Marc Andreessen (3:08)

Yeah, so I think there's kind of a fake story and then there's a real story. So the fake story is kind of the classic, you know, kind of the classic Marxist story, which is, you know, only the rich people have it, only the fancy people have it, you know, the big tech companies have it, everybody else is kind of going to be left out in the cold. That's not actually what's happening. And there's a lot of data on this now that has been released by these companies to justify about to say. So the real story is this is already probably the most democratic, you know, small D technology of all time in the sense of the very best AI in the world is fully available on the apps that anybody can download. And you know, take your pick, ChatGPT, Claude, Gemini, Grok, you know, Mistral, any of these, by the way, deepsea, China, you download any of these apps, you're getting state of the art, like the full most sophisticated, powerful AI capability in the world. And you know, the number of people already who downloaded these apps is north of a half billion on its way to a billion. And individual people are figuring out basically how to incorporate this in their lives. And what you see in the data is there's maybe what you'd expect, which is there are a slice of people who just use these new systems all the time, like literally all day for everything. And in a lot of cases they're reporting that they're getting enormous benefits from that. And then there's a lot of people who are experimenting and trying to figure it out. And then there are people who are just not, for whatever reason, not interested or not engaged. But I would say it's incredible out of the gate how distributed this technology already is. And then I could just say like, I don't have, you know, with all my resources and with all my connections, I don't have access to a better AI than the one that you just download off the App Store. And so I think this is actually like, just an incredible story of the most advanced technology in the world being available to everybody right out of the gate.

Marc Halperin (4:48)

You got to get people to use it, to take advantage of it. Right? So I've got a friend who's drafted a book and took it to his agent, and the agent said, It's 140,000 words. You got to cut it down to 70,000. And I said, if you try to do that by hand, even if you hire someone, it's going to take you months. I can do it in an hour. And I can say to AI, don't change the style, don't change the tone, don't cut anything that, you know, ruins the story. And he said, that's immoral. The publisher will be mad that. That I did it that way. It's not right. How should I answer that person?

Marc Andreessen (5:25)

Yeah. So the exact same arguments, you know, emerged, you know, years ago with the introduction of computers. Right. I actually just. I've been watching a lot of, you know, old science fiction movies with my kid. And, you know, there's this famous science fiction movie, Tron, from 1982, you know, that had the first computer, kind of the first real computer graphics movies. And it was disqualified for an Oscar for special effects because it used computers. Right. And so there's this kind of long tradition of, like, whatever the new tool is, is sort of illegitimate, and there must be something wrong with it in this particular case. I mean, there's no doubt there are people who feel the way that your friends feels. That issue was actually litigated in the last Hollywood strikes on the film and TV side of the creative profession. The last round of strikes. Actually, it's actually funny. They started streaming strikes, and then AI hit, and they became AI Strikes. But the settlement with the studios, actually with the unions, was that the following, which is, if you're a writer and you use AI, that's totally fine. What was not allowed is for the studio to basically use the AI and then claim it was a writer. But basically what the unions and studios in Hollywood decided was, it's another tool. It's like the word processor. It's like the personal computer. It's like using a printer instead of writing out a manuscript by hand. And so I think there are people who feel like your friend does, but I think the world is already adapting very fast. To using it. And frankly, one of those reasons you probably pointed out to your friend is I don't even know that anybody could tell anymore. Right. And so, you know, if you're going to have a moral prohibition on something that people can just do and nobody knows about, like, you know, is that really going to work? And so I think those, those sort of self imposed barriers are probably going to collapse quite quickly.

Marc Halperin (6:59)

I hope so. Fortune put out a list of the top American companies using AI. Alphabet, Visa, JPMorgan Chase. Top three we talked about just now. On an individual level, if you were the CEO of a company or advising a CEO, how important is it to be on that list? In other words, how important is it to get to your company to adapt? Whether it's for internal or consumer facing, how important is it right now?

