JD·万斯的 AI 演讲、技术乐观派与末日派、关税与 AI 版权案：纳瓦尔·拉维坎特做客

Jason Calacanis (00:00:00): Great job, Nava. You rocked it. Naval Ravikant (00:00:01): Maybe I should have said this on air, but that was literally the most fun podcast I've ever recorded. Jason Calacanis (00:00:06): Oh, that's on air. Cut that in. Chamath Palihapitiya (00:00:08): Yeah. Put it in the show. Put it in the show. Naval Ravikant (00:00:09): I had my theory on why you were number one, but now I have the realization. Jason Calacanis (00:00:13): What's the actual reason? You know us for a long time. David Friedberg (00:00:14): Yeah. What was your theory? What's the reality? Naval Ravikant (00:00:16): My theory was that my problem with going on podcast is usually the person I'm talking to is not that interesting. They're just asking the same questions, and they're dialing it in, and they're not that interested. It's not like we're having a pure level actual conversation. So that's why I wanted to do AirChat and Clubhouse and things like that because Jason Calacanis (00:00:33): you can Naval Ravikant (00:00:33): actually have a conversation. Oh, I see. Right? And what you guys have very uniquely is four people, you know, of whom at least three Speaker 5 (00:00:41): are intelligent. No kidding. Jason Calacanis (00:00:43): I think you're saying that Saks isn't here. I did see yeah. What? Wait. Saks isn't even hearing you say that before? That is Speaker 5 (00:00:50): so fast. Naval Ravikant (00:00:50): Fast. Right. Of whom at least three are intelligent, and all of you get along, and you can have an ongoing conversation. That's a very high hit rate. Normally in a podcast, you only get one interesting person, and now you've got three, maybe four. Right? Okay. So that to me was why I always discuss the am I Who are you Jason Calacanis (00:01:08): talking to is number Naval Ravikant (00:01:09): We don't know. The children remain mysterious forever. Of the four, right, the the the problem is, like, if you get people together to talk, two is a good conversation. Three possibly, four is the max. That's why the dinner table at a restaurant, four top. Right? You don't do five or six because then it splits into multiple conversations. So you had four people who were capable of talking. Right? That I thought was a secret, but there's another secret. The sec the other secret is you guys are having fun. You're talking over each other. You're making fun of each other. You're actually having fun. So that's why I'm saying this is the most fun podcast I've ever been on. On. That's Awesome. That's why you'll Speaker 5 (00:01:43): be so nice. David Friedberg (00:01:43): Welcome back anytime of all. Thanks, bro. Welcome back. Yes. Absolutely. Yeah. He had fun, guys. Jason Calacanis (00:01:48): One eight and three smart guys. I can't even believe you'd say that about Sachs. Naval Ravikant (00:01:55): He's not even here to defend himself. Sorry, David. Jason Calacanis (00:02:00): We'll let your winners ride. Rain man David Sachs. And instead, we open sourced it to the fans, and they've just gone racing with it. Love you, sis. Queen of quinoa. Queen of quinoa. I'm Alright, everybody. Welcome back to the number one podcast in the world. We're really excited. Today, Back again. Your sultan of science, David Freeberg. What do you got going on there, Freeberg? What's in the background? Everybody wants to know. I Naval Ravikant (00:02:31): used to play David Friedberg (00:02:32): I used to play a lot of a game called SimEarth on my Macintosh LC way back in the day. Jason Calacanis (00:02:38): That tracks. Naval Ravikant (00:02:39): Yeah. Jason Calacanis (00:02:40): That tracks. And, of course, with us again, your chairman David Friedberg (00:02:44): What games did you play growing up, JKL? Actually, I'm kinda curious. Did you ever play the game? Jason Calacanis (00:02:48): Say Andrea, Allison, Susan. I mean, it was like a lot of cute girls. I was out dating girls, Freeburg. David Friedberg (00:02:58): Yeah. Jason Calacanis (00:02:58): I was not on my Apple toon playing Civilization. David Friedberg (00:03:02): Let me find one of those pictures. Speaker 5 (00:03:04): Woah. Jason Calacanis (00:03:04): Woah. Don't get me in trouble, man. Speaker 5 (00:03:05): Yeah. Jason Calacanis (00:03:06): The Eighties were eighties were good to me in Brooklyn. Chamath Palihapitiya (00:03:08): Rejection, the video game. Yes. Jason Calacanis (00:03:11): You have three lives. Reject it. Reject it. It's a numbers game, Chamath. As you know, as you well know, Speaker 5 (00:03:17): it is a numbers game. Chamath Palihapitiya (00:03:19): Yeah. David Friedberg (00:03:19): Nick, go ahead. Pull up, pull up Rico Suave here. Jason Calacanis (00:03:22): Oh, no. What is this one? Naval Ravikant (00:03:23): Oh, it's a Speaker 5 (00:03:36): Yeah. Here he is out slaying. How about your uncle with the Vinjay cap, please? Naval Ravikant (00:03:36): Is epic. You know what he was slaying Chamath Palihapitiya (00:03:37): in there? David Friedberg (00:03:38): A snack. Yeah. Naval Ravikant (00:03:39): You have put Prius epic and Postus epic. Right? David Friedberg (00:03:42): Correct. And waitlist. Beef jerky. Jason Calacanis (00:03:46): Ladies and gentlemen find my Leonardo DiCaprio picture, please, and replace my fat Jay Howell picture with that. Thank you. Oh, god. I was fat. Man, plus forty pounds is a lot heavier than I Naval Ravikant (00:03:57): Snow joke. Chamath Palihapitiya (00:03:58): Snow joke. Jason Calacanis (00:03:59): 40 pounds is a lot. Same thing. There's so many great emo photos of me. Chamath Palihapitiya (00:04:03): I'm proud of you. Jason Calacanis (00:04:05): Thank you, my man. Thank you, Speaker 5 (00:04:06): my man. Jason Calacanis (00:04:07): If you want a good photo Can Chamath Palihapitiya (00:04:08): you get through the intros, please, so we can start? Come on. Quick. Jason Calacanis (00:04:11): How you doing, brother? How you doing, chairman dictator? Good. Good. Good. Good. Good. Good. Good. Good. Good. Good. Speaker 5 (00:04:16): Good. Good. Good. Good. Good. Good. Good. Jason Calacanis (00:04:16): Good. Good. Good. Good. Good. Good. Good. Good. Good the zen like mage of the early stage. He has such a way with words. He's the Socrates of nerds. Please welcome my guy, Namaste Naval. How you doing? The intros are back. Naval Ravikant (00:04:39): That is the best intro I've ever gotten. I didn't think I don't I didn't think you could do that. That was amazing. That's your superpower right there. Lock it in. Quick venture capital. Just do that. Jason Calacanis (00:04:48): Absolutely. That's actually you know what? Interestingly, yeah, Naval Ravikant (00:04:51): that's podcast in the world, like someone said. Jason Calacanis (00:04:54): I mean, that's what I'm manifesting. It's getting close. We've been in the top 10. So, I mean, the weekends are good for all in. Naval Ravikant (00:05:00): This this one will hit number one. This one will go viral. Jason Calacanis (00:05:02): Think it could. If you have some really great pithy insights, we might go right to the top. Yeah. Just gotta Naval Ravikant (00:05:08): do new audience. I just gotta do a Sieg Heil, and it'll go viral. Speaker 5 (00:05:11): Oh, no. No. Jason Calacanis (00:05:12): Oh, no. Are you gonna send us your heart? Naval Ravikant (00:05:15): My heart goes out to you. Jason Calacanis (00:05:17): I my heart I I end here at the heart. I don't send it out. I keep it right here. I put both hands on the heart, and I hold it nice and steady. I hold it in. It's sending out to you, but just not explicitly. Alright. For those of you who don't know, Nava was an entrepreneur. He kicked a bit of ass. He got his ass kicked, and then he started venture hacks. And he started emailing folks and saying, you know, twenty fifteen, twenty years ago, maybe fifteen, here are some deals in Silicon Valley. He went around. He started writing 50 k, hundred k checks. He hit a bunch of home runs, and, he turned venture hacks into angel list. And then he, has invested in a ton of great startups. Maybe give us some of the greatest hits there, Devon. Naval Ravikant (00:06:03): Yeah. Twitter, Uber, Notion, bunch of others, Postmates, Udemy, a lot of unicorns, David Friedberg (00:06:10): bunch of coming. Speaker 5 (00:06:11): I don't know. Naval Ravikant (00:06:11): It's it's actually a lot of deals at this point, but, honestly, I'm not necessarily proud of being an investor. Investor to me is a side job. It's a hobby. So I do start ups. How how Chamath Palihapitiya (00:06:21): do you define yourself? Naval Ravikant (00:06:24): I don't. I mean, I guess these days, I would say more like building things. You know, every every so called career is an evolution. Right? Yeah. And all of you guys are independent, and you kinda do what you're most interested in. Right? That's the point of making money. So you can just do what you want. So these days, I'm really into building and crafting products. So I built one recently called AirChat. It kinda didn't work. I'm still proud of what I built and got to work with an incredible team. And now I'm building a new product. This time, I'm going to hardware. Speaker 5 (00:06:53): Oh. Naval Ravikant (00:06:54): And I'm just building something that I really want. I I'm not And you funded all yourself, Naval? Partially, I bring investors along. Last time, they got their money back. Previous times, they've made money. Next time, hopefully, they'll make a lot of money. It's good to bring your friends along. Chamath Palihapitiya (00:07:09): I'll be honest. I love that you said I love the product, but it didn't work. Not enough people say that. Naval Ravikant (00:07:14): Yeah. No. I I built a product that I loved, that I was proud of, but it didn't catch fire. And it was a social product, so it had to catch fire for it to work. So I found the team great homes. They all got paid. The investors that I brought in got their money back. And I learned a ton, which I'm leveraging into the new thing. But the new thing is much harder. The new thing is hardware and software and David Friedberg (00:07:34): But what Chamath Palihapitiya (00:07:34): did you what did you learn building in 2024 and 2025 that you didn't know maybe before then? Naval Ravikant (00:07:40): The main thing was actually just the craft. The craft of pixel by pixel designing a software product and launching it. I guess the main thing I took away that was a learning was that I really enjoyed building products and that I wanted to build something even harder and something even more real. And I think, like a lot of us, I'm inspired by Elon and, you know, all the incredible work he's done. So I don't wanna build things that are easy. I wanna build things that are hard and interesting. And I wanna take on more technical risk and less market risk. This is the classic VC learning. Right? Which is you wanna build something that if people get it, if you can deliver it, you know people will want it. And it's just hard to build as opposed to you build it and you don't know if they want it. So that's Jason Calacanis (00:08:27): a learning. AirChat was a lot of fun. Speaker 5 (00:08:28): For those of Jason Calacanis (00:08:28): you who don't know, it was kind of like a social media network where you could ask a question and then people could respond, and it was like an audio based Twitter. Would you say that was the the best way to describe Naval Ravikant (00:08:40): it? Audio Twitter, asynchronous, AI transcripts, and all kinds of AI to make it easier for you, translation. Really good way for kinda try to make podcasting type conversations more accessible to everybody. Because, honestly, one of the reasons I don't go on podcast, I don't like being intermediated, so to speak. Right? Where you sit there and someone interviews you and then you go back and forth and you go through the same old things. I just wanna talk to people. I want peer relationships kinda like you guys have running here. Chamath Palihapitiya (00:09:07): Naval, what happened when you went through that phase, there was a period where it just seemed like something had gone on in your life and you just knew the answers. You were just so grounded. It's not to say that you're not grounded now, but you're you're less active posting and writing. But there was this period where I think all of us were like, alright. What does Naval think? Naval Ravikant (00:09:27): Oh, really? Oh, okay. That's news to me. Chamath Palihapitiya (00:09:30): I would say it would be like the late teens, the early twenties. Jason, you can correct me if I'm David Friedberg (00:09:34): getting the dates wrong, but it's Chamath Palihapitiya (00:09:35): in that moment where, like, these Navalisms and this sort of philosophy really started to I think people had a tremendous respect for how you were thinking about things. I I'm just curious, like, what were you going through something in that moment? Or, like Oh, yeah. Yeah. Yeah. Yeah. That's right. Naval Ravikant (00:09:49): No. They're very insightful. Yeah. Twenty so I've I've been on Twitter since 02/2007 because I was an early investor, but I never really tweeted. I didn't get featured. I had no audience. I was just doing the usual techie guy thing talking to each other. And then I started AngelList in 2010. The original thing about matching investors to startups didn't scale. It was just an email list that exploded at early on, but then just didn't scale, so we didn't have a business. And I was trying to figure out the business, and at the same time, I got a letter from the Securities Exchange Commission saying, oh, you're acting as an unlikes broker dealer. And I'm like, what? I'm not making any money. I'm not I'm just making intros. I'm not taking anything. It's just a public service. But even then, they were coming after me. So I wasn't and I'd raised a bunch of money from investors. So I was in a very high stress period of my life. Now looking back, it's almost comical that I was stressed over it. But at the time, it all felt very real. The weight of everything was on my shoulders, expectations, people, money, regulators. And I eventually went to DC and got the law changed to legalize what we do, which ironically enabled a whole bunch of other things like ICOs and incubator days and so on, demo days. Speaker 5 (00:10:55): But in that process, Naval Ravikant (00:10:55): I was in a process, I was in a very high stress period of my life, and I just started tweeting whatever I was going through, whatever realizations I was happening. It's only in stress that you sort of are forced to grow. And so whatever internal growth I was going through, I just started tweeting it, not thinking much of it. And it was a mix of there are three things that I kind of always kind of are are running through. One is I love science. You know, I'm an amateur. Love physics. Let's just leave it at that. I love reading a lot of philosophy and thinking deeply about it. And I like making money. Right? Truth, love, Speaker 5 (00:11:29): and money. Naval Ravikant (00:11:29): That's my joke on my Twitter bio. Those are the three things that I keep coming back to. And so I just started tweeting about all of them. And I think before that, the expectation was that someone like me should just be talking about money. Stay in your lane. And people have been playing it very safe. And so I think the combination, the three sort of caught people's attentions because every person thinks about everything. We don't just stay in our lane in real life. We're dealing with our relationships. We're dealing with our relationship with the universe. We're dealing with what we know to be true and, you know, with science and how we make decisions and how we figure things out. We're also dealing with the practical everyday material things of how to deal with our spouses or girlfriends or wives or husbands and how to make money and how to deal with our children. So I'm just tweeting about everything. I just got interested in everything. I'm tweeting about it, and and a lot of it, my best stuff was just notes to self. It's like, hey. Don't forget this. Chamath Palihapitiya (00:12:23): Don't forget that. Remember that one? How to get rich. David Friedberg (00:12:25): That one was the first threads, Jason Calacanis (00:12:27): and that one went to the bank. Super viral. Yeah. No. Super banger. Chamath Palihapitiya (00:12:30): Yeah. David Friedberg (00:12:30): Yeah. Yeah. Naval Ravikant (00:12:31): I think that is still the most viral thread ever on Twitter. I like timeless things. I I like philosophy. I like things that are still apply in the future. I like compound interest, if you will, in ideas. Obviously, recently, x has become so addictive that we're all checking it every day. And Elon's built the perfect for you. He's built TikTok for nerds, and we're all on it. But normally, I try to ignore the news. Obviously, last year, things got real. We all had to pay a lot of attention to the news. But I just like to tweet timeless things. I I don't know. I mean, people pay attention. Sometimes