AI transcript
0:00:09 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.
0:00:16 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.
0:00:20 It occasionally gets things wrong. When it gets things wrong, it’s able to self-critique.
0:00:23 And you have to kind of work with it the way that you work with a person.
0:00:27 You want to take advantage of the fact that it’s creative, and then you want to be tolerant of the fact that it’s not always correct.
0:00:35 AI basically has snapped everything right back into the 20-mile-square radius around where I sit to just an incredible degree.
0:00:42 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.
0:00:49 There’s a bakery owner somewhere using the same AI as Google’s CEO, and according to Marc Andreessen, the bakery owner is winning.
0:00:55 The man who invented the modern web browser and built multi-billion dollar companies just revealed something remarkable.
0:00:57 AI is spreading backwards through society.
0:01:03 Individuals first, small businesses second, Fortune 500 companies third, government last.
0:01:07 The exact opposite of how computers evolve from mainframes to smartphones.
0:01:11 Marc says half a billion people already have the world’s most sophisticated AI on their phones.
0:01:16 So the question is, why are most using it to write emails while only some are using it to build empires?
0:01:22 Today, we’re sharing a conversation Marc Andreessen had with Marc Halperin on the show Next Up.
0:01:26 They talk about the specific prompts that transform AI into a world-class advisor,
0:01:31 why Silicon Valley just snapped back into a 20-mile radius after five years of dispersion,
0:01:35 and the uncomfortable truth about America’s AI race with China.
0:01:36 We hope you enjoy.
0:01:46 All right, next up, Marc Andreessen, innovator, creator, and damn successful businessman.
0:01:50 Early on, he invented the Mosaic Internet Browser, co-founded Netscape,
0:01:58 and since then, he has been the animating force and investor behind a lot of very successful companies,
0:02:01 including some at the multiple-billion-dollar level.
0:02:06 He co-founded his firm, Andreessen Horowitz, a general partner there,
0:02:12 and they do a lot of stuff about a lot of stuff, and he knows a lot about a lot.
0:02:13 Marc, welcome.
0:02:15 Thank you, Marc. It’s great to be here.
0:02:16 Really happy to have you.
0:02:21 So much about AI I want to talk to you about, so we’re going to spend a lot of the time on that.
0:02:32 First off, it’s tempting to say right now, and when I think about AI, I think about where are we now and where are we going.
0:02:37 It’s tempting to say it’s between, like, really smart, highly educated people who are adapting to it
0:02:42 and then people who just don’t have the capacity to do that in their jobs easily.
0:02:48 But what I’m finding is at people who do what I do, people who are well-educated, very privileged,
0:02:50 there’s a have-nots there.
0:02:52 I’m a baby using it.
0:02:58 I’m not using it very sophisticatedly very often, but I am Einstein compared to some of my counterparts.
0:03:01 And I’m wondering, is that how you see it?
0:03:05 And what do you think differentiates those who understand how powerful it is even now
0:03:08 versus those who seem oblivious to it?
0:03:12 Yeah, so I think there’s kind of a fake story, and then there’s a real story.
0:03:16 So the fake story is kind of the classic Marxist story, which is, you know,
0:03:19 oh, only the rich people have it, only the fancy people have it,
0:03:23 the big tech companies have it, everybody else is kind of going to be left out in the cold.
0:03:25 And that’s not actually what’s happening.
0:03:31 And there’s a lot of data on this now that has been released by these companies to justify what I’m about to say.
0:03:35 So the real story is this is already probably the most democratic, you know,
0:03:39 small-D technology of all time in the sense of the very best AI in the world
0:03:42 is fully available on the apps that anybody can download.
0:03:48 And, you know, take your pick, ChachiPT, Klau, Gemini, Grok, you know, Mistral, any of these.
0:03:50 By the way, DeepSeek, China.
0:03:55 You download any of these apps, you’re getting state-of-the-art, like, the full, most sophisticated,
0:03:57 powerful AI capability in the world.
0:04:01 And, you know, the number of people already who downloaded these apps is north of a half billion
0:04:03 on its way to a billion.
0:04:08 And individual people are figuring out, you know, basically how to appropriate this in their lives.
0:04:11 And what you see in the data is there’s, you know, maybe what you’d expect,
0:04:14 which is there are a slice of people who just use these new systems all the time,
0:04:16 like literally all day for everything.
0:04:21 And, you know, in a lot of cases, they’re reporting that they’re getting enormous benefits from that.
