Stephen Schwarzman: Going Big in Business, Investing, and AI | Lex Fridman Podcast #96

The following is a conversation with Stephen Schwarzman, CEO and co-founder of Blackstone, one of the world's leading investment firms with over $530 billion of assets under management. He's one of the most successful business leaders in history. I recommend his recent book called, "'What It Takes'," that tells stories and lessons from his personal journey. Stephen is a philanthropist and one of the wealthiest people in the world. Recently, signing the Giving Pledge, thereby committing to give the majority of his wealth to philanthropic causes. As an example, in 2018, he donated $350 million to MIT to help establish his new College of Computing, the mission of which promotes interdisciplinary, big, bold research in artificial intelligence. For those of you who know me, know that MIT is near and dear to my heart and always will be. It was and is a place where I believe big, bold, revolutionary ideas have a home. And that is what is needed in artificial intelligence research in the coming decades. Yes, there's institutional challenges, but also there's power in the passion of individual researchers, from undergrad to PhD, from young scientists to senior faculty. I believe the dream to build intelligence systems burns brighter than ever in the halls of MIT. This conversation was recorded recently, but before the outbreak of the pandemic. For everyone feeling the burden of this crisis, I'm sending love your way. Stay strong, we're in this together. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, Masterclass and ExpressVPN. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex and getting ExpressVPN at expressvpn.com slash LexPod. This show is sponsored by Masterclass. Sign up at masterclass.com slash Lex to get a discount and support this podcast. When I first heard about Masterclass, I thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking communication, Will Wright, creator of SimCity and Sims on game design, Carlos Santana on guitar, Gary Kasparov on chess, Daniel Negrano on poker, and many, many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. By the way, you can watch it on basically any device. Once again, sign up at masterclass.com slash Lex to get a discount and to support this podcast. This show is sponsored by ExpressVPN. Get it at expressvpn.com slash LexPod to get a discount and to support this podcast. I've been using ExpressVPN for many years. I love it. It's easy to use, press the big power on button and your privacy is protected. And if you like, you can make it look like your location is anywhere else in the world. I might be in Boston now, but it can make it look like I'm in New York, London, Paris, or anywhere else in the world. This has a large number of obvious benefits. Certainly, it allows you to access international versions of streaming websites like the Japanese Netflix or the UK Hulu. ExpressVPN works on any device you can imagine. I use it on Linux, shout out to Ubuntu 2004, Windows, Android, but it's available everywhere else too. Once again, get it at expressvpn.com slash LexPod to get a discount and to support this podcast. And now here's my conversation with Steven Schwarzman. Let's start with a tough question. What idea do you believe, whether grounded in data or in intuition, that many people you respect disagree with you on? Well, there isn't all that much anymore since the world's so transparent. But one of the things I believe in, put it in the book, what it takes is, is if you're gonna do something, do something very consequential. Do something that's quite large, if you can, that's unique. Because if you operate in that kind of space, when you're successful, it's a huge impact. The prospect of success enables you to recruit people who wanna be part of that. And those type of large opportunities are pretty easily described. And so not everybody likes to operate at scale. Some people like to do small things because it is meaningful for them emotionally. And so occasionally you get a disagreement on that. But those are life choices rather than commercial choices. That's interesting. What good and bad comes with going big? See, we often, in America, think big is good. What's the benefit, what's the cost? In terms of just bigger than business, but life, happiness, the pursuit of happiness? Well, you do things that make you happy. It's not mandated. And everybody's different. And some people, if they have talent, like playing pro football, other people just like throwing the ball around, not even being on a team. What's better? Depends what your objectives are, depends what your talent is, depends what gives you joy. So in terms of going big, is it both for impact on the world and because you personally, it gives you joy? Well, it makes it easier to succeed, actually. Because if you catch something, for example, that's cyclical, that's a huge opportunity, then you usually can find some place within that huge opportunity where you can make it work. If you're prosecuting a really small thing and you're wrong, you don't have many places to go. So I've always found that the easy place to be and the ability where you can concentrate human resources, get people excited about doing like really impactful big things, and you can afford to pay them, actually, because the bigger thing can generate much more in the way of financial resources. So that brings people out of talent to help you. And so altogether, it's a virtuous circle, I think. How do you know an opportunity when you see one in terms of the one you wanna go big on? Is it intuition, is it facts, is it back and forth deliberation with people you trust? What's the process? Is it art, is it science? Well, it's pattern recognition. And how do you get to pattern recognition? First, you need to understand the patterns and the changes that are happening. And that's either, it's observational on some level. You can call it data, or you can just call it listening to unusual things that people are saying that they haven't said before. And I've always tried to describe this. It's like seeing a piece of white lint on a black dress, but most people disregard that piece of lint. They just see the dress. I always see the lint. And I'm fascinated by how did something get some place it's not supposed to be? So it doesn't even need to be a big discrepancy. But if something shouldn't be someplace in a constellation of facts that sort of made sense in a traditional way, I've learned that if you focus on why one discordant note is there, that's usually a key to something important. And if you can find two of those discordant notes, that's usually a straight line to someplace. And that someplace is not where you've been. And usually when you figure out that things are changing or have changed, and you describe them, which you have to be able to do because it's not some odd intuition. It's