they like what I write. Sometimes they they go nonlinear on me. But, yeah, the how to get rich sweet storm was a big one. Chamath Palihapitiya (00:13:10): Is it problematic when people now meet you because the the hype versus the reality, there's, like, it's discordant now because people if they absorb this content, they expect to see some crazy dating, yeah, floating in the in the air. You know what I mean? Yes. Naval Ravikant (00:13:25): Yeah. Like, many of you have stopped drinking, but I used to, like, have the occasional glass of wine. And there was a moment there where I went and met with an information reporter back when I used to meet with reporters. And she said, where are we gonna meet? So I said, oh, let's meet at the the wine merchant, and we'll gather a glass of wine. David Friedberg (00:13:41): She's like, what you drink? Naval Ravikant (00:13:43): Like, it was like a big deal for Speaker 5 (00:13:44): No. No. No. I'm David Friedberg (00:13:45): so disappointed. Speaker 5 (00:13:47): I was Naval Ravikant (00:13:47): like, I'm an entrepreneur. Most of them are alcoholics or psychedelics or Jason Calacanis (00:13:51): Yeah. For Naval Ravikant (00:13:52): sure. Whatever it takes to medicate. David Friedberg (00:13:54): Yeah. Yeah. Right. Naval Ravikant (00:13:57): Yeah. When they say I'm on therapy, you know what that that's code for? Yeah. So, yes, it is highly Jason Calacanis (00:14:03): disoriented. Listen. Naval Ravikant (00:14:04): Yeah. I'm almost reminded of that, line in the matrix where that agent is about to, like, shoot one of the matrix characters and says only human. Right? So that's what I wanted to say to everybody, like, only human. Chamath Palihapitiya (00:14:15): Yeah. Yeah. Yeah. Jason Calacanis (00:14:17): You did a recently a podcast with Tim Ferriss on parenting. This was out there. I love this. I bought the book from this guy. Speaker 5 (00:14:26): Yeah. Jason Calacanis (00:14:27): Just give a a brief overview of this philosophy of parenting. Chamath Palihapitiya (00:14:30): Oh, I didn't listen to this after I read this. Tell us Jason Calacanis (00:14:33): what is your gonna love this. I this spoke to me, Speaker 5 (00:14:35): but it Jason Calacanis (00:14:36): was a little crazy. Naval Ravikant (00:14:37): Yeah. So I'm a big fan of David Deutsch. David Deutsch, I think, is basically the smartest living human. He's a scientist David Friedberg (00:14:42): who's fired. Naval Ravikant (00:14:44): Yeah. Quantum computation. And he's written a couple of great books, but it's about the intersection of the greatest theories that we have today, the theories with the most reach. And those are epistemology, the theory of knowledge, evolution, quantum physics, and computation. Jason Calacanis (00:14:58): This is the beginning of Infinity Guy. That's the book. Infinity is the second book. Reference. Yeah. Naval Ravikant (00:15:03): Correct. Yes. The fabric of reality is another book. I've spent a fair bit of time with him, done some podcast with him, hired and worked with people around him. And I'm just really impressed because it's like the the the framework that's made me smarter, I feel like. Because we're all fighting aging. Our brains are getting slower, and we're always trying to have better ideas. So as you age, you should have wisdom. That's your substitute for the raw horsepower of intelligence going down. And so scientific wisdom, I take from David. Not take, but, you know, I learned from David. And one of the Speaker 5 (00:15:31): things that he pioneered is called taking children seriously. And it's this Naval Ravikant (00:15:31): idea that you should take your pioneered is called taking children seriously. And it's this idea that you should take your children seriously like adults. You should always give them the same freedom that you would give an adult. If you wouldn't speak that way with your spouse, if you wouldn't force your spouse to do something, don't force a child to do something. And it's only through the latent threat of physical violence. Hey. I can control you. I can make you go to your room. I can take your dinner away or whatever that you intimidate children. And it resonated with me because I grew up very, very free. My father wasn't around when I was young. My mother didn't have the bandwidth to watch us all the time. She had other things to do. And so I kind of was making my own decisions from an extremely young age. From the age of five, nobody was telling me what to do. And from the age of nine, I was telling everybody what to do, so I'm used to that. And I've been homeschooling my own kids, so the philosophy resonated. And I found this guy Aaron Stupel on AirChat, and he was an incredible expositor of the philosophy. He lives his life with it 99% as extreme as one can go. So his kids can eat all the ice cream they want and all the Snickers bars they want. They can play on the iPad all they want. They don't have to go to school if they don't feel like it. They dress how they want. They don't have to do anything they don't want to do. Everything is a discussion, negotiation, explanation, just like you would with a roommate or an adult living in your house. And it's kind of insane and extreme. But I live my own home life in that arc, in that direction. And I'm a very free person. I don't have an office to go to. I try really not to maintain a calendar. If I can't remember it, I don't wanna do it. I don't send my kids to school. I really try not to coerce them. And so, obviously, that's an extreme model, but I was Sorry. Sorry. Naval Ravikant (00:17:14): Sorry. Chamath Palihapitiya (00:17:14): Hold on a second. Naval Ravikant (00:17:15): So Yeah. Yeah. Chamath Palihapitiya (00:17:16): Your kids if they if they were like, I want Haagen Dazs and it's 9PM, you're like, okay. Naval Ravikant (00:17:24): Two nights ago, I did this. I ordered the Haagen Dazs. It wasn't Haagen Dazs, it was a different brand that David Friedberg (00:17:28): I ordered it. Chamath Palihapitiya (00:17:29): I'm just gonna go through a David Friedberg (00:17:30): couple of examples of what we do. We do it Naval Ravikant (00:17:31): at ice cream at 9PM, and we all ate at sausage. Yeah. Chamath Palihapitiya (00:17:33): So they're like, dad, I want And they're happy. They're Naval Ravikant (00:17:35): happy kids. Chamath Palihapitiya (00:17:36): I wanna be on my iPad. I'm playing Fortnite. Leave me alone. I'll go to sleep when I want. You're like, okay. Naval Ravikant (00:17:42): My oldest probably plays iPad nine hours a day. Chamath Palihapitiya (00:17:45): Okay. So then your other kid pees in their pants because they're too lazy to walk to the bathroom? Naval Ravikant (00:17:50): They don't do that because they don't, like, pee in their pants. Speaker 5 (00:17:52): No. No. I under Chamath Palihapitiya (00:17:53): I understand. Speaker 5 (00:17:53): But I'm Chamath Palihapitiya (00:17:53): just saying, like, there's a spectrum of all of these things. Right? Yeah. And your point of view is a % of it is allowed, and you have no judgment. Naval Ravikant (00:18:01): No. That's not where I am. Chamath Palihapitiya (00:18:03): Okay. That's Naval Ravikant (00:18:03): where that's where Aaron is. My rules are a little different. My rules are they gotta do one hour of math or programming plus two hours of reading every single day. And the moment they've done that, they're free creatures. And everything else is a negotiation. We have to persuade them. It's a persuasion, I should say, not even a negotiation. And even the hour hour of math and two hours of reading, really, you get fifteen to thirty minutes of math, maybe an hour if you're lucky, and you get half an hour to two hours of reading if Chamath Palihapitiya (00:18:30): you don't mind. Think the long term consequences of that are? And then also, what is the long term consequences, let's say, on health if they're making decisions you know are just not good, like the ice cream thing at 9PM? Speaker 5 (00:18:42): Yeah. How do Chamath Palihapitiya (00:18:43): you how do you manage that in your mind? Naval Ravikant (00:18:45): I think whatever age you're at, whatever part you're at in life, you're still always struggling with your own habits. I think all of us, for example, still eat food and feel guilty or wanna eat something that we shouldn't be eating, and we're still always evolving our diets, and kids are the same. So my oldest is already he passed on the ice cream last time, and he said, I wanna eat healthier because finally I managed to get through them and persuade him that he should be healthier. My younger kids will eat it, but they'll eat a limited amount. My middle kid will sometimes eat Chamath Palihapitiya (00:19:12): some raw vegetables. So if they say something, you'll enable it, but then you'll guide you'll be like, hey. Listen. Like, this is not the choice I would make. I don't think but if you want it, I do it. Naval Ravikant (00:19:21): Yeah. I'll try it, but you also have to be careful, but you don't wanna intimidate them, and you don't wanna be so overbearing that then they just view dad as, like, controlling. Speaker 5 (00:19:29): I I Chamath Palihapitiya (00:19:30): find this so fascinating. And so what do you think happens to these kids at the like, I'm sure you have a vision of what they'll be like when they're fully formed adults. Like, what is that vision? Naval Ravikant (00:19:39): I I try not to. They're gonna be who they're gonna be. This is kinda how I grew up. I kinda did what I wanted. Jason Calacanis (00:19:45): I I would rather Naval Ravikant (00:19:47): I would rather they have agency than turn out exactly the way I want. Because agency is the hardest thing. Right? Having control over your own life, making your own decisions. And I don't want them to be happy. Speaker 5 (00:19:59): I have Naval Ravikant (00:19:59): a very happy household. Chamath Palihapitiya (00:20:01): What is the Plato, what's Plato's goal? Eudaimonia? Right? Like Eudaimonia? Naval Ravikant (00:20:05): Yeah. The happy one, Aristotle. The Chamath Palihapitiya (00:20:07): or like the the fulfillment, this concept. Is that what you want for them? Naval Ravikant (00:20:11): I don't really want anything for them. I just want them to be free and their best selves. God. I want them Jason Calacanis (00:20:20): Shamath was worrying about details. He's got, like, 17 kids now. I don't know if you know, but Shamath has got, like, a whole David Friedberg (00:20:26): bunch of things he got. But I Jason Calacanis (00:20:27): love this interview because the guy made a really interesting point, which was they're gonna have to make these decisions at some point. They're gonna have to learn the pros and cons, the the upside, the downside to all these things, eating iPad, and the quicker you get them to have agency to make these decisions for themselves with knowledge to ask questions, the more secure it will be. I find it a fascinating discussion. I like cause and effect, especially in teenagers, now that I have a teenager. It's really good for them to learn, hey. You know, if you don't do your homework, you have a problem, and then you gotta solve that problem. How are we gonna solve that problem? So I like to present it as, what's your plan? Anytime they have a problem, eight year old kids, 15 year old kids, I'd say, what's your plan to solve this? And then I'd like to hear their plan and let me know if you wanna brainstorm it. But I thought it was a very interesting super interesting discussion. Naval Ravikant (00:21:20): I I would say overall, my kids are very happy. The household is very happy. Everybody gets along. Everybody loves Speaker 5 (00:21:28): each other. Naval Ravikant (00:21:29): Yeah. Some of them are way ahead of their peers. Nobody's behind in anything that matters. Mhmm. Nobody seems unhealthy in any obvious way. No one has aberrant eating habits. I haven't even found an really an aberrant behavior that's out of line. So it's all good. Jason Calacanis (00:21:44): Self correcting. It's like a I worry I worry a David Friedberg (00:21:46): lot about this, like, iPad situation. I see my kids on an iPad, and it's almost like unless they're doing an interactive project, if they end up watching Naval Ravikant (00:21:57): Says says the guy who has a video game theme Yeah. David Friedberg (00:21:59): In the background. Interactive. Right? Naval Ravikant (00:22:01): Who probably and who probably grew up playing video games nonstop and probably spends nine hours a day on his screen just called a phone. So Jason Calacanis (00:22:08): Yeah. Naval Ravikant (00:22:09): Yeah. It's the same thing, man. David Friedberg (00:22:10): Well, I mean, I feel like watch is it but do they watch shows without No. No. There's a Speaker 5 (00:22:15): there's a Naval Ravikant (00:22:15): there's a hypocrisy to picking up your phone and then saying to your kid, no, you can't use your iPad. I grew up playing video games nonstop and video games when I was older, and I was an avid gamer until just a few years ago. David Friedberg (00:22:26): Well, no. I mean, I'm not I'm not I'm not criticizing the the iPad. I was obviously on a computer since I was four years old, so I totally get it. And I think the question for me is, like but I didn't have the ability to play a thirty minute show and then play the next thirty minute show and the next thirty minute show and then sit there for two hours and just have a show playing the whole time. I was Yeah. You know, interacting on the computer and doing stuff and building stuff Speaker 5 (00:22:51): Yeah. David Friedberg (00:22:51): Which was a little different for me Naval Ravikant (00:22:54): from a use case perspective. We we we did use to control their YouTube access, although now we don't do that. The only thing I asked them is that they put on captions when they're watching YouTube so that helps their reading. They learn to read fast. Jason Calacanis (00:23:06): That's a good tip. Yeah. I like that one. Naval Ravikant (00:23:07): I will say that one of my kids is really into YouTube. The other two are not. Like, they just got over it. And to the extent that they use YouTube, it's mostly because they're looking up videos on their favorite games. They wanna know how to be better at a game. Jason Calacanis (00:23:20): Alright. Let's keep moving through this docket. We have David Sachs with us here. So, David, give us your philosophy of parenting. Okay. Next item on the docket. Let's go. David Sacks (00:23:30): Saw that some real issues. This is the show is not Chamath Palihapitiya (00:23:33): a Parenting show? David Sacks (00:23:35): A parenting show. David Friedberg (00:23:36): Or Yeah. Jason Calacanis (00:23:36): I asked David, what what's your parenting philosophy? He said, oh, I set up their trust four years ago. So he's he's good. Tries to set up. Everything's good. Parent philosophy. Chamath Palihapitiya (00:23:46): G r a t. Check. Speaker 5 (00:23:50): You're all set, guys. Jason Calacanis (00:23:52): Let me know how it works out. Alright. Speaking of working out, we've got a vice president who isn't cuckoo for Cocoa Puffs and who actually understands what AI is. J. D. Vance gave a great speech. I watched it myself. He talked about AI in Paris. This was on Tuesday at the AI Action Summit, whatever that is. And he gave a fifteen minute banger of a speech. He talked about over regulating AI and America's intention to dominate this. And we happen to have with us, Naval, the czar, the czar of AI. So before I go into all the details about the speech, I don't wanna steal your thunder. Sacks, this this, speech had a lot of, verbiage, a lot of ideas that I've heard before that maybe we've all talked about. Maybe tell us a little bit about how this all came together and how proud you are. I mean, gosh, having a vice president who understands AI is just it's mind blowing. He could speak on a topic that's topical credibly. This was an awesome moment for America, I think. David Sacks (00:24:55): What are you implying there, JKL? Jason Calacanis (00:24:57): I'm implying you might have workshopped it with him. No. Or that he's smart. Both of those things. David Sacks (00:25:02): The vice president wrote the speech or at least directed all of it. So Okay. The ideas came from him. I'm not gonna take any credit whatsoever for this. Jason Calacanis (00:25:10): Okay. Well, it was on point. Maybe you could talk about that. Speaker 5 (00:25:12): I agree David Sacks (00:25:12): it was on point. I think it was a very well crafted and well delivered speech. Jason Calacanis (00:25:16): He made four main points about the Trump administration's approach to AI. He's gonna ensure, this is point one, that American AI continues to be the gold standard. Fantastic check. Two, he says that the administration understands that excessive regulation could kill AI just as it's taking off. And he did this in front of all the EU elites who love regulation, did it on their home court. And then he said, number three, AI must remain free from ideological bias as we've talked