0:04:23 And then there’s a lot of people who are experimenting and trying to figure it out.
0:04:26 And then there are people who are just, you know, not, you know,
0:04:28 for whatever reason, not interested or not engaged.
0:04:32 But I would say it’s incredible out of the gate how distributed this technology already is.
0:04:36 And then I could just say, like, I don’t have, you know, with all my resources
0:04:39 and with all my connections, I don’t have access to a better AI
0:04:41 than the one that you just downloaded off the App Store.
0:04:44 And so I think this is actually, like, just an incredible story
0:04:47 of the most advanced technology in the world being available to everybody right out of the gate.
0:04:51 You got to get people to use it to take advantage of it, right?
0:04:55 So I’ve got a friend who’s drafted a book and took it to his agent.
0:04:58 And the agent said, it’s 140,000 words.
0:04:59 You got to cut it down to 70,000.
0:05:02 And I said, if you try to do that by hand,
0:05:05 even if you hire someone, it’s going to take you months.
0:05:06 I can do it in an hour.
0:05:09 And I can say to AI, don’t change the style.
0:05:11 Don’t change the tone.
0:05:14 Don’t cut anything that, you know, ruins the story.
0:05:17 And he said, that’s immoral.
0:05:22 The publisher will be mad that I did it that way.
0:05:22 It’s not right.
0:05:24 How should I answer that person?
0:05:29 Yeah, so the exact same arguments, you know, emerged, you know, years ago with the introduction
0:05:30 of computers, right?
0:05:35 I actually just, I’ve been watching a lot of, you know, old science fiction movies with my
0:05:35 kid.
0:05:39 And, you know, there’s this famous science fiction movie, Tron, from 1982, you know, that
0:05:41 had the first, kind of the first real computer graphics movies.
0:05:44 And it was disqualified for an Oscar for special effects because it used computers.
0:05:46 Right?
0:05:49 And so there’s this kind of long tradition of, like, whatever the new tool is, it’s
0:05:51 sort of illegitimate, and there must be something wrong with it.
0:05:54 In this particular case, I mean, there’s no doubt there are people who feel the way that
0:05:55 your friend feels.
0:06:02 That issue was actually litigated in the last Hollywood strikes, in the movie, on the film
0:06:04 and TV side of the creative profession.
0:06:04 Yeah.
0:06:08 The last round of strikes actually, it’s actually funny, it started as streaming strikes, and
0:06:10 then AI hit, and it became AI strikes.
0:06:15 But the settlement with the studios, actually, with the unions was that, the following, which
0:06:18 is, if you’re a writer and you use AI, that’s totally fine.
0:06:22 What’s not allowed is for the studio to basically use the AI and then claim it was a writer.
0:06:28 But basically, what the unions and studios in Hollywood decided was, it’s another tool, it’s
0:06:32 like the word processor, it’s like the personal computer, it’s like, you know, it’s like using
0:06:34 a printer instead of writing out a manuscript by hand.
0:06:39 And so I think there are people who feel like your friend does, but I think the world is already
0:06:41 adapting very fast to using it.
0:06:45 And frankly, one of those reasons you probably pointed out to your friend is, like,
0:06:48 I don’t even know that anybody could tell anymore, right?
0:06:52 And so, you know, if you’re going to have a moral prohibition on something that people can
0:06:55 just do and nobody knows about, like, is that, you know, is that really going to work?
0:06:59 And so I think those sort of self-imposed barriers are probably going to collapse quite quickly.
0:07:00 I hope so.
0:07:07 Fortune put out a list of the top American companies using AI.
0:07:11 Alphabet, Visa, JPMorgan Chase, top three.
0:07:15 We talked about just now on an individual level.
0:07:20 If you were the CEO of a company or advising a CEO, how important is it to be on that list?
0:07:24 In other words, how important is it to get your company to adapt, whether it’s for internal
0:07:25 or consumer-facing?
0:07:27 How important is it right now?
0:07:32 Yeah, so this goes back to actually where we started, which is, and in fairness, the
0:07:37 old model of adapting actually computers when computers came out, the old model was the
0:07:40 largest institutions get technology first and then everybody else gets it later.
0:07:44 And so, you know, the way the computer rolled out was the government actually got mainframe
0:07:46 computers first starting in the 1940s.
0:07:50 And then big companies got computers in the mainframes in the 1950s, 1960s.
0:07:54 Small companies started to get computers, what were called minicomputers at the time in the
0:07:54 1970s.
