. With sauce of some kind? No sauce. I'm not a sauce person. Okay, well that's no respect. Are you saucy? No, I'm not saucy at all. I'm just giving you respect. The people that cover themselves with sauce are the people that... Are you being the saucest? 100%. The people that... I'll have people here in Texas that were like like legit barbecue like aficionados or whatever you call that. They will put sauce on their barbecue. They'll like dip it and stuff. They'll have like different sauces, right? I did that the last time, I think. You did? I put a little bit of sauce on my barbecue. It's not cool. It's not cool. It's disrespecting the meat. It's just not cool. It's like putting ketchup on a steak, on an aged steak. I don't judge people for putting sauce, but for certain things I don't need sauce. I don't judge people. It sounds like you're very emotionally charged for this. For anything except putting sauce. Except putting sauce on their barbecue. It's the one thing I judge them on. No, I don't care. But it is... I like great basic ingredients. Why is it all slow motion? Because I activated eagle eye. I just don't know what I'm looking for. That's the problem. I keep chatting with you. And forgetting what we're doing. Oh, shoot. Alright, check it out. Oh, it's there. Oh, cool. It has a... What is that? It's like a scent? What is it?... We're looking for an animal. Okay, so then we focus on the track. And then... So all you have to do is press RB while focusing on the track. I just don't know where the track went. Oh, there we go. So you see how it's like... How do you know we're hunting for an animal? Oh, stop tracking. I see. It's a giant TV and the text is blurry. I'm pretty sure my vision doesn't suck that bad. No, it's definitely... I think it's just too much stimuli. Like it's just a giant screen. You don't know where to look. Giant screen on low resolution or something? I don't know what it is. It's just a quality thing. Oh, yeah. Oh, yeah. Is there any other ones? Go get them. Go get the meat. I don't know how to uncrouch. You press this button. Oh, okay. Let a man handle it. I like how you did the hunting and I'm now doing the... The gathering. The gathering. Oh, hey. Hey. What the... Wouldn't it tell me to do stuff with it? No, you have to look for more deer. Okay. Why is he crouching? Looks like he's really trying to be stealth. Anyway, besides fried chicken, what else? I love sweets. So I love chocolate. Dark? I'm a milk chocolate girl. But I love dark chocolate. Yeah, me too. I'm a milk chocolate girl. Because it was... So much creamier. Yeah, it's more delicious. But then like the sophisticated people... How do I run? Dark chocolate's not bad. I'll have dark chocolate with some nut butter in it. But people will judge you because if you're a real chocolate person you're going to do dark chocolate because it's the more sophisticated, complicated flavor, right? That's fake. That's like someone going to some restaurant and being like, if you don't order this, then you didn't really go to that place. I don't think that really matters. I think it's all subjective. Say we like coffee. I still drink instant coffee. Do you like instant coffee? I don't think I've ever had instant coffee. I don't like to admit it because people say that... Because they don't consider instant coffee real coffee. It's coffee. And it's reliable. I can count on it. I know the flavor. It's good. I know the amount. The aroma. The whole point of coffee... Not the whole point. Can you make it with hot water? Yeah, with hot water. Hot water. I'm just running around. Not that way. What are you doing? I just asked you. Oh, so I should follow this guy? But he's just crouching. Well, you have to use your eagle eye. What's the eagle eye thing? It's these two. You click them down at the same time. And you've got to look around because you're going to run out of eagle eye. How do I... I think we lost the animal. Hold on. Cancel it. Wait. Don't do it yet. Just go back to where that animal was and then look for the... Right. Then look for the scent. Chocolate. What are your favorites? Like something naughty, though. Because you eat very clean. I don't think I use the word naughty to describe... When describing food, it makes me uncomfortable. Does it? It's such a weird word to use. I'm feeling naughty. I don't think I feel naughty. I think that's not... That's just not in my vocabulary. Yeah. Is this back? Is this where it is? Uh... Why is he following you like that? I think he likes the view. I don't know. Oh, okay. So the animal's over there. So get close to it and then just look around and I'm sure you'll find the scent. I love baking, by the way. Actually baking? Yeah. So cookies, like oatmeal raisin. The best cookie is oatmeal raisin. I've got a lot of trouble over this. Non-chocolate chip? Yeah. I went to war on Twitter over this. You're a chocolate chip girl? Yeah. So I'm doing oatmeal raisin for me. Like warm oatmeal raisin. So one of my nephews really loves oatmeal raisin. The other one loves chocolate chip. Am I following? Yeah, that's a scent. Anyway, oatmeal raisin cookie, like a thick oatmeal raisin cookie. Thick? Yeah. It has to be thick. The thin ones, it makes no sense. Because it's not enough cookie? Yeah, there's not enough meat and substance to the cookie. Good job. Just like a warm, thick oatmeal raisin cookie with some milk. It's your jam. With almond milk, actually. Almond milk? Yeah. With a cookie. The creamy almond milk or like real almond milk? I don't know what real almond milk is. Yeah, real but not sweetened. Unsweetened. Looking for the horse. Got to take the steer on the horse. Oh, there it is. Nice. This horse is great. What's your favorite cookie? Chocolate chip. Yeah, I love a chocolate chip cookie because there's so many different ways of making it. I'm sure there's the same thing for oatmeal raisin. Are you going to leave the animal? No, I'm going to grab it. I had to move the horse. So I had the option to grab it. So you can make like cakey chocolate chip cookies. Sure. You can make like a gooey chocolate chip cookie. You can make a chewy one. You got to go gooey. Maybe chewy gooey. Chewy gooey. It depends on what you can add molasses. Do you want it to crumble or do you want it to be chewy? I don't like a crispy. I like chewy. Yeah, good. There's a, you know, growing up in I think it's like in the Soviet Union that had I think there's a kind of cake. I don't know how they call it in English but it's muragina kucha, which is an antil cake I think. Is it like an angel hair cake? No. It's condensed milk. Oh. With a bunch of you know what condensed milk is? Yes, of course. Of course? I'm Cuban. Oh. Leche con la salada. Do Cubans do this kind of thing? What do they use it for? You use it for a lot of different things but... Desserts. Desserts, yes. You can also yeah, you can make a lot of different things with it. It's delicious. It's like very sweet and gooey. Probably portable for you. It's a cake with I don't know, it's called anthill. People can look it up. It's great. It was just a source of happiness because my mom would make it every year for my birthday. Oh, that's delicious. But then you like as you grow up you realize like, oh, this is probably really bad for you. Yeah, it's not great. And I'm the only one that eats it so when she makes it it's like Am I going to do like this 20,000 calorie contraption? Am I really going to take this on? And I do because I can't do a slice of it. No, you just keep going. The gods of cake. So your mom likes to bake too? Yeah. What else does she bake? What else is your favorite thing? Like a home cooked meal? I think it's just being with family is the favorite thing versus like a specific meal. Probably like barbecuing like, I'll usually grill. I'll make meat. So just getting together around a grill. And then enjoying the meal with family. And then just drink like whiskey vodka. I feel that way about traveling. Like people romanticize going to different places but I think it's really about the company that you keep. It almost feels like we're having a conversation but we're actually on a horse having a conversation. It does feel like we're on a horse. Which one am I and which one are you? I think they look the same. Look how big that deer is. In the back of my horse. It's kind of incredible. This