Netflix co-founder Reed Hastings: stories, schools, superpowers

This week, Reid and Aria sit down with Netflix co-founder Reed Hastings. Reed has seen technology rewrite the rules of entertainment before, but AI takes him back to his beginnings: he studied it at Stanford in the late '80s, decades before it became the only conversation in tech. Few people have watched this moment build from as many vantage points: he's served on the boards of Microsoft, Meta, Bloomberg, and, now, Anthropic. In this episode, they talk about what AI changes in entertainment in the stories themselves, and who gets to tell them. We ask what AI can deliver for education, an area Reed has poured hundreds of millions to reform. We dig into whether the disruption coming for workers is a wages problem, a jobs problem, or something else entirely. And we ask what a two-superpower AI race means for everyone else. Note: we recorded this episode with Reed Hastings before he announced that he won't stand for re-election to the Netflix board. For more info on the podcast and transcripts of all the episodes, visit https://www.possible.fm/podcast/

• 0:00Speaker 00

  In the 1980s, I was in the AI wave that was expert systems and they were public companies and the fifth generation and the Japanese were going to be this big threat and you know, and that AI didn't work, but this one is. Anything that lives in the emotional realm will be impacted, not as much by AI, because we humans react to these things emotionally. And so, again, I think we'll not watch robots playing basketball. STEM practically took over Stanford University.

• 0:28Speaker 01

  Totally.

• 0:29Speaker 00

  And now, maybe what we'll see is a rotation, you know, back to the humanities and to understanding, combination of history and literature. If I had a three-year-old today, I would be like doubling down on the emotional skills. In 20 years, robots will do maybe 1% of the plumbing.

• 0:48Speaker 01

  At most.

• 0:49Speaker 02

  Reed Hastings is the co-founder and former CEO of Netflix, the company that helped define the streaming era. And in doing so, rewired how 2 billion people spend their evenings. Under his leadership, Netflix launched streaming, pioneered the original content model with House of Cards, went global in 190 countries, and produced some of the most watched programming in TV history. He ran it for 25 years.

• 1:18Speaker 01

  But Reed's ambitions have always extended well beyond entertainment. He served on the boards of Microsoft and Meta. He's currently on the boards of Bloomberg and Anthropic. He's given hundreds of millions of dollars to education reform, and he holds a master's degree in artificial intelligence from Stanford from 1988, before most of us had AI on our radar.

• 1:37Speaker 02

  Today, we're asking, what does someone with that vantage point across entertainment, technology, AI safety, and the long arc of institutional change actually think is happening right now? Where is the leverage? What are we getting wrong? And what would it look like for this moment to go genuinely well for humanity?

• 2:01Speaker 01

  This is a conversation about technology as a civilizational lever, about whether the people building AI and the people governing it are asking the right questions, about what entertainment can teach us about human nature and what human nature can teach us about AI, and about what it means to have spent 35 years watching technology reshape the world and to still believe the best is ahead.

• 2:25Speaker 02

  And now to our conversation with Reed Hastings. Reed, awesome as usual to talk with you. I thought we'd start with something a little light for both of us. So I'll answer this too, but we'll start with you. In various weird ways, we get mistaken for each other. What was one of the funny ways that comes to mind for you about being mistaken for me? And then I will, I will also answer that question.

• 2:45Speaker 00

  Reed Hoffman, Reed Hastings, both in tech. So I get introduced sometimes to conferences and someone's done the quick chat GPT and they, you know, do it on Reed or Reed H or something and they call me the founder of LinkedIn. And I'm very excited because that's a hell of a business.

• 3:00Speaker 02

  Yes, well, and similarly, because Netflix is a hell of a business. I think the last one that I got and this out of, you know, many, many was, oh my God, that Wednesday show is awesome. You guys have done such a great job, which I'm now passing along to.

• 3:13Speaker 00

  It is.

• 3:14Speaker 02

  It's an awesome show, but you know, like that kind of thing. And, you know, we've been doing this for a while. So when we get the emails, we just don't afford them to each other.

• 3:22Speaker 01

  Exactly. All right, well, people confuse you guys, but let's see if you guys confuse yourselves with each other. So I'm going to say a quote and you guys are going to tell me who said it. Shout it out. Most entrepreneurial ideas will sound crazy, stupid and uneconomic. And then they'll turn out to be right.

• 3:43Speaker 02

  I think that's me.

• 3:45Speaker 00

  I would totally disagree.

• 3:47Speaker 01

  I lost Reed.

• 3:48Speaker 00

  Most turn out to be wrong. That's the whole point of the contrarian thesis. And then occasionally they're right.

• 3:54Speaker 02

  Yes, but they'll, they sound stupid.

• 3:56Speaker 01

  No, Reed Hastings, you said it.

• 3:59Speaker 00

  I did not. I'm sharing that's a misquote.

• 4:02Speaker 01

  Oh my God, we're going to fact check.

• 4:04Speaker 00

  Okay, let's, let's hit it from the top. But the quote is, you got to have a contrarian thesis and everyone else thinks you're stupid, basically. And then it turns out to be right, which is rare. The whole point is that most of the time the entrepreneurs fail because the idea doesn't work.

• 4:21Speaker 01

  Oh, God, they're so similar that they're confusing each other's quotes. All right, the future isn't something that experts and regulators can meticulously design. It's something that society explores and discovers collectively.

• 4:34Speaker 00

  Boring.

• 4:36Speaker 02

  So that means me and it's accurate.

• 4:38Speaker 01

  That was Reid Hoffman. Thank you. Thank you. All right, we have a few more.

• 4:41Speaker 02

  Boring is frequently how Reid talks to me, but you know, it's the details.

• 4:46Speaker 00

  The entertainment part of Netflix, the key to that was always, not that I am, but always trying to be thrilling and boring is the only sin in entertainment.

• 4:55Speaker 01

  There you go. All right, Stone Age, Bronze Age, Iron Age, we define entire epics of humanity by the technology that they use. Reid Hastings, all right, we got that. All right, two more. We are homo technae. When we cross the river, we are deepening our understanding of technology and ourselves.

• 5:16Speaker 01

  That was Reid Hoffman. And last one, companies rarely die from moving too fast and they frequently die from moving too slowly.

• 5:26Speaker 01

  That was Reid Hastings, but I feel like you've said such similar stuff, such similar stuff.

• 5:31Speaker 02

  It's frickin' brack, you know, blitzkilling.

• 5:33Speaker 01

  Thank you for humoring me.

• 5:35Speaker 00

  Who's the better investor?

• 5:39Speaker 02

  Who's more entertaining?

• 5:40Speaker 01

  All right, there you go.