about here on this program. And then number four, the White House, he said, will, quote, maintain a pro worker growth path for AI so that it can be a potent tool for job creation in The US. So what are your thoughts on the four major bullet points in in his, speech here in, Paris? David Sacks (00:26:03): Well, I think that the vice president, you knew he was gonna deliver an important speech as soon as he got up there and said that I'm here to talk about not AI safety, but AI opportunity. And to understand what a bracing statement that was and really almost like a shot across the bow, you have to understand the history and context of these events. For the last couple of years, the last couple of these events have been exclusively focused on AI safety. The last in person event was in The UK at Bletchley Park, and the whole conference was devoted to AI safety. Similarly, the European AI regulation obviously is completely preoccupied with safety and trying to regulate away safety risks before they happen. Similarly, you had the Biden EO, which was based around safety, and then you have just the whole media coverage around AI, which is preoccupied with all the risks from AI. So to have the vice president get up there and say right off the bat that there are other things to talk about in respect to AI besides safety risks, that actually there are huge opportunities there, was a breath of fresh air and, like I said, kind of a shot across the bow. And, yeah, you could see almost see some of the Eurocrats. They needed their fainting couches after that. Jason Calacanis (00:27:20): Eurocrats. David Sacks (00:27:22): Trudeau looks like his dog just died. So I think that was just a really important statement right off the bat to set the context for the speech, which is AI is a huge opportunity for all of us because really that point just has not been made enough. And it's true. There are risks, but when you look at the media coverage and when you look at the dialogue that the regulators have had around this, they never talk about the opportunities. It's always just around the risk. So I think that was a very important corrective. And then like you said, he went on to say that The United States has to win this AI race. We wanna be the gold standard. We wanna dominate. Jason Calacanis (00:27:57): That was my favorite part. David Friedberg (00:27:58): Yeah. David Sacks (00:27:59): And and by the way, that language about dominating AI and and winning the global race, that is in president Trump's executive order from week one. So this is very much elaborating on the official policy of of this administration. And the vice president then went on to say that he specified how we would do that. Right? We have to win some of these key building block technologies. We wanna win in chips. We wanna win in AI models. We wanna win in applications. He said we need to build. We need to unlock energy for these companies. And then most of all, we just need to be supportive towards them as opposed to regulating them to death. And he had a lot to say about the the risk of overregulation, how often it's big companies that want regulation. He warned about regulatory capture, which our friend Bill Girtley would like. And he said that so, basically, having less regulation can actually be more fair. It can create a more level playing field for small companies as well as big companies. And then he he said to the Europeans that we want you to be partners with us. We wanna lead the world, but we want you to be our our partners and benefit from this technology that we're gonna take the lead in creating. But you also have to be a good partner to us. And then he specifically called out the overregulation that Europeans have been engaged in. He mentioned the Digital Services Act, which has acted as, like, a speed trap for American companies. It's American companies who've been overregulated and fined by these European regulations because the truth of the matter is that it's American technology companies that are winning the race. And so when Europe passes these onerous regulations, they fall most of all on American companies, and he's basically saying we need you to rebalance and and correct this because it's not fair and it's not smart policy, and it's not gonna help us collectively win this AI race. And that kinda brings me just to to the last point is I don't think he mentioned China by name, but, clearly, he talked about adversarial countries who are using AI to control their populations to engage in censorship and thought control. And he basically painted a picture where it's like, yeah, you could go work with them or you could work with us. And we're we have hundreds of years of shared history together. David Sacks (00:30:08): We believe in things like free speech, hopefully, and we want you to work with us. But if you are gonna work with us, then you have to cooperate, and we have to create a reasonable regulatory regime. Jason Calacanis (00:30:20): Naval, did you see the, speech and your thoughts just generally on JD Vance and and having somebody like this, you know, representing us and wanting to win Yeah. American exceptionalism. Surprising, Naval Ravikant (00:30:31): very impressive. I thought he was polite, optimistic, and just very forward looking. Just it's what you would expect an entrepreneur or a smart investor to say. So I was very impressed. I think the idea that America should win, great. I think that we should not regulate, I also agree with I'm not an AI doomer. I don't think AI is gonna end the world. That's a separate conversation. But there's this religion that comes along in many faces, which is that, oh, climate change is gonna end the world. AI is gonna end the world. Asteroid's gonna end the world. COVID nineteen is gonna end the world. And it just has a way of fixating your attention. Right? It captures everybody's attention at once. So it's a very seductive thing. And I think in the case of AI, it's really been overplayed by incentive bias, you know, motivated reasoning by the companies who are ahead, and they wanna pull up the ladder behind them. I I think they genuinely believe it. I think they generally believe that there's safety risk, but I think they're motivated to believe in those safety risks, and then they pass that along. But it's kind of a weird position because they have to say, oh, it's so dangerous that you shouldn't just let open source go at it, and you should let just a few of us work with you on it. But it's not so dangerous that a private company can't own the whole thing. Speaker 5 (00:31:38): Right. Naval Ravikant (00:31:38): Yeah. Because if it was truly the Manhattan Project, if they were building nuclear weapons, you wouldn't want one company to own that. Sam Altman famously said that AI will capture the light cone of all future value. In other words, like all value ever created at the speed of light from here will be captured by AI. So if that's true, then I think open source AI really matters, and little tech AI really matters. The problem is that the nature of training these models is highly centralized. They benefit from supercomputer clustered compute, so it's not clear how any decentralized model could compete. So to me, the real issue boils down to is how do you push AI forward while not having just a very small number of players control the entire thing. And we thought we had that solution with the original OpenAI, which was a nonprofit and was supposed to do it for humanity. But now because of they wanna incentivize the team and they wanna raise money, they have to privatize at least a part of it. Although it's not clear to me why they need to privatize the whole thing. Like, why do you need to buy out the nonprofit portion? You could leave a nonprofit portion and you could have the private portion for the incentives. But I think that the the real challenge is how do you keep AI from naturally centralizing because all the economics and the technology underneath are centralizing in nature. If you really think you're gonna create God, do you wanna put God on a leash with one entity controlling God? That to me is the real fear. Not I'm not scared of AI. I'm scared of what a very small number of people who control AI do to the rest of us for our own good because that's how it always works. Jason Calacanis (00:33:07): So well said. Probably should go with the Greek model, having many gods and, heroes as well. Freeberg, you heard the, JD Vance speech, I assume. What are your thoughts on overregulation and, maybe to Naval's point, one person owning this versus open source? David Friedberg (00:33:23): I think that there's this kind of big definition of social balance right now on what I would call techno optimism and techno pessimism. Generally, people sort of fall into one of those two camps. Generally speaking, techno optimists, I would say, are folks that believe that accelerating outcomes with AI, with automation, with bioengineering, manufacturing, semiconductors, quantum computing, nuclear energy, etcetera, will usher in this era of abundance by making by creating leverage, which is what technology gives us. Technology will make things cheaper, and it will be deflationary and it will give everyone more, so it creates abundance. The challenge is that people who already have a lot worry more about the exposure to the downside than they desire the upside. And so, you know, the techno pessimists are generally, like, the EU and large parts, frankly, of The United States are worried about the loss of x, the loss of jobs, the loss of this, the loss of that. Whereas countries like China and India are more excited about the opportunity to create wealth, the opportunity to create leverage, the opportunity to create abundance for their people. You know, GDP per capita in your in the EU, sixty thousand dollars a year. GDP per capita in The United States, like 82,000. But GDP per capita in India is 2,500 and China is 12,600. There's a greater incentive in those countries, to manifest upside than there is for The United States and the EU who are more worried about manifesting downside. And so it is a very difficult kind of social battle that's underway. I do think, like, over time, those governments and those countries and those social systems that embrace these technologies are gonna become more capitalist, and they're gonna require less government control and intervention in job creation, the economy, payments to people, and so on. And the countries that are more techno pessimistic are unfortunately gonna find themselves asking for greater government control, government intervention in markets, governments creating jobs, government making payments to people, governments effectively running the economy. My personal view, obviously, is that I'm a very strong advocate for technology acceleration because I think in nearly every case in human history, when a new technology has emerged, we've largely found ourselves assuming that the technology works in the framework of today or of yesteryear. David Friedberg (00:35:52): The automobile came along, and no one envisioned that everyone in The United States would own an automobile, and therefore, you would need to create all of these new industries like mechanics and car dealerships, roads, all the people servicing building roads, and all the other industry that emerged. Chamath Palihapitiya (00:36:07): Motels. David Friedberg (00:36:08): And it's it's very hard for us to sit here today and say, okay. AI is gonna destroy jobs. What's it gonna create and be right? I think we're very likely gonna be wrong whatever estimations we we give. The area that I think is most underestimated is the large technical projects that seem technically infeasible today that AI can unlock. For example, habitation in in the oceans. Like, it's very difficult for us to envision, like, creating cities underwater and creating cities in the oceans or creating cities on the moon or creating cities on Mars or finding new places to live. Those are, like, technically, people might argue, oh, that sounds stupid. I don't wanna go do that. But at the end of the day, like, human civilization will drive us to wanna do that. But those technically are very hard to pull off today, but AI can unlock a new set of industries to enable those transitions. So I think we really get it wrong when we try and assume the technology as a transplant for last year or last century and then we kind of become techno pessimists because we're worried about losing what we have. Jason Calacanis (00:37:03): Are you a techno pessimist? Are you optimist? Because I you, bring up the downside of an awful lot here on the program, but you are working every day in a very optimistic way to breed, you know, better strawberries and potatoes for folks. So you're Naval Ravikant (00:37:17): a little bit of Speaker 5 (00:37:17): a No. David Friedberg (00:37:18): I have no techno pessimism whatsoever. I try and point out why the other side is acting the way they are. Jason Calacanis (00:37:22): Got it. Okay. Putting it in full context. Speaker 5 (00:37:24): And what David Friedberg (00:37:24): I'm trying to highlight is I think that that framework is wrong. I think that that framework of trying to transplant new technology Speaker 5 (00:37:30): Sure. David Friedberg (00:37:31): Onto the old way of things operating is the wrong way to think about it. And it creates this you know, because of this manifestation about worrying about downside, it creates this fear that that creates regulation like we see in the EU. And as a result, China's GDP will scale while the EUs will stagnate if that's where they go. That's my assessment or my opinion on what will happen. Jason Calacanis (00:37:49): And, Chamath, you wanna wrap this up for us? What are your thoughts on JD? I'll give you two. Okay. Chamath Palihapitiya (00:37:54): The first is I would say, this is a really interesting moment where I would call this the tale of two vice presidents. Very early in the Biden administration, Kamala was dispatched on an equally important topic at that time, which was illegal immigration. And she went to Mexico and Guatemala. And so you actually have a really interesting AB test here. You have both vice presidents dealing with what were in that moment incredibly important issues. And I think that JD was focused. He was precise. He was ambitious. And even the part of the press that was very supportive of Kamala couldn't find a lot of very positive things to say about her. And the feedback was it was meandering. She was ducking questions. She didn't answer the questions that she was asked very well. And it's so interesting because it's a bit of a microcosm then to what happened over these next four years and her campaign, quite honestly, which you could have taken that window of that feedback. And unfortunately for her, it just continued to be very consistent. So that was one observation I had because I heard him give the speech. I heard her and I had this kind of moment where I was like, wow, two totally different people. The second is on the substance of what JD said. I said this on Tucker and I'll just simplify all of this into a very basic framework, which is if you want a country to thrive, it needs to have economic supremacy, and it needs to have military supremacy. In the absence of those two things, societies crumble. And the only thing that underpins those two things is technological supremacy, and we see this today. So on Thursday, what happened with Microsoft? They had a $24,000,000,000 contract with the United States army to deliver some whiz bang thing, and they realized that they couldn't deliver it. And so what did they do? They went to Anduril. Now why did they go to Anduril? Chamath Palihapitiya (00:39:58): Because Anduril has the technological supremacy to actually execute. A few weeks ago, we saw some attempts at technological supremacy from the Chinese with respect to DeepSeek. So I think that this is a very simple existential battle. Those who can harness and govern the things that are technologically superior will win, and it will drive economic vibrancy and military supremacy, which then creates safe, strong societies. That's it. So from that perspective, JD nailed it. He saw the forest from the trees. He said exactly what I think needed to be said and put folks on notice that you're either on the ship or you're off the ship. And I think that that was really good. Jason Calacanis (00:40:43): Yep. And there was like, a little secondary conversation that emerged, Sachs, that I would love to engage you with if you're willing, which is this civil war, quote, unquote, between maybe MAGA one point o, MAGA two point o, techies, vert in the MAGA party like ourselves, and maybe the core MAGA folks. Let me pull up the tweet here in JD's own word, and he's been engaging people in his own words. It's very clear that he's writing these tweets, a distinct difference between other politicians and this administration, and they just tell you what they think. Here it