game just looks beautiful. It's like realistic. Wait, did you say bear? Yeah, what do we do with that? Oh, I gotta get on my horse. It's a bear. What are we gonna do about the bear? Aim weapon? RT? Alright, I guess we won't shoot it. Could be cocaine bear. It looks like cocaine bear. Look how big it is. Actually in the trailer for cocaine bear, the cocaine bear doesn't look big. He doesn't? He looks kind of skinny. Well he's a CGI now. Yeah, I understand this but like it... I think they realized they can't make the cocaine bear fat. Because then he would be lazy. Yeah, it would be a slow movie. You have to have a skinny agile bear. Yeah, like just woke up from hibernation. Yeah, took some cocaine. And some caffeine. And just go nuts. I really want to see that movie. Just to see... Like how far they take it? Like how can you have a movie for two hours on a premise that feels like it should not last longer than 10 seconds? It feels like a joke that you say amongst friends for like 10 minutes. And like maximum 10 minutes. You have this weird banter about it and it gets weird after like 3 minutes. So literally... This is based on a true story, right? So literally they're gonna... I love the name. It is. There was some cocaine in the woods, dropped off in the woods. So they're gonna do that. And you're gonna say, oh, it looks like some bear ate into it. That takes like 2 minutes to introduce. What else is there? Maybe half the movie is just like the cocaine story. Could be. Or maybe like looking at how the cocaine changes the relationship the bear has with his family. And other bears. Going like the Lion King way. Yeah, I don't know. It's a very silly movie. It could be like a cool action film. Maybe they're going like... I think it might be hilarious. Kills a bunch of... Like the bear kills a bunch of people. I almost hope that it's really dumb because I think it would be funnier that way. I hope Liam Neeson is it. Who's that? Liam Neeson. He made a giant mistake. For stealing my daughter. That would be great. He would call the bear. Is that the guy from Taken? Yeah, Taken. That's the one. I am a sucker for those movies. For Taken? I am taking all of them. He's in a bunch of... He plays the same exact guy and he is such a badass. Those movies freaked me out. I think it was probably a good thing. I'd love to talk to him on a podcast. He's a really interesting dude. And he like... Same with... What's the guy from Breaking Bad? I don't know his name but I know who you're talking about. Aaron something? That's the blonde guy. The older guy. I don't know what his name is. Bryan Cranston I want to say. He's like a badass in real life too. I like it when you're like... When you don't just play the part. Like it's part of who you are. I feel like playing the part made him more of a badass. And he embraced it. The part changed him. And that's really cool. I mean when you play a meth dealer for like 10 seasons whatever it is. That's gonna change you. Yeah. Definitely. I mean it's part of you now. It's like when you do any job. It becomes... It consumes you. Yeah. You've been working like crazy right? I work a lot. Yeah. I work like 60 or 70 hours a week. That's good. I love it. Hard work is good. Yeah. It's important.... It's interesting when you spend 60 or 70 hours a week doing something. Because before that I wasn't working. It's like become my entire life. It's all that I think about. To the point that sometimes when I go to a restaurant I'll see an elderly person. A person who's having a hard time walking. And I'm like I should be in the lab working. What am I doing? Why am I here? That's really good. That means you really care about it. I mean you were talking about it when I met you. About prosthetics and all that kind of stuff. That was a passion. It's cool that you found that passion in this work. It's great. Yeah. I'm skinning a deer. Here we go. I'm kidding. Did you have to press something? Just why? Did you do any animal work? Ever? Yeah. Dissecting in high school and college. Yeah. For anatomy and physiology. Yeah. It's funny. I miss high school for the educational aspects. Were you funny in high school? What were you like in high school? Very stoic. I read a lot. And wrestling and sports. And just that. Was there any book that really shaped you in high school? Yeah. Like a lot. A lot. First it was like The Stranger. Which is probably by Albert Camus. He... I just re-read it recently and it's not nearly as good. As when you read it? I've read other books that I've read it and they're much better. Or is it not as good in comparison to books that you've read after that? See there's other books like Dostoevsky Gets Better and Better as I get older. And I read that in high school. But The Stranger was like meh. But it's the first time I had this feeling of existentialism of like it's the first time I really intensely felt like what's the meaning of it all? Like felt it. Not just Like an existential... Yeah. Interesting. And then of course you like take it way too seriously. Yeah and you get like really depressed and nervous. Yeah. You know the one that really hit me is Animal Farm. Oh that's a great book. Can I tell you which character I like the most? And then you tell me which one you like the most. Can you guess? Uh... It's not the pigs. Is it the the... Molly? The horse that likes pretty... How dare you? Benjamin the donkey. Nope. Who's cynical about everything. Nope. I feel like it's obvious. It's Boxer. Oh yeah. Now you're just... Working harder. Yeah obviously it's mine too. You're stealing my best... My vibe. Yeah. Yeah I will work harder. I think hard work is a lot more important than... Human intelligence doesn't vary all that much. Like when you're smart I mean there's only... Like you can't get much smarter. So you think hard work beats the cliche talent. Yeah. I think like a combination of the two probably. Or like even just being passionate. And putting in the work. Because you could be passionate and lazy. And I think sometimes if you think you're really smart it kind of holds you back. To where you feel like you don't have to try as hard. Yeah. But then it leads to like a very I think boring life. But who knows. For some people they enjoy that. This is straight up a movie. Yeah it's beautiful. What do you think is the meaning of life? I feel like it's a good thing to ask while we're watching a bunch of cowboys ride through the woods. I think nothing in life matters except for love and human connection. Like nothing else is really all that important. Like I think when you look back on life you look back on the moments that you shared with other people. How deeply you loved them. How deeply you felt things. I think all of that is important. Everything else is just noise. I agree. This is really beautiful. The seasons are changing. Yeah. Before our eyes. What do you think is the meaning of life? How good you can ride a horse. And how pretty you look in a cowboy hat. That's probably it. So it's not wearing shorts barefoot on a beach. On a horse. When the feeling strikes you. That's so romantic. A ridiculous photo of me. It's my favorite photo. I've never seen him in person. It's a fabulous photo. The funny thing is there's a bunch of shirtless versions of that. There's shirtless versions? It was like ridiculous. I rode the horse shirtless but then I put on a shirt. This is too ridiculous to take a picture of. Like what are you doing? It was cool. Being on sand is a different experience. It's like looking out over the ocean. It's cool. It's an incredible feeling. Why did you just shoot a gun? I had binoculars. Sorry. This is how all bad things happen. This is why we can't have nice things. I think this is a good place to end it. I think so too. What game should we play next time? Do you have ideas? Maybe we'll play GTA. Could be. Good thought. What's your big takeaway from this journey we took together? Do you like the game? I love the game. I love it too. It's almost nostalgic. That would be fun. Nostalgic personally for you? I used to play this as a kid. I see. I thought you meant it takes me back. It takes me back to my old days when I used to ride horses in summer camp. Me too. Your shirtless Mexico trip. I don't talk about that time. You don't talk about that time. The things I've seen. The things these eyes have seen.