• 5:42Speaker 00

  Well, it turns out that operating personality is really different from allocating capital personality. So, operating personality, you're like a dog with a bone, you never give up on a problem, you just work it, you work it. And investing personality is staying very broad, not falling in love with an idea, you know, cutting your losses and moving on. And like when I tried investing, I just fell in love with all the entrepreneurs and kept giving them money and none of it worked out. And when Reid tried operating, you know, we quickly found the right guy in Jeff to operate for him, who was an amazing operator.

• 6:16Speaker 01

  Fair enough. Reid, I'll turn it over to you.

• 6:18Speaker 02

  So, you were CEO of Netflix for 25 years. And then when you handed over the role, January 2023,

• 6:27Speaker 02

  What happened the next day? What did you, what did you then go do?

• 6:33Speaker 00

  My schedule evaporated, so you know, I had, first of all, it was a secret. And second, you know, I had a whole bunch of work meetings and a pretty full schedule that I then wasn't going to do. A bunch of internal and external things. You know, first couple of days, it was just like be at home and shock and, and you know, a lot of calls and just people saying congratulations, kind of nice, sweet things. And then, you know, I said, well, I've always wanted to ski a lot and I've only been able to ski five or 10 days a year because of work. So I'm going to take February and March and, you know, ski my brains out. So mostly that's what I did.

• 7:15Speaker 00

  And that was a super fun release and fulfillment, but it wasn't really planned. And it gave space, you know, really to the company. And you kind of, in many cases, it's good to have the C, the ex-CEO not be itching to like call in to make decisions and how about lunch Ted? Greg, let's talk about strategy.

• 7:37Speaker 01

  That episode of Love is Blind was terrible.

• 7:40Speaker 00

  So I was able to just enjoy myself and, and yeah, focus on, well, snowboarding.

• 7:46Speaker 02

  Was there anything that you found surprising that you missed?

• 7:51Speaker 00

  No, the huge surprise is how much I was okay with moving on. I thought I would like miss everything, you know, because it was my all entire life. I loved every second of it. And what I was just realized, I had done everything I wanted. I had, you know, done this huge global rollout. I had lived on an airplane around the world and every week in, you know, Seoul or Mumbai or Berlin, and it was incredibly fun and exciting, but I didn't need any more of it. And so I was super surprised that I didn't like yearn to get back in the saddle. You know, and of course there's aspects you miss and the people I missed. But, uh, you know, I stayed, I've stayed in touch with them on sort of a personal basis.

• 8:37Speaker 00

  So it was surprisingly easy and because I certainly have heard of people who have a very hard time with it.

• 8:43Speaker 01

  We've certainly see some CEOs who stepped away and then had to go right back because they missed it so much.

• 8:48Speaker 02

  Even in your former industry.

• 8:49Speaker 01

  But beyond Netflix, you've been on the boards of Meta, Bloomberg, so many influential companies, and these companies were some tech, some less, different business models, different industries. Like, what did you learn from being on the board of such diverse companies, obviously in addition to Netflix, about the AI and media ecosystem?

• 9:09Speaker 00

  Well, the lucky break of my professional life in that way was that in the 2005, Microsoft was looking to get someone from tech on the board. And, but they have conflict rules, so they couldn't have, you know, the head of Cisco on the board, you know. And so they started going down the list, you know, of tech people. And after a year, they had gotten down to the head of a domestic DVD rental service, Reed Hastings, for an interview. And so I was like, you want to interview me? And then I went up and met with Steve Ballmer and Bill Gates, and we really hit it off. And a little while after that, they put me

• 9:52Speaker 00

  on the board of directors of the Microsoft Corporation, which, you know, was a million times larger than Netflix at that time, and super global and super long term in their thinking. So the stuff I got out of it was amazing, because they were willing to work on projects for things 10 years ahead. And like, I had never been able to do that because we, the company, didn't have enough profit stream to do that kind of thing. And so it was such incredible learning for me. Then later, as social became really important, I thought, oh, you know, I'm kind of old, I should really get much closer to this, this is going to transform Netflix, like it'll transform photos and things. So I got on the board of Facebook.

• 10:34Speaker 00

  And Mark Zuckerberg was very open in the company and I tried to do what I could to help and I certainly learned a ton about social, but then it turned out that social really had very little to do with movies and TV shows. Yes. So it wasn't like this huge transformation of the rest of the universe like in the way that AI is. So those were two long-term born summits I did and I learned a lot on and I certainly encourage all the CEOs I know to do one or two other companies, hopefully big companies where they can learn from. Yep. And then I got on the Bloomberg board really as a favor to my friend Mike Bloomberg, who's an incredible philanthropist. He's been number one in the last two years of most giving in the US and just a great human being and a great philanthropist.

• 11:19Speaker 00

  So that's been a favor and fun. And then I'm on the board right now of Anthropic as well as Netflix. And on Netflix, it's pretty passive because the CEOs trust me and I trust them and so it's just kind of easy. But Anthropic is really exciting and intense and you know, I've really come to appreciate the team, the mission, and it's neat to have a seat kind of on the, on the front edge of what they're doing. Absolutely.

• 11:47Speaker 02

  Well, one of the things some people know, but very early days in LinkedIn, I wrote to you asking you to join the board because you're one of the top board picks for Silicon Valley intelligent people. But I want to go back to the Microsoft. So, so you were there before me. I joined in 2017, actually called you and as usual, got advice on the stuff. What do you think, speaking of long projectors, Satya's done a great job at Microsoft. What do you think the, the things were, were the right setup for Satya doing that? How much of that's, you know, kind of Satya's own brand of things and how much of that's kind of the, the patterns of work that were already present at Microsoft?

• 12:34Speaker 00

  Well, let's think about why is Microsoft 10, 15 times more valuable than when he started? You know, the profit stream has continued to grow, but then it grew a lot before that under Steve Ballmer. And so Office has stayed a very strong franchise and they have withstood, you know, some erosion from Google, but there was no wholesale change. Okay, so they kind of won the Office wars and they've made Office good enough that, you know, fewer people are switching, so they stabilized that. Windows didn't particularly get stabilized, you know, Apple in particular has continued to grow in the face of of Apple. Search has continued, Google search has continued to grow, so Bing and all those, and so like

• 13:19Speaker 00

  Windows and Bing, you know, haven't really delivered. Azure has delivered in a big way. It's delivered in a big way because of the AI workload. Okay, that's the big validating workload. So then that comes back to Satya made one incredibly ballsy, insightful decision, which is to invest in OpenAI back in 2018.

• 13:39Speaker 02

  I thought you were going to say buy LinkedIn, but that's okay. You know, keep going.

• 13:42Speaker 00

  So, you know, he bet big on AI and that catapulted them both reputationally and in terms of other, a little bit on the prop and the Azure business. So it was the workload that then has grown Azure into a monster and a big success, which because Amazon had the, had their own, first their first party workload, plus all the early adopters.