just focusing on facts. It's almost like a scientific discovery, if you will. When you describe it to other people in the real world, they tend to do absolutely nothing about it. And that's because humans are comfortable in their own reality. And if there's no particular reason at that moment to shake them out of their reality, they'll stay in it, even if they're ultimately completely wrong. And I've always been stunned that when I explain where we're going, what we're doing, and why, almost everyone just says, that's interesting. And they continue doing what they're doing. And so I think it's pretty easy to do that. But what you need is a huge data set. So before AI and people's focus on data, I've sort of been doing this mostly my whole life. I'm not a scientist, let alone a computer scientist. And you can just hear what people are saying when somebody says something or you observe something that simply doesn't make sense. That's when you really go to work. The rest of it's just processing. You know, on a quick tangent, pattern recognition is a term often used throughout the history of AI. That's the goal of artificial intelligence, is pattern recognition, right? But there's, I would say, various flavors of that. So usually, pattern recognition refers to the process of the, we said dress and the lint on the dress. Pattern recognition is very good at identifying the dress, is looking at the pattern that's always there, that's very common and so on. You almost refer to a pattern that's like in, what's called outlier detection in computer science, right? The rare thing, the small thing. Now, AI is not often good at that. Do you, just almost philosophically, the kind of decisions you made in your life, based scientifically, almost on data, do you think AI in the future will be able to do? Is it something that could be put down into code or is it still deeply human? It's tough for me to say, since I don't have domain knowledge in AI to know everything that could or might occur. I know, sort of in my own case, that most people don't see any of that. I just assumed it was motivational. But it's also sort of, it's hard wiring. What are you wired or programmed to be finding or looking for? It's not what happens every day. That's not interesting, frankly. I mean, that's what people mostly do. I do a bunch of that too, because that's what you do in normal life. But I've always been completely fascinated by the stuff that doesn't fit. Or the other way of thinking about it, it's determining what people want without them saying it. That's a different kind of pattern. You can see everything they're doing. There's a missing piece. They don't know it's missing. You think it's missing, given the other facts you know about them. And you deliver that, and then that becomes sort of very easy to sell to them. To linger on this point a little bit, you've mentioned that in your family, when you were growing up, nobody raised their voice in anger or otherwise. And you said that this allows you to learn to listen and hear some interesting things. Can you elaborate, as you have been, on that idea? What do you hear about the world if you listen? Well, you have to listen really intensely to understand what people are saying, as well as what people are intending. Because it's not necessarily the same thing. And people mostly give themselves away. No matter how clever they think they are. Particularly if you have the full array of inputs. In other words, if you look at their face, you look at their eyes, which are the window on the soul, it's very difficult to conceal what you're thinking. You look at facial expressions and posture. You listen to their voice, which changes. When you're talking about something you're comfortable with or not, are you speaking faster? Is the amplitude of what you're saying higher? Most people just give away what's really on their mind. They're not that clever. They're busy spending their time thinking about what they're in the process of saying. And so if you just observe that, not in a hostile way, but just in an evocative way, and just let them talk for a while, they'll more or less tell you almost completely what they're thinking, even the stuff they don't want you to know. And once you know that, of course, it's sort of easy to play that kind of game. Because they've already told you everything you need to know. And so it's easy to get to a conclusion if there's meant to be one, an area of common interest, since you know almost exactly what's on their mind. And so that's an enormous advantage, as opposed to just walking in some place and somebody telling you something and you believing what they're saying. There's so many different levels of communication. So a powerful approach to life you discuss in the book on the topic of listening and really hearing people is figuring out what the biggest problem and bothering a particular individual or group is, and coming up with a solution to that problem, and presenting them with a solution, right? In fact, you brilliantly describe a lot of simple things that most people just don't do. It's kind of obvious. Find the problem that's bothering somebody deeply. And as you said, I think you've implied that they will usually tell you what the problem is. But can you talk about this process of seeing what the biggest problem for a person is, trying to solve it, and maybe a particularly memorable example? Yeah, sure. You know, if you know you're gonna meet somebody, there are two types of situations. Chance meetings, and you know, the second is you know you're gonna meet somebody. So let's take the easiest one, which is you know you're gonna meet somebody. And you start trying to make pretend you're them. It's really easy. What's on their mind? What are they thinking about in their daily life? What are the big problems they're facing? So if they're, you know, to make it a really easy example, you know, make pretend, you know, they're like President of the United States. Doesn't have to be this president. It can be any president. So you sort of know what's more or less on their mind because the press keeps reporting it. And you see it on television. You hear it. People discuss it. So you know if you're gonna be running into somebody in that kind of position, you sort of know what they look like already. You know what they sound like. You know what their voice is like. And you know what they're focused on. And so if you're gonna meet somebody like that, what you should do is take the biggest unresolved issue that they're facing and come up with a few interesting solutions that basically haven't been out there or that you haven't heard anybody else was thinking about. So just to give you an example, I was sort of in the early 1990s and I was invited to something at the White House which was a big deal for me because I was like a person from no place. And I had met the president once before because it was President