Gilbert Strang: Four Fundamental Subspaces of Linear Algebra

So let's talk about linear algebra a little bit, because it is such a, it's both a powerful and a beautiful subfield of mathematics. So what's your favorite specific topic in linear algebra, or even math in general, to give a lecture on, to convey, to tell a story, to teach students? Okay, well, on the teaching side, so it's not deep mathematics at all, but I'm kind of proud of the idea of the four subspaces, the four fundamental subspaces, which are, of course, known before, long before my name for them, but. Can you go through them? Can you go through the four subspaces? Sure I can, yeah. So the first one to understand is, so the matrix, maybe I should say the matrix. What is the matrix? What's a matrix? Well, so we have like a rectangle of numbers. So it's got N columns, got a bunch of columns, and also got an M rows, let's say. And the relation between, so of course, the columns and the rows, it's the same numbers. So there's gotta be connections there, but they're not simple. The columns might be longer than the rows, and they're all different, the numbers are mixed up. First space to think about is, take the columns. So those are vectors, those are points in N dimensions. What's a vector? So a physicist would imagine a vector, or might imagine a vector as a arrow in space, or the point it ends at in space. For me, it's a column of numbers. You often think of, this is very interesting in terms of linear algebra, in terms of a vector. You think a little bit more abstract than how it's very commonly used, perhaps. You think this arbitrary multidimensional space. Right away, I'm in high dimensions. In the dreamland. Yeah, that's right, in the lecture, I try to. So if you think of two vectors in 10 dimensions, I'll do this in class, and I'll readily admit that I have no good image in my mind of a vector, of a arrow in 10 dimensional space, but whatever. You can add one bunch of 10 numbers to another bunch of 10 numbers, so you can add a vector to a vector, and you can multiply a vector by three, and that's, if you know how to do those, you've got linear algebra. You know, 10 dimensions. Yeah. You know, there's this beautiful thing about math, if we look at string theory, and all these theories which are really fundamentally derived through math, but are very difficult to visualize. How do you think about the things, like a 10 dimensional vector, that we can't really visualize? Yeah. Do you, and yet, math reveals some beauty underlying our world in that weird thing we can't visualize. How do you think about that difference? Well, probably, I'm not a very geometric person, so I'm probably thinking in three dimensions, and the beauty of linear algebra is that it goes on to 10 dimensions with no problem. I mean, if you're just seeing what happens if you add two vectors in 3D, yeah, then you can add them in 10D. You're just adding the 10 components. So, I can't say that I have a picture, but yet I try to push the class to think of a flat surface in 10 dimensions. So, a plane in 10 dimensions, and so that's one of the spaces. Take all the columns of the matrix, take all their combinations, so much of this column, so much of this one, then if you put all those together, you get some kind of a flat surface that I call a vector space, space of vectors, and my imagination is just seeing like a piece of paper in 3D. But anyway, so that's one of the spaces, that's space number one, the column space of the matrix, and then there's the row space, which is, as I said, different, but came from the same numbers. So, we got the column space, all combinations of the columns, and then we got the row space, all combinations of the rows. So, those words are easy for me to say, and I can't really draw them on a blackboard, but I try with my thick chalk. Everybody likes that railroad chalk, and me too. I wouldn't use anything else now. And then the other two spaces are perpendicular to those. So, like if you have a plane in 3D, just a plane is just a flat surface in 3D, then perpendicular to that plane would be a line. So, that would be the null space. So, we've got two, we've got a column space, a row space, and there are two perpendicular spaces. So, those four fit together in a beautiful picture of a matrix. Yeah, yeah, it's sort of a fundamental, it's not a difficult idea, comes pretty early in 1806, and it's basic.