Marc Andreessen (7:28)

Yeah, so this, this goes back to actually where we started, which is, and in fairness, the old model of adapting actually computers. When computers came out, the old model was the largest institutions get technology first and then everybody else gets it later. And so, you know, the way the computer rolled out was the government actually got mainframe computers first starting in 1940s, and then big companies got computers, mainframes. In the 1950s, 1960s, small companies started to get computers. We're called minicomputers at the time, the 1970s. And then we as individuals only got PCs in the 1980s. And so it took 40 years for basically technology to cascade down from the largest organizations in the world to small businesses and to the individual. This technology AI is going the opposite, which is, like I said, the most sophisticated capabilities are available on the consumer app today. And then what we're finding is consumers are adapting the fastest just individuals in their lives. The small businesses are then adopting right after that because, you know, a small business typically is just, you know, a person who's, you know, making decisions for their own business. Very, very easy to, to do new things. Big companies are then following small companies. And so, you know, the companies on that list, some, you know, obviously some of them are doing interesting things. But in general, big companies right now are pretty tied up in knots internally, kind of in all their processes and in all their legacy systems and all their, you know, organization and training and, but their unions and like all the other issues they have to deal with, they're actually relatively slow to adopt compared to individuals and small businesses. And then government is the late adopter. Right? And so governments, of course are already trying to figure out kind of how to adapt to this technology, but they're not adopting it very fast because they can't because of all their rules and systems and bureaucracy. And so there's been a real inversion of how technology moves through our society that's really become. AI is becoming a case study for. And so the answer to your question is, I think big company CEOs, and many of them are doing this, but I think they really have to force the issue on this inside their companies because these big companies are just such now giant bureaucracies with so many rules that by default they'll smother new ideas. And so it's a real act of leadership to get on a list like that and be able to actually say kind of with pride, like, we're on the leading edge.

Marc Halperin (9:35)

So if your friend owned a bakery and he said, mark, I want you to come in and help me figure out how to use AI. Well, how could someone own a single storefront bakery? Use it now.

Marc Andreessen (9:45)

Yeah, I mean, so, I mean, there's, I mean, there's, you know, there's dozens of ways, you know, it obviously depends on what your business falls are.

Marc Halperin (9:51)

They're, they're, they're baker.

Marc Andreessen (9:52)

Dozens of ways they know. Exactly. And so, yeah, I mean, look, first thing you can do is just say, look, you know, review, you know, do a performance review for me. Like, just feed in. You know, here's my, here, my, here's my staffing schedule. You know, what, what do you think of it? Give me a critique of it. You know, here's the last, you know, 100 emails we've gotten from customers. What are the, what are the, what are the patterns of that? Here's the copy for the ad that we're going to place the local newspaper, put up on Facebook or whatever. What do you think of this? Let it do it. Let it do a performance assessment. A lot of people find it very effective for personal coaching. And so the owner might use it that way or might ask the employees to use it that way. And then I think where the power really kicks in is you're a small business owner. You've got one bakery now you want to have two bakeries and you want to have a brand. And then maybe if that works, you're going to have five and then 50 and then 500, and then you're going to have packaged products going to supermarkets and so forth. And then there you basically turn the AI into a thought partner, right? And you basically say, okay, what are the best ways to expand from a single outlet to multiple and to turn this into a larger business? And the AI, because it's been trained on some large percentage of the total amount of human knowledge. It has within it all the information on how Ray Kroc turned McDonald's from a single restaurant in McDonald's and how all these other entrepreneurs before actually did this. And so it can explain with you and help you, you know, figure out how to do this for your own business. And then, you know, the thing that you get into as you use it is basically it's just like, wow, it's like having the world's best coach, mentor, therapist, right, Advisor, you know, board member, but it's like infinitely patient. And so it's like, it's happy to have the conversation. It's happy to have the conversation 50 times. It's happy if you admit your insecurities and will coach you through them. You know, it's happy if you run wild speculations that don't make any sense. It's happy to do all that at 4 in the morning. And so the people who are using it a lot are finding it's, you know, it actually turns out to be very supportive in their, in their real life.

Marc Halperin (11:42)

Could you say, here's the recipe for our best selling cinnamon rolls. How could I make it better? Would that.