• 14:05Speaker 02

  Yes.

• 14:05Speaker 00

  Okay, so it was really hard for Azure for a while.

• 14:08Speaker 02

  Yeah, early adopters like Netflix.

• 14:10Speaker 00

  That's right. So where Satya gets incredible, he also internally, you know, he just got people talking and working together more than Steve had been able to do. But that, I mean, again, IBM was a nice place to work, but they just didn't take any product bits that really delivered.

• 14:26Speaker 02

  Yes.

• 14:27Speaker 00

  And Satya took a huge product that that did deliver.

• 14:30Speaker 01

  So talking about AI, everyone is talking about AI and you have also joined the public conversation. Where do you think people are asking the wrong questions, maybe having the wrong answers? Or like, what is part of the discourse of AI that you think is totally missing that people should be talking about more?

• 14:48Speaker 00

  Well, I'm not sure if whether AGI comes in eighteen months or six years, it really is gonna make much difference. So I think we should just sort of say, you know, it's coming fast. And how do we want society to be? What do we imagine in ten or twenty years? You know, sort of get over the idea of like the the intensity of of how fast it's happening to it's here. And what will we do? And how does it work? And, um, you know, how will the legal profession work? Like, as an example, in education, people say, oh, it doesn't change at all. And, you know, look at how medicine has changed from fifty years ago. Educators are, you know, recalcitrant because they don't want to change. But if you look at the practice of law, like, you know,

• 15:33Speaker 00

  pleading before the Supreme Court, it's identical to a hundred years ago. And we're sort of proud of that, right? So I imagine things like that, you know, briefing before a Supreme Court will actually work identically in twenty years when AI is is fully ubiquitous, right? Now, the briefs will get AI edited and improved, and the research will be a little faster. But, you know, it's kind of like in the noise in the way that today Lexis Nexis is.

• 16:00Speaker 01

  Yeah.

• 16:00Speaker 00

  Or or or Word for legal briefs. So some areas of the economy has a huge change, some areas not so much. So I I think, again, there's so much focus on, you know, is the current version of Claude Code, you know, this or that, and, you know, as opposed to, okay, it's gonna happen. And the robot side, the humanoid robot's gonna happen. So then what will society be in ten to twenty years?

• 16:26Speaker 01

  Well, you're saying if so, education, medicine, law, those are either sort of highly regulated industries or industries with big unions. Do you think that's why they might be affected less and others will be affected more? Or to actually throw your question back at you, do you think there's a profession that will be the most affected by AI, whether it's in three years or ten?

• 16:47Speaker 00

  Well, I was gonna say least affected, I think, will be entertainment. Like, you're not gonna watch a basketball game of robots.

• 16:52Speaker 01

  Right. March Madness is not gonna be taken over by AI.

• 16:55Speaker 00

  So we like the human conflict, and that draws us in. So most, like, percentage reduction in employment. One theory would be software engineers, because everyone's working really hard on kind of automated software development. But there's a substantial chance that while many companies will have reduced software engineering employment, there'll be many other opportunities for more software.

• 17:19Speaker 01

  Right.

• 17:20Speaker 00

  So that kind of elastic response is, well, it's what we've seen in radiology, which is an interesting example, because radiology is image processing. Computers and AI are much better than humans at, and have been now for several years. Okay? And so you can now go into an MRI center, and if you're self-pay, 300 bucks and get an MRI. It's dramatically down in pricing, and so people are getting many more scans, and they're being read by AI with a radiologist approving them. So I had thought four years ago, gonna be devastation in radiology. It's gonna be the first, you know, I am profession.

• 17:57Speaker 01

  Everyone talked about this, right? Obvious.

• 17:59Speaker 00

  Well, we have a shortage now. We have 35,000 radiologists. We need about 40,000. Wages are high. And so it's a good example of, it's easy to get focused on, you know, the disaster case with, you know, Armageddon. We love movies about Armageddon. We have them in our religions. You know, it's like, we love disaster. So we're drawn to these scenarios of AI wiping out things, okay? And again, it hasn't happened in radiology. Maybe it will eventually, but not in the last five years. So I'm gonna, my hunch is that many professions will be resilient, and that there's certainly much more demand for healthcare. So now, is there much more demand for legal services? Maybe.

• 18:41Speaker 00

  I mean, poor people are definitely under-lawyered, they can take advantage of a lot. So maybe there will be a whole elastic response there, and we'll see. But if I had to guess, it might be lawyers as the kind of most affected, because it's very verbal, and it's somewhat formulaic. Not as much as writing software, but it's somewhat formulaic.

• 19:03Speaker 02

  Well, and also, if we thought about... Like what would be an increase in productivity if you had actually people shifting from legal work, which is generally transactional costs on things that are happening to actually production of things, that would actually be a general positive thing in society. And I say this as a child of two lawyers. So I actually think it would be a good thing if the work shifted more towards how do we build more products and services? What are the ways that we create entertainment, create other work, you know, other kinds of things versus versus the transactional cost, which is legitimately there on a number of things, but the increased length transactional cost that's illegal?

• 19:42Speaker 00

  Well, I think where we both are is no one quite knows exactly, right, which fields will be, but what I think we both see is an era of great promise that the next 20 years will be super exciting. And I think it will usher in this era of abundance through both scenarios, which is again, you've got the white collar symbolic processing stuff that's getting pioneered now, like lawyering, writing software. And then we've got the Android humanoid robots coming at some pace. So that'll be pretty exciting.

• 20:16Speaker 02

  So one of the things that, you know, obviously, a lot of discussion of AI is on the question is, is there safety issues? And, you know, the safety issues range, you know, we've been in these conversations, anything from various smart people being, you know, as you were referring to earlier, you know, apocalypse doomsayers, you know, whether it's it's it's it's Terminator scenarios, whether it's jobs, et cetera. So what do you think the right way of trying to navigate the development of all of these, what we both agree are amazing future capabilities, medicine, amplification of software engineering, a whole bunch of other things, and navigating the safety? How much of that should be technical

• 21:01Speaker 02

  work, right? Constitutional AI, et cetera? How much of that should be incentives? How much of that should be regulatory? What's what's what are the guideposts that you throw out there as or principles by which people should think about how to navigate both keeping up our speed in building AI for all the good things and also navigating safety?

• 21:22Speaker 00

  Well, in the safety, we can break it down into a couple of categories. So there's the super disaster Skynet-y case where like AI takes over.

• 21:32Speaker 02

  Soon to be a Netflix film New Year.