Yann LeCun: Can Neural Networks Reason? | AI Podcast Clips

Do you think neural networks can be made to reason? Yes, there is no question about that. Again, we have a good example, right? The question is how? So the question is how much prior structure do you have to put in the neural net so that something like human reasoning will emerge from it, from learning. Another question is, all of our kind of model of what reasoning is that are based on logic are discrete and are therefore incompatible with gradient-based learning. And I'm a very strong believer in this idea of gradient-based learning. I don't believe that other types of learning that don't use kind of gradient information, if you want. So you don't like discrete mathematics? You don't like anything discrete? Well, it's not that I don't like it. It's just that it's incompatible with learning and I'm a big fan of learning, right? So in fact, that's perhaps one reason why deep learning has been kind of looked at with suspicion by a lot of computer scientists, because the math is very different. The math that you use for deep learning, you know, it kind of has more to do with, you know, cybernetics, the kind of math you do in electrical engineering than the kind of math you do in computer science. And, you know, nothing in machine learning is exact, right? Computer science is all about sort of, you know, observational compulsive attention to details of, like, you know, every index has to be right. And you can prove that an algorithm is correct, right? Machine learning is the science of sloppiness, really. That's beautiful. So, OK, maybe let's feel around in the dark of what is a neural network that reasons or a system that works with continuous functions that's able to do, build knowledge, however we think about reasoning, build on previous knowledge, build on extra knowledge, create new knowledge, generalize outside of any training set ever built. What does that look like? If, yeah, maybe do you have inklings of thoughts of what that might look like? Yeah, I mean, yes and no. If I had precise ideas about this, I think, you know, we'd be building it right now. But and there are people working on this or whose main research interest is actually exactly that. Right. So what you need to have is a working memory. So you need to have some device, if you want, some subsystem that can store a relatively large number of factual, episodic information for, you know, a reasonable amount of time. So, you know, in the brain, for example, there are kind of three main types of memory. One is the sort of memory of the state of your cortex. And that sort of disappears within 20 seconds. You can't remember things for more than about 20 seconds or a minute if you don't have any other form of memory. The second type of memory, which is longer term, but still short term, is the hippocampus. So you can, you know, you came into this building, you remember where the exit is, where the elevators are. You have some map of that building. That's stored in your hippocampus. You might remember something about what I said, you know, a few minutes ago. I forgot it all already. Of course, it's been erased. But, you know, but that would be in your hippocampus. And then the longer term memory is in the synapse, the synapses. Right. So what you need if you want a system that's capable of reasoning is that you want the hippocampus-like thing. Right. And that's what people have tried to do with memory networks and, you know, neural training machines and stuff like that. Right. And now with transformers, which have sort of a memory in their kind of self-attention system, you can think of it this way. So that's one element you need. Another thing you need is some sort of network that can access this memory, get an information back, and then kind of crunch on it, and then do this iteratively multiple times. Because a chain of reasoning is a process by which you update your knowledge about the state of the world, about, you know, what's going to happen, etc. And that has to be this sort of recurrent operation, basically. And you think that kind of, if we think about a transformer, so that seems to be too small to contain the knowledge that's, to represent the knowledge that's contained in Wikipedia, for example. But a transformer doesn't have this idea of recurrence. It's got a fixed number of layers, and that's the number of steps that, you know, limits, basically, its representation. But recurrence would build on the knowledge somehow. I mean, it would evolve the knowledge and expand the amount of information, perhaps, or useful information within that knowledge. But is this something that just can emerge with size? Because it seems like everything we have now is too small. No, it's not clear. I mean, how you access and write into an associative memory in an efficient way. I mean, sort of the original memory network maybe had something like the right architecture, but if you try to scale up a memory network so that the memory contains all Wikipedia, it doesn't quite work. Right. So there's a need for new ideas there. Okay. But it's not the only form of reasoning. So there's another form of reasoning, which is through, which is very classical also in some types of AI. And it's based on, let's call it energy minimization. Okay. So you have some sort of objective, some energy function that represents the quality or the negative quality. Okay. Energy goes up when things get bad and they get low when things get good. So let's say you want to figure out, you know, what gestures do I need to do to grab an object or walk out the door? If you have a good model of your own body, a good model of the environment, using this kind of energy minimization, you can do planning. And in optimal control, it's called model predictive control. You have a model of what's going to happen in the world as a consequence of your actions. And that allows you to, by energy minimization, figure out a sequence of action that optimizes a particular objective function, which minimizes the number of times you're going to hit something and the energy you're going to spend doing the gesture and et cetera. So that's a form of reasoning. Planning is a form of reasoning. And perhaps what led to the ability of humans to reason is the fact that, or, you know, species that appear before us had to do some sort of planning to be able to hunt and survive and survive the winter in particular. And so, you know, it's the same capacity that you need to have. So in your intuition, if we look at expert systems and encoding knowledge as logic systems, as graphs, in this kind of way, is not a useful way to think about knowledge? Graphs are a little brittle or logic representation. So basically, you know, variables that have values and constraints between them that are represented by rules, it's a little too rigid and too brittle, right? So some of the early efforts in that respect were to put probabilities on them. So a rule, you know, if you have this and that symptom, you know, you have this disease with that probability, and you should prescribe that antibiotic with that probability, right? That's the mycin system from the 70s. And that's what that branch of AI led to, you know, Bayesian networks and graphical models and causal inference and variational, you know, method. So there is, I mean, certainly a lot of interesting work going on in this area. The main issue with this is knowledge acquisition. How do you reduce a bunch of data to a graph of this type? It relies on the expert, on the human being to encode, to add knowledge. And that's essentially impractical. Yeah. It's not scalable. That's a big question. The second question is, do you want to represent knowledge as symbols? And do you want to manipulate them with logic? And again, that's incompatible with learning. So one suggestion, which Geoff Hinton has been advocating for many decades, is replace symbols by vectors. Think of it as pattern of activities in a bunch of neurons or units or whatever you want to call them. And replace logic by continuous functions. Okay. And that becomes now compatible. There's a very good set of ideas written in a paper about 10 years ago by Leon Boutou, who is here at Facebook. The title of the paper is From Machine Learning to Machine Reasoning. His idea is that a learning system should be able to manipulate objects that are in a space and then put the result back in the same space. So it's this idea of working memory, basically. And it's very enlightening. And in a sense, that might learn something like the simple expert systems. You can learn basic logic operations there. Yeah, quite possibly. Yeah. And there's a lot of debate on how much prior structure you have to put in for this kind of stuff to emerge. That's the debate I have with Gary Marcus and people like that.