Marc Andreessen (11:46)

Yes. Yeah, 100%. Yeah, you can say, you can say. And by the way, part of the art of AI, right, is what questions to ask it, right? Because, you know, it turns out, you know, it turns, it can answer, you know, many, many different questions. So you have to, you have to actually get creative at this. Yeah. And so you could say, like, here's my current recipe, you know, how might I improve it? You can also say, you know, what's the best cinnamon roll recipe in the world? Work backwards from that. And then you could also say, look, I want to make the best one in the world, but I need to do it in a sen. Price. You know what, you know what, you know, what are the ways to cost. Optimize. All right, so the other thing you can ask, by the way, the other thing you can ask it is you can ask it, what question should I be asking? Right. And so you could plug in, I run a bakery, what question should I be asking? And you'll find it, it's actually a thought partner in helping you figure out what questions to ask. Right?

Marc Halperin (12:29)

Brilliant. So the other day I said, I want to know every Republican who voted against any of the articles of impeachment against Bill Clinton. Give me the list of every Republican. And it came back and it listed some Democrats mixed in there and it said they were Democrats and I said back, I only want Republicans. And it said, oh, sorry, I inadvertently included Democrats. Now I could understand a human being, a junior researcher, doing that, but how could AI make a mistake, have it pointed out to it and say, oh yeah, how could that be in the model? Yeah.

Marc Andreessen (13:04)

So this gets technical and I'd be delighted to get deeply into the technical details. I'll try to resist. It's a new kind of computer and the way to think about it is computers up until now have been what you might call like hyper literal. Right? Where computers up until now like they do math really fast, but they do the same thing every single time. They exhibit no creativity whatsoever. And if you expect them to exhibit creativity, they just can't do it. And then if they make a mistake, it's because the human programmer made a mistake. And that has made computers super useful for running large math exercises, doing a lot of things that computers do. But of course, computers have never been creative. Computer's never been able to write you poetry or work with you on your cinnamon bun recipe. Like it's just never even been a thing that we can think about. So it's never had kind of that human element of creativity to it. This is just a completely different kind of computer that has these characteristics that are frankly more like a person, which is it's right most of the time, it occasionally gets things wrong. When it gets things wrong, it's able to self critique and you have to kind of work with it the way that you work with a person. And so you have to basically figure out as you use it, like you want to take advantage of the fact that it's creative and then you want to be tolerant of the fact that fact that it's not always correct, just like you're working with a person. Now having said that, when it makes easily avoidable mistakes, where it's just like makes boneheaded fact mistakes, you know, we call those hallucinations. The latest systems are much, much, much better at not doing that. They're, they're, they're much more accurate. And in particular for anybody watching this, if you want to kind of see this in action, I'll just give an example. If you, if you buy the, the full version of ChatGPT, there's a model called GPT Pro, GPT 5 Pro, which is the latest one. And then there's something called Deep Research which is a switch that you turn on. And if you use GPT5Pro with deep research and you ask a question like that, like at this point, I think it's, I wouldn't say it's bulletproof, but like it's really good as things fastly grounded and literally, you can watch it work and it'll literally go out on the Internet. It'll like check all the authoritative sources and it'll, you know, It'll go on Congress.gov or whatever and check the voting records and verify that. And so I think that problem is being ironed out kind of as we speak. Yeah.

Marc Halperin (15:04)

For people watching, listening, who haven't used it or not used it much, the thing you said about good prompts is so key. And that does differentiate the, you know, the people really getting productive at it from not. And one of the things that you and I have talked about is it is hilarious. It can write. If you give it the right prompts, it can write stuff that is so funny. And where does that come from? How does it have the capacity to understand? Because humor involves metaphors and sophistication and humanity. How can it do that?