• 21:34Speaker 00

  Yeah, and we, you know, absolutely have to prevent it. It's not something that's gonna happen in the short term. But the danger is that we could slide into it. As these things take care of more and more of our life. So I think because the downside of recovery from that, because we don't have time travel, you know, is extremely hard. That's when we have to think about even if it's low probability, sort of like massive nuclear war. We have to do some stuff about it to prevent it. Because it would be so disastrous. Okay, so that's the kind of mass nuclear war equivalent case that they take over. Then the other case is, you know, North Korean soldiers use it to design a virus. And, you know, a lot of people die.

• 22:19Speaker 00

  So think of it as in the hands of the wrong people. It's very powerful. One scenario is sort of combined with synthetic biology. Another scenario is cracking into other computer systems. So it turns out AI is very good at breaking in, finding bugs in open source things through code analysis, or finding bugs through closed things by probing in the way that national security agencies do today. But instead now it's in the hands of, you know, terrorists or other people. So again, think of it, those are two specific examples of bad people using AI as a powerful tool to do very bad things.

• 23:03Speaker 00

  And so there, we've got to make sure that the whole industry does tech prevention, that it's hard to do. Now, right now, they're sort of, everyone is doing that because they don't want to see these scenarios, but you could imagine that it might need to be regulated over time to insist that all of the sufficiently powerful AI systems protect against these kind of scenarios. And probably, some of them will happen, and then we'll set up a protection regimen afterwards to prevent that kind of thing. But no one of them is gonna like destroy all humanity at once like massive nuclear war might.

• 23:39Speaker 01

  All right, we're gonna go from nuclear war to AI writing.

• 23:43Speaker 02

  Which some people think is nuclear war, but it's.

• 23:46Speaker 01

  So, the New York Times recently ran a blind test and 86,000 people took it. And I don't know if you saw the results, but they were showing folks snippets of AI writing versus human writing and 54% of people preferred the AI writing. And so, some people argued like, ah, that was short form, that wasn't novels, like that's what AI is particularly good at. Other people were so devastated that more people preferred the AI writing. Like, what do you think that, like, what does this mean? Does this mean that most writing is going to become AI in the future? Or like, what are the implications of a test like this where regular people preferred the AI writing?

• 24:22Speaker 00

  You know, I think short form writing on a specific topic is a very different.

• 24:27Speaker 01

  Yeah.

• 24:27Speaker 00

  Writing a story.

• 24:28Speaker 01

  Sure.

• 24:28Speaker 00

  And developing character and a character arc and a conflict and a resolution. Just look at how Shakespeare still has a huge impact, you know, when it was 400 years ago.

• 24:41Speaker 01

  Yeah.

• 24:41Speaker 00

  And no one's been quite as good as him at a certain broad range of things. So, I think it's an extremely rare talent of, of the very high end AI. But like, average writing is, I don't think the way to analyze it. And I'm not surprised that the AI is better than the average writer today.

• 25:00Speaker 01

  Right, fair enough. And so, thinking of like, thinking about all these creative revolutions, it's like, you were there for DVD to streaming and now, obviously, lots of people, they're concerned about AI is the entertainment industry. So, forget the tools that people use, whether we'll, you know, use AI for editing or scripting or whatever, but the actual stories that are being told, like, do you think the AI era ushers in new stories or different people who are telling these stories? Like, what will the effects be?

• 25:27Speaker 00

  Well, in, people have been talking about democratization of film.

• 25:30Speaker 01

  Right.

• 25:30Speaker 00

  For 50 years. And so, like, the early wave of democratization was in the 90s when you could take it with digital instead of celluloid film.

• 25:39Speaker 01

  Sure.

• 25:39Speaker 00

  And so, you could do more takes and the cost of filmmaking was going to come down and that was going to democratize film. And, you know, it really didn't change. We got, you know, bigger budgets, higher special effects, we did reshoots more.

• 25:52Speaker 01

  We just raised it up, yeah.

• 25:53Speaker 00

  So, it turned out that the constraint really wasn't the film cost. There's lots of student films produced today, produced back then. And they just don't break through and take our recent success with K-pop demon hunters. I mean, you know, in some ways.

• 26:07Speaker 01

  I have a 10-year-old and 8-year-old and a 5-year-old. I certainly know about it.

• 26:11Speaker 00

  It's like our 28th animated film.

• 26:15Speaker 00

  Okay, you know, it's like even for us, it's really, really hard. And God knows we want to repeat K-pop, but you know, other than we'll do the sequel. But other than it's like.

• 26:25Speaker 01

  Lightning strikes.

• 26:26Speaker 00

  Lightning strikes. So, I mean, we are really working hard, but think of it as it's a very subtle set of high-end things. So it'll help a little, particularly in TV when you gotta do a lot of episodes and, you know, it'll help a little bit on the scripting. Where it'll help particularly is then script to screen. Okay, so you've got a big crowd shot, you know, and like, you know, a big stadium. Okay, that might be, you know, a very expensive VR shot now, special effects shot. But, you know, now it'll be AI.

• 26:56Speaker 01

  Right.

• 26:57Speaker 00

  And that'll be lower cost. So the mechanical parts.

• 27:00Speaker 01

  Yeah.

• 27:00Speaker 00

  Or industrial parts will be lower cost. But the backbone, the story, and then the, back to the basketball example. So we don't want to watch robots.

• 27:10Speaker 01

  Right.

• 27:10Speaker 00

  I think we're gonna want, people will pay for real actors.

• 27:13Speaker 01

  Absolutely.

• 27:14Speaker 00

  And people they recognize in that way. So, but we'll see. I mean, you know, there's definitely a threat of short form, you know, does, do young people only go on TikTok, okay, and never, you know, watch a podcast or a Netflix, we'll see.

• 27:30Speaker 01

  I mean, we'll also see Val Kilmer has a new film out and he's been dead for several years. And so AI Val Kilmer, we'll see if that's a success or not.

• 27:39Speaker 00

  Yep, recovering past IP and extending it is a niche. Yep.

• 27:44Speaker 02

  And by the way, people will watch robots, one of the great Netflix Love, Death and Robots series, right, you know, etc. So like there are, it's what do you watch robots doing is the interesting question.

• 27:54Speaker 00

  There you go.

• 27:55Speaker 02

  Now, what do you think are some of the interesting, more side effects? Like, obviously, you know, if you came to me today and said, hey, AI will be, have a, will, will help us improve identification of potential hits early that's like, seems unlikely unless there's some like analysis of major data streams that, you know, the humans don't do yet. But what are some of the more like side cases of how AI comes into this? You know, it could be, you know, also like, you know, an AI discuss the content with. I mean, like, what are some of the things that kind of, not just reinventing the process, but thinking about AI at the corner cases or add a corner case that may become big?