Bjarne Stroustrup: Deep Learning, Software 2.0, and Fuzzy Programming

So a crazy question, but I work a lot with machine learning, with deep learning. I'm not sure if you touch that world much, but you could think of programming as a thing that takes some input. Programming is the task of creating a program, and a program takes some input and produces some output. So machine learning systems train on data in order to be able to take in input and produce output. But they're messy, fuzzy things, much like we as children grow up. You know, we take some input, we make some output, but we're noisy. We mess up a lot. We're definitely not reliable. Biological systems are a giant mess. So there's a sense in which machine learning is a kind of way of programming, but just fuzzy. It's very, very, very different than C++, because C++ is, just like you said, it's extremely reliable, it's efficient, you can measure, you can test it in a bunch of different ways. With biological systems or machine learning systems, you can't say much except sort of empirically saying that 99.8% of the time it seems to work. What do you think about this fuzzy kind of programming? Do you even see it as programming? Is it totally another kind of world? I think it's a different kind of world. And it is fuzzy, and in my domain, I don't like fuzziness. That is, people say things like they want everybody to be able to program. But I don't want everybody to program my airplane controls or the car controls. I want that to be done by engineers. I want that to be done with people that are specifically educated and trained for doing, building things. And it is not for everybody. Similarly, a language like C++ is not for everybody. It is generated to be a sharp and effective tool for professionals, basically, and definitely for people who aim at some kind of precision. You don't have people doing calculations without understanding math, right? Counting on your finger is not going to cut it if you want to fly to the moon. And so there are areas where an 84% accuracy rate, 16% false positive rate is perfectly acceptable and where people will probably get no more than 70. You said 98%. What I have seen is more like 84, and by really a lot of blood, sweat, and tears, you can get up to 92 and a half. So this is fine if it is, say, pre-screening stuff before the human look at it. It is not good enough for life-threatening situations. And so there's lots of areas where the fuzziness is perfectly acceptable and good and better than humans, cheaper than humans, but it's not the kind of engineering stuff I'm mostly interested in. I worry a bit about machine learning in the context of cars. You know much more about this than I do. I worry too. But I'm sort of an amateur here. I've read some of the papers, but I've not ever done it. And the idea that scares me the most is the one I have heard, and I don't know how common it is, that you have this AI system, machine learning, all of these trained neural nets, and when there's something that's too complicated, they ask the human for help. But the human is reading a book or asleep, and he has 30 seconds or three seconds to figure out what the problem was that the AI system couldn't handle and do the right thing. This is scary. I mean, how do you do the cutover between the machine and the human? It's very, very difficult. And for the designer of one of the most reliable, efficient, and powerful programming languages, C++, I can understand why that world is actually unappealing. It is for most engineers. To me, it's extremely appealing because we don't know how to get that interaction right, but I think it's possible. But it's very, very hard. It is. And I was stating a problem, not a solution. That is impossible. I would much rather never rely on the human. If you're driving a nuclear reactor or an autonomous vehicle, it's much better to design systems written in C++ that never ask human for help. Let's just get one fact in. All of this AI stuff is on top of C++. So that's one reason I have to keep a weather eye out on what's going on in that field, but I will never become an expert in that area. But it's a good example of how you separate different areas of applications, and you have to have different tools, different principles, and they interact. No major system today is written in one language, and there are good reasons for that.


Noam Chomsky: Language is the Basis of Reason and Creativity

So how deep do the roots of language go in our brain? Our mind, is it yet another feature like vision or is it something more fundamental from which everything else springs in the human mind? Well, in a way it's like vision. There's something about our genetic endowment that determines that we have a mammalian rather than an insect visual system. And there's something in our genetic endowment that determines that we have a human language faculty. No other organism has anything remotely similar. So in that sense, it's internal. Now there is a long tradition which I think is valid going back centuries to the early scientific revolution at least that holds that language is the sort of the core of human cognitive nature. It's the source, it's the mode for constructing thoughts and expressing them. That is what forms thought. And it's got fundamental creative capacities. It's free, independent, unbounded and so on. And undoubtedly I think the basis for our creative capacities and the other remarkable human capacities that lead to the unique achievements and not so great achievements of the species. The capacity to think and reason, do you think that's deeply linked with language? Do you think the way we, the internal language system is essentially the mechanism by which we also reason internally? It is undoubtedly the mechanism by which we reason. There may also be other, there are undoubtedly other faculties involved in reasoning. We have a kind of scientific faculty, nobody knows what it is. But whatever it is that enables us to pursue a certain lines of endeavor and inquiry and to decide what makes sense and doesn't make sense and to achieve a certain degree of understanding of the world that uses language but goes beyond it. Just as using our capacity for arithmetic is not the same as having the capacity.


Elon Musk: Physics View of Love | AI Podcast Clips

Do you think we will ever create an AI system that we can love and loves us back in a deep meaningful way like in the movie Her? I think AI will be capable of convincing you to fall in love with it very well. And that's different than us humans? You know we start getting into a metaphysical question of like do emotions and thoughts exist in a different realm than the physical? And maybe they do, maybe they don't, I don't know. But from a physics standpoint I tend to think of things, you know, like physics was my main sort of training. And from a physics standpoint, essentially if it loves you in a way that you can't tell whether it's real or not, it is real. Just a physics view of love. If you cannot prove that it does not, if there's no test that you can apply that would make it, allow you to tell the difference, then there is no difference. And it's similar to seeing our world as simulation. There may not be a test to tell the difference between what the real world and the simulation and therefore from a physics perspective it might as well be the same thing. Yes. And there may be ways to test whether it's a simulation. There might be, I'm not saying there aren't, but you could certainly imagine that a simulation could correct, that once an entity in the simulation found a way to detect the simulation it could either restart, you know, pause the simulation, start a new simulation, or do one of many other things that then corrects for that error.


Michael Kearns: Algorithmic Trading and the Role of AI in Investment at Different Time Scales