is. I'll try and write something to address this in detail. This is JD Vance's tweet. But I think this civil war is overstated. Though, yes, there are some real divergences between the populists, I would describe that as MAGA, and the techies. But briefly, in general, I dislike substituting American labor for cheap labor, my views on immigration, and offshoring flow from this. I like growth and productivity gains, and this informs my view on tech and regulation when it comes to AI specifically. The risks are, number one, overstated to your point, Nval, or two, difficult to avoid. One of my many real concerns, for instance, is about consumer fraud. That's a valid reason to worry about safety. But the other problem is much worse if a peer nation is six months ahead of The US on AI. Again, I'll try and say more. And this is JD going right at, I think, one of the more controversial topics, Sachs, that the administration is dealing with and has dealt with when it comes to immigration and tech because these two things are dovetailing each other. If we lose millions of driver jobs, which we will in the next ten years, just like we lost millions of cashier jobs, well, that's gonna impact how our nation and many of the voters look at the border and immigration. We might not be able to let as many people immigrate here if we're losing millions of jobs to AI and self driving cars. What are your thoughts on him engaging this directly, Sachs? David Sacks (00:42:49): Well, the first point he's making there is about wage pressure. Right? Which is when you throw open our borders or you throw open American markets to products that can be made in foreign countries by much cheaper labor that's not held to the same standards, the same minimum wage or the same union rules or the same safety standards that American labor is and has a huge cost advantage, then you're creating wage pressure for American workers. And he's opposed to that. And I think that is an important point because I think the way that the media or neoliberals like to portray this argument is that somehow MAGA's resistance to unlimited immigration is somehow based on xenophobia or something like that. No. It's based on bread and butter kitchen table issues, which is if you have this ridiculous open border policy, it's inevitably gonna create a lot of wage pressure for people at the bottom of the pyramid. So I think JD is making that argument. But and this is point two. He's saying I'm not against productivity growth. So technology is good because it enables all of our workers to improve their productivity, and that should result in better wages because workers can produce more. The value of their labor goes up if they have more tools to be productive. So there's no contradiction there, and I think he's explaining why there isn't a contradiction. A point I would add, he doesn't make this point in that tweet, but I would add is that one of the problems that we've had over the last, I don't know, thirty years is that we have had tremendous productivity growth in The US, but labor has not been able to capture it. All that benefit has basically gone to capital or to companies, and I think a big part of the reason why is because we've had this largely unrestricted immigration policy. David Sacks (00:44:28): So I think if you were to tamp down on immigration, if you're to stop the illegal immigration, then labor might be able to capture more of the benefits of productivity growth, and that would be a good thing. It'd be a more equitable distribution of the gains from productivity and from technology and that, I think, would help tamp down this growing conflict that you see between technologists and the rest of the country or certainly the heartland of the country. Jason Calacanis (00:44:57): Naval, this is a okay. You wanna add anything else, David? Alright. David Sacks (00:45:00): Well, I think just the final point he makes in that tweet is that he talks about how we live in a world in which there are other countries that are competitive. And, specifically, he he doesn't mention China, but he says, we have a peer competitor. And it's gonna be a much worse world if they end up being six months ahead of us on AI rather than six months behind. That is a really important point to keep in mind. I think that the whole Paris AI summit took place against the backdrop of this recognition because just a few weeks ago, we had deep sea and it's really clear that China is not a year behind us. They're hot on our heels or only maybe months behind us. And so if we hobble ourselves with unnecessary regulations, if we make it more difficult for our AI companies to compete, that doesn't mean that China's gonna follow suit and copy us. They're gonna take advantage of that fact, and they're gonna win. Jason Calacanis (00:45:48): Alright, Nava. This seems to be one of the main issues of our time. Four of the five people on this podcast right now are immigrants. So we have this amazing tradition in America. This is a country built by immigrants for immigrants. Do you think that should change now in the face of job destruction, which I know you've been tracking self driving pretty acutely. We both have an interest there, I think, over the years. You know, what's the solution here if we're gonna see a bunch of job displacement, which will happen for certain jobs. We all we all kinda know that. Should we shut the border and not let the next Naval, Chamath, Sachs, and Freiburg into the country? Well, let Naval Ravikant (00:46:28): me let me declare my biases upfront. I'm a first generation immigrant. I moved here when I was nine years old, but rather my parents did, and then I'm a naturalized citizen. So obviously, I'm in favor of some level of immigration. That said, I'm assimilated. I consider myself an American first and foremost. I bleed red, white, and blue. I believe in the Bill of Rights and the Constitution. First and second and fourth and all the proper amendments. I get up there every July 4, and I deliberately defend the second amendment on Twitter, at which point half my followers go bananas. You know? Because you're because they're not supposed to. I'm supposed to be a good immigrant. Right? And and carry the usual set of coherent leftist policies, globalist policies. So I think that legal high skill immigration with room and time for assimilation makes sense. You wanna have a brain drain on the best and brightest coming to the freest country in the world to build technology and to help civilization move forward. And, you know, as Chamath was saying, economic power and military powers downstream of technology. In fact, even culture is downstream of technology. Look at what the birth control pill did, for example, to culture or what the automobile did to culture or what radio and television did to culture and then the Internet. So technology drives everything. And if you look at wealth, wealth is a set of physical transformations that you can affect. And that's a combination of capital knowledge, and the bigger input to that is knowledge. And so The US has become the home of knowledge creation, thanks to bringing in the best and brightest. You could even argue deep seek part of the reason why we lost that is because a bunch of those kids, they studied in The US, but then we sent them back home. Chamath Palihapitiya (00:48:08): Right. Naval Ravikant (00:48:08): So I think you absolutely Is that actually accurate Jason Calacanis (00:48:11): that they were, Yeah. Yeah. Chamath Palihapitiya (00:48:12): Yeah. Some A Naval Ravikant (00:48:13): few of them. Speaker 5 (00:48:14): Really? Oh Jason Calacanis (00:48:14): my god. That's, like, exhibit a. Wow. I didn't know that. David Friedberg (00:48:17): So I Naval Ravikant (00:48:17): think you absolutely have to split skilled, assimilated immigration, which is a small set, and it has to be both. They have to both be skilled and they have to become Americans. That oath is not meaningless. Right? It has to mean something. So skilled, assimilated immigration. You have to separate that from just open borders. Whoever can wander in, just come on in. That that latter part makes no sense. David Sacks (00:48:38): If the Biden administration had only been letting in people with 50 IQs, we wouldn't have this debate right Naval Ravikant (00:48:44): now. Absolutely. Yeah. David Sacks (00:48:45): The reason why we're having this debate is because they just Jason Calacanis (00:48:47): number one. David Sacks (00:48:48): They just opened the border and let millions and millions of people in. Naval Ravikant (00:48:50): It was to their advantage to conflate legal and illegal immigration. So every time you would be like, well, we can't just open the borders. Just say, well, what about Elon? What about this? And they would just parade David Sacks (00:49:00): If they were just letting in the Elons and the Jensens and David Friedberg (00:49:04): Friedbergs. David Sacks (00:49:05): We wouldn't be having the same conversation today. Chamath Palihapitiya (00:49:07): The correlation between open borders and wage suppression is irrefutable. We know that data. And I think that the Democrats, for whatever logic, committed an incredible error in basically undermining their core cohort. I wanna go back to what you said because I think it's super important. There is a new political calculus on the field, and I agree with you. I think that the the three cohorts of the future are the asset light working in middle class. That's cohort number one. There are probably a hundred to a 50,000,000 of those folks. Then there are patriotic business owners, and then there's leaders in innovation. Those are the three. And I think that what MAGA gets right is they found the middle ground that intersects those three cohorts of people. And so every time you see this sort of left versus right dichotomy, it's totally miscast. And it sounds discordant to so many of us because that's not how any of us identify. Right? And I think that that's a very important observation because the policies that we adapt will need to reflect those three cohorts. What is the common ground amongst those three? And on that point, Naval is right. There's not a lot that those three would say is wrong with a very targeted form of extremely useful legal immigration of very, very, very smart people who agree to assimilate and be a part of America. I mean, I'm so glad you said it the way you said it. Like, I remember growing up where my parents would try to pretend that they were in Sri Lanka and sometimes I would get so frustrated. I'm like, if you wanna be in Sri Lanka, go back to Sri Lanka. I wanna be Canadian because it was easier for me to make friends. It was easier for me to have a life. I was trying my best. I wanted to be Canadian. And then when I moved to The United States Twenty Five Years ago, I wanted to be American. Mhmm. And I feel that I'm American now, and I'm proud to be an American. And I think that's what you want. You want people that embrace it. Chamath Palihapitiya (00:51:14): Doesn't mean that we can't dress up in a show war kameez every now and then. But the point is like, what do you believe? And where is your loyalty? Jason Calacanis (00:51:22): Freeberg, we used to have this concept of in a melting pot of this assimilation and that was a good thing then it became cultural appropriation we we kind of made a right turn here where where do you stand on this recruiting the best and brightest and forcing them to assimilate, making sure that they're down Speaker 5 (00:51:40): with it. Chamath Palihapitiya (00:51:40): We're good to see Jason. Jason Calacanis (00:51:40): We're good to find that Chamath Palihapitiya (00:51:41): people that care to be here. Jason Calacanis (00:51:43): Yeah. Let me restate that. Find I David Sacks (00:51:45): reject that premise of this whole conversation. Jason Calacanis (00:51:48): Wait. Wait. Hold on. David Sacks (00:51:49): Look. I'm a look. I'm a first generation American who moved here when I was five and became a citizen when I was 10. And, yes, I'm fully American, and that's the only country I have any loyalty to. But I the the premise that I reject here is that somehow an AI conversation leads to an immigration conversation because millions of jobs are gonna be lost. We don't know that. Chamath Palihapitiya (00:52:10): That's also true. David Friedberg (00:52:11): I agree with you. David Sacks (00:52:12): A huge assumption Naval Ravikant (00:52:13): I completely agree with you. David Sacks (00:52:14): Into the doomerism that AI is gonna wipe out millions of jobs. That is David Friedberg (00:52:17): not And I think it's David Sacks (00:52:18): not a great evidence. David Friedberg (00:52:19): I think it's gonna create more jobs than any Speaker 5 (00:52:21): jobs in the industry. David Sacks (00:52:22): Been lost by AI? Let's be real. We've had AI for two and a half years, and I think it's great. But so far, it's a better search engine, and it helps high school kids cheat on their essays. I mean, come on. Jason Calacanis (00:52:32): Believe that self driving is coming? Hold on a second. Sachs, you don't believe that millions Naval Ravikant (00:52:38): But but hold on. Those those driver jobs weren't even there ten years ago. Uber came along and created all these driver jobs. DoorDash created all these driver jobs. So k. What technology does yes. Technology destroys jobs, but it replaces them with opportunities that are even better. And then either you can go capture that opportunity yourself or an entrepreneur will come along and create something that allows you to capture those opportunities. AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable. Yes. There is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English. They talk back to you in plain English. But I think, David is absolutely right. I think we will see job creation by AI that will be as fast or faster than job destruction. You saw this even with the Internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job. New jobs, really opportunities, because job is a wrong word. Job implies someone else has to give it to me, and it's sort of like they're handed out to zero sum game. Forget all that. It's opportunities. After COVID, look at how many people are making money by working from home in mysterious little ways on the Internet that you can't even quite grasp. David Sacks (00:53:49): Here's the way I categorize it. Okay. Is that whenever you have a new technology, you get productivity gains. You get some job disruption, meaning that part of your job may go away, but then you get other parts that are new and hopefully more elevated, you know, more interesting. And then there is some job loss. I just think that the third category will follow the historical trend, which is that the first two categories are always bigger, and you end up with more net productivity and more net wealth creation. And we've seen no evidence to date that that's not gonna be the case. Now it's true that AI is about to get more powerful. You're gonna see a whole new wave of what are called agents this year. A agentic products are able to do more for you, but there's no evidence yet that those things are gonna be completely unsupervised and replace people's jobs. So, you know, I think that we have to see how this technology evolves, and I think one of the mistakes of, let's call it, the European approach is assuming that you can predict the future with perfect accuracy or such good accuracy that you can create regulations today that are gonna avoid all these risks in the future. And we just don't know enough yet to be able to Speaker 5 (00:54:55): do that. David Sacks (00:54:55): That's a false level of certainty. Chamath Palihapitiya (00:54:57): I agree with you. And the companies that are promulgating that view is what Naval said, those that have an economic vested interest in at least convincing the next incremental investor that this could be true because they want to make the claim that all the money should go to them so they could hoover up all the economic gains. And that's the that is the part of the cycle we're in. So if you, if you actually stratify these reactions, there's the small startup companies in AI that believe there's a productivity leap to be had, and that there's going to be prosperity. Everybody on the sidelines watching, and then a few companies that have an extremely vested interest in them being a gatekeeper because they need to raise the next 30 or $40,000,000,000 trying to convince people that that's true. And if you view it through that lens, you're right, Sachs. We have not accomplished anything yet that proves that this is gonna be cataclysmically bad. And if anything, right now, history would tell you it's probably gonna be like the past, which is generally productive and accretive to society. David Sacks (00:55:55): Yeah. And just to bring it back to JD's speech, which is where we started, I think it was a quintessentially American speech in the sense that he said we should be optimistic about the