• 28:39Speaker 02

  Is there any of that that you've had musings on yet?

• 28:43Speaker 00

  We haven't found, say, the equivalent of sports betting. So sports betting is a whole kind of value emotional engagement layer on top of sports.

• 28:51Speaker 01

  Yep.

• 28:52Speaker 00

  It's not really AI enabled and kind of nothing to do with AI. But we're always with entertainment, looking for things that, what's a layer of conversation? What's a layer of engagement?

• 29:03Speaker 00

  You know, that enriches the experience.

• 29:07Speaker 00

  So, you know, maybe AI will improve that, but it's not obvious what that will be. And to some part, the beauty of a show or a movie is that it is, you know, kind of self-contained. And, you know, that it's, it's this, you know, it's been more than a hundred years. We've had films. And so it's like a novel where the novel as an art form has really stayed constant. And so there's something about, you know, the size and the capability that people are used to. Sure, there's short stories and sure, there's epics, but like almost all of the business is novels. And what people read, and I think there's a lot of that with film and TV series that they're not artifacts.

• 29:49Speaker 00

  They're really reflections of human attention span and stories.

• 29:53Speaker 01

  I feel like people have been complaining forever about, you know, you have one superhero movie hit, and then you have 25 more superheroes or like Barbie hits. And then all of a sudden you have toys, like toy stories. Like you're not, we're not getting sort of the diversity of hits because people are looking at an algorithm. Or they're, well, you know, you got to put this star with this story and then, and so you don't maybe get a K-pop demon hunters, which like you said, was the 28th and no one could predicted it. Obviously we're in sort of the, the time of heated rivalry when no one could have predicted that. Do you think AI will, will flatten things? Like, will AI lead to people just, you know, betting on past success because the algorithm told it to? And so they'll take less chances or that's already happening? Like, how does AI affect it from a data perspective?

• 30:38Speaker 00

  You know, very, very little. We're really predicting for a kind of that human conflict and something. You know, you want something that's both familiar but also fresh.

• 30:48Speaker 01

  Yeah.

• 30:48Speaker 00

  So those are our tensions. In terms of like over-sequelization, you look at the amount of new content that Netflix is producing, that's really gone away. In other words, sure, we'll have some sequels and think of season two of Wednesday was, you know, season three, et cetera. So that's always been a part of the business. It's very enjoyable for people because it's a story they already know and you see more of it. But you don't want it to be the only thing. And that's certainly not true today. Today, we have an incredible set of new films coming out all the time.

• 31:19Speaker 01

  Yeah. And do you, like, how well do you think Netflix can predict a hit? Like, sometimes things come by surprise, but you're like, no, no, no, we got it. We know. Or you're like, ah, we, sometimes we don't.

• 31:29Speaker 00

  Yeah, it's a mix of both.

• 31:30Speaker 01

  Okay.

• 31:30Speaker 00

  So, uh, season twos, we have much more.

• 31:33Speaker 02

  Yes.

• 31:35Speaker 01

  You have more data there. All right, fair enough.

• 31:37Speaker 02

  One of the many smart things that Ted Sarandos said is that there's a much better business in increasing the upside, the quality, the volume of the reception of content by 10% than cutting costs by 50%. And it was a way of kind of lensing to why is AI potentially really amazing?

• 32:01Speaker 02

  What are the kinds of things in terms of thinking about how AI can be additive? That you think that the entertainment industry should be thinking about broadly? Given, obviously, there's a lot of concerns and uncertainty around it.

• 32:14Speaker 00

  You know, in entertainment, there will be a lot of work on special effects and sort of things that didn't fit in a budget before can now be done, you know, using AI. So that's a good example. But more or less, I think, anything that lives in the emotional realm will be impacted not as much by AI because we humans react to these things emotionally. And so, again, I think we'll not watch robots playing basketball. And so it's the easiest example for people to get that things that are emotionally pleasure, emotional stimulation, will still do. So, you know, you like to give and get real flowers, not fake flowers. So it's like, I don't think that's changing just because of AI.

• 32:59Speaker 00

  So where AI is very good is that thinking and logic like coding, wow, it's really, it's breaking too. So I think there's just, think of it as tremendous excitement in medicine, in biology, and things that are very factual, logical, hard, and complex, and things that are emotional, you know, will be, it's not that it won't eventually be able to add value, but that's certainly not the big thrust of the AI world.

• 33:26Speaker 01

  All right, this is something I'm very excited to talk about. You and I share a deep passion for education, and I feel like education is like at the center of AI. It's like, is it gonna usher in a new era where everyone has amazing tutors and education is supercharged? Or are public school students especially perhaps just gonna have AI slop constantly? Like, as a philanthropist who's invested a lot here and sort of studied the education, especially in the United States, how do you think AI is gonna affect education?

• 33:58Speaker 00

  Well, there's two kind of big questions, which is, one, what are we educating kids for? What kind of society are we educating them for? What skills should they have? So the kind of goal state, you know, in the past was pass a lot of AP exams.

• 34:14Speaker 01

  Sure.

• 34:14Speaker 00

  Okay, and that's probably not the right goal state for the future world. So there's a big discussion to have, which is, what are the skills that you're trying to target for your kids? And then second is implementation, which is, can we use AI tutors to, whatever we decide is important, to teach more of that, to make teachers' lives better, to have kids learn more. So there are two different discussions that get kind of mushed together. I would say on the second, like, how to teach more, then there's some relatively clear paths of doing, you know, different kinds of AI tutors, and, you know, just like we're gonna have AI doctor, AI lawyer, there'll be AI teacher, and that will come along.

• 34:55Speaker 00

  And it'll be, it'll be easier in private schools, it'll be easier in charter schools, it'll be harder in, in school district schools, because of all the regulations they have. It'll be easier outside of the US where they're more willing to, to do some of these things. So, you know, that will happen. It's unclear, the first question, which is, what's, if you have a three-year-old or a five-year-old...

• 35:20Speaker 00

  What do you want them to learn?

• 35:21Speaker 01

  Totally.

• 35:22Speaker 00

  Because the hard skills like that we used to value STEM.

• 35:26Speaker 01

  Mm hmm.

• 35:26Speaker 00

  Okay, that's probably like coding. Like we were, you know, we spent twenty five years saying, learn the code, learn the code. Oops. You know, don't learn the code, don't learn the code. So it's probably true that like all the hard facts of, you know, biology, chemistry, physics will be extremely specialized and not necessary general knowledge.

• 35:48Speaker 01

  Hmm.

• 35:48Speaker 00

  Um, and and probably not that valuable, let's say, if you had an AP result in this.

• 35:54Speaker 01

  Yes.