You've worn many hats, one of which, the one that first caused me to become a big fan of your work many years ago is algorithmic trading. So I have to just ask a question about this because you have so much fascinating work there. In the 21st century, what role do you think algorithms have in the space of trading, investment, in the financial sector? Yeah, it's a good question. I mean, in the time I've spent on Wall Street and in finance, I've seen a clear progression and I think it's a progression that kind of models the use of algorithms and automation more generally in society, which is the things that kind of get taken over by the algos first are sort of the things that computers are obviously better at than people, right? So first of all, there needed to be this era of automation, right, where just financial exchanges became largely electronic, which then enabled the possibility of trading becoming more algorithmic because once the exchanges are electronic, an algorithm can submit an order through an API just as well as a human can do at a monitor. It can do it really quickly, it can read all the data. Yeah, and so I think the places where algorithmic trading have had the greatest inroads and had the first inroads were in kind of execution problems, kind of optimized execution problems. So what I mean by that is at a large brokerage firm, for example, one of the lines of business might be on behalf of large institutional clients taking what we might consider difficult trades. It's not a mom and pop investor saying, I want to buy 100 shares of Microsoft. It's a large hedge fund saying, I want to buy a very, very large stake in Apple and I want to do it over the span of a day. And it's such a large volume that if you're not clever about how you break that trade up, not just over time, but over perhaps multiple different electronic exchanges that all let you trade Apple on their platform, you will move, you'll push prices around in a way that hurts your execution. So this is an optimization problem. This is a control problem, right? And so machines are better. We know how to design algorithms that are better at that kind of thing than a person is going to be able to do because we can take volumes of historical and real-time data to kind of optimize the schedule with which we trade. And similarly, high-frequency trading, which is closely related but not the same as, obviously, optimized execution, where you're just trying to spot very, very temporary mispricings between exchanges or within an asset itself, or just predict directional movement of a stock because of the kind of very, very low-level granular buying and selling data in the exchange. Machines are good at this kind of stuff. It's kind of like the mechanics of trading. What about the, can machines do long-term sort of prediction? Yeah. So I think we are in an era where clearly there have been some very successful quant hedge funds that are in what we would traditionally call still in the stat arb regime. So- What's that? Stat arb referring to statistical arbitrage. But for the purposes of this conversation, what it really means is making directional predictions in asset price movement or returns. Your prediction about that directional movement is good for, you have a view that it's valid for some period of time between a few seconds and a few days. And that's the amount of time that you're going to kind of get into the position, hold it, and then hopefully be right about the directional movement and buy low and sell high as the cliche goes. So that is a kind of a sweet spot, I think, for quant trading and investing right now and has been for some time. When you really get to kind of more Warren Buffett style time scales, right? Like my cartoon of Warren Buffett is that Warren Buffett sits and thinks what the long-term value of Apple really should be. And he doesn't even look at what Apple's doing today. He just decides, I think that this is what its long-term value is and it's far from that right now. And so I'm going to buy some Apple or short some Apple and I'm going to sit on that for 10 or 20 years. So when you're at that kind of time scale or even more than just a few days, all kinds of other sources of risk and information. So now you're talking about holding things through recessions and economic cycles. Wars can break out. So there you have to understand human nature at a level. Yeah, and you need to just be able to ingest many, many more sources of data that are on wildly different time scales, right? So if I'm an HFT, I'm a high-frequency trader, like I don't, I really, my main source of data is just the data from the exchanges themselves about the activity in the exchanges, right? And maybe I need to pay, I need to keep an eye on the news, right? Because that can cause sudden, the CEO gets caught in a scandal or gets run over by a bus or something that can cause very sudden changes. But I don't need to understand economic cycles. I don't need to understand recessions. I don't need to worry about the political situation or war breaking out in this part of the world because all I need to know is as long as that's not going to happen in the next 500 milliseconds, then my model's good. When you get to these longer time scales, you really have to worry about that kind of stuff. And people in the machine learning community are starting to think about this. We held a, we jointly sponsored a workshop at Penn with the Federal Reserve Bank of Philadelphia a little more than a year ago on, I think the title was something like Machine Learning for Macroeconomic Prediction. And referring specifically to these longer time scales. And it was an interesting conference, but it left me with greater confidence that we have a long way to go to... And so I think that people that, in the grand scheme of things, if somebody asked me like, well, whose job on Wall Street is safe from the bots? I think people that are at that longer time scale and have that appetite for all the risks involved in long-term investing and that really need kind of not just algorithms that can optimize from data, but they need views on stuff. They need views on the political landscape, economic cycles and the like. And I think they're pretty safe for a while, as far as I can tell. So Warren Buffet's job is safe for a little while. Yeah, I'm not seeing a robo Warren Buffet anytime soon. To give him comfort.


Who is Satoshi Nakamoto? (Vitalik Buterin) | AI Podcast Clips

So before we talk about the fundamental ideas behind Ethereum and cryptocurrency, perhaps it'd be nice to talk about the origin story of Bitcoin and the mystery of Satoshi Nakamoto. You gave a talk that started with sort of asking the question, what did Satoshi Nakamoto actually invent? Maybe you could say who is Satoshi Nakamoto and what did he invent? Sure, so Satoshi Nakamoto is the name by which we know the person who originally came up with Bitcoin. So the reason why I say the name by which we know is that this is an anonymous fellow who has shown himself to us only over the internet, just by first publishing the white paper for Bitcoin, then releasing the original source code for Bitcoin, and then talking to the very early Bitcoin community on Bitcoin forums and interacting with them and helping the project along for a couple of years. And then at some point in late 2010 to early 2011, he disappeared. So Bitcoin is a fairly unique project in how it has this kind of mythical, kind of quasi-godlike founder who just kind of popped in, did the thing, and then disappeared and we've somehow just never heard from him again. So in 2008, so the white paper was the first, do you know if the white paper was the first time the name would actually appear, Satoshi Nakamoto? I believe so. So how is it possible that the creator of such an impactful project remains anonymous? That's a tough question and there's no similarity to it in the history of technology as far as I'm aware. Yeah. So one possibility is that it's Hal Finney because Hal Finney was kind of also active in the Bitcoin community as Hal Finney in those two beginning years. And Hal is one of the people in the early Cypherpunk community. He was a computer scientist, cryptographers, people interested in technology, internet freedom, like those kinds of topics. Is it correct that he seemed to have been involved in either the earliest or the first transaction of Bitcoin? Yes. The first transaction of Bitcoin was between Satoshi and Hal Finney. Do you think he knew who Satoshi was? If he was Satoshi, you probably know. How is it possible to work so closely with people and nevertheless not know anything about their fundamental identity? Is this like a natural sort of characteristic of the internet? If we were to think about it, because you and I just met now, there's a depth of knowledge that we now have about each other that's like physical. My vision system is able to recognize you, I can also verify your identity of uniqueness. It's very hard to fake you being you. So the internet has a fundamentally different quality to it, which is just fascinating. Yeah, this is definitely interesting. I definitely just know a lot of people just by their internet handles. And to me, when I think of them, I see their internet handles and one of them has a profile picture as this face that's not quite human with a bunch of psychedelic colors in it. And when I visualize him, I just visualize that. That's not an actual face. You are the creator of the second, well, at least currently the second most popular cryptocurrency, Ethereum. So on this topic, if we just stick on Satoshi Nakamoto for a little bit longer, you may be the most qualified person to speak to the psychology of this anonymity that we're talking about. Your identity is known, I've just verified it. But from your perspective, what are the benefits in creating a cryptocurrency and then remaining anonymous? If it can psychoanalyze Satoshi Nakamoto, is there something interesting there? Or is it just a peculiar quirk of him? It definitely helps create this kind of image of this kind of neutral thing that doesn't belong to anyone. You've created a project and because you're anonymous and because you also disappear or as unfortunately happened to Halfini, if that is him, he ended up dying of Lou Gehrig's disease and he's in a cryogenic freezer now. But if you pop in and you create it and you're gone and all that's remaining of that whole process is the thing itself, then no one can go and try to interpret any of your other behavior and try to understand like, oh, this person wrote this thing in some essay at age 16 where he expressed particular opinions about democracy. And so because of that, this project is a statement that's trying to do this specific thing. Instead, it creates this environment where the thing is what you make of it. It doesn't have the burden of your other ideas, political thought and so on. So now that we're sitting with you, do you feel the burden of being kind of the face of Ethereum? I mean, there's a very large community of developers, but nevertheless, is there like a burden associated with that? There definitely is. This is definitely a big reason why I've been trying to kind of push for the Ethereum ecosystem to become more decentralized in many ways, just encouraging a lot of kind of core Ethereum work to happen outside of the Ethereum foundation and of expanding the number of people that are making different kinds of decisions, having multiple software limitations instead of one and all of these things. There's a lot of things that I've tried to do to remove myself as a single point of failure because that is something that a lot of people criticize me for. So if you look at the most fundamentally successful open source projects, it seems that it's like a sad reality when I think about it, is it seems to be that one person is a crucial contributor often, if you look at Linus for Linux, for the kernel. That is possible. I'm definitely not planning to disappear. That's an interesting tension that projects like this kind of desire a single entity, and yet they're fundamentally distributed. I don't know if there's something interesting to say about that kind of structure and thinking about the future of cryptocurrency. Does there need to be a leader? There's different kinds of leaders. There's dictators who control all the money. There's people who control organizations. There's high priests that just have themselves and their Twitter followers. What kind of leader are you, would you say? These days, I'm actually a bit more in the high priest direction than before. I definitely actually don't do all that much of going around and ordering Ethereum Foundation people to do things because I think those things are important. If there's something that I do think is important, I do just usually say it publicly or just say it to people. Quite often, projects just start doing it. That's rarely just on small groups.