Bush because his son was in my dormitory. So I had met him at Parents' Day. I mean it's just like the oddity of things. So I knew I was gonna see him because that's where the invitation came from. And so there was something going on and I just thought about two or three ways to approach that issue. And at that point I was separated and so I had brought a date to the White House and so I saw the president and we sort of went over in a corner for about 10 minutes and discussed whatever this issue was. And I later went back to my date. It was a little rude but it was meant to be confidential conversation and I barely knew her. And she said, what were you talking about all that time? I said, well, you know, there's something going on in the world and I've thought about different ways of perhaps approaching that and he was interested. And the answer is of course he was interested. Why wouldn't he be interested? There didn't seem to be an easy outcome. And so conversations of that type, once somebody knows you're really thinking about what's good for them and good for the situation, it has nothing to do with me. I mean, it's really about being in service to the situation, then people trust you and they'll tell you other things because they know your motives are basically very pure. You're just trying to resolve a difficult situation and help somebody do it. So these types of things, that's a planned situation. That's easy. It's just sometimes you just come upon somebody and they start talking and that requires different skills. You can ask them, what have you been working on lately? What are you thinking about? You can ask them, has anything been particularly difficult? And you can ask most people if they trust you for some reason, they'll tell you. And then you have to instantly go to work on it. And that's not as good as having some advanced planning, but almost everything going on is like out there. And people who are involved with interesting situations, they're playing in the same ecosystem. They just have different roles in the ecosystem. And you can do that with somebody who owns a pro football team that loses all the time. We specialize in those in New York. And you already have analyzed why they're losing. Inevitably, it's because they don't have a great quarterback, they don't have a great coach, and they don't have a great general manager who knows how to hire the best talent. Those are the three reasons why a team fails. Because there are salary caps, so every team pays a certain amount of money for all their players. So it's gotta be those three positions. So if you're talking with somebody like that, inevitably, even though it's not structured, you'll know how their team's doing and you'll know pretty much why. And if you start asking questions about that, they're typically very happy to talk about it because they haven't solved that problem. In some case, they don't even know that's the problem. It's pretty easy to see it. So I do stuff like that, which I find is intuitive as a process, but leads to really good results. Well, the funny thing is when you're smart, for smart people, it's hard to escape their own ego and the space of their own problems, which is what's required to think about other people's problems. It requires for you to let go of the fact that your own problems are all important and then to talk about your, I think while it seems obvious, and I think quite brilliant, it's a difficult leap for many people, especially smart people, to truly empathize with the problems of others. Well, I have a competitive advantage. I like it. Which is, I don't think I'm so smart. That's good. So it's not a problem for me. Well, the truly smartest people I know say that exact same thing. Yeah, being humble is really useful, competitive advantage, as you said. How do you stay humble? Well, I haven't changed much. Since? Since I was in my mid-teens. I was raised partly in the city and partly in the suburbs. And whatever the values I had at that time, those are still my values. I call them middle-class values. That's how I was raised. And I've never changed. Why would I? That's who I am. And so the accoutrement of the rest of your life has gotta be put on the same solid foundation of who you are. Because if you start losing who you really are, who are you? So I've never had the desire to be somebody else. I just do other things now that I wouldn't do as a middle-class kid from Philadelphia. I mean, my life has morphed on a certain level. But part of the strength of having integrity, of personality, is that you can remain in touch with everybody who comes from that kind of background. And even though I do some things that aren't like that, in terms of people I'd meet or situations I'm in, I always look at it through the same lens. And that's very psychologically comfortable and doesn't require me to make any real adjustments in my life, and I just keep plowing ahead. There's a lot of activity and progress in recent years around effective altruism. I wanted to bring this topic with you because it's an interesting one from your perspective. You can put it in any kind of terms, but it's philanthropy that focuses on maximizing impact. How do you see the goal of philanthropy, both from a personal motivation perspective and a societal big picture impact perspective? Yeah, I don't think about philanthropy the way you would expect me to, okay? I look at sort of solving big issues, addressing big issues, starting new organizations to do it, much like we do in our business. We keep growing our business, not by taking the original thing and making it larger, but continually seeing new things and building those, and sort of marshaling financial resources, human resources. And in our case, because we're in the investment business, we find something new that looks like it's gonna be terrific, and we do that, and it works out really well. All I do in what you would call philanthropy is look at other opportunities to help society, and I end up starting something new, marshaling people, marshaling a lot of money, and then at the end of that kind of creative process, so somebody typically will ask me to write a check. I don't wake up and say, how can I give large amounts of money away? I look at issues that are important for people. In some cases, I do smaller things because it's important to a person, and I can relate to that person. There's some unfairness that's happened to them, and so in situations like that, I'd give money anonymously and help them out. And it's like a miniature version of addressing something really big. So at MIT, I've done a big thing, helping to start this new school of computing, and I did that because I saw that there's sort of like a global race on in AI, quantum, and other major technologies, and I thought that the US could use more enhancement from a competitive perspective, and I also, because I get to China a lot and I travel around a