Marc Andreessen (15:38)

Yeah, so this gets to this idea of how it's trained. So basically what these systems are is they're basically the accumulation of human knowledge over time. And by the way, most of the training data is just literally the Internet. Right. So one of the reasons that this is happening now and not 20 years ago is because the Internet finally got big enough, but just the web finally got big enough to have like all this information in it. Right. And so if you go out on the Internet today, you can find all kinds of material online. You can find classic screenplays from the golden age of cinema 400 years ago. You can find literally people joking with each other on social media all day long. You can find professional comedians doing oral histories of how they did great comedy. So there's just, there's incredible amounts of information that are online about comedy and about what's funny. And then all of that information is in the training data. So it's all kind of fed into the AI during the training process. And the AI basically processes it through like any other kind of of data and comes out the other end and just basically is like, oh, you know, now that AI is a world class expert in humor, right? And of course, you know, look, you could be an expert in humor and I'd actually be funny, right? And they're, you know, they're, I don't know, probably professors of comedy or something like that in colleges who aren't very funny. But like, it just, it knows so much about what humor is. It knows so much about the pattern of jokes. It knows so much about what makes people laugh. It has so many examples, you know, to be able to learn from. And, you know, the professional comedians will tell you there are patterns to comedy. Right? You know, there are. You know, I worked with a professional comedian once with something, and he said, you know, the key to it is specificity. Like, you need to get you to just, like, nail the reference. You know, another comedian will say the key is, you know, timing or pacing or the callback to the previous job or whatever, you know, the punchline, whatever it is. And so it just, it knows all that. And then it's just, you know, it's now so powerful that it's actually. Yeah, yeah. Quite honestly, I find, especially at like 2 in the morning, I find these things hysterical.

Marc Halperin (17:28)

Yeah. All right, with just a minute left before we take a break, what's your advice to an individual who's barely used it or hasn't used it? What's your advice to them to sort of how to get started?

Marc Andreessen (17:38)

Yeah, so I mean, by far the best way to do it is just download it and use it. And like I said, there's several good. Elon's got Grok, which is now fantastic, by the way. It's actually interesting how these things are getting built into products now. So the new versions of X, formerly Twitter, actually, if you go to any post on X, there's a little rock icon that looks like a little black hole icon in the upper right corner of the post. And if you click on it actually calls up the Grok AI to explain the post to you, right? And so, like, it literally is like, it can explain to you that, you know, if there's some post on politics or something, you don't understand what's happening. You just, you've lost the threat of the topic. You just like block that button and you get in a dialogue with the AI. Little AI window pops up and explains the post and you can ask it for more details. And so it's like built into that product. Google's actually built AI now into search. And so now when you do searches, it has this thing called AI mode and you bunk on it and edit it. You know, in addition to getting the 10 blue links for Google, you now get into an AI dialog. And so you just start using those products or you just download one of these apps and start using it. And like I said, a really great question is like, okay, how do I use you? Right? Like. Or you can teach me. Works really well. You can say, you know, teach me how to use you in the best way you know. You know, teach me how to use you for my business, you know, for this project. And it'll, you know, these things love to talk, and it'll, it'll happily sit there and chatter away and take you through it.

Marc Halperin (18:58)

Yeah, just my, my sort of analog to the way you just said it is ask it for what you want as specifically as possible. Don't hold back. Be really specific, and it will do what you ask. All right, more with Marc Andreessen. That's next up. Stay tuned. If you're 64 years old or older, this is an important announcement. The Department of Justice recently sued three major Medicare brokers for claiming they were unbiased while allegedly pushing people into plans that got them the biggest kickbacks. It's true. So many insurance agents that just can't be trusted. But you also cannot rely on the government to give you the best information that you need either. That's why I want you to know about something called chapter. CHAPTER was started by people who went through all of this personally after their own parents were pushed into the wrong Medicare plan by an agent who was more focused on commissions than on good care. Chapter's mission is very simple. They want to give every American the honest, straightforward Medicare advice that they deserve. And here's what makes them different from everybody else. They're the only Medicare advisor that compares every plan nationwide, not just a few. That saves their clients an average of eleven hundred dollars a year. There's really no reason not to call. It's quick, it's easy, and they can review your options in under 20 minutes. If you're in the right plan already, they'll let you know that. But if there's a better plan, they'll help you make the switch. This could be the most important call you make this year. Dial £250 and say chapter Medicare to get peace of mind. Again, that's £250 and say chapter Medicare.