Einstein Carried His Luggage (Eric Weinstein and Lee Smolin) | AI Podcast Clips

There are things which are right there in front of us which we miss. And I'll quote my friend Eric Weinstein in saying, look, Einstein carried his luggage, Freud carried his luggage, Marx carried his luggage, Martha Graham carried her luggage, etc. Edison carried his luggage. All these geniuses carried their luggage. But not once before relatively recently did it occur to anybody to put a wheel on luggage and pull it. And it was right there waiting to be invented for centuries. So this is Eric Weinstein. What do the wheels represent? Are you basically saying that there's stuff right in front of our eyes that once it just clicks, we put the wheels in the luggage, a lot of things will fall into place? Yes. That's what I do. And every day I wake up and think, why can't I be that guy who was walking to the airport? What do you think it takes to be that guy? Because like you said, a lot of really smart people carried their luggage. What just psychologically speaking, so Eric Weinstein is a good example of a person who thinks outside the box. Who resists almost conventional thinking. You're an example of a person who by habit, by psychology, by upbringing, I don't know, but resists conventional thinking as well, just by nature. Thank you, that's a compliment. That's a compliment? Good. So what do you think it takes to do that? Is that something you were just born with? I doubt it. From my studying some cases, because I'm curious about that, obviously. And just in a more concrete way, when I started out in physics, because I started a long way from physics, so it took me a long, not a long time, but a lot of work to get to study it and get into it. So I did wonder about that. And so I read the biographies, in fact I started with the autobiography of Weinstein and Newton and Galileo and all those people. And I think there's a couple of things. Some of it is luck, being in the right place at the right time. Some of it is stubbornness and arrogance, which can easily go wrong. And I know all of these are doorways, if you go through them slightly at the wrong speed or in the wrong angle, they're ways to fail. But if you somehow have the right luck, the right confidence or arrogance, caring, I think Einstein cared to understand nature with a ferocity and a commitment that exceeded other people of his time. So he asked more stubborn questions, he asked deeper questions. I think, and there's a level of ability and whether ability is born in or can be developed to the extent to which it can be developed, like any of these things, like musical talent. You mentioned ego, what's the role of ego in that process? Confidence. Confidence, but do you, in your own life, have you found yourself walking that knife's edge of too much or too little, so being overconfident and therefore leading yourself astray or not sufficiently confident to throw away the conventional thinking of whatever the theory of the day, of theoretical physics? I don't know if I, I mean, I've contributed what I've contributed, whether if I had had more confidence in something, I would have gotten further, I don't know. Certainly I'm sitting here at this moment with very much my own approach to nearly everything, and I'm calm, I'm happy about that. But on the other hand, I know people whose self-confidence vastly exceeds mine, and sometimes I think it's justified and sometimes I think it's not justified.


Ray Dalio: What Elon Musk, Steve Jobs, and Other Shapers Have in Common | AI Podcast Clips