0:07:59 And then, you know, we as individuals only got, you know, PCs in the 1980s.
0:08:03 And so it took 40 years for basically technology to cascade down from the largest organizations
0:08:05 in the world to small businesses and to the individual.
0:08:13 This technology, AI, is going the opposite, you know, which is like I said, the most sophisticated
0:08:15 capabilities are available on the consumer app today.
0:08:20 And then what we’re finding is consumers are adapting the fastest, just individuals in their
0:08:20 lives.
0:08:25 Then small businesses are then adopted right after that because, you know, a small business
0:08:27 typically is just, you know, a person who’s, you know, making decisions for their own business.
0:08:30 Very, very easy to do new things.
0:08:33 Big companies are then following small companies.
0:08:37 And so, you know, the companies on that list, some of, you know, obviously some of them are
0:08:40 doing interesting things, but in general, big companies right now are pretty tied up in knots
0:08:44 internally, kind of in all their processes and in all their legacy systems and all their, you
0:08:48 know, organization and training and, but their unions and like all the other issues they have
0:08:52 to deal with, you know, they’re, they’re actually relatively slow to adopt compared to individuals
0:08:52 and small businesses.
0:08:55 And then, and then government is, is the late adopter, right?
0:08:58 And so governments, of course, are already trying to figure out, you know, kind of how to adapt
0:09:02 to this technology, but they’re not adopting it very fast because they can’t because of all
0:09:03 their rules and systems and bureaucracy.
0:09:07 And so there’s been a real inversion of how technology moves through our society.
0:09:10 That’s really become, you know, AI is becoming a case study for.
0:09:15 And so the answer to your question is, I think big company CEOs and, you know, many of them
0:09:19 are, are, are, are doing this, but I think they really have to force the issue on this
0:09:22 inside their, their companies because the, you know, these big companies are just such now
0:09:27 giant bureaucracies with so many rules that like by, by default, they’ll smother new ideas.
0:09:31 And so it’s a, it’s a real active leadership to, you know, to get on a list like that and be
0:09:34 able to, you know, actually say kind of with pride, like we’re on the leading edge.
0:09:39 So if your friend owned a bakery and he said, Mark, I want you to come in and help me figure
0:09:45 out how to use AI, well, how could a, someone owns a single storefront bakery, use it now?
0:09:45 Yeah.
0:09:49 I mean, so there’s, I mean, there’s, you know, there’s dozens of ways, you know, it obviously
0:09:51 depends on what your business goals are.
0:09:53 They’re, they’re, they’re baker dozens of ways.
0:09:55 They’re, they’re, exactly.
0:09:59 And so, yeah, I mean, look, the first thing you can do is just say, look, you know, review,
0:10:02 you know, do a performance review for me, like just feed in, you know, here’s my, here’s
0:10:03 my staffing schedule.
0:10:05 You know, what, what do you think of it?
0:10:06 Give me a critique of it.
0:10:09 You know, here’s the last, you know, a hundred emails we’ve got from customers.
0:10:12 One of the, one of the, one of the patterns of that, you know, here’s the copy for the
0:10:15 ad that we’re going to place in the local newspaper, you know, put up on Facebook or whatever, like,
0:10:17 you know, what, what, you know, what do you think of this?
0:10:19 You know, let it, let it do it, let it do a performance assessment.
0:10:22 A lot of people find it very effective for personal coaching.
0:10:26 And so, you know, the owner might use it that way or might, you know, ask the employees
0:10:27 to use it that way.
0:10:31 And then I think where the power really kicks in is, okay, you’re a, you’re a, you know,
0:10:33 you’re a small business owner, you’ve got one bakery, now you want to have
0:10:34 two bakeries, right?
0:10:37 And you want to have a brand and then maybe if that works, you’re going to have five and
0:10:40 then 50 and then 500, and then you’re going to have, you know, packaged products going to
0:10:41 supermarkets and so forth.
0:10:44 And then, and then there you basically turn the AI into a thought partner, right?
0:10:47 And you basically say, okay, what, you know, what are the best ways to expand from a single,
0:10:51 you know, outlet to, you know, to multiple and to turn, you know, turn this into a larger
0:10:51 business.
0:10:55 And, you know, the AI, you know, it’s been, you know, because it’s been trained on, you know,
0:10:59 some large percentage of, of the total amount of human knowledge, like it has within
0:11:03 all the information on how, you know, Ray Kroc turned McDonald’s from, you know, a single
0:11:06 restaurant in the McDonald’s and how all these other, you know, entrepreneurs go through or
0:11:07 actually did this.