opportunities here, which I think is basically right. And we wanna lead. We want to take advantage of this. We don't wanna hobble it. We don't even fully know what it's gonna be yet. We are gonna center workers. We wanna be pro worker. And I think that if there are downsides for workers, then we can mitigate those things in the future. But it's too early to say that we know what the program should be. It's more about a statement of values at this point. Jason Calacanis (00:56:33): Do you think it's too early, Freeberg, given Optimus and all these robots being created, what we're seeing in self driving? You've talked about the ramp up with Waymo. To actually say we will not see millions of jobs and millions of people get displaced from those jobs? Naval Ravikant (00:56:51): What do Jason Calacanis (00:56:51): you think, Friedberg? I'm curious your thoughts because that is the counterargument. David Friedberg (00:56:55): My experience in the workplace is that AI tools that are doing things that an analyst or knowledge worker was doing with many hours in the past is allowing them to do something in minutes. That doesn't mean that they spend the rest of the day doing nothing. What's great for our business and for other businesses like ours that can leverage AI tools is that those individuals can now do more. And so our throughput, our productivity as an organization has gone up, and we can now create more things faster. So whatever the product is that my company makes, we can now make more things more quickly. We can do more development You're Speaker 5 (00:57:34): seeing that Jason Calacanis (00:57:35): on the ground. Correct? At a hollow And David Friedberg (00:57:36): I'm seeing it on the ground. And I don't think that this, like, transplantation of how bad AI will be for jobs is the right framing as much as it is about an acceleration of productivity. And this is why I go back to the point about GDP per capita and GDP growth. Countries, societies, areas that are interested or industries that are interested in accelerating output, in accelerating productivity, the ability to make stuff and sell stuff, are going to rapidly embrace these tools because it allows them to do more with less. And I think that's what I really see on the ground. And then the second point I'll make is the one that I mentioned earlier, and and I'll wrap up with a third point, which is I think we're underestimating the new industries that will emerge drastically dramatically. There is going to be so much new that we are not really thinking deeply about right now that we could do a whole another two hour brainstorming session on on what AI unlocks in terms of large scale projects that are traditionally or typically or today held back because of the constraints on the technical feasibility of these projects. And that ranges from accelerating to new semiconductor technology to quantum computing to energy systems to transportation to habitation, etcetera, etcetera. There's all sorts of transformations in every industry that's possible as these tools come online, and that will spurn insane new industries. The most important point is the third one, which is we don't know the overlap of job loss and job creation if there is one. And so the rate at which these new technologies impact and create new markets but I think Naval is right. I think that what happens in capitalism and in free societies is that capital and people rush to fill the hole of new opportunities that emerge because of AI and that those grow more quickly than the old bubbles deflate. So if there's a deflationary effect in terms of job need in other industries, I think that the loss will happen slower than the rush to take advantage of creating new things will happen on the other side. So my bet is probably on the order of, I think, new things will be created faster than old things will be lost. Jason Calacanis (00:59:37): I think And, actually, Naval Ravikant (00:59:38): as a quick side note to that, the fastest way to help somebody get a job right now, if you know somebody in the market who's looking for a job, the best thing you can do is say, hey. Go download the AI tools and just start talking to them. Just start using them in any way. And then you can walk into any employer in almost any field and say, hey. I understand AI, and they'll hire you David Friedberg (00:59:57): in the Speaker 5 (00:59:58): same way. Jason Calacanis (00:59:58): Naval, you and I watched this happen. We had a front row seat to it back in the day when you were doing venture hacks and I was doing Open Angel Forum. We had to like fight to find five or 10 companies a month. Then the cost of running these companies went down. They went down massively from 5,000,000 to start a company to 2, then to 250 k, then to a hundred k. I think what we're seeing is, like, three things concurrently. You're gonna see all these jobs go away for automation, self driving cars, cashiers, etcetera. But we're gonna also see static team size at places like Google. They're just not hiring because they're just having the existing bloated employee base learn the tools. But I don't know if you're seeing this, the number of startups able to get a product to market with two or three people and get to a million in revenue is booming. What are you seeing in the startup landscape? Naval Ravikant (01:00:48): Definitely what you're saying in that there's leverage, but at the same time, the I think the more interesting part is that new startups are enabled that could not exist otherwise. My last startup, AirChat, could not have existed without AI because we needed a transcription translation. Even the current thing I'm working on, it's not an AI company, but it cannot exist without AI. It is relying on AI. Even at AngelList, we're significantly adopting AI. Like, everywhere you turn, it's more opportunity, more opportunity, more opportunity. And people like to go on, Twitter or the artist formerly known as Twitter. And and and, basically, they like to exaggerate. Like, oh my god. We've hit AGI. Oh my god. I just replaced my all my mid level engineers. Oh my god. I've stopped hiring. To me, that's, like, moronic. The the the two valid ones are the one man entrepreneur shows where there's, like, one guy or one gal, and they're, like, scaling up like crazy things to AI. Jason Calacanis (01:01:38): Catherine. Shout out. Speaker 5 (01:01:39): Or there Naval Ravikant (01:01:40): are people who are embracing AI and being like, I need to hire. And I need to hire anyone who can even spell AI. Like, anyone who's even used AI. Just come on in. Come on in. Again, I would say the easiest way to see that AI is not taking jobs or creating opportunities is go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI. Tinker with it. And then go reapply for that job that rejected you and watch how they pull you in. David Sacks (01:02:04): In 2023, an economist named Richard Baldwin said AI won't take your job. It's someone using AI that will take your job because they know how to use it better than you. And that's kind of become a meme, and you see it floating around x, but I think there's a lot of truth in that. You know, as long as you remain adaptive and you keep learning and you learn how to take advantage of these tools, you should do better. And if you wall yourself off from the technology and don't take advantage of it, that's when you put yourself at risk. Naval Ravikant (01:02:29): Another way to think about it is these are natural language computers. So everyone who's intimidated by computers before should no longer be intimidated. You don't need to program anymore in some esoteric language or learn some obscure mathematics to be able to use these. You can just talk to them and they talk back to you. That's magic. Jason Calacanis (01:02:46): The new programming language is English. Chamath, you wanna wrap us up here on this opportunity slash displacement slash fast. Chamath Palihapitiya (01:02:54): I was gonna say this before, but I I'm pretty unconvinced anymore that you should bother even learning many of the hard sciences and maths that we used to as underpinnings. Like, I used to believe that the right thing to do was for everybody to go into engineering. I'm not necessarily as convinced as I used to be because I used to say, well, that's great first principles thinking, etcetera, etcetera, and you're you're gonna get trained in a toolkit that will scale. And I'm not sure that that's true. I think like you can, you can use these agents and you can use deep research and all of a sudden they replace a lot of that skill. So what's left over it's creativity, it's judgment, it's history, it's psychology. It's all of these other sort of like soft computer. Jason Calacanis (01:03:39): Leadership, communication. Chamath Palihapitiya (01:03:40): That allow you to manipulate these models in constructive ways. Because when you think of like the prompt engineering that gets you to great answers, it's actually just thinking in totally different orthogonal ways and non linearly. So that's my last thought, which is it does open up the aperture. Meaning, for every smart mathematical genius, there's many, many, many other people who have high EQ. And all of a sudden, this tool actually takes the skill away from the person with just a high IQ and says, if you have these other skills now, you can compete with me equally. And I think that that's liberating for a lot of people. Jason Calacanis (01:04:15): I'm in the camp of more opportunity. You know, I I got to watch the movie industry a whole bunch when the digital cameras came out and more people started making documentaries. More people started making independent film shorts. And then, of course, the YouTube revolution. People started making videos on YouTube or podcasts like this. And if you look at what happened with, like, the special effects industry as well, we need far fewer people to make a Star Wars movie, to make a Star Wars series, to make a Marvel series. As we've seen, now we can get the Mandalorian, Ashoka, and all these other series with smaller numbers of people and they look better than obviously the original Star Wars series or even the prequels. So there's gonna be so many more opportunities. We're now making more TV shows, more series, everything we wanted to see of every little character. That's the same thing that's happening in startups. I can't believe that there is a app now, Navaal, called Slopes just for, skiing. And there are 20 really good apps for just meditation. And there are 10 really good ones just for fasting. Like, we're going down this long tail of opportunity, and there'll be plenty of million to 10 million dollar businesses for us, you know, if people learn to use these tools. David Sacks (01:05:27): I love how that's the thing that tips you over. Jason Calacanis (01:05:31): Which one? David Sacks (01:05:33): The the opposite. Marvel movie or an extra Star Wars show, so that tips you over. Jason Calacanis (01:05:38): I think for a lot of people, it's it feels great that David Sacks (01:05:41): Yeah. I may take over the world, but, I'm gonna get next to a Star Wars movie. So I'm I'm cool Speaker 5 (01:05:45): with it. Jason Calacanis (01:05:46): I mean, it's are you not entertained? David Sacks (01:05:48): One final point on this is Yeah. Look. I mean, given the choice between the two categories of techno optimist and techno pessimist, I'm definitely in the optimist camp, and I think and I think we should be. But I I think there's actually a third category that I would submit, which is techno realist, which is technology is gonna happen. Trying to stop it is like ordering the tides to stop. If we don't do it, somebody else will. China's gonna do it or somebody else will do it. And it's better for us to be in control of the technology, to be the leader, rather than passively waiting for it to happen to us. And I just think that's always true. It's better for businesses to be proactive and take the lead, disrupt themselves instead of waiting for someone else to do it, and I think it's better for countries. And I think you did see this theme a little bit. I mean, these are my own views. I don't wanna ascribe them to the vice president, but you did see, I think, a hint of the techno realism idea in his speech and in his tweet, which is, look, AI is gonna happen. We might as well be the leader. If we don't, we could lose in a key category that has implications for national security, for our economy, for many things. So that's just not a world we wanna live in. So I think a lot of this debate is sort of academic because whether you're an optimist or pessimist, just sort of glass half empty, half full, the question is just, is it gonna happen or not? And I think the answer is yes. So then we wanna control it. This is you know, let's just boil it down. There's not a tremendous amount of choice in this, I think. Naval Ravikant (01:07:19): I would agree heavily with one point, and I would just tweak another. The point I would agree with is that it's gonna happen anyway, and that's what DeepSeek proved. You can turn off the flow of chips to them, and you can turn off the flow of talent. What do they do? They just get more efficient, and they exported it back to us. They sent us back the best open source model when our guys were staying closed source for safety reasons. David Sacks (01:07:39): And yeah. Exactly. Naval Ravikant (01:07:40): And I think DeepSeek Jason Calacanis (01:07:43): safety of their equity. David Sacks (01:07:44): Yeah. DeepSeek exploded the fallacy that The US has a monopoly in this category and that somehow, therefore, we can slow down the train and that we have total control over the train. And I think what DeepSeek showed us, no. If we slow down the train, they're just gonna win. Naval Ravikant (01:07:59): Yeah. The part the part where I try to tweak a little bit is the idea that we are gonna win. By we, when you say America, the problem is that the best way to win is to be as open, as distributed, as innovative as possible. If this all ends up in the control of one company, they're actually gonna be slower to innovate than if there's a dynamic system. And that dynamic system, by its nature, will be open. It will leak to China. It will leak to India. But these things have powerful network effects. We know this about technology. Almost all technology has network effects underneath. And so even if you are open, you're still gonna win, and you're still gonna David Sacks (01:08:34): control all Speaker 5 (01:08:34): of the network. David Sacks (01:08:34): The Internet. That was all true for the Internet. Right? The Internet's an open technology. It's based on terms David Friedberg (01:08:38): of But who who runs Naval Ravikant (01:08:39): But who who runs the market? David Sacks (01:08:40): Companies. All the dominant companies are US companies because they were Speaker 5 (01:08:43): in the league. Naval Ravikant (01:08:44): Exactly right. Exactly right. David Friedberg (01:08:45): Because we we embrace the open Internet. We embrace the open Internet. Right? That was different. David Sacks (01:08:48): So there will be benefits for all of humanity, and I think the vice president's speech was really clear that, look, we want you guys to be on board. We wanna be good partners. However, there are definitely gonna be winners economically, militarily. And in order to be one of those winners, you have to be a leader. Jason Calacanis (01:09:04): Who's gonna get to AGI first, Naval? Is it gonna be an open source? Who's gonna win? Is it gonna be open source or closed source? Who's gonna win the day? If we're sitting here five, ten years from now and we're looking at the top three language models which Speaker 5 (01:09:16): is gonna be I wish I had a lot Naval Ravikant (01:09:17): of trouble for this but I don't think we know how to build AGI but that's that's a much longer discussion. Jason Calacanis (01:09:20): Okay. Gotcha. I sign. Who's gonna have the best model five years from now? Chamath Palihapitiya (01:09:23): Hold on. I I a % agree with you. Naval Ravikant (01:09:25): I just think it's a different thing. But what we're building are these incredible natural language computers. And, actually, David, in a very pithy way, summarize the two big use cases. It's search and it's homeworks. It's paperwork. It's it's really paperwork. And and Make me a research that we're talking about disappearing are actually paperwork jobs. They're paperwork shuffling. These are made up jobs. Like, the federal government is they're finding out through Doge. You know, a third of it is, like, people digging holes in spoons and the another third are filling them back up. David Sacks (01:09:51): They're filling up paperwork and then burying it in a mine shaft. Naval Ravikant (01:09:54): They're buying it in a mine shaft in Iron Mountain. Yeah. So I I I think a lot of these made up jobs And David Sacks (01:09:58): then they're gonna go down the mine shaft to get the paperwork when someone retires and bring it up. Naval