You mentioned shapers, Elon Musk, Bill Gates, what, who are the shapers that you find yourself thinking about when you're constructing these ideas? The ones that define the archetype of a shaper for you? Well, as I say, a shaper for me is somebody who comes up with a great visualization, usually a really unique visualization, and then actually builds it out that makes the world different, changes the world in that kind of a way. So when I look at it, Mark Benioff with Salesforce, Chris Anderson with TED, Mohammed Yunus with Social Enterprise and Philanthropy, Jeffrey Canada and Harlem Children's Zone, there are, all domains have shapers who have the ability to visualize and make extraordinary things happen. What are the commonalities between some of them? The commonalities are, first of all, the excitement of something new, that call to adventure, and then again, that practicality, the capacity to learn. The capacity then, they're able to be, in many ways, full-range. That means they're able to go from the big, big picture down to the detail. So let's say, for example, Elon Musk, he describes, he gets a lot of money from selling PayPal, his interest in PayPal. He said, why isn't anybody going to Mars or outer space? What are we gonna do if the planet goes to hell? And how do we gonna get that? Nobody's paying attention to that. He doesn't know much about it. He then reads and learns and so on. Says, I'm gonna take, okay, half of my money, and I'm gonna put it in there, and I'm gonna do this thing, and he learns, blah, blah, blah, blah, blah, and he's got creative, okay. That's one dimension. So he gave me the keys to his car, which was just early days in Tesla, and he then points out the details. Okay, if you push this button here, it's this, the detail. So he's simultaneously talking about the big, the big, big, big picture. Okay, when does humanity going to abandon the planet? But he will then be able to take it down into the detail so he can go, let's call it helicoptering. He can go up, he can go down, and see things at those types of perspective. And then you've seen that with the other shapers as well. And that's a common thing that they can do that. Another important difference that they have in mind is how they deal with people. I mean, meaning there's nothing more important than achieving the mission. And so what they have in common is that there's a test that I give these personality tests because they're very helpful for understanding people. And so I gave it to all these shapers. And one of the things in workplace inventory test is this test, and it has a category called concern for others. They're all having concern for others. This includes Mohammed Yunus, who invented microfinance, social enterprise, impact investing, as Mohammed Yunus received the Nobel Peace Prize for this, Congressional Medal of Honor. One of the, fortune determined, one of the 10 greatest entrepreneurs of our time. He's built all sorts of businesses to give back money in social enterprise, a remarkable man. He has nobody that I know practically can have more concern for others. He lives a life of a saint. I mean, very modest lifestyle, and he puts all his money into trying to help others. And he tests low on what's called concern for others because what it really, the questions under that are questions about conflict to get at the mission. So they all, Jeffrey Canada, who changed Harlem Children's Zone and developed that to take children in Harlem and get them well taken care of, not only just in their education, but their whole lives. Harm, him also, concern for others. What they mean is that they can see whether those individuals are performing at a level, an extremely high level, that's necessary to make those dreams happen. So when you think of, let's say, Steve Jobs was famous for being difficult with people and so on, and I didn't know Steve Jobs, so I can't speak personally to that, but his comments on, do you have A players, and if you have A players, if you put in B players, pretty soon you'll have C players and so on. That is a common element of them, holding people to high standards and not letting anybody stand in the way of the mission. What do you think about that kind of idea, sorry to pause on that for a second, that the A, B, and C players, and the importance of, so when you have a mission, to really only have A players and be sort of aggressively filtering for that. Yes, but I think that there are all different ways of being A players, and I think, and what a great team, you have to appreciate all the differences in ways of being A players, okay? That's the first thing, and then you always have to be super excellent, in my opinion, you always have to be really excellent with people to help them understand themselves and get in sync with them about what's true about them and their circumstances and how they're doing so that they're having a fabulous personal development experience at the same time as you're dealing with them. So when I say that they're all different ways, this is one of the then qualities, you asked me what are the qualities, so one of the third qualities that I would say is to know how to deal well with your not knowing and to be able to get the best expertise so that you're a great orchestrator of different ways so that the people who are really, really successful, unlike most people believe that they're successful because of what they know, they're even more successful by being able to effectively learn from others and tap into the skills of people who see things different from them. Brilliant, so how do you, when that personality being, first of all, open to the fact that there's, other people see things differently than you and at the same time have supreme confidence in your vision, is there, just the psychology of that, do you see a tension there between the confidence and the open-mindedness? And now it's funny because I think we grow up thinking that there's a tension there, right? That there's a confidence and the more confidence that you have, there's a tension with the open-mindedness and not being sure, okay? Confident and accurate are almost negatively correlated in many people. They're extremely confident and they're often inaccurate. And so I think one of the greatest tragedies of people is not realizing how those things go together because instead it's really that by saying, I know a lot and how do I know I'm still not wrong? And how do I take that best thinking available to me and then raise my probability of learning? All these people think for themselves, okay? I mean, meaning they're smart, but they take in like vacuum cleaners, they take in ideas of others, they stress test their ideas with others, they assess what comes back to them in the form of other thinking and they also know what they're not good at and what other people who are good at the things that they're not good at, they know how to get those people and be successful all around because nobody has enough knowledge in their heads. And that I think is one of the great differences. So the reason my company has been successful in terms of this is because of an idea meritocratic decision-making, a process by which you can get the best ideas. You know, what's an idea meritocracy? An idea meritocracy is to get the best ideas that are available out there and to work together with other people in the team to achieve that.


Noam Chomsky: Good and Evil in Human Nature

You've said that evil in society arises from institutions, not inherently from our nature. Do you think most human beings are good, they have good intent, or do most have the capacity for intentional evil that depends on their upbringing, depends on their environment, on context? I wouldn't say that they don't arise from our nature. Anything we do arises from our nature. And the fact that we have certain institutions, not others, is one mode in which human nature has expressed itself. But as far as we know, human nature could yield many different kinds of institutions. The particular ones that have developed have to do with historical contingency, who conquered whom, and that sort of thing. They're not rooted, they're not rooted in our nature in the sense that they're essential to our nature. So it's commonly argued that these days that something like market systems is just part of our nature. But we know from a huge amount of evidence that that's not true. There's all kinds of other structures. It's a particular fact about a moment of modern history. Others have argued that the roots of classical liberalism actually argue that what's called sometimes an instinct for freedom, an instinct to be free of domination by illegitimate authority is the core of our nature. That would be the opposite of this. And we don't know. We just know that human nature can accommodate both kinds.


Noam Chomsky: Neuralink and the Expansion of Cognitive Capacity

So I just spent a day at a company called Neuralink, and what they do is try to design what's called the brain machine, brain computer interface. So they try to do thousands readings in the brain, be able to read what the neurons are firing and then stimulate back, so two way. Do you think their dream is to expand the capacity of the brain to attain information? Sort of increase the bandwidth at which we can search Google kind of thing. Do you think our cognitive capacity might be expanded, our linguistic capacity, our ability to reason might be expanded by adding a machine into the picture? Can be expanded in a certain sense, but a sense that was known thousands of years ago. A book expands your cognitive capacity. Okay, so this could expand it too. But it's not a fundamental expansion. It's not totally new things could be understood. Well, nothing that goes beyond their native cognitive capacities. Just like you can't turn the visual system into an insect system. Well, I mean, the thought is perhaps you can't directly, but you can map. You could, but we know that without this experiment. You could map what a bee sees and present it in a form so that we could follow it. In fact, every bee scientist does that. But you don't think there's something greater than bees that we can map and then all of a sudden discover something, be able to understand a quantum world, quantum mechanics, be able to start to be able to make sense. Students at MIT study and understand quantum mechanics. But they always reduce it to the infant, the physical. I mean, they don't really understand. Oh, you don't, there's things. That may be another area where there's just a limit to understanding. We understand the theories, but the world that it describes doesn't make any sense. So, you know, the experiment, the Schrödinger's cat, for example, can understand the theory, but as Schrödinger pointed out, it's an unintelligible world. So, one of the reasons why Einstein was always very skeptical about quantum theory, he described himself as a classical realist, in one's intelligibility. He has something in common with infants in that way.