lot compared to a regular person, I can see the need to have control of these types of technologies so when they're introduced, we don't create a mess like we did with the internet and with social media, unintended consequence that's creating all kinds of issues and freedom of speech and the functioning of liberal democracies. So with AI, it was pretty clear that there was enormous difference of views around the world by the relatively few practitioners in the world who really knew what was going on, and by accident, I knew a bunch of these people who were like big famous people, and I could talk to them and say, why do you think this is a force for bad? And someone else, why do you feel this is a force for good? And how do we move forward with the technology but at the same time make sure that whatever is potentially sort of on the bad side of this technology with, for example, disruption of workforces and things like that, that could happen much faster than the Industrial Revolution, what do we do about that and how do we keep that under control so that the really good things about these technologies, which will be great things, not good things, are allowed to happen? So to me, this was one of the great issues facing society, the number of people who were aware of it were very small. I just accidentally got sucked into it, and as soon as I saw it, I went, oh my God, this is mega, both on a competitive basis globally, but also in terms of protecting society and benefiting society. So that's how I got involved, and at the end, sort of the right thing that we figured out was sort of double MIT's computer science faculty and basically create the first AI-enabled university in the world and in effect be an example, a beacon to the rest of the research community around the world academically, and create a much more robust US competitive situation among the universities, because if MIT was gonna raise a lot of money and double its faculty, well, you could bet that a number of other universities were gonna do the same thing. At the end of it, it would be great for knowledge creation, great for the United States, great for the world. And so I like to do things that I think are really positive things that other people aren't acting on that I see for whatever the reason. First, it's just people I meet and what they say, and I can recognize when something really profound is about to happen or needs to, and I do it, and at the end of the situation, somebody says, can you write a check to help us? And then the answer is sure, I mean, because if I don't, the vision won't happen. But it's the vision of whatever I do that is compelling. And essentially, I love that idea of whether it's small at the individual level or really big, like the gift to MIT to launch the College of Computing. It starts with a vision, and you see philanthropy as, the biggest impact you can have is by launching something new, especially on an issue that others aren't really addressing. And I also love the notion, and you're absolutely right, that there's other universities, Stanford, CMU, I'm looking at you, that would essentially, the seed will create other, it'll have a ripple effect that potentially might help you us be a leader or continue to be a leader in AI, this potentially very transformative research direction. Just to linger on that point a little bit, what is your hope long-term for the impact the college here at MIT might have in the next five, 10, even 20, or let's get crazy, 30, 50 years? Well, it's very difficult to predict the future when you're dealing with knowledge production and creativity. Yeah, MIT has obviously some unique aspects globally, and there's four big sort of academic surveys. I forget whether it was QS, there's the Times in London, the US News, and whatever. One of these recently, MIT, was ranked number one in the world, right? So leave aside whether you're number three somewhere else, in the great sweep of humanity, this is pretty amazing. So you have a really remarkable aggregation of human talent here. And where it goes, it's hard to tell. You have to be a scientist to have the right feel. But what's important is you have a critical mass of people, and I think it breaks into two buckets. One is scientific advancement, and if the new college can help sort of either serve as a convening force within the university, or help sort of coordination and communication among people, that's a good thing, absolute good thing. The second thing is in the AI ethics area, which is in a way equally important, in a way equally important, because if the science side creates blowback, so that science is a bit crippled in terms of going forward, because society's reaction to knowledge advancement in this field becomes really hostile, then you've sort of lost the game in terms of scientific progress and innovation. And so the AI ethics piece is super important, because in a perfect world, MIT would serve as a global convener, because what you need is you need the research universities, you need the companies that are driving AI and quantum work, you need governments who will ultimately be regulating certain elements of this, and you also need the media to be knowledgeable and trained so we don't get sort of overreactions to one situation, which then goes viral, and it ends up shutting down avenues that are perfectly fine to be walking down or running down that avenue, but if enough discordant information, not even correct necessarily, sort of gets, is pushed around society, then you can end up with a really hostile regulatory environment and other things. So you have four drivers that have to be sort of integrated. And so if the new school of computing can be really helpful in that regard, then that's a real service to science, and it's a service to MIT. So that's why I wanted to get involved for both areas. And the hope is, for me, for others, for everyone, for the world, is for this particular college of computing to be a beacon and a connector for these ideas. Yeah, that's right, I mean, I think MIT is perfectly positioned to do that. So you've mentioned the media, social media, the internet, this complex network of communication with flaws, perhaps. Perhaps you can speak to them. I personally think that science and technology has its flaws but ultimately is, one, sexy, exciting. It's the way for us to explore and understand the mysteries of our world. And two, perhaps more importantly for some people, it's a huge way to, a really powerful way to grow the economy, to improve the quality of life for everyone. So how do we get, how do you see the media, social media, the internet as a society having a healthy discourse about science? First of all, one that's factual and two, one that finds science exciting, that invests in science, that pushes it forward, especially in this science fiction, fear-filled field of artificial intelligence? I think that's a little above my pay grade