0:11:10 And so it can, you know, explain with you and help you, you know, figure out how to do this
0:11:10 for your own business.
0:11:14 And then, you know, the thing that you get into as you use it is basically, it’s just
0:11:17 like, wow, it’s like having the world’s best coach, mentor, therapist, right?
0:11:19 Advisor, you know, board member.
0:11:22 But it’s like infinitely patient.
0:11:25 And so it’s like, it’s happy to have the conversation.
0:11:27 It’s happy to have the conversation 50 times.
0:11:30 It’s happy if you admit your insecurities, it’ll coach you through them.
0:11:33 You know, it’s happy if you run wild speculations that don’t make any sense.
0:11:35 It’s happy to do all that at four in the morning.
0:11:39 And so the people who are using it a lot are finding it’s, you know, it actually turns out
0:11:41 to be very supportive in their real life.
0:11:45 Could you say, here’s the recipe for our best-selling cinnamon rolls?
0:11:46 How can I make it better?
0:11:47 Would that, would that?
0:11:48 Yeah, a hundred percent.
0:11:53 Yeah, you can say, you can say, and by the way, part of the art of AI, right, is what
0:11:54 questions to ask it, right?
0:11:57 Because, you know, it turns out, you know, it turns, it can answer, you know, many, many
0:11:57 different questions.
0:12:00 So you have to, you have to actually get creative at this.
0:12:00 Yeah.
0:12:03 And so you can say, like, here’s my current recipe, you know, how might I improve it?
0:12:06 You can also say, you know, what’s the best cinnamon roll recipe in the world?
0:12:08 We’re backers from that.
0:12:11 And then you could also say, look, I want to make the best run in the world, but I need to do
0:12:12 it at an intense price.
0:12:15 You know, what, you know, what, you know, what are the ways to cost optimize?
0:12:18 All right, so the other, yeah, go ahead.
0:12:20 By the way, the other thing you can ask it is you can ask it, what questions should
0:12:21 I be asking?
0:12:22 Right?
0:12:24 And so you could plug in, I run a bakery, dot, dot, dot.
0:12:25 What questions should I be asking?
0:12:29 And you’ll find it, it’s actually a thought partner in helping you figure out what questions
0:12:29 to ask.
0:12:30 Right, brilliant.
0:12:34 So the other day I said, I want to know every Republican who voted against any of the articles
0:12:36 of impeachment against Bill Clinton.
0:12:38 Give me the list of every Republican.
0:12:43 And it came back and it listed some Democrats and mixed in there.
0:12:44 And it said they were Democrats.
0:12:47 And I said back, I only want Republicans.
0:12:51 And it said, oh, sorry, I inadvertently included Democrats.
0:12:55 Now, I could understand a human being, a junior researcher doing that.
0:13:01 But how could AI make a mistake, have it pointed out to it, and say, oh, yeah, how could that
0:13:02 be in the model?
0:13:08 Yeah, so this gets technical, and I’d be delighted to get deeply into the technical details.
0:13:09 I’ll try to resist.
0:13:11 It’s a new kind of computer.
0:13:15 And the way to think about it is computers up until now have been what you might call
0:13:19 like hyperliteral, right, where computers up until now, like they do math really fast,
0:13:22 but like they do the same thing every single time.
0:13:24 They exhibit no creativity whatsoever.
0:13:28 And if you expect them to exhibit creativity, like, you know, they just can’t do it.
0:13:30 And then if they make a mistake, it’s because the human programmer made a mistake.
0:13:34 And that has made computers, you know, super useful for running like, you know, large math
0:13:37 exercises, you know, doing a lot of things that computers do.
0:13:39 But of course, computers have never been creative, right?
0:13:44 Computers have never been able to write you poetry or work with you on your cinnamon bun
0:13:44 recipe.
0:13:46 Like, it’s just never even been a thing that we can think about.
0:13:49 So it’s never had kind of that human element of creativity to it.
0:13:53 This is just a completely different kind of computer that has these characteristics that
0:13:57 are frankly more like a person, which is it’s right most of the time.
0:13:58 It occasionally gets things wrong.
0:14:00 When it gets things wrong, it’s able to self-critique.
0:14:04 And you have to kind of work with it the way that you work with a person.
0:14:08 And so you have to basically figure out as you use it, like you want to take advantage
0:14:09 of the fact that it’s creative.