Ravikant (01:10:01): You know what? Jason Calacanis (01:10:02): I'm gonna get them some thumb drives. We can increase the throughput of the elevator with some thumb drives. It would be incredible. Naval Ravikant (01:10:07): What we found out is the d the DMV has been running the government for the last seventy years. It's been a compound. Compound. That's that's really what's going on. Speaker 5 (01:10:14): The d Naval Ravikant (01:10:15): DMV is in charge. David Sacks (01:10:16): I mean Yeah. If the world ends in nuclear war, god forbid, the only thing that's that's be left will be the cockroaches and then a bunch of, like, government government documents. Jason Calacanis (01:10:25): TPS reports. David Sacks (01:10:26): The TPS reports down in a mineshaft. Chamath Palihapitiya (01:10:28): Basically. Yeah. Jason Calacanis (01:10:31): Let's take a moment, everybody, to thank Arzahar. We miss him. We wish you could be here for the whole show. Chamath Palihapitiya (01:10:39): Thank you, czar. Speaker 5 (01:10:40): Thank you Chamath Palihapitiya (01:10:40): to the czar. We miss David Sacks (01:10:41): you. We Jason Calacanis (01:10:43): miss you, little buddy. I wish we could talk about Ukraine, but we're not allowed. Get back to work. We'll talk about it another time. Over coffee. Chamath Palihapitiya (01:10:49): Thank you so much. Speaker 5 (01:10:50): I'll see Jason Calacanis (01:10:50): you in the commissary. Thanks for the invite. Bye. Speaker 5 (01:10:53): Thank you. Jason Calacanis (01:10:54): Man, I'm so excited. I'm Naval. Sachs invited me to go to the the military mess. I'm gonna be in the commissary. David Friedberg (01:11:00): We didn't, JK. You invited yourself. Be honest. Jason Calacanis (01:11:02): I did. Yes. I did. I put it on his calendar. Naval Ravikant (01:11:04): To keep the conversation moving, let me segue a point that came up that was really important into tariffs. And the point is even though the Internet was open, The US won a lot of the Internet. A lot of US companies won the Internet. Yep. And they won that because we got there the firstest with the mostest, as they say, in the military. And that matters because a a lot of technology businesses have scale economies and network effects underneath, even basic brand based network effects. If you go back to the late nineties, early '2 thousands, very few people would have predicted that we would have ended up with Amazon basically owning all of ecommerce. You would have thought it would have been a perfect competition and very spread out. And that applies to how we ended with Uber as basically one taxi service or we end up with Airbnb. Meta, Airbnb. It's just network effects. Network effects. Network effects rule the world around me. But when it comes to tariffs and when it comes to trade, we act like network effects don't exist. The classic Ricardian comparative advantage dogma says that you should produce what you're best at. I produce what I'm best at, and we trade. And then even if you wanna charge me more for it, if you wanna impose tariffs for me to ship to you, I should still keep keep tariffs down because I'm better off. You're just selling me stuff cheaply. Great. Or if you wanna subsidize your guys, great. You're selling me stuff cheaply. The problem is that is not how most modern businesses work. Most modern businesses have network effects. As a simple thought experiment, suppose that we have two countries. Right? I'm China. You're The US. I start out by subsidizing all of my companies and industries that have network effects. So I'll subsidize TikTok. I'll ban your social media, but I'll push mine. Naval Ravikant (01:12:41): I will subsidize my semiconductors, which tend do tend to have winner take all in certain categories, or I'll subsidize my drones. And then BYD. Exactly. BYD, self driving, whatever. And then when I win, I own the whole market, and I can raise prices. And if you try to start up a competitor, then it's too late. I've got network effects. Or if I've got scale economies, I can lower my price to zero, crash you out of business. No one in their right mind will invest, and I'll raise prices right back up. So you have to understand that certain industries have hysteresis or they have network effects or they have economies of scale. And these are all the interesting ones. These are all the high margin businesses. So in those, if somebody is subsidizing or they're raising tariffs against you to protect your industries and let them develop, you do have to do something. You can't just completely back down. Jason Calacanis (01:13:28): Any other thoughts, Jamoth, about tariffs and network effects? It does seem like we do wanna have, redundancy in supply chain. So there are some exceptions here. Any, thoughts on how this might play out? Because, yeah, Trump brings up tariffs every forty eight hours, and then it doesn't seem like any of them land. So I don't know. I'm I'm still on my seventy two hour Trump rule, which is whatever he says, wait seventy two hours and and then maybe see if it actually comes to pass. Where do you stand on all these tariffs and tariff talk? Chamath Palihapitiya (01:13:58): Well, I think the tariffs will be a plug. Are they coming? Absolutely. The quantum of them, I don't know. And I think that the way that you can figure out how extreme it will be, it'll be based on what the legislative plan is for the budget. So there's two paths right now. Path one, which I think is a little bit more likely, is that they're gonna pass a slimmed down plan in the senate just on border security and military spending, And then they'll kick the can down the road for probably another three or four months on the budget. Plan two is this one big beautiful bill that's irking its way through the house. And there, they're proposing trillions of dollars of cuts. In that mode, you're going to need to raise revenue somehow and especially if you're giving away tax breaks. And the only way to do that is probably through tariffs or one way to do it is through tariffs. My honest opinion, Jason, is that I think we're in a very complicated moment. I think the senate plan is actually on the margins more likely and better. And the reason is because I think that Trump is better off getting the next sixty to ninety days of data. I mean, we're in a real pickle here. We have persistent inflation. We have a broken Fed. They're totally asleep at the switch. And the thing that Yellen and Biden did, which in hindsight now was extremely dangerous, is they issued so much short term paper that in totality, we have $10,000,000,000,000 we need to finance in the next six to nine months. So it could be the case that we have rates that are like five, five and a quarter, five and a half percent. I mean, that that's extremely bad at the same time as inflation, at the same time as delinquencies are ticking up. So I think tariffs are probably going to happen, Speaker 5 (01:15:57): but Chamath Palihapitiya (01:15:57): I think that Trump will have the most flexibility if he has time to see what the actual economic conditions will be, which will be more clear in three, four, five months. And so I almost think this big beautiful bill is actually counterproductive because I don't not sure we're gonna have all the data we need to get it right. Jason Calacanis (01:16:18): Fred Berg, any thoughts on these, tariffs you've been involved in the global, marketplace, especially when it comes to produce and wheat and all this corn and everything? What what do you think the dynamic here is gonna be, or is it saber rattling in a tool for Trump? David Friedberg (01:16:35): The biggest buyer of US ag exports is China. Jason Calacanis (01:16:38): China. David Friedberg (01:16:38): Ag exports are a major revenue source, major income source, and a major part of the economy for a large number of states. And so there will be, as there was in the first Trump presidency, very likely, very large transfer payments made to farmers because China is very likely gonna tariff imports or stop making import purchases altogether, which is what happened during the first presidency. When they did that, the federal government, I believe, had transfer payments of north of $20,000,000,000 to farmers. This is a not negligible sum, and it's a not negligible economic effect because there's then a rippling effect throughout the ag economy. So I think that's one key thing that I've heard folks talk about is the, the activity that's gonna be needed to support the farm economy as The US's biggest ag customer disappears. In the early twentieth century, we didn't have an income tax, and the federal revenue was almost entirely dependent on tariffs. When tariffs were cut, there was an expectation that there would be a decline in federal government revenue, but what actually happened is volume went up. So lower tariffs actually increased trade, increased the size of the economies. This is where a lot of economists take their basis in, hey, guys. If we do these tariffs, it's actually gonna shrink the economy. It's gonna cause a reduction in trade. The counterbalancing effect is one that has not been tested in economics, right, which is what's gonna happen if simultaneously we reduce the income tax and reduce the corporate income tax and basically increase capital flows through reduced taxation while doing the tariff implementation at the same time. So it's a grand economic experiment, and I think we'll learn a lot about what's gonna happen here as this all moves forward. I do think, ultimately, many of these countries are gonna capitulate to some degree, and we're gonna end up with some negotiated settlement that's gonna hopefully not be too short term impactful on the economies and the people and the jobs that are dependent on trade. Chamath Palihapitiya (01:18:35): Economy feels like it's in a very precarious place. Naval Ravikant (01:18:39): It does to asset holders. David Friedberg (01:18:41): Yeah. To asset holders. Naval Ravikant (01:18:42): And and, obviously, they've left it in a bad place in the last administration, and we shut down the entire country for a year over COVID. And the bill for that has come due, and that's reflected inflation. I I think there are a couple other points in tariffs. First is it's not just about money. It's also about making sure we have functional middle class with good jobs. Because if you have a non tariff world, maybe all the gains go to the upper class and an underclass. And then you can't have a functioning democracy when the average person is on one of those two extremes. So I think that's one issue. Another is strategic industries. If you look at it today, probably the largest defense contractor in the world is DJI. They got all the drones. Even in Ukraine, both sides are getting all their drone parts from DJI. Now they're getting it through different supply chains and so on. But Ukrainian drones and Russian drones, the vast majority of them are coming through China through DJI. And we don't have that industry. If we have a kinetic conflict right now and we don't have good drone supply chain internally in The US, we're probably gonna lose because those things are autonomous bullets. That's the future of all warfare. We're buying f 30 fives, and the Chinese are building swarms of natters. At scale. At scale. So we do have to reonshore those critical supply chains. And what is a drone supply chain? It's not just there's not a thing called drone. It's like motors and semiconductors and Jason Calacanis (01:19:57): It's a lot of pieces. Naval Ravikant (01:19:58): And optics and lasers and just everything across the board. So I think there are other good arguments for at least reassuring some of these industries. We need them. And the The United States is very lucky that it's very autarkic. We We have all the resources with all the supplies. We can we can be upstream of everybody with all the energy. To the extent, we're importing any energy. That is a choice we made. That is not because fundamentally we lack the energy. Right. Yeah. It's because of we and all the oil resources and the natural gas and fracking combined with all the work we've done in nuclear fission and small reactors, we should absolutely be energy independent. Jason Calacanis (01:20:34): Running the table on, and we should we should have a massive surplus. And, hey. You know, if you're if you're worried about, you know, a couple of million of DoorDash, Uber drivers losing their jobs to automation, like, hey, there's gonna be factories to build these parts for these drones that we're gonna need. So there there's a lot of opportunity, I guess, for people to Chamath Palihapitiya (01:20:54): And there Naval Ravikant (01:20:54): is and there is a difference between different kinds of jobs. Those kinds of jobs are better jobs, building difficult things at scale physically that we need for both national security and for innovation. Those are better jobs than, you know, paperwork, writing essays for other people to read. Yeah. Or even driving cars. Jason Calacanis (01:21:12): Alright. Listen. I wanna get to two more stories here. We have a really interesting copyright story that I wanted to touch on. Thompson Reuters just won the first major US AI copyright case, and fair use played a major role in this decision. This has huge implications for AI companies here in The United States. Obviously, OpenAI and the New York Times, Getty Images versus Stability. We've talked about these, but it's been a little while because the legal system takes a little bit of time and these are very complicated cases as we've talked about. Thomson Reuters owns Westlaw. If you don't know that, it's kind of like LexisNexis. It's one of the the legal databases out there that lawyers use to to find cases, etcetera. And they have a paid product with some reason analysis of legal decisions back in 2020. This is two years before ChatGPT. Reuters sued a legal research competitor called Ross for copyright infringement. Ross had created an AI powered legal search engine. Sounds great. But Ross had asked Westlaw if they would pay a license to its content for training. Westlaw said no. This all went back and forth, and then Ross signed a similar deal with a company called LegalEase. The problem is LegalEase's database was just copied and pasted from a bunch of Westlaw answers. So Reuters, Westlaw, sued Ross in 2020, accusing the company of being vicariously liable for LegalEase's direct infringement. Super important point. Anyway, the judge originally favored Ross in fair use. This week, the judge reversed this ruling and found Ross liable, noting that after further review, fair use does not apply in this case. This is the first major win, and, we debated this. So here's a clip. You know, you heard it here first on the all in pod. What I would say is, you know, when you look at that fair use doctrine, I've got a lot of experience with it. Due to the fourth factor test, I'm sure you're well aware of this, is the effect of the use on the potential market and the value of the work. If you look at the lawsuits that are starting to emerge, it is Getty's right to then make derivative products based on their images. Jason Calacanis (01:23:14): I think we would all agree. Stable diffusion, when they use these open web, that is no excuse to use an open web crawler to avoid getting a license from the original owner of that. Just because you can technically do it doesn't mean you're allowed to do it. In fact, the open web projects that provide these say explicitly, we do not give you the right to use this. You have to then go read the copyright laws on each of those websites. And on top of that, if somebody were to steal the copyrights of other people, put it on the open web, which is happening all day long, still if you're building a derivative work like this, you still need to go get it. So it's no excuse that I took some site in Russia that did a bunch of copyright violation and then I indexed them for my training model. So I think this is going to result David Friedberg (01:23:55): Hey, Britt? Naval Ravikant (01:23:56): Hey, Britt, Chamath Palihapitiya (01:23:56): can you shoot me in the face and let me know when this segment's going? Okay. Jason Calacanis (01:24:01): Oh, great. Chamath Palihapitiya (01:24:03): I feel the same way. Jason Calacanis (01:24:04): Same way now. Exactly. David Friedberg (01:24:06): I know. Me too. Yeah. Okay. Good good segment. Let's move on. Jason Calacanis (01:24:10): Well, since these guys don't give a about copyright holdings, can you call it? What do you think about, you know, I I'm so glad you're here, Navaal, to actually talk about the topics these two other guys would would have engaged with. A limb. Naval Ravikant (01:24:21): I'm gonna go to an even thinner limb and say I largely agree with you. I think it's a bit rich to crawl the open web, hoover up all the data, offer direct substitution for a lot of use cases because, you know, now you start and end with the AI model. It's not even like you link out like Google