because trying to control social media to make it do what you want to do appears to be beyond almost anybody's control. And the technology is being used to create what I call the tyranny of the minorities. Okay, a minority is defined as two or three people on a street corner. Doesn't matter what they look like, doesn't matter where they came from, they're united by that one issue that they care about and their job is to enforce their views on the world. And in the political world, people just are manufacturing truth and they throw it all over and it affects all of us. And sometimes people are just hired to do that, I mean, it's amazing. And you think it's one person, it's really just sort of a front for a particular point of view. And this has become exceptionally disruptive for society and it's dangerous and it's undercutting the ability of liberal democracies to function. And I don't know how to get a grip on this and I was really surprised when we, you know, I was up here for the announcement last spring of the College of Computing and they had all these famous scientists, some of whom were involved with the invention of the internet and almost every one of them got up and said, I think I made a mistake. And as a non-scientist, I never thought I'd hear anyone say that and what they said is, more or less, to make it simple, we thought this would be really cool, inventing the internet, we could connect everyone in the world, we can move knowledge around, it was instantaneous, it's a really amazing thing. He said, I don't know that there was anyone who ever thought about social media coming out of that and the actual consequences for people's lives. You know, there's always some younger person, I just saw one of these yesterday, it was reported on the national news, he killed himself when people used social media to basically, you know, sort of ridicule him or something of that type. This is dead. This is dangerous. And, you know, so I don't have a solution for that other than going forward, you can't end up with this type of outcome. Using AI to make this kind of mistake twice is unforgivable. So interestingly, at least in the West and parts of China, people are quite sympathetic to, you know, sort of the whole concept of AI ethics and what gets introduced when and cooperation within your own country, within your own industry, as well as globally, to make sure that the technology is a force for good. On that really interesting topic, since 2007, you've had a relationship with senior leadership with a lot of people in China. And an interest in understanding modern China, their culture, their world, much like with Russia, I'm from Russia, originally, Americans are told a very narrow one-sided story about China that I'm sure misses a lot of fascinating complexity, both positive and negative. What lessons about Chinese culture, its ideas as a nation, its future, do you think Americans should know about, deliberate on, think about? Well, it's sort of a wide question that you're asking about. You know, China's a pretty unusual place. First, it's huge. You know, you got, it's physically huge. It's got a billion three people. And the character of the people isn't as well understood in the United States. Chinese people are amazingly energetic. If you're one of the billion three people, one of the things you gotta be focused on is how do you make your way, you know, through a crowd of a billion 2.99999 other people. Another word for that is competitive. Yes, they are individually highly energetic, highly focused, always looking for some opportunity for themselves because they need to, because there's an enormous amount of just literally people around. And so, you know, what I've found is they'll try and find a way to win for themselves. And their country is complicated because it basically doesn't have the same kind of functional laws that we do in the United States and the West. And the country is controlled really through a web of relationships you have with other people. And the relationships that those other people have with other people. So it's an incredibly dynamic culture where if somebody knocks somebody up on the top who's three levels above you and is in effect protecting you, then you're like a, you know, sort of a floating molecule there, you know, without tethering, except the one or two layers above you, but that's gonna get affected. So it's a very dynamic system, and getting people to change is not that easy because if there aren't really functioning laws, it's only the relationships that everybody has. And so when you decide to make a major change and you sign up for it, something is changing in your life. There won't necessarily be all the same people on your team. And that's a very high-risk enterprise. So when you're dealing with China, it's important to know almost what everybody's relationship is with somebody. So when you suggest doing something differently, you line up these forces. In the West, it's usually you talk to a person and they figure out what's good for them. It's a lot easier. And in that sense, in a funny way, it's easier to make change in the West, just the opposite of what people think. But once the Chinese system adjusts to something that's new, everybody's on the team. It's hard to change them, but once they're changed, they are incredibly focused in a way that it's hard for the West to do in a more individualistic culture. So there are all kinds of fascinating things. One thing that might interest the people who are listening, we're more technologically based than some other group. I was with one of the top people in the government a few weeks ago, and he was telling me that every school child in China is going to be taught computer science. Now imagine 100% of these children. This is such a large number of human beings. Now, that doesn't mean that every one of them will be good at computer science, but if it's sort of like in the West, if it's like math or English, everybody's gonna take it. Not everybody's great at English. They don't write books, they don't write poetry, and not everybody's good at math. Somebody like myself, I sort of evolved to the third grade and I'm still doing flashcards. I didn't make it further in math, but imagine everybody in their society is gonna be involved with computer science. I just even pause on that, I think computer science involves at the basic beginner level programming and the idea that everybody in the society would have some ability to program a computer is incredible. For me, it's incredibly exciting and I think that should give United States pause and consider what, talking about philanthropy and launching things, there's nothing like launching, sort of investing in young, the youth, the education system because that's where everything launches. Yes, well, we've got a complicated system because we have over 3,000 school districts around the country. China doesn't worry