0:14:13 And then you want to be tolerant of the fact that it’s not always correct, just like you’re
0:14:14 working with a person.
0:14:18 Now, having said that, when it makes easily avoidable mistakes, where it’s just like makes
0:14:21 boneheaded fact mistakes, you know, we call those hallucinations.
0:14:26 The latest systems are much, much, much better at not doing that.
0:14:27 They’re much more accurate.
0:14:31 And in particular, for anybody watching this, if you want to kind of see this in action, I’ll
0:14:31 just give an example.
0:14:38 If you buy the full version of ChatGPT, there’s a model called GPT Pro, GPT 5 Pro, which is the
0:14:38 latest one.
0:14:41 And then there’s something called Deep Research, which is a switch that you turn on.
0:14:45 And if you use GPT 5 Pro with Deep Research and you ask a question like that, like at this
0:14:50 point, I think it’s, I wouldn’t say it’s bulletproof, but like it’s really good as things
0:14:53 fastly grounded and literally you can watch it work and it’ll literally go out on the
0:14:57 internet and it’ll like check all the authoritative sources and it’ll, you know, it’ll go on
0:15:00 commerce.gov or whatever and check the voting records and verify that.
0:15:04 And so I think that problem is being ironed out, you know, kind of as we speak.
0:15:04 Yeah.
0:15:09 For people watching, listening who haven’t used it or not used it much, the thing you said
0:15:11 about good prompts is so key.
0:15:16 And that does differentiate, you know, the people really getting productive at it from not.
0:15:20 And one of the things that you and I have talked about is it is hilarious.
0:15:26 It can write, if you give it the right prompts, it can write stuff that is so funny.
0:15:29 And, and where does that come from?
0:15:31 How does it have the capacity to understand?
0:15:35 Because humor involves metaphors and sophistication and humanity.
0:15:37 How can, how could it, how can it do that?
0:15:39 Yeah.
0:15:42 So this gets to, this gets to this idea of how it’s trained.
0:15:47 So, so basically what these systems are is they’re basically the accumulation of human
0:15:51 knowledge over time, sort of, and by the way, most of the training data is just literally
0:15:52 the internet, right?
0:15:56 So one of the reasons that this is happening now and not 20 years ago is because the internet
0:16:00 finally got big enough, but just the web finally got big enough to have like all this information
0:16:00 in it, right?
0:16:05 And so if you go out on the internet today, you know, you can find, you know, all kinds of
0:16:08 material online that’s, you know, it’s, you can find like, you know, classic screenplays
0:16:11 from, you know, the gold age of cinema for a hundred years ago.
0:16:15 You know, you can find, you know, literally, you know, people joking with each other on
0:16:16 social media all day long.
0:16:20 You know, you can find, you know, professional comedians doing oral histories of, you know,
0:16:21 how they did great comedy.
0:16:25 So there’s just like, there’s incredible amounts of information that are online about comedy
0:16:25 and about what’s funny.
0:16:29 And then all of that information is in the training data.
0:16:31 So it’s all kind of fed into the AI during the training process.
0:16:36 And the AI basically processes it through like any other kind of data and comes out the other
0:16:40 grand and just basically is like, oh, you know, now that AI is a world-class expert in
0:16:40 humor, right?
0:16:44 And of course, you know, look, you could be an expert in humor and not actually be funny,
0:16:45 right?
0:16:47 And they’re, you know, they’re, I don’t know, probably professors of comedy or something like
0:16:48 that in colleges who aren’t very funny.
0:16:53 But like, it just, it knows so much about what humor is.
0:16:55 It knows so much about the pattern of jokes.
0:16:58 It knows so much about what make people laugh.
0:17:01 It has so many examples, you know, to be able to learn from.
0:17:05 And, you know, the professional comedians will tell you there are patterns to comedy,
0:17:05 right?
0:17:08 You know, there are, you know, I worked with a professional comedian once with something
0:17:10 and he said, you know, the key to it is specificity.
0:17:12 Like you need to get, you need to just like nail the reference.
0:17:15 You know, another comedian will say the key is, you know, timing or pacing or the callback
0:17:17 to the previous jump or whatever, you know, the punchline, whatever it is.
0:17:20 And so it just, it knows all that.
0:17:24 And then it’s just, you know, it’s now so powerful that it’s actually, yeah, I, yeah,
0:17:28 quite honestly, I find, especially at like two in the morning, I find these things
0:17:28 hysterical.