did. And then you just close off the models for safety reasons. I think if you trained on the open web, your model should be open source. Jason Calacanis (01:24:40): Yeah absolutely. So that would be a fine thing. I have a prediction here. I think this is all going to wind up like the Napster Spotify case. For people who don't know, Spotify pays I think 65¢ on the dollar to the original underwriters of of that content, the music industry. And they figured out a way to make a business and Napster is roadkill. I think that there is a non zero chance, like, it might be five or 10%, that OpenAI is gonna lose the New York Times lawsuit and they're gonna lose it hard and there could be injunctions. And I think it's the settlement might be that these language models, especially the closed ones, are gonna have to pay some percentage in a negotiated settlement of their revenue Speaker 5 (01:25:23): Have you Jason Calacanis (01:25:24): half, two thirds to the content holders. And this could make the content industry have a massive, massive uplift and a and a and a massive resurgence. Chamath Palihapitiya (01:25:34): I think that the problem there's an example on the other side of this, which is that there's a company that provides technical support for Oracle, third party company. And Oracle has tried umpteen times to sue them into oblivion using copyright infringement as part of the justification. And it's been a pall over the stock for a long time. The company's name is Rimini Street. Don't ask me why it's on my radar, but I just I've I've been looking at it. And they lost this huge lawsuit, Oracle one, and then it went to appellate court, and then it was all vacated. Why am I bringing this up? I think that the legal community has absolutely no idea how these models work. Because you can find one case that goes one way and one case that goes the other. And what I would say should become standard reading for anybody bringing any of these lawsuits. There's an incredible video that Carpathi just dropped, that Andre just dropped, where he does, like, this deep dive into LLMs, and he explains chat GPT from the ground up. It's on YouTube. It's three hours. It's excellent. And it's very difficult to watch that and not get to the same conclusion that you guys did. I'll just leave it at that. I tend to agree with this. Naval Ravikant (01:26:49): There's also a good old video by Ilya Sutzkavor where he he was a found I believe the founding chief scientist or CTO of OpenAI. And he talks about how these these large language models are basically extreme compressors. And he models them entirely as their ability to compress. And they're lossy lossy compression. Exactly. Lossy lossy compression. Exactly. Chamath Palihapitiya (01:27:09): Exactly. So Naval Ravikant (01:27:10): And and Google got sued for fair use back in the day, but the way they managed to get past the argument was they were always linking back to you. They showed Jason Calacanis (01:27:17): you the time you provided them. Traffic. Yeah. Naval Ravikant (01:27:19): They sent you the traffic. Chamath Palihapitiya (01:27:20): This is lossy compression. It is absolutely I'm now on your pay I I hate to say this, Jason. I agree with you. You were you were right. Jason Calacanis (01:27:34): You were right. That's all I wanted to hear all Speaker 5 (01:27:36): these years. Jason Calacanis (01:27:37): You were right. Speaker 5 (01:27:38): That's why I Naval Ravikant (01:27:39): was shaking my head when I saw those videos because I was like, oh man, Jason was right. Chamath Palihapitiya (01:27:44): Jason was right. Oh my god. Jason Calacanis (01:27:46): No. I just I've been through this so many times that these I think this is, you know, Rupert Murdoch said we should hold the line with Google and not allow them to index our content without a license. And Google navigated it successfully and they were able to to not get him to stop. I think what's happened now is that the New York Times remembers that. They they all remember losing their content and these snippets and the one box to Google, and they couldn't get that genie back in the bottle. I think the New York Times realizes this is their payday. I think the New York Times will make more money from licenses from LLMs than they will make from advertising or subscriptions eventually. This will renew the model. Naval Ravikant (01:28:32): Almost. I think the New York Times content is worthless to an LLM, but that's a different story. I think Speaker 5 (01:28:37): they have Jason Calacanis (01:28:37): actual about the content. If you David Friedberg (01:28:38): don't, political reason, whatever. Jason Calacanis (01:28:39): But I can tell you as a user, I loved the Wirecutter. I think you knew Brian and everybody over the Wirecutter. We that was like such a new thing. Naval Ravikant (01:28:47): Fair enough. Yeah. Wirecutter. Speaker 5 (01:28:48): What a Jason Calacanis (01:28:48): great product. I used to pay for the New York Times. I no longer pay for the New York Times. My main reason was I would go to the Wirecutter. Yeah. And I would just buy whatever they told me to buy. Now I go to ChatChippy Tea which I pay for. And ChatChippity tells me what to buy based on the wire cutter. So it's it and I'm already paying for it, so I stopped paying for it. David Friedberg (01:29:08): I philosophically disagree with all of your nonsense on this topic. All three of you are wrong, and I'll tell you why. Chamath Palihapitiya (01:29:16): No. David Friedberg (01:29:16): Number one, if information is out in the open Internet Mhmm. I I believe it's accessible and it's viewable, and I view an LLM or a web crawler as basically being a human that's reading and can store information in its brain, can if it's out there in the open, if it's behind a paywall, a %. If it's behind some protected password Speaker 5 (01:29:34): Wait. Wait. Naval Ravikant (01:29:35): Wait. Wait, David Scavenger. In that in that case, can a Google crawler just crawl entire site and serve it on Google? Why can't they do that? David Friedberg (01:29:42): There so here here's the fair use. The fair use is you cannot copy you cannot repeat the content. You cannot take the content and and repeat it. Naval Ravikant (01:29:49): That is how the law is currently written. But now Yeah. What I have is I have a tool that can remix it with just the other pieces of similar content, and I can change the words slightly and maybe even translate into different language. So where does it stop? David Friedberg (01:30:01): Do you know the musical artist Girl Talk? We should have done a Girl Talk, track here today, but he Jason Calacanis (01:30:06): He's got the musical taste. It's good. Oh, good. Here we go. David Friedberg (01:30:10): He basically take take small samples of popular tracks, and he made and he got sued for the same problem. There was another guy named White Panda, I believe, had the same problem. Ed Sheeran got sued for this. Naval Ravikant (01:30:21): Yeah. But but their entire sites, like Stack Overflow and WikiHow, that are basically disappeared now because you can just swallow them all up and you can just spit it all back out and chat GPT with slight changes. So Yep. I I think that the the first and foremost test David Friedberg (01:30:33): how much of a slight change is is exactly the right question. Yeah. Naval Ravikant (01:30:35): Which is how much are David Friedberg (01:30:36): you changing? Naval Ravikant (01:30:36): Yeah. So that's the question. Are and it actually boils out of the AGI question. Are these things actually intelligent? Are they learning? Are they compressing and regurgitating? That's the question. David Friedberg (01:30:45): I wonder this about humans, and that's why I bring up the white panda, the girl talk in audio, but also visual art. There was always artists and all even in classical music. I don't know if you guys are classical music people, but, right, there was a there there's a demonstration of how, you know, one composer learned from the next and that you can actually crack the music as kind of being standing on the shoulders of the prior. And the same is true in almost all art forms and almost all human knowledge and maybe That's right. Communication. Naval Ravikant (01:31:11): It's very hard to figure that out. David Friedberg (01:31:13): Yeah. That's exactly right. That's a hard one. Naval Ravikant (01:31:15): Very hard to figure that out, which is why I come back to there's only one of two stable solutions to this. And it's gonna happen anyway. If we don't crawl it, the Chinese will crawl it. Right? Deep seek proved that. So there's only one of two stable solutions. Either you pay the copyright holders, which I actually think doesn't work, and the reason is because someone in China will crawl it and they just dump the weights. Right? So they can just crawl and dump the compressed weights. Or if you crawl, make it open. At least contribute something back to open source. Right? You crawled open data, contribute it back to open source. And the people who don't wanna be crawled, they're gonna have to go to a huge lens to protect their data. Now Now everybody knows to protect the data. Jason Calacanis (01:31:53): Yeah. Well, the licensing thing is happening here. I have a book out from Harper Business on the shelf behind me, and, I'm getting 2,500 for the next three years for, Microsoft indexing. So they're going out and they're licensing stuff. And, they're going to David Friedberg (01:32:10): put $2,500. So you're going to Jason Calacanis (01:32:13): Literally, I'm getting $2,500 for three years, a bunch of Harper David Friedberg (01:32:16): To go into an LLM. Jason Calacanis (01:32:18): To go into Microsoft specifically. And I you know what? I'm gonna sign it, I decided, because I just wanna set the precedent. Maybe next time it's 10,000. Maybe next time it's 250. I don't care. I just wanna see people have their content respected, and I'm just hoping that Sam Weltman loses this lawsuit and they get an injunction against it. Hey, well, just because he's just such a weasel in terms of, like, making Stop. Open AI into a closed thing. I mean, I like Sam personally Stop. But I think what he did was, like, the super weasel move of all time for his own personal benefit. If he if he and this whole lying, like, oh, I have no equity. I get health care. Chamath Palihapitiya (01:32:53): He does it for the Jason Calacanis (01:32:54): And now I get 10%. Chamath Palihapitiya (01:32:55): Oh, bro. He does it. What was this? Love? What what was the statement? He does it for the Speaker 5 (01:32:59): I do Chamath Palihapitiya (01:33:00): it for the joy, the happiness. Benefit. Jason Calacanis (01:33:02): The benefits. I think he got health care. Naval Ravikant (01:33:04): I think in OpenAI's defense, they do need to raise a lot of money, and they gotta incent their employees. But that doesn't mean they need to take over the whole thing. That the nonprofit portion can still stay the nonprofit portion and get the lion's share of the benefits and be the board, And then he can have an incentive package and employees can have an incentive package and make sure that you're Jason Calacanis (01:33:22): percentage of the revenue. Naval Ravikant (01:33:23): Just give him, like, 10% of Jason Calacanis (01:33:25): the revenue goes to the team. Chamath Palihapitiya (01:33:26): Bought out Naval Ravikant (01:33:26): right now for 40,000,000,000, and then the whole thing disappears into a closed system. That part makes no sense to me. Jason Calacanis (01:33:32): That's called a shell game and a scam. Naval Ravikant (01:33:34): Yeah. I think Sam and his team would do better to leave the nonprofit part alone, leave an actual independent nonprofit board in charge, and then have a strong incentive plan and a strong fundraising plan for the investors and the employees. So I think this is workable. It's just trying to grab it all. It just seems way off, especially when it was built on open algorithms from Google, open data from the West, and other nonprofit funding from Elon and others. Jason Calacanis (01:33:58): I mean, what a great proposal, like, we just workshopped here. What if they just they what do they make? 6,000,000,000 a year? Just take 10% of it, 600,000,000 every year, and that goes into Chamath Palihapitiya (01:34:08): a bonus. They're losing money, Jason. So they have to Jason Calacanis (01:34:11): Okay. Eventually No. Naval Ravikant (01:34:12): But even equity. They could they could give equity to the people in building it, but they could still leave it in the control of the nonprofit. I just don't understand this conversion. I mean, there was a there was a board coup. Right? The board tried to fire Sam, and Sam took over the board. Now it's his handpicked board. So it also looks like self dealing. Right? And, yeah, they'll get an independent evaluation, but we all know that game. You hire a valuation expert who's gonna say what you're gonna say and they'll check David Friedberg (01:34:34): the box. Box. Naval Ravikant (01:34:35): Yeah. If they're gonna capture the light code of all future value or build super intelligence, we Chamath Palihapitiya (01:34:39): know that it's Naval Ravikant (01:34:39): worth a lot more. That's why Elon just bid a hundred billion. Chamath Palihapitiya (01:34:42): Exactly. You're saying you're saying the things that actually the regulators and and the legal community have no insight because they'll see a fairness opinion and they think, oh, it says fairness and opinion. Two words side by side. It must be fair. And they don't know how all of this stuff is gained. So yeah. Jason Calacanis (01:34:58): Yeah. I've man, I've I got stories about four zero nine a's that would Naval Ravikant (01:35:02): Exactly. Oh, yeah. Or anything David Friedberg (01:35:03): that you just described. Speaker 5 (01:35:04): Four zero Chamath Palihapitiya (01:35:04): nine a's are gained. Yeah. These fairness opinions are gained. But the the the the reality is I don't think the legal and the judicial community has any idea. Jason Calacanis (01:35:13): I mean, imagine if a founder you invested in, this is just a total imaginary situation, Naval, had, like, a great term sheet at some incredible dollar amount, didn't take it, ran the valuation down to, like, under a million, gave themselves a bunch of shares, and then took it three months later. Speaker 5 (01:35:29): Well, I Jason Calacanis (01:35:29): don't know. What would that be called? What does it come? Yeah. David Friedberg (01:35:33): Securities fraud. Can we Jason Calacanis (01:35:34): wrap up? Yeah. Let's wrap on your story. Chamath Palihapitiya (01:35:35): I had an interesting Nick will show you the photo. I had an interesting dinner on Monday with Brian Johnson, the don't die guy. Came over to my house. Jason Calacanis (01:35:43): How's his erection doing overnight? Chamath Palihapitiya (01:35:45): What we talked about is that he's got three hours a night of nighttime erections. Wow. Look at this. By the way, first of all, I'll tell you. I think that family. Hey. David Friedberg (01:35:55): I I Chamath Palihapitiya (01:35:55): I think that he's Coon. Coon. Jason Calacanis (01:35:56): Coon. Wait. Naval Ravikant (01:35:57): Which one of those is giving him the erection? Chamath Palihapitiya (01:35:59): No. No. No. He measures his nighttime erections. Jason Calacanis (01:36:01): I think Coon has given him the erection. But he but he said Chamath Palihapitiya (01:36:05): he said that when he started so by the way, he said he's he was 43 when he started this thing. He was basically clinically obese. Yeah. And in these next four years has become a specimen. He now has three hours a night of nighttime erections, but that's not the interesting thing. At the end of this dinner by the way, his skin is incredible. I I was not sure because when you see the pictures online, but his skin in real life is like a porcelain doll's. I've both my wife and I were like, we've never seen skin like this, and it's incredibly soft. Jason Calacanis (01:36:35): Wait. Wait. Wait. Wait. Woah. Woah. Woah. How do you know his skin is soft? Chamath Palihapitiya (01:36:38): You know, you brush your hand against his forearm or whatever, you know, he gives a hug at the end of the night. I'm telling you the guy's So is this Jason Calacanis (01:36:45): his hand supple skin? Chamath Palihapitiya (01:36:46): Bro, it's the softest skin I've ever touched in my life. Anyways, that's not the point. It was really fascinating dinner. He walked through his whole protocol. But at the end of it, I think it was Nikesh, the CEO of Palo Alto Networks. He was just like, give me the top three things. Top three. And of the top three things, what I'll boil it down to is the top one thing, which is like 80% of the 80%. It's all about sleep. Ask him to guess sleep. And he walked through his nighttime routine, and it's incredible, and it's straightforward. It's really simple. It's like how you do a wind down. Anyways, I have tried to Jason Calacanis (01:37:24): Explain the