• 35:55Speaker 00

  The things that are more emotional, how you read people, how you work with them, um, uh, probably are quite valuable because they're much harder for the computers to do and and humans uh like doing them with other humans more often. So I think we'll see a kind of shift of the value, you know, STEM practically took over Stanford University.

• 36:17Speaker 01

  Totally.

• 36:18Speaker 00

  Okay, and now maybe what we'll see is a rotation, you know, back to the humanities and to um understanding combination of uh history and literature, but also kind of the the physiology of the brain and um, you know, how we interact with each other. If I had a three year old today, I would be like doubling down on the emotional skills. There's some great middle schools, one's a charter school Valor, another's a private school Flourish, and you know, they really focus like in seventh grade on these emotional circles where you sit around and talk about your feelings and because they feel like this kind of skill and knowing yourself, they interact with other human beings is gonna be the thing that sustains those kids, you know, through their working life.

• 37:03Speaker 01

  Do you, I feel like when people talk about AI in education, Alpha School always comes up, we had Mackenzie on the pod a few months ago, and I feel like some people are like. The criticism is like, they're not even using the cutting edge AI. Other people say, look at their test scores. They're doing, you know, twice as well as anyone else. Some people complain about equity, you know, for $40,000 a year.

• 37:24Speaker 00

  Sixty thousand. It's fantastic. If you can afford it, go.

• 37:28Speaker 01

  So why do you, like, the thing I love about it is actually less about the AI, but more just about the, like, giving agency to kids, focusing on other things. Like, what do you, why do you think Alpha School is so great?

• 37:39Speaker 00

  Well, it starts with Mackenzie and Joe's philosophy that the kids have to love school and they love vacation. So the number one goal is the kids don't want to go on vacation. They want to stay in school because they love it so much. Then they start from, okay, if we want them to love it and we need them to know the basics up to do well on tests, what are we going to do? And so they do two hours on software a day where, you know, it's relatively practice and drilling and these kinds of things. But they have a coach really motivating and helping. And then they get the reward for that is they get to spend the rest of the day doing stuff they want. Either a set of the schools are for athletes and people for sports, or they spend the rest of the afternoon doing, like, watching TED Talks and talking about them or a range of things.

• 38:24Speaker 00

  But I would say they're kind of like the Tesla Roadster. That was the first Tesla, over $100,000 sports car specialist thing. But it set electric cars as the aspiration. Then they were cool because the first electric car was this, you know, very high, extremely fast accelerating thing. So that's Alpha School is our Tesla Roadster for AI schools.

• 38:48Speaker 01

  And you think it can be done, we can go down the cost chain and we can do it at a lower amount?

• 38:53Speaker 00

  A hundred percent. Model three will be coming.

• 38:55Speaker 01

  I love it.

• 38:56Speaker 00

  So, yeah, there'll be more and more innovation at that end.

• 38:59Speaker 01

  Cool. So Reid, we talked about education and how there's enormous opportunity for change. Alpha School, which is operating within the United States. How is education going to change outside the United States with AI?

• 39:10Speaker 00

  Well, I think what we'll see is tremendous flourishing of AI teacher in an international situation. So we have pretty good teachers in the US and pretty high satisfaction and rich countries generally do. But in lower income countries, the education budget might be $300 per kid per year and the class size might be 50 to 70 kids. And there's just not a lot of learning going on. And I think the combination of a Starlink on every school and tablet for every child, and then really good AI software will close the gap. So think of the way mobile phones are ubiquitous in the developing world. I think AI learning will be ubiquitous and that will help. I don't

• 39:51Speaker 00

  know that they'll leapfrog the advanced countries, but they'll certainly close the gap that we've seen historically. And in places, they may leapfrog.

• 40:01Speaker 01

  I feel like lately, there's been like breathless articles everywhere about how one laptop per child was the hope, and then it was really a failure, and we put so much money into it and it didn't work. And then other people are saying like, well, that's really nice that you want that, but you know, the cost of compute is too much. Like, what would you say to those people who think that like, we've heard tech solutions in education before, but it's not going to happen this time?

• 40:23Speaker 00

  Yeah, there's always the crash dream phenomena. Like, you know, in the 1980s, I was in the AI wave that was expert systems, and they were public companies and the fifth generation, and the Japanese were going to be this big threat and, you know, and that AI didn't work. But this one is. So just think, just because it failed before, it was too early, it doesn't mean it won't work. So I think the one tablet per child around the world is very scalable, builds on the mobile phone platforms. And it is some of the same ideas that one laptop per child had, but that was just 20 years too early.

• 41:00Speaker 01

  Yep. And I assume you think the cost of compute is just going to go through, through the floor, and so that it won't be a barrier to entry for folks in the developing world?

• 41:07Speaker 00

  That's right. The costs are really driven off the phone market. So, you know, we have $800 phones in the US, but in most of the world, you know, there's $50 phones are quite usable. And so think of it as $50 phone and a Starlink per school and some solar panels, you know, so it's very scalable.

• 41:29Speaker 01

  Fantastic.

• 41:30Speaker 02

  So one of the things that you said earlier, which I, I completely agree with, and one of the things I think I would partially reframe, and it's kind of a question leading into education. I think our human skills, you know, how we collaborate, getting into humanity, understanding these things, I do think will amplify up. And the skill of learning coding obviously goes away because it's like, oh, this does the code. But I think the various, two things that I think will still be pretty deep in what we're doing is, one is a good systematic understanding of what truth in the world is around, so like biology, physics, chemistry, et cetera. Because that kind of iteration of understanding the nature of the world we're in, I think is pretty familiar scientific thinking.

• 42:15Speaker 02

  Is it like the patterns of thinking, I think, are important. The patterns of strategy are important. And I think actually even coding will go that way. Because part of the thing is, is wow, people say, well, should I study, should I stop studying computer science? Like, well, no, you should study computer science, not coding. Right? Like, more of the kind of the thinking about the system or the pattern of it, in terms of how we operate. And I think that will become more general. I'm curious what you think of my modest reframing of your earlier statement.

• 42:48Speaker 00

  I think I'd just study math. You know, if you want to get to like-

• 42:53Speaker 02

  Well, ALMs are terrible, terrible accounting, so yes.

• 42:55Speaker 00

  So, you know, whether it's algebra, I mean, there's so many interesting things in math. If you want to help people, like, kind of learn abstraction or search for truth. You know, look, there's gonna be some role for science and a few people will be drawn to it. But think of the last 20 years. We've been, as a society, STEM, STEM, STEM, learn to code, STEM, STEM, STEM. So I just think that as everyone sees that coding is overdone, my guess is we'll see that STEM is overdone. And the kinds of things that you do with a biology background will be done so much better and faster by AI that it'll be hard to compete for jobs in that space.