0:17:29 Yeah.
0:17:29 All right.
0:17:31 Just a minute left before we take a break.
0:17:35 What’s your advice to an individual who’s barely used it or hasn’t used it?
0:17:38 What’s your advice to them to sort of how to get started?
0:17:39 Yeah.
0:17:42 So, I mean, by far the best way to do it is just download it and use it.
0:17:45 And like I said, you know, there’s, there’s several good, you know, Elon’s got Brock, you
0:17:46 know, which is, which is now fantastic.
0:17:50 By the way, you know, it’s actually interesting how these things are getting built into products
0:17:50 now.
0:17:56 So, you know, the new versions of X, you know, formerly Twitter, actually, if you go to any
0:18:00 post on X, there’s a little Brock icon that looks like a little, a little black hole
0:18:01 icon on the upper right corner of the post.
0:18:06 And if you click on it, it actually calls up the Brock AI to explain the post to you.
0:18:06 Right.
0:18:10 And so like, it literally is like, it can explain to you that, you know, if there’s
0:18:12 some post on politics or something, you don’t understand what’s happening.
0:18:15 You just, you have lost the thread of the topic.
0:18:19 You just like bonk that button and you get in a dialogue with the AI, a little AI window
0:18:21 pops up and explains the post and you can ask it for more details.
0:18:23 And so it’s like built into that product.
0:18:25 Google’s actually built AI now into search.
0:18:29 And so now when you do searches, it has this thing called AI mode and you bonk on it.
0:18:33 And, you know, in addition to getting the 10 blue links from Google, you now get into
0:18:33 an AI dialogue.
0:18:37 And so you just start using those products or you just download one of these apps and
0:18:38 start using it.
0:18:41 And like I said, a really great question is like, okay, how do I use you?
0:18:42 Right.
0:18:44 Like, or you can teach, teach me works really well.
0:18:47 You can say, you know, teach me how to use you in the best way.
0:18:51 You know, teach, you know, teach, you know, teach me how to use you for my business, you
0:18:52 know, for this project.
0:18:56 And it’ll, you know, these things love to talk and it’ll, it’ll happily sit there and
0:18:58 chatter away and take you through it.
0:19:03 Yeah, it just, I, my, my sort of analog to the way you just said it is ask it for what
0:19:05 you want as specifically as possible.
0:19:08 Don’t hold back, be really specific and it will do what you ask.
0:19:09 All right.
0:19:11 More with Mark Andreessen.
0:19:11 That’s next up.
0:19:12 Stay tuned.
0:19:19 If you’re 64 years old or older, this is an important announcement.
0:19:24 The Department of Justice recently sued three major Medicare brokers for claiming they were
0:19:29 unbiased while allegedly pushing people into plans that got them the biggest kickbacks.
0:19:30 It’s true.
0:19:35 So many insurance agents, they just can’t be trusted, but you also cannot rely on the government
0:19:37 to give you the best information that you need either.
0:19:40 That’s why I want you to know about something called Chapter.
0:19:44 Chapter was started by people who went through all of this personally.
0:19:49 after their own parents were pushed into the wrong Medicare plan by an agent who was more
0:19:52 focused on commissions than on good care.
0:19:54 Chapter’s mission is very simple.
0:19:59 They want to give every American the honest, straightforward Medicare advice that they deserve.
0:20:02 And here’s what makes them different from everybody else.
0:20:07 They’re the only Medicare advisor that compares every plan nationwide, not just a few.
0:20:11 That saves their clients an average of $1,100 a year.
0:20:13 There’s really no reason not to call.
0:20:14 It’s quick.
0:20:14 It’s easy.
0:20:17 And they can review your options in under 20 minutes.
0:20:20 If you’re in the right plan already, they’ll let you know that.
0:20:23 But if there’s a better plan, they’ll help you make the switch.
0:20:26 This could be the most important call you make this year.
0:20:31 Dial pound 250 and say Chapter Medicare to get peace of mind.
0:20:35 Again, that’s pound 250 and say Chapter Medicare.
0:20:38 All right, welcome back.
0:20:40 We’re here with Mark Andreessen still.
0:20:47 Mark, are you of the school that says that the United States is in an existential struggle with China?
0:20:48 Do you subscribe to that point of view?
0:20:52 I was going to say, I hope that’s not true, right?
0:20:56 You know, I hope this is not going to walk all the way to the situation that we ended up in with the Soviet Union.