Marc Andreessen (20:37)

All right.

Marc Halperin (20:38)

Welcome back. We're here with Marc Andreessen. Still. Mark, are you of the school that says that we're in an exit? The United States is in an existential state struggle with China. Do you subscribe to that point of view?

Marc Andreessen (20:49)

I was gonna say, I hope that's not true. Right. You know, I hope this is not gonna walk all the way to the situation that we ended up in with the Soviet Union. You know, like most like, you know, like you, I grew up in an era, I'm sure. See, if you, you remember this, like, you know, I I growing up thinking there was a significant chance that, like, we're all gonna die, you know, from nuclear war. And so I hope it doesn't get back to that level of intensity. But. But I do think there are a lot of historical parallels to what happened between the US and the USSR in the 20th century happening right now. And you have two hegemonic superpowers that both have visions. They both have visions of how society should be structured and how the global political system should be structured. And obviously, I think America's is better, but they both have visions and they're both working to that end. And then they both have international strengths and weaknesses, militarily, technologically, economically, culturally. And, you know, there is that kind of geopolitical fight happening. So I hope we stay in this kind of, I don't know what you call it, mode of, like, coopetition, you know, tension without, you know, without military strife. You know, I hope we stay, you know, in that mode, but, like, it's a sufficiently fraught situation, you know, that we certainly need. And you know, and by the way, have a national strategy for how to win that. And we need to make sure that we do. Right.

Marc Halperin (22:08)

Do they have any one or two advantages over us in terms of AI?

Marc Andreessen (22:12)

Yeah, they do. So they have all. They have two advantages. And by the way, I should say we have many advantages. I'm very bullish on the US And I think we're better positioned. I wouldn't trade places with them. And we could talk about that. But having said that, they do have strengths. And in particular, they have two key strengths. Number one is they do have the advantages of a command economy. And generally speaking, or 100%, I'm on the side of free markets and decentralization and having a dynamic economy. And we have advantage. We have much better entrepreneurial ecosystem and so forth. Having said that, they do have this advantage where when their government decides that something's a national priority, like, they just do it. And by that I mean, not only does the government do it, but they just tell the private sector you do the following, right? And so sort of the, you know, the. They had this, you know, thing the Soviets had where they, you know, the entirety of society is able to, you know, go up against. Go up against single missions. You know, we're just a lot more fractious than that. And so, you know, we kind of navigate our way through this in our own way, but not, you know, we don't have anywhere near that level of organization. So that gives them the ability to execute against specific areas of focus in arguably a superior way. And then the other advantage that they have is we in the US voluntarily be industrialized starting 30, 40 years ago. And that industrialization, the making of physical things, and particularly the making of machines, has moved substantially to China. And the way that we think about machines now is that basically they're the hardware version of software. They're the embodied version of AI. And so, you know, the car is not just steel and glass anymore. It's, you know, it's a robot on wheels. You know, the drone isn't just a toy, a toy anymore. It's a, it's a computer, you know, that flies through the air, you know, that navigates itself. You know, robots are coming, you know, you know, we're going to live in a world that's just like, completely awash with robots in the decades ahead. And China's just like. As a consequence, in the last 30 years of policy, China is just like, way ahead on everything involved in building physical things. And then this administration and others have had visions of how to recapture that. But we have a long way to.

Marc Halperin (24:15)

Go as the US tries to become more of a manufacturing country. It would seem to me AI integrated into manufacturing is extremely powerful. Are they ahead of us on that? As you said, our biggest companies here are slow adapters of AI. Are there big manufacturers now using AI more than we are?