• 43:40Speaker 02

  So shifting to another thread, one of the things I think AI will do is it will break us a little bit of the industrial model, which is the industrial model tends to be the- You know, go to high school, go to college, learn, now go work. And learning then, now work. And I think ongoing learning will be one of the key things. Do you think that will also be part of, not just like, I have this one learning period, but it's like, I'm constantly interweaving learning with what I'm doing?

• 44:07Speaker 00

  Absolutely. So, you know, trying to think through the ongoing skill acquisition, you know, by, by learning things has probably, you know, been important for a long time because the stuff you learned in high school changes so much. And the knowledge in the field changes so much. And that's only going to continue. So certainly, learning will need to be for people who want to make a living intellectually constant. But I don't think that's, it's like a more of the past because that's been true for a while. It's just going to be even more true, you know, in the, in this new world.

• 44:42Speaker 01

  So we learned earlier that you were the one that said, Stone Age, Bronze Age, Iron Age, we define entire epochs of humanity by the technology that they use. And so we're entering the AI age. Do you think even more than previous ages that now, if you are left out of the AI age, either personally or sort of as a country, like that, that now is the time that some folks might actually fall behind and there's going to be a bigger divergence between those who embrace the AI age and those who fall behind?

• 45:13Speaker 00

  Well, I don't know that just embracing it, like if you're a small country in Europe that has a glorious past, I don't think it's whether you embrace it or not that it's going to change the outcome. I mean, you know, you gotta try to figure out a strategy because, you know, it's going to be dominated, you know, by China and the US. Okay, how does the middle powers like Canada, you know, thrive? And I think we owe, you know, we're part of that thinking and solution to be able to build a world that we all want to live in.

• 45:46Speaker 01

  And so what would you do for these middle powers? Like, they don't want to live in a world where it's just the China, just China and the US.

• 45:54Speaker 00

  I don't know that they have much of a choice. Yeah. So I think it's, I mean, what they're doing is linking up together. Yep. You know, and I think that probably makes sense. Um, and certainly, you know, they'll embrace using, you know, American AI. Sure. They'll need to. And, you know, maybe they will be able to get some local things going or they'll do it by treaty where, you know, where they get, they're not going to get shut off. Right. But think of it as AI is going to accentuate income gaps, both in the US. Right. And between the US and, and other countries. So, you know, it's going to create tensions, just like it does in one society. It does between societies.

• 46:36Speaker 02

  I do think that one of the things, and I think you would agree that, that, that actually having an active AI strategy for the countries, for the industries, et cetera, is actually in fact really important.

• 46:50Speaker 02

  I think it's less important to be going, it isn't that, you know, so-called digital sovereignty isn't also important. But the most important thing is to actually be modernizing your, your kind of industry, your countries, your companies, your workforce. Because it's a little bit like the industrial revolution, like one of the things I put in super agency is that, you know, England quartered the population of France, tenth the population in China, multi-century industry, you know, and did not invent the industrial revolution. But multi centuries empire, because they embraced the industrial revolution most robustly early. Would you also think that when you get to thinking about this from a

• 47:31Speaker 02

  countries or industry or industries or companies perspective, that they should adopt that same thing of like, we have to have an active strategy in being there early?

• 47:40Speaker 00

  Well, your example's interesting. So you said the UK was led industrialization. So that's kind of the equivalent of America today.

• 47:48Speaker 02

  Yes.

• 47:49Speaker 00

  So you didn't really phrase it as, you know, what should Argentina do?

• 47:52Speaker 02

  Yeah.

• 47:53Speaker 00

  About industrialization, which is a very hard challenge because the UK did everything in its power to keep Argentina from being able, country, to industrialize, to maintain their strength of their power. So if you are a middle power like Argentina, should you have an industrialization policy? Sure, probably that makes sense. Will it work? Not clear at all because the power imbalance in the UK was so high. So they would, they were laws preventing, you know, looms and various things from being in India. So the cotton, you know, from India had to come and then get processed in the UK and they enforced those laws with their military. So I, you know, it sounds all great that Belgium should have a, you know, an AI policy.

• 48:38Speaker 00

  And Estonia is a small country that's done a lot on, say, digital ID and do good government tech. So I guess that's better than not doing it. But I don't know that it's actually much of an answer for a middle of a country. I mean, I think the challenges for a middle power country are quite substantial and I don't have a good solution, but I think, you know, in them linking up and then doing things and working well. And I hope that the US, as the Western leader of that, is, you know, embracing in a very, in a very important way, you know, which is not the current America first policy. But I think it's much more in our long-term interest to have a long and strong allies.

• 49:21Speaker 01

  So earlier you said that you think AI is going to usher in this great era of abundance and, you know, whether it's 10 years or 20 years, you know, when, when sort of AGI gets here. Like, what are the things that need to happen for that to be true? Are there conditions that need to be met now for that to happen? And did you mean just in the US in terms of the abundance or could it be global abundance too?

• 49:43Speaker 00

  Depends kind of how the IP is shared or the rewards of it, but I think it'll be pretty global. So just like you saw in the industrialization, it really did lift all boats. You know, it, it's at a different level than in the host country.

• 49:56Speaker 01

  Yeah.

• 49:57Speaker 00

  But, so let's take nuclear fusion, you know, and if we can actually make it work, you know, which will be assisted by AI, you know, then we've got a tremendous energy source. If through it, we're able to bring down the cost of solar, you know, or invent new types of batteries and storage, you know, it could really revolutionize energy usage and production, which then brings us to, you know, age of abundance. So in early, in early nuclear, we were a little bit naive and we thought electricity would be too cheap to meter. Okay, so you know, we're probably not going to get to that. Um, but you know, that's the kinds of thinking for abundance that we want to do.

• 50:40Speaker 00

  So if you think about housing and you know, it's very expensive to build. What if it was robots building it, you know, 24 hours a day? So then you got, okay, you've got carpenters not working, so that's a negative, but you've got, you know, low cost, very custom, beautiful housing. So that would be, you know, another example. Um, so you know, I think in each industry, we're going to see much lower costs. Um, for doing things and then incredible amounts of inventive energy because maybe we don't need to build a house that way. Maybe you just print it, you know, in some giant 3D printer. So there'll, there'll be both tech revolution in that way, which again would be like nuclear fusion.

• 51:19Speaker 01

  Yeah.

• 51:19Speaker 02

  I'm going to shift to one other zone of subject because I think this is something that people frequently misunderstand. What do you think are, why is so much of this innovation happen in Silicon Valley? What are the things that make Silicon Valley kind of a unique creator of these kinds of technologies? Why is it half of the NASDAQ is within 30 miles of where we're currently sitting?