about that as a concept. They make a decision at the very top of the government that that's what they want to have happen and that is what will happen. And we're really handicapped by this distributed power in the education area, although some people involved with that area will think it's great, but you would know better than I do what percent of American children have computer science exposure, my guess, no knowledge, would be 5% or less. And if we're gonna be going into a world where the other major economic power, sort of like ourselves, has got like 100% and we got five and the whole computer science area is the future, then we're purposely or accidentally actually handicapping ourselves and our system doesn't allow us to adjust quickly to that. So, you know, issues like this, I find fascinating and if you're lucky enough to go to other countries, which I do, and you learn what they're thinking, then it informs what we ought to be doing in the United States. So the current administration, Donald Trump, has released an executive order on artificial intelligence. Not sure if you're familiar with it, in 2019. Looking several years ahead, how does America sort of, we've mentioned in terms of the big impact, we hope your investment in MIT will have a ripple effect, but from a federal perspective, from a government perspective, how does America establish, with respect to China, leadership in the world at the top for research and development in AI? I think that you have to get the federal government in the game in a big way. And that this leap forward technologically, which is gonna happen with or without us, you know, really should be with us, and it's an opportunity, in effect, for another moonshot kind of mobilization by the United States. I think the appetite actually is there to do that. At the moment, what's getting in the way is the kind of poisonous politics we have. But if you go below the lack of cooperation, which is almost the defining element of American democracy right now in the Congress, if you talk to individual members, they get it, and they would like to do something. Another part of the issue is we're running huge deficits. We're running trillion dollar plus deficits. So how much money do you need for this initiative? Where does it come from? Who's prepared to stand up for it? Because if it involves taking away resources from another area, our political system is not real flexible to do that. If you're creating this kind of initiative, which we need, where does the money come from? And trying to get money when you've got trillion dollar deficits, in a way, could be easy. What's the difference of a trillion and a trillion? A little more. But it's hard with the mechanisms of Congress. But what's really important is this is not an issue that is unknown, and it's viewed as a very important issue. And there's almost no one in the Congress when you sit down and explain what's going on who doesn't say we've gotta do something. Let me ask the impossible question. You didn't endorse Donald Trump, but after he was elected, you have given him advice, which seems to me a great thing to do, no matter who the president is, to positively contribute to this nation by giving advice. And yet, you've received a lot of criticism for this. So on the previous topic of science and technology and government, how do we have a healthy discourse, give advice, get excited, conversation with the government about science and technology without it becoming politicized? Well, it's very interesting. So when I was young, before there was a moonshot, we had a president named John F. Kennedy from Massachusetts here, and in his inaugural address as president, he asked not what your country can do for you, but what you can do for your country. Now, we had a generation of people my age, basically people who grew up with that credo. And sometimes you don't need to innovate. You can go back to basic principles, and that's good basic principle. What can we do? Americans have GDP per capita of around $60,000. It's not equally distributed, but it's big. And people have, I think, an obligation to help their country. And I do that, and apparently I take some grief from some people who project on me things I don't even vaguely believe. But I'm quite simple. I tried to help the previous president, President Obama. He was a good guy, and he was a different party, and I tried to help President Bush, and he's a different party. I sort of don't care that much about what the parties are. I care about, even though I'm a big donor for the Republicans, but what motivates me is what are the problems we're facing? Can I help people get to sort of a good outcome that'll stand any test? But we live in a world now where sort of the filters and the hostility is so unbelievable. In the 1960s, when I went to school, and university, I went to Yale, we had so much stuff going on. We had a war called the Vietnam War. We had sort of black power starting, and we had a sexual revolution with the birth control pill. There was one other major thing going on, and the drug revolution. There hasn't been a generation that had more stuff going on in a four-year period than my era, yet there wasn't this kind of instant hostility if you believed something different. Everybody lived together and respected the other person. And I think that this type of change needs to happen, and it's gotta happen from the leadership of our major institutions. And I don't think that leaders can be bullied by people who are against sort of the classical version of free speech and letting open expression and inquiry. That's what universities are for, among other things, Socratic methods. And so I have, in the midst of this onslaught of oddness, I believe in still the basic principles, and we're gonna have to find a way to get back to that. And that doesn't start with the people sort of in the middle to the bottom who are using these kinds of screens to shout people down and create an uncooperative environment. It's gotta be done at the top with core principles that are articulated. And ironically, if people don't sign on to these kind of core principles where people are equal and speech can be heard and you don't have these enormous shout down biases subtly or out loud, then they don't belong at those institutions. They're violating the core principles. And that's how you end up making change, but you have to have courageous people who are willing to lay that out for the benefit of not just their institutions, but for society as a whole. So I believe that will happen, but it needs the commitment of senior people to make it happen. Courage, and I think for such great leaders, great universities, there's a huge hunger for it. So I am too very optimistic that it will come. I'm now personally taking a step into building a startup first time, hoping to change the world, of course. There are thousands, maybe more, maybe millions of other