0:21:02 You know, like you, I grew up in an era, I’m sure you remember this.
0:21:08 Like, you know, growing up thinking there was a significant chance that, like, we’re all going to die from nuclear war.
0:21:10 And so I hope it doesn’t get back to that level of intensity.
0:21:19 But I do think there are a lot of historical parallels to what happened between the U.S. and the USSR in the 20th century, you know, happening right now.
0:21:24 And, you know, you have, you know, two hegemonic superpowers that both have, you know, visions.
0:21:29 You know, they both have visions of how society should be structured and how the sort of global political system should be structured.
0:21:33 And, you know, obviously I think America’s is better, you know, but they both have visions.
0:21:37 And, you know, they’re both working, you know, to that end.
0:21:39 And then they both have international strengths.
0:21:42 So this is militarily, technologically, economically, culturally.
0:21:46 And, you know, there is that kind of geopolitical fight happening.
0:21:56 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.
0:21:59 You know, I hope we stay, you know, in that mode.
0:22:03 But, like, it’s a sufficiently fraught situation, you know, that we certainly need.
0:22:06 And, you know, and by the way, have a national strategy for how to win that.
0:22:07 And we need to make sure that we do.
0:22:07 Right.
0:22:11 Do they have any one or two advantages over us in terms of AI?
0:22:13 Yeah, they do.
0:22:15 So they have all, they have two advantages.
0:22:18 And by the way, I should say, we have many advantages.
0:22:19 I’m very bullish on the U.S.
0:22:20 And, you know, I think we’re a better position.
0:22:23 I like, I wouldn’t trade places with them.
0:22:24 And we could talk about that.
0:22:26 But having said that, they do have strengths.
0:22:29 And in particular, they have two key strengths.
0:22:32 Number one is, they do have the advantages of a command economy.
0:22:41 And, you know, like, generally speaking, or 100%, like, I’m on the side of, like, you know, free markets and, you know, decentralization and, you know, having a dynamic economy.
0:22:45 And we have advantage, you know, we have much, you know, we have much better entrepreneurial ecosystem and so forth.
0:22:51 Having said that, they do have this advantage where, when their government decides that something’s a national priority, like, they just do it.
0:22:56 And by that, I mean, not only does the government do it, but they just tell the private sector, you do the following, right?
0:23:03 And so it’s sort of, you know, they have this, you know, thing the Soviets have where, you know, the entirety of society is able to, you know, go up against single missions.
0:23:06 You know, we’re just a lot more fractious than that.
0:23:10 And so, you know, we kind of navigate our way through this on our own way, but not, you know, we don’t have anywhere near that level of organization.
0:23:16 So that gives them the ability to execute against specific areas of focus in, you know, in arguably a superior way.
0:23:26 And then the other advantage that they have is, you know, we volunteer, we in the U.S. voluntarily deindustrialized, you know, starting, you know, 30, 40 years ago.
0:23:33 And, you know, that industrialization, you know, the making of physical things, and particularly the making of machines, you know, has moved substantially to China.
0:23:40 And, you know, the way that we think about machines now is that they’re basically, you know, they’re the hardware version of software, right?
0:23:41 They’re the embodied version of AI.
0:23:45 And so, you know, the car is not just steel and glass anymore.
0:23:47 It’s a, you know, it’s a robot on wheels.
0:23:50 You know, the drone isn’t just a toy anymore.
0:23:55 It’s a computer, you know, that flies through the air, you know, that navigates itself.
0:23:56 You know, robots are coming.
0:24:01 You know, we’re going to live in a world that’s just, like, completely washed with robots in the decades ahead.
0:24:08 And China is 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.
0:24:13 And, you know, then, you know, this administration and others have had visions of how to recasture that.
0:24:15 But, you know, we have a long way to go.
0:24:24 As the U.S. tries to become more of a manufacturing country, it would seem to me AI integrated into manufacturing is extremely powerful.
0:24:27 Are they ahead of us on that?
0:24:31 As you said, our biggest companies here are slow adapters of AI.
0:24:35 Are there big manufacturers now using AI more than we are?
0:24:39 Yeah, so I think Unleashed, we could do that faster and better.
0:24:47 Like, if we could manufacture in the U.S. the way that we used to 30 or 40 years ago, we could definitely do that faster for, you know, for a variety of reasons.
0:24:51 Including the fact that we have better software engineers, you know, we have a more flexible and dynamic economy.
0:24:53 You know, we could do that faster.