• 51:42Speaker 00

  Well, I think if you look at the financial city of London, or you look at New York, or you look at Detroit for cars. Um, this is not something specific about tech. Um, you get very positive reinforcement when you've got a whole lot of talented people that can switch jobs and not have to move. And then they move the ideas. So in the U S, we don't have very high protection against the ideas walking out the door. So it makes it can be very hard for a given company because they feel like, oh, my secret spread. But it makes it very productive for the economy and for the ecosystem that those ideas do spread.

• 52:21Speaker 00

  So I think of it as liquidity and employees changing is probably the key ingredient. Which is a combination of things like LinkedIn of, I wish we had non, non employer based healthcare. Um, so if you had it, you know, in some other ways than employer based, that you'd have more liquidity. The less we do non competes, the better. It's one of the things I think that the Biden FTC had right of making it easier to compete with existing companies. Um, by eliminating non competes. So those are the, that liquidity of movement, I think is the most important thing.

• 52:59Speaker 02

  So one of the. Questions, maybe a last question before we get to rapid fire on jobs is obviously the general discourse is loss of jobs, you know, and kind of other sorts of issues. But there's way insufficient discussion on wages. Because even though, in fact, you know, action back, I think there will be a lot of creation of jobs, a lot of transformation of jobs. But what will happen, a little bit like the earlier comment in radiology, is there will be a, okay, which of these jobs are super valuable, compensation goes up, which of these jobs become less valuable, compensation goes down. Have you had any thoughts, because you're a systems thinker, on the wages effects, what

• 53:40Speaker 02

  countries, companies, industries, but specifically also individuals should be doing in kind of navigating what will be happening within wages?

• 53:48Speaker 00

  Well, let's see, you describe as some jobs is valuable, but like, you know, teachers are very valuable and not paid very much.

• 53:54Speaker 02

  Yes.

• 53:55Speaker 00

  So I don't think pay follows value very much. It follows shortages and demand and supply. Okay. So the question is, for wages, what jobs will be in shortage?

• 54:06Speaker 02

  Yeah.

• 54:07Speaker 00

  And I think it's all those jobs that are emotional, that computers are not very good at, because we'll, we'll have a lot of need in those. And the jobs that are more administrative, you know, those are going to have lower wages because you're competing with computer, uh, who, who could do that job. So again, it's really where AI does a job well, it, it's cost done by a human, or its pay will be less. And where it's super hard for the AI to do, it'll be, you know, continued high wages.

• 54:38Speaker 01

  I feel like a lot of people are telling people that the solution to that is trades. Everyone's like, oh, become a plumber, HVAC, electrician, because those are in shortage right now. Obviously, like, the big question there is like, how soon robots will catch up? Like, what do you, like, it matters if that's going to be five years, or 20 years, or 40 years, in terms of people getting wage premiums from the trades? Like, what, what would you tell people in that respect?

• 55:00Speaker 00

  Okay, so let's look at electric cars. So 2007, we had self-drive, sorry, I should say self-driving cars. 2007 was the DARPA challenge and it was like, it actually did work in self-driving cars in a limited lab. And now 20 years from now, it pretty much works, okay? Uh, but the percentage of miles driven, self-driving by the machines, by high-end Teslas and by Waymos, it's gotta be less than 1% of global miles.

• 55:29Speaker 01

  Easy.

• 55:30Speaker 00

  That's after 20 years. So we're not even to the stage of that DARPA challenge. That is, we don't have a demonstration in the home, okay, that can do all these things. So think of it as, in 20 years, robots will do maybe 1% of the plumbing.

• 55:46Speaker 01

  At most, right.

• 55:47Speaker 00

  Okay, so it just takes a super long time to build, deploy, and then to get them to be lower cost, higher safety than others. But I think over 50 years, it will happen. So that's still gonna be a great field for the next 20 years, uh, if we're talking plumbing specifically.

• 56:04Speaker 01

  Thanks.

• 56:06Speaker 02

  So now rapid fire, unless there's another question.

• 56:08Speaker 00

  Let's do it.

• 56:08Speaker 02

  All right. Is there a movie, song, or book that fills you with optimism for the future?

• 56:14Speaker 00

  There's a cool movie I watched recently, The Queen of Chess, and it's about a Eastern European 1980s who, guy, family who raises his three daughters to get out of poverty via chess. And they all three become grandmasters and get to a middle-class or better living through this dedication. And so, uh, it's a situation where there's no reason they should have had hope, being in 1980s, you know, Romania. And yet they did, and they worked towards a future that has been great. Uh, so it's a, I love a documentary like that.

• 56:48Speaker 01

  All right, I gotta check that out. What is a question that you wish people would ask you more often?

• 56:53Speaker 00

  I think people focus a lot on business success, which I've been, you know, super fortunate on, and less on joy. And so I think the question would be, what gives you joy? How do you increase joy in your life?

• 57:07Speaker 01

  All right. How do you increase joy in your life? Let's hear it.

• 57:10Speaker 00

  I would say that I'm trying to do more on the mindfulness and on the appreciation, noticing much of my work life was relatively frantic, kind of lots of email, short burst stuff. And I think I could have integrated more mindfulness into that busy time. But certainly now that I'm retired, I can.

• 57:31Speaker 01

  Love it.

• 57:32Speaker 02

  So where do you see progress or momentum outside of your industry? Let's call that tech entertainment that inspires you.

• 57:40Speaker 00

  Definitely medical work. I mean, the amount of improvement in cancer therapies, health, understanding, insulin resistance. I mean, it goes on and on. And what we're slowly learning of the brain, of the body, and then the brains, you know, even slower, but making some progress on that.

• 57:59Speaker 01

  All right. Our final question. Can you leave us with a final thought on what is possible to achieve in the next 15 years if everything breaks humanity's way? And what's the first step to get there?

• 58:10Speaker 00

  Well, if everything breaks human humanity's way, it's because AI has unleashed human flourishing. And we find the political mechanisms to share that across within our country, across different income groups, and then between countries. The world as a whole is enhanced. And a first step for that would be to realize how interconnected we are between people in our country and then between countries. And trying to get away from win-lose to win-win.

• 58:42Speaker 01

  Totally. Amen. Thanks so much.

• 58:45Speaker 02

  Reid, always a pleasure.

• 58:46Speaker 00

  Indeed.

• 58:47Speaker 02

  Possible is produced by Palette Media. It's hosted by Ari Finger and me, Reid Hoffman. Our showrunner is Sean Young. Possible is produced by Tanasi Delos, Katie Sanders, Spencer Strasmore, Imo Zhu, Trent Barboza, and Tifadzwa Nirmarundwe.

• 59:03Speaker 01

  Special thanks to Surya Yalimanchili, Sayida Sabieva, Ian Alice, Greg Beato, Parth Patel, and Ben Ralas.