first-time entrepreneurs like me. What advice, you've gone through this process, you've talked about the suffering, the emotional turmoil it all might entail. What advice do you have for those people taking that step? I'd say it's a rough ride, and you have to be psychologically prepared for things going wrong with frequency. You have to be prepared to be put in situations where you're being asked to solve problems you didn't even know those problems existed. For example, renting space, it's not really a problem unless you've never done it. You have no idea what a lease looks like, right? You don't even know the relevant rent in a market. So everything is new, everything has to be learned. What you realize is that it's good to have other people with you who've had some experience in areas where you don't know what you're doing. Unfortunately, an entrepreneur starting doesn't know much of anything, so everything is something new. I think it's important not to be alone because it's sort of overwhelming, and you need somebody to talk to other than a spouse or a loved one because even they get bored with your problems. Getting a group, if you look at Alibaba, Jack Ma was telling me they basically were like a financial death's door at least twice, and the fact that it wasn't just Jack, people think it is because he became the public face and the driver, but a group of people who can give advice, share situations to talk about, that's really important. And that's not just referring to the small details like renting space. No. It's also the psychological burden. Yeah, and because most entrepreneurs at some point question what they're doing because it's not going so well, or they're screwing it up and they don't know how to unscrew it up because we're all learning, and it's hard to be learning when there are like 25 variables going on. If you're missing four big ones, you can really make a mess. And so the ability to in effect have either an outsider who's really smart that you can rely on for certain type of things, or other people who are working with you on a daily basis. Most people who haven't had experience believe in the myth of the one person, one great person makes outcomes, creates outcomes that are positive. Most of us, it's not like that. If you look back over a lot of the big successful tech companies, it's not typically one person. And you will know these stories better than I do because it's your world, not mine. But even I know that almost every one of them had two people. I mean, if you look at Google, that's what they had, and that was the same at Microsoft at the beginning. And it was the same at Apple. People have different skills, and they need to play off of other people. So the advice that I would give you is make sure you understand that so you don't head off in some direction as a lone wolf and find that either you can't invent all the solutions, or you make bad decisions on certain types of things. This is a team sport. Entrepreneur means you're alone, in effect. And that's the myth, but it's mostly a myth. Yeah, I think, and you talk about this in your book, and I could talk to you about it forever, the harshly self-critical aspect to your personality and to mine as well in the face of failure. It's a powerful tool, but it's also a burden that's very interesting, very interesting to walk that line. But let me ask in terms of people around you, in terms of friends, in the bigger picture of your own life, where do you put the value of love, family, friendship, in the big picture journey of your life? Well, ultimately, all journeys are alone. It's great to have support. And when you go forward and say, your job is to make something work, and that's your number one priority, and you're gonna work at it to make it work, it's like superhuman effort. People don't become successful as part-time workers. It doesn't work that way. And if you're prepared to make that 100 to 120% effort, you're gonna need support, and you're gonna have to have people involved with your life who understand that that's really part of your life. Sometimes you're involved with somebody, and they don't really understand that, and that's a source of conflict and difficulty. But if you're involved with the right people, whether it's a dating relationship or a spousal relationship, you have to involve them in your life, but not burden them with every minor triumph or mistake. They actually get bored with it after a while, and so you have to set up different types of ecosystems. You have your home life, you have your love life, you have children, and that's like the enduring part of what you do. And then on the other side, you've got the sort of unpredictable nature of this type of work. What I say to people at my firm who are younger, usually, well, everybody's younger, but people who are of an age where they're just having their first child, or maybe they have two children, that it's important to make sure they go away with their spouse at least once every two months. It's just some lovely place where there are no children, no issues. Sometimes once a month, if they're sort of energetic and clever. And that- And reaffirm your values as a couple. And you have to have fun. If you don't have fun with the person you're with, and all you're doing is dealing with issues, then that gets pretty old. And so you have to protect the fun element of your life together. And the way to do that isn't by hanging around the house and dealing with sort of more problems. You have to get away and reinforce and reinvigorate your relationship. And whenever I tell one of our younger people about that, they sort of look at me, and it's like the scales are falling off of their eyes, and they're saying, geez, I hadn't thought about that. I'm so enmeshed in all these things, but that's a great idea. And that's something, as an entrepreneur, you also have to do. You just can't let relationships slip because you're half overwhelmed. Beautifully put, and I think there's no better place to end it. Steve, thank you so much. I really appreciate it. It was an honor to talk to you. My pleasure. Thanks for listening to this conversation with Stephen Schwarzman, and thank you to our sponsors, ExpressVPN and Masterclass. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex, and getting ExpressVPN at expressvpn.com slash LexPod. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars and Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Stephen Schwarzman's book, What It Takes. It's as hard to start and run a small business as it is to start a big one. You will suffer the same toll financially and psychologically as you bludgeon it into existence. It's hard to raise the money and to find the right people. So if you're going to dedicate your life to a business, which is the only way it will ever work, you should choose one with a potential to be huge. Thank you for listening and hope to see you next time.