Marc Andreessen (24:35)

Yeah. So, so I think we, so I think unleashed, we could do that faster and better. Like, if, if we could manufacture in the US the way that we used to 30 or 40 years ago, we could definitely do that faster for, for, you know, for, for a variety of reasons, including the fact, I mean, we have better software engineers. We, you know, we have a more flexible and dynamic economy. You know, we could do that faster. The, the, the big issue is just we have chosen to not be a manufacturing economy. Like, we, we chose to move that, to move that offshore. And, you know, we were, for a very long time, we were very proud that we moved that offshore for, you know, for a variety of reasons. And so the challenge is not so much that, you know, that we couldn't, in theory, do exactly what you just described better than they can. It's just like if, if you just, if you're not manufacturing things, then you can't do that at all. Right? Which, which is the situation that we've worked ourselves into. And so, you know, just, they're, you know, they're, they're, you know, their car, just to pick one, their car industry is like, moving like Incredibly fast with this, you know, we, and look, we have to, you know, we have our superstar companies, we have Tesla, you know, in particular, that's world class with us. And, you know, still, you know, better than, better than the Chinese today. But like the Chinese are moving really fast. And if you talk to people, we don't have a lot of exposure to Chinese cars in the US because the trade barriers are so high that they really are not cost effective to sell here. But it's like if you go to the Middle east and talk to just like normal affluent people, they're now driving Chinese cars by choice. Not because they can't afford a Mercedes because the Chinese cars are better and the Chinese cars are full, self driving, electric, autonomous, voice AI. They're state of the art, know exactly what you're talking about. And we have just, we still have car companies, but xtesla, mainly what they do is they assemble third party parts that are coming from other places. The Chinese are just doing a much more specific, advanced level of unified hardware and AI manufacturing. By the way, you see that in drones. Virtually the entire global drone industry and virtually the entirety of the drone industry in terms of people using drones in the US virtually 100% of those drones are made in China. And again, that's not because we couldn't make them, it's because we chose a set of policies that drove that industry offshore.

Marc Halperin (26:31)

We better start making them. I want to talk to you about Silicon Valley. As much as it's been covered for the last quarter century, I don't think the coverage is even close to explaining how significant it has been. They're great stories like yours of people who have, have been so successful, but the influence over our culture, our government, our economy, it's just in the world, it's just so massive is if someone like you understands engineering, markets, economics, technology. There was a long period where you had to live in Silicon Valley if you, if you wanted to succeed and have the, the relationships and the interactions. Is that still the case? Is Silicon Valley still a place you have to physically be if you want to excel? Someone with those skills?

Marc Andreessen (27:17)

Yeah. So I should start by saying I'm an import, right? So I'm from out of town. You know, I grew up in the rural Midwest, Wisconsin, you know, kind of, you know, in a tundra. And so, you know, I, you know, I didn't grow up here. I, you know, I didn't get to participate kind of in the heyday of, you know, back when we actually it was called Silicon Valley because they originally Made chips here, right? Yeah. You know, speaking of manufacturing, of course blocks have stopped doing that. You know, that's not thoroughly illegal in California. And so, you know, I wasn't here for that. I wasn't here for the personal computer. And so I'm an inheritor of, you know, the phenomenon that you're describing that other people built.

Marc Halperin (27:50)

Well, what year did you show up?

Marc Andreessen (27:52)

Yeah, so I showed up in 1994. And you know, Silicon Valley is really dated. You know, it's sort of based in the early 50s, you know, with Hewlett Packard in particular as sort of the original company.

Marc Halperin (28:03)

But the 90s. The 90s is when so much of what we think of now in terms of consumer facing, social media, Internet. Right. I mean, that's a pretty big dividing line. So, yeah, you missed the Hewlett Packard days, but you were there for the phase we're in now, right?

Marc Andreessen (28:18)