wind down briefly. Chamath Palihapitiya (01:37:27): Let's just say that because Brian goes to bed much earlier, so our normal time. Let's just say, you know, ten, ten thirty. So my time, I try to go to bed by 10:30. He's like, you need to be in bed. You need to, first of all, stop eating three or four hours before. Right? Okay. And I do that. I eat at 06:30, so I have about three hours. You're in bed by 09:30 or ten. You deal with the self talk. Right? Like, okay. Here's the active mind telling you all the things you have to fix in the morning. Talk it out, put it in its place, say I'm gonna deal with this in the morning. Jason Calacanis (01:37:56): Write it down in a journal, you're saying? Chamath Palihapitiya (01:37:57): Whatever you do. So that you put it away. You cannot be on your phone. Jason Calacanis (01:38:02): That's gotta be in a different room. Chamath Palihapitiya (01:38:03): It's or you just gotta be able to shut it down and then read a book so that you're actually just engaged in something. And and and he said that he typically falls asleep within three to four minutes of getting into bed and starting his Jason Calacanis (01:38:16): day. What? Chamath Palihapitiya (01:38:18): I tried it so I've been doing it since I had dinner with him on Monday. Last night, I fell asleep within fifteen minutes. The hardest part for me is to put the phone away. I can't do it. Jason Calacanis (01:38:28): Of course. Of course. What about you, Nuvalta, is your one down in Chamath Palihapitiya (01:38:31): the world? Speaker 5 (01:38:32): So I Naval Ravikant (01:38:32): know I know Brian pretty well, actually. And I joke that I'm married to the female Brian Johnson because my wife has some of his routines. But she's, like, the natural version, no supplements, and she's intense. And I think when Brian saw my sleep score from my eight sleep, he was just he was he was just like, you're gonna die. He's like, you're literally gonna die. Jason Calacanis (01:38:54): What are you guys, like, 70, 80? Naval Ravikant (01:38:55): No. It's it's terrible. It's awful. But it's Tell Jason Calacanis (01:38:58): me what's your number? What's your number? It was Naval Ravikant (01:39:00): like his thirties, forties, but yeah. But it it's also because I don't sleep much. I only sleep a few hours a night, and I also move around a lot in the bed and so on. But it's fine. I I never have trouble falling asleep, but I I would say that Brian's, yes, skin care routine is amazing. His diet is incredible. He is a genuine character. I do think a lot of what he's saying minus the supplements, I'm not a big believer in supplements. Yeah. Does work. I don't know if it's necessarily going to slow down your aging but you'll look good and you'll feel good. Yeah sleep is the number one thing. In terms of falling asleep, I don't think it's really about whether you look at your phone or not, believe it or not. I think it's about what you're doing on your phone. If you're doing anything that is cognitively stressful or getting your mind to spin, then yes. So you think, like, you Chamath Palihapitiya (01:39:42): can scroll TikTok and fall asleep is fine? Naval Ravikant (01:39:46): Anything that's entertaining or that is, like, you you could read a book, right, on your Kindle or in your iPad, and I think you'd be fine falling asleep. Or you can listen to, like, some meditation video or some spiritual teacher or something and that'll actually help you fall asleep. But if you're on x or if you're checking your email, then heck yeah, that's gonna keep you up. So my hack for sleep is a little different. I normally fall asleep within minutes. And the way I do it is I've, you you all have a meditation routine. Chamath Palihapitiya (01:40:13): You have a set time? You have a set time Naval Ravikant (01:40:15): now? No. No. I sleep whenever I feel like. Usually around one in the morning, two in the morning. Chamath Palihapitiya (01:40:19): God damn. I'm in bed by ten. Yeah. I need to sleep. Naval Ravikant (01:40:22): I'm an owl. But if you wanna fall asleep, the hack I found is everybody has tried some kind of a meditation routine. Just sit in bed and meditate. And your mind will hate meditation so much that if you force it to choose between the fork of meditation and sleeping, you will Speaker 5 (01:40:38): fall asleep Naval Ravikant (01:40:39): once every time. Chamath Palihapitiya (01:40:40): Well, okay. So after I Naval Ravikant (01:40:41): did sleep, you'll end up meditating, which is great too. Jason Calacanis (01:40:44): So just the, like, the meditation you do the body scan. Chamath Palihapitiya (01:40:47): The coder to this story was a friend a friend of mine came to see me from from The UAE, and he was here on Tuesday. And I was telling him about the dinner with Brian. And he told me the story because he's friends with Khabib, the UFC fighter. And he says, you know, when Khabib goes to his house, he eats anything and everything. Fried food, pizzas, whatever. But he trains consistently. And my friend Adallah says, how are you able to do that? And how does it not affect your physiology? He goes, I've learned since I was a kid, I sleep three hours after I train in the morning and I sleep ten hours at night. And I've done it since I was like 12 or 13 years old. Jason Calacanis (01:41:23): That's a lot of sleep. Chamath Palihapitiya (01:41:24): It's a lot of sleep. Jason Calacanis (01:41:26): I you know, the direct correlation for me is if I, do something cognitively like, you know, big heavy duty conversations or whatever. So no heavy conversations at the end of the night. No existential conversations at the end of the night. And then if I go rucking, I have the you know, on the ranch, I put on a 35 pound weight vest. I walk off Chamath Palihapitiya (01:41:45): the at night before you go to bed. Jason Calacanis (01:41:47): No. No. No. If I do it anytime during the day, typically do it in the morning or the afternoon. But the one to two mile ruck with the 35 pounds, whatever it is, it just tires my whole body out so that when I do lay down Chamath Palihapitiya (01:41:59): Is that why you don't prepare for the pod? Jason Calacanis (01:42:03): You know, I mean, this pod is the top 10 pod in the world, Shema. Do you think it's an accident? Chamath Palihapitiya (01:42:10): Freebird, what's your what's your sleep routine? Can you just go to bed? You just Jason Calacanis (01:42:13): like go to bed. Chamath Palihapitiya (01:42:13): When I take Jason Calacanis (01:42:14): a warm bath and I send J. Cali a picture of my feet. David Friedberg (01:42:18): I'll wait till J. Cali's done. I I do take a nice warm bath. Jason Calacanis (01:42:22): I nailed it. Chamath Palihapitiya (01:42:23): But you do you do it every night, a warm bath? David Friedberg (01:42:26): I do a yeah. I do a warm bath every night. Jason Calacanis (01:42:28): With candles too. Chamath Palihapitiya (01:42:29): And do you do it right before you go to bed? David Friedberg (01:42:32): Yeah. I usually do it after I put the kids down, and I'll basically start to wind down for bed. I do watch TV sometimes, but I do have the problem and the mistake of looking at my phone probably for too long before I turn the lights off. Chamath Palihapitiya (01:42:43): So do you have a consistent time where you go to bed or no? David Friedberg (01:42:48): Usually, eleven to midnight and then up at 06:30. Chamath Palihapitiya (01:42:54): Man, I I need I need eight hours. Otherwise, I'm a mess. Jason Calacanis (01:42:56): I go to bed. Eight. I hit between six and seven consistently. I try to go to bed that eleven to 1AM window and get up the seven to eight window. David Friedberg (01:43:04): My my problem is if I have work to do, I'll get on the computer or my laptop. And then when I start that after in my evening routine, I can't stop. And then all of a sudden, it's, like, three in the morning, and I'm like, oh, no. What did I just do? And then I still have to get up at 06:30. So that does happen to me. Naval Ravikant (01:43:19): So last night was unusual for me, but it was kinda funny anyway. I thought, oh, I should go to bed early because I'm an all in. Yeah. But I ended up eating ice cream with the kids late. Jason Calacanis (01:43:30): Wait. Wait. What was the brand? You say you went for another brand. I wanna know the brand. Naval Ravikant (01:43:34): I think it's Van Leeuwen or something like that. David Friedberg (01:43:36): Oh, from Van Leeuwen. Of course. New York and Brooklyn Speaker 5 (01:43:39): is good. Naval Ravikant (01:43:39): That is good. The holiday cookies and cream. Oh my god. So good. Chamath Palihapitiya (01:43:42): Yeah. It's so good. Van Leeuwen. Naval Ravikant (01:43:44): Polish that off. Then I was like, I probably ate too much to go to bed, so I better work out. So I did a kettlebell workout. David Friedberg (01:43:52): You sound Jason Calacanis (01:43:52): like Chamath. What did you say? Speaker 5 (01:43:54): Oh, you're David Friedberg (01:43:55): so good. I have Naval Ravikant (01:43:55): I have eight kettlebells right here right next to Chamath Palihapitiya (01:43:57): my end. Oh, gosh. David Friedberg (01:43:58): Yeah. Freebird, this is called Jason Calacanis (01:44:00): working out, Chamath Palihapitiya (01:44:01): Freebird. What you're seeing here Naval Ravikant (01:44:03): And then while I'm doing my kettlebell suitcase carry, I was texting with an entrepreneur friend. So you can tell how intense my workout was. And he's in Singapore, so it was in the middle of the night for me and early for him. Oh, I know. Time to go to bed. I was like I was like, okay. Now I gotta get to bed. How do I get to bed? I'm my body is all amped up. I've got food in my stomach. Brain. My brain is all my brain is all amped up, and all in podcast is tomorrow. And what time is it? It's 01:30 in the morning. I better get to bed. Oh, yeah. So I I put on, like, a little one of those spiritual videos to calm me down. And then I just and then I got in bed, and I was like, there's no way I'm falling asleep. And I started meditating, and five minutes later, I was asleep. Jason Calacanis (01:44:45): You know, actually, the Dalai Lama has these great on his YouTube channel, he's got these great, like, two hour discussions. You get about twenty, thirty minutes into that. You will fall asleep. Well, yeah. Naval Ravikant (01:44:55): My my David Friedberg (01:44:55): but my learning is Yeah. Watch any Dharma lecture from the SS center. Naval Ravikant (01:44:59): Exactly. Yeah. And my my lesson is my learning is that the mind will do anything to avoid meditation. Yeah. David Friedberg (01:45:07): Yes. By the way, did you guys see just before we wrap, did you see all the confirmations? RFK Jr confirmed. Brooke Rowland's confirmed. By the way, if you look at Polymarket, Polymarket had it all right a couple weeks ago. Like I Naval Ravikant (01:45:18): was trying to pull it. Market. There was a moment where TMC fell to, like, 56%. There's a moment when RFK fell to 75%, but then they bounced back and it was done. Jason Calacanis (01:45:27): You could've all You could've sniped that, man. You could've made money. David Friedberg (01:45:29): Yeah. Polymarket had it. And the media the media was like, no way he's getting confirmed. Yeah. This is not gonna happen, but Polymarket knows. It's so interesting. Naval Ravikant (01:45:37): Well, I I saw a very insightful tweet, and I forget who wrote it, so I'm sorry I can't give credit. But the guy basically said, look, Trump has a narrow majority in the house and the senate. Left is pointless. It's all about keeping the right wing in line. So it's all the people saying to the senators, hey. I'm gonna primary you. It's Nicole Shanahan saying, I'm gonna primary you. It's Scott Pressler saying, I'm moving to your district. That's the stuff that's moving the needle and causing the confirmations to go through. That's how you get Kash Patel. That's how you get Tulsi Gabbard at DNI. That's how you get RFG and stuff. Jason Calacanis (01:46:21): Any of these? Do you think any of them are too spicy for your taste? Or you just like the whole burn it down, put in the crazy, like, outsiders and and David Friedberg (01:46:29): It's a bad characterization. That's not a fair characterization. Jason Calacanis (01:46:33): I mean, the outsiders Honestly, Naval Ravikant (01:46:34): it's like, I never thought I'd see it. But I think between Elon and Sachs and people like that, we actually have builders and doers and financially intelligent people and economically intelligent people in charge. And, you know, despite all the craziness, Elon's not doing this for the money. He's doing it because he thinks it's the right thing Speaker 5 (01:46:49): to do. Chamath Palihapitiya (01:46:49): Of course. And having He moved into the Roosevelt Speaker 5 (01:46:53): business with the Metrobus. Naval Ravikant (01:46:53): I I think with many of us, I had I had bought into the great forces of history mindset where it's just like, okay. It's inevitable. This is what's happening. Government always gets bigger, always gets slower. David Friedberg (01:47:02): Me too. Naval Ravikant (01:47:03): Me too. We just have to try and get stuff built before they just shut everything down and we turn to Europe. But the thing that happened then was, you know, Caesar crossed crossed the Rubicon. The great man theory of history played out, and we're living in that time. And it's an it's an inspiration to all of us despite Sam Altman and Elon's current fighting. I know Sam was inspired by Elon at one point, and I think all of us are inspired by Elon. I mean, the guy can be the Diablo player and do Doge and run SpaceX and Tesla and Boring and Neuralink. I mean, it's incredibly impressive. It makes us that's why I'm doing a hardware company now. It makes me wanna do something useful with my life. You know? Elon always makes me question, am I doing something useful enough with my life? It's why I don't wanna be an investor. You know, Peter Thiel, ironically, he's an investor, but he's inspirational in that way too because he's like, yeah. The future just doesn't just happen. You have to go make it. So, you know, we get to go make the future, and I'm just glad that Elon and Doge and others are making Jason Calacanis (01:47:56): the future drive. Where? What the what do we got going on here? I'll give Naval Ravikant (01:47:59): you a real quick update. All in podcast in a couple of months. But it's really it's really difficult. Speaker 5 (01:48:03): I'm not Naval Ravikant (01:48:04): sure I can pull it off. So let me try. Let me just make sure it's by Jason Calacanis (01:48:06): Is it drone related? Is it self driving related? Naval Ravikant (01:48:09): Drones drones are cool, but no. It's not. Speaker 5 (01:48:11): Maybe all in the podcast should be David Friedberg (01:48:11): an angel investor. Oh, yeah. That's syndicate. Jason Calacanis (01:48:14): Yeah. Let's do it. Give me a free stock. David Friedberg (01:48:17): No no syndicate, Jason. Just our money. Jason Calacanis (01:48:19): Talk about you know how I learned about syndicates was Naval. The first syndicate I ever did on AngelList, I think is still the biggest. I don't know. 5%, and Navaal's my partner on this, for calm.com. Naval Ravikant (01:48:31): I think you'll love what I'm working on if I pull it off. I think you guys will love it. Speaker 5 (01:48:35): I'd love Naval Ravikant (01:48:35): to show you a demo. Jason Calacanis (01:48:36): Send the check. Get that cherry chip Van Lewin. Chamath Palihapitiya (01:48:39): I love you guys. Jason Calacanis (01:48:40): What have we learned? Chamath Palihapitiya (01:48:41): I gotta go. Okay. Big shout out to Bobby and to Chelsea. That's a huge, huge, huge dream for America. Jason Calacanis (01:48:46): I'm stoked about both of them. Naval Ravikant (01:48:48): Yeah. Congratulations. Jason Calacanis (01:48:50): I love me so David Friedberg (01:48:51): Thanks for coming. Bobby Kennedy Speaker 5 (01:48:54): back on David Friedberg (01:48:54): the pod. Jason Calacanis (01:48:55): Let's get Bobby hey, Bobby. Come back on the pod. Four, Lazar David Sacks, your sultan of science, David Freiberg, the chairman dictator, Chamath Palihapitiya, and namaste Nava. I am the world's greatest moderator. And I'll see you next time on the All in Pine. Namaste, bitches. Bye Speaker 5 (01:49:18): bye. We'll Jason Calacanis (01:49:20): let your winners ride. Rain man David. And it said we open sourced it to the fans, and they've just gone crazy with it. Love you, West. Queen of quinoa. Speaker 5 (01:49:40): Besties are gone. 13. That is my dog. Can you get a wish in your driveway syntax? We're not We should all just get a room Chamath Palihapitiya (01:49:52): and just have one big huge orgy because they're all just useless. Speaker 5 (01:49:55): It's like this, like, sexual tension Chamath Palihapitiya (01:49:56): that we just need to release somehow. Let your feet. David Friedberg (01:50:01): Let your feet. Where Jason Calacanis (01:50:04): did you get merchandise? Turkey's arm back.