Pixel 6 AI explained | Lex Fridman

Here's the new Pixel 6 Pro from Google. You're now seeing the results of it running a computationally intensive neural network in real time that I put on there for testing purposes. It's using TensorFlow Lite and the new Tensor chip that is optimized for AI. I am unboxing this AI because as a robotics and AI person, I'm interested in seeing how innovation in AI hardware and software is increasingly taking over the smartphone space. Also, unboxing AI makes me think of Pandora's box, the myth that serves as the metaphor for the mystery and the power of AI. I know this is just a phone, but let's pause for a second to think. This computer has over 200,000 times the processing power of the computer that first landed humans on the moon and over 2 million times the RAM. We are engineering our way to superhuman intelligence one phone at a time. One small step for phone and soon enough, one giant leap for a hybrid of machine and mankind. Let's talk about the specs. Here's the comparison of the Pixel 6 to the Pixel 6 Pro across various specs, highlighting what to me are the key differences in yellow and in green, what are the key similarities? So key differences, $300 in price. Also the Pixel 6 Pro has a slightly higher display, slightly higher resolution and a 120 Hertz refresh rate versus the 90 Hertz refresh rate. Though honestly, I've been using both phones for almost a week now and I don't feel any difference between them. The key similarity to me on the AI and the computational side is that they both have the same SoC system on a chip, the Google Tensor. To me, the RAM and storage are very important but once you get to a certain threshold, it really doesn't matter. 12 gigabytes feels the same as eight gigabytes and the same goes for the storage. Both phones have a 50 megapixel wide angle. Now that produces a 12 megapixel image because Google combines the two by two pixel groups into single effective pixel to cut noise and improve color dynamic range. There's also the 12 megapixel ultra wide that's used to decrease noise for both the photos and the videos. And the Pro has a 48 megapixel telephoto lens which results in one key difference I think. It provides a 4X optical zoom plus a 20X digital zoom via machine learning via their super resolution algorithm. The rest to me is pretty much the same. Both phones feel amazing in my hand but of course, me being who I am, I care mostly about what's on the inside and that's the Google Tensor. Now let's talk about the Tensor chip. My main flagship phone for machine learning applications this year has been the Samsung Galaxy S21 Ultra 5G pictured here with the Pixel 6 and the Pixel 6 Pro. The Galaxy Brain is powered by Snapdragon 888. The Pixel Brain is powered by the new Tensor chip. Both are truly amazing machines. I think AI innovation in both hardware and software will be what matters in flagship smartphones over the next decade. This is where the battle is. Let's now look at the details of the technical specs of the Tensor system on a chip and also the philosophical vision behind its architecture. The key components of the architecture of the Tensor system on a chip are the CPUs, the GPU, ISP, TPU, Context Hub, and the Titan M2. Depending on the application, various components of this chip can be used at the same time, leading to what Google is calling heterogeneous computing. For the CPU, there is two big CPU cores with a Cortex-X1. There's two medium CPU cores with the A76 and there's four small CPU cores with the A55. This is in contrast with the most common design for the flagships, which is one big Cortex-X1 core and three medium A78 cores. It's funny that Google says that having one big CPU core is good for benchmarks but not good for the experience. It's funny because, as you'll see in the benchmarks, the Pixel 6 actually performs really well on the single core Geekbench 5 test. Performance-wise, the benefit of having two Cortex-X1s is that you can distribute a thermal budget across them so there's less overheating on intensive tasks like 4K 60 FPS video. So in initial tests, there's a lot less overheating so you'll be able to shoot video for much longer. Besides the CPUs, there's the GPU. There's an upgrade in that. There's the ISP, Image Signal Processor, that's optimized for image and video processing in terms of machine learning. And then there's the more general machine learning engine that's the Tensor Processing Unit. The Context Hub does ultra-low power ambient computing and the Titan M2 does hardware security. Like I said, I've been using the Galaxy S21 Ultra with a Snapdragon 888 for many months now. And so it's nice to take a look at some benchmarks for the CPU, GPU, and NPU for these two flagship chips. Now, the big caveat here, as you probably know, is that benchmarks often don't reflect real-life performance so arguably they don't actually matter. But the main takeaway story here is that these are both amazing chips. In Geekbench 5 CPU benchmark, Pixel 6 outperforms the Galaxy S21 on single-core test and the Galaxy S21 outperforms Pixel 6 on the multi-core test. For the Geekbench machine learning benchmark, the Snapdragon wins on the CPU and the GPU and the Pixel 6 wins on the NPU. The Geekbench machine learning benchmark, by the way, uses TensorFlow Lite. And there's also the AI Benchmark 4 that's specialized for machine learning. It runs a huge number of different neural networks on the devices. And there, once again, Pixel 6 far outperforms Galaxy S21. In fact, it leads every other smartphone on the current AI Benchmark 4 leaderboard. Again, I think the takeaway here in terms of benchmarks is that Pixel 6 does well on machine learning tasks and Snapdragon does well on CPU, GPU-centric tasks. But they're both, again, incredible machines. I think the important thing here is what does this heterogeneous computing enable in terms of software features? And the Pixel 6 provides a huge number of seamlessly integrated machine learning algorithms, increasing the vibrancy of the color with the HDR Plus for the images and HDR Net for the video, improving the accuracy and the efficiency of the face detection, again, both for images and video. And then there's just a huge number of cool features like face on blur, motion mode that adds blur to moving objects. There's the magic eraser that's actually shown here on screen where you can select certain parts of the object. They can be removed and then intelligently filled based on what the background is. Then for images, there's real tone that's looking at skin color, making sure this shows up looking great on photos. Honestly, the video is where the fun is. Like I said, HDR Net, that's an incredible use of neural networks. I actually personally think super resolution algorithms are one of the coolest applications of computer vision in terms of its maybe simplicity and usefulness and impact. And there's a huge number of applications outside of visual domain. So speech, automatic speech recognition, you're talking about deployment of state-of-the-art ASR algorithms that pay attention to context, pauses, is able to do noise removal. And on the language side, there's neural machine translation. Obviously Google is taking natural language NLP really seriously in both the textual domain in speech, that's audio, and again, back to images and video. This is incredible leveraging to do heterogeneous computing on AI hardware to enable all kinds of cool computational photography features. Okay, let's look at some takeaways. My two favorite AI chips for Android now are the Google Tensor and the Snapdragon 888. Time will tell which wins for which applications, but for now competition in this space is great for everyone. If you want me to talk about other AI systems or about running machine learning code on this and on other phones, let me know. I'll close with a quote from Eliezer Yudkowsky. By far, the greatest danger of AI is that people conclude too early that they understand it. Thanks for watching and hope to see you next time.