Yeah, but I just bring it up because basically the history of Silicon Valley, it's a sequence of waves, right? And so this is part of what makes it special is AI is like wave 9 or wave 10 of these just major basic microprocessors and smartphones and kind of cloud and social and mobile, all these kind of the PC kinds of, all these waves of hit. So anyway, my point is when the value. We're the inheritor of a tradition and a system and a model that was built by other people. And then to your question on geographic focus, this is very interesting thing playing out right now. So a couple of things. So one is, look, like I said, the technology that's built in Silicon Valley is diffusing nationally and globally into ordinary people's hands, like at a far faster rate than in the past. So you don't have to be in Silicon Valley to get access to the best technology. Like you can now get that from everywhere. And that's very important because that didn't used to be the case. Having said that, if you want to be at the company or start a company that's going to build the leading edge technology itself from scratch, I would say at this point maybe you don't need to be in Silicon Valley proper, but you better strongly considering if you're not, there's maybe three or four other places in the country, you can give it a shot. But primarily the people that want to do that are coming to Silicon Valley. And the important thing in the last five years that happened actually was during COVID we all thought actually that the Silicon Valley geographic concentration was actually unwinding. And we thought that virtual Work and remote work and you could be able to start companies everywhere. And you had all these kind of booms happening in places like Miami and Austin and other places with lots of high tech entrepreneurs. And it felt like the whole thing was really distributing out. AI basically has snapped everything right back into the 20 mile square radius around where I sit to just an incredible degree. So I would say like almost 100% of the actually interesting AI companies in the west are happening at sort of ground zero right here in Silicon Valley. And then, by the way, and this is good news and bad news, by the way, the other place in the world where these things are happening is basically the Shanghai, Beijing, access of China. These are the two places. And then you also say a very important thing which is it's just not happening elsewhere in the world and there's, there's kind of high tech clusters in other places. But if you're a sharp AI person and I'll just pick on one. London. You have already moved to California or you're going to, because they have just essentially decided to outlaw it. The EU has decided to outlaw it. And so people are being driven to the US and to California, I think, in a way that's even more concentrated than it was when I first got here.

Marc Halperin (30:45)

All right, last question. Name inventions in human history that have more benefited the lives of individuals than the iPhone.

Marc Andreessen (30:55)

Oh, well, I mean, you know, if you go far enough back, you know, electric lighting was a big deal. You know, steam power was a big deal. You know, obviously antibiotics are the easy call. I mean, you know, the Internet itself, you know, electricity, you know, it's, you know, indoor plumbing, you know, it's hard to question those. And people sometimes say like, you know, you guys aren't inventing important things. Like, why are you inventing something as important as indoor plumbing? And it's like, well, that was a big one, I can see. But like, you know, we did, we did solve that problem. We could move on.

Marc Halperin (31:26)

I would. If you said, if you said give up your iPhone or switch to an outhouse, I would switch to an outhouse.

Marc Andreessen (31:32)

I think, you know, I think there's a lot to that. And maybe the serious point underneath, underneath that which I. Oh, I was being serious.

Marc Halperin (31:39)

I was being serious.

Marc Andreessen (31:40)

Well, no, so maybe say the generalization you can make for that is, I think people may be systematically underrated the importance of communication. So being able to be connected with other people and then being able to actually, you know, be able to learn things, be able to get access to information. Like those two things. There's something in the culture. I was just saying, in Silicon Valley culture, there's something where, like, those are, like, looked out on as less important. Then I actually think, to your point, like, they're actually incredibly important and they're foundational for everything else that people do. I mean, you know, human connection and human learning is, you know, both of those are at the center of everything that we do. And so, yeah, no, I would make that same trade.

Marc Halperin (32:13)

Here's my idea for a reality show. You put someone like us in Cleveland for a week without their smartphone and give them. And give them a series of tasks which they would otherwise conduct with their smartphone. Good luck.

Marc Andreessen (32:26)

By the way, I had. I had relatives in the 70s who still had outhouses, right? Like, yeah, it's fine 100%. Well, it's fine in Iowa in January. You start to reconsider whether that's fine in the middle of the night when it's 40 below. But like, the past, the past was not that long ago.

Marc Halperin (32:48)

All right, Mark Andreessen, very grateful to you. I scratched the surface. I had a list of about 15,000 questions that AI went down to me to 1500, but we didn't get to them all. Very grateful to you, though, for making time and again. So just not many people on the planet who understand this stuff as well as you do. So grateful to you for sharing and hopefully we inspired a few people to learn how to use, use the latest technology. Thank you.

Marc Andreessen (33:11)

Good. Fantastic. Thank you, Mark.

Podcast Host / Narrator (33:14)

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