0:24:56 The big issue is just we have chosen to not be a manufacturing economy.
0:24:59 Like, we chose to move that offshore.
0:25:04 And, you know, for a very long time, we were very proud that we moved that offshore for, you know, for a variety of reasons.
0:25:11 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.
0:25:15 It’s just like, if you just, if you’re not manufacturing things, then you can’t do that at all.
0:25:15 Right?
0:25:17 Which is the situation that we’ve worked ourselves into.
0:25:24 And so, you know, just, you know, their car, just to pick one, their car industry is, like, moving, like, incredibly fast with this.
0:25:28 You know, and look, we have to, you know, we have our superstar companies.
0:25:32 We have Tesla, you know, in particular that’s world-class at this and, you know, still, you know, better than the Chinese today.
0:25:34 But, like, the Chinese are moving really fast.
0:25:38 And if you talk to people, we don’t have a lot of exposure to Chinese cars in the U.S.
0:25:42 because the terrain barriers are so high that they really are not cost-effective in the sell here.
0:25:48 But it’s, like, if you go to the Middle East and talk to just, like, normal affluent people, you know, they’re not driving Chinese cars by choice.
0:25:51 You know, not because they can’t afford a Mercedes, but because the Chinese cars are better.
0:25:56 And the Chinese cars are, like, full self-driving, electric, autonomous, you know, voice AI.
0:25:59 Like, they’re, like, state-of-the-art, they’re exactly what you’re talking about.
0:26:08 And we have just, you know, we still have car companies, but ex-Tesla, you know, mainly what they do is they assemble, you know, third-party, you know, parts that are coming from other places.
0:26:14 You know, the Chinese are just doing a much more specific, advanced level of unified hardware and AI manufacturing.
0:26:16 By the way, you see that in drones.
0:26:21 Like, virtually the entire global drone industry and virtually the entirety of the drone industry, you know, in terms of people using drones,
0:26:24 in the U.S., like, virtually 100% of those drones are made in China.
0:26:26 And, again, that’s not because we couldn’t make them.
0:26:29 It’s because we chose a set of policies that drove that industry offshore.
0:26:32 We better start making them.
0:26:33 I want to talk to you about Silicon Valley.
0:26:42 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.
0:26:47 There are great stories like yours of people who have been so successful.
0:26:52 But the influence over our culture, our government, our economy, it’s just, and the world is just so massive.
0:27:04 If someone like you understands engineering, markets, economics, technology, there was a long period where you had to live in Silicon Valley.
0:27:10 If you wanted to succeed and have the relationships and the interactions, is that still the case?
0:27:16 Is Silicon Valley still a place you have to physically be if you want to excel, someone with those skills?
0:27:20 Yeah, so I should start by saying I’m an import, right?
0:27:21 So I’m from out of town.
0:27:26 You know, I grew up in the rural Midwest, in Wisconsin, you know, kind of, you know, in a tundra.
0:27:29 And so, you know, I didn’t grow up here.
0:27:36 I, you know, I didn’t get to participate kind of in the heyday of, you know, back when we actually, by the way, it was called Silicon Valley because they originally made chips here, right?
0:27:39 You know, speaking of manufacturing, they first locked blocks, I stopped doing that.
0:27:42 You know, that’s not thoroughly illegal in California.
0:27:45 And so, you know, I wasn’t here for that.
0:27:46 I wasn’t here for the personal computer.
0:27:50 And so I’m an inheritor of, you know, the phenomenon that you’re describing that other people built.
0:27:52 What year did you show up?
0:27:54 Yeah, so I showed up in 1994.
0:28:02 And, you know, Silicon Valley is really dated, you know, it sort of based in the early 50s, you know, with Hewlett-Packard in particular, sort of the original company.
0:28:11 But the 90s is when so much of what we think of now in terms of consumer-facing, social media, internet, right?
0:28:12 I mean, that’s a pretty big dividing line.
0:28:17 So, yeah, you missed the Hewlett-Packard days, but you were there for the phase we’re in now, right?
0:28:23 Yeah, but I just bring it up because basically the history of Silicon Valley, it’s a sequence of waves, right?
0:28:34 And so it’s part of what makes it special is, you know, AI is like wave 9 or wave 10 of these, like, just major, you know, basic microprocessors and smartphones and, you know, kind of cloud and social and mobile.
0:28:38 So, like, all these, you know, kind of, you know, the PC, you know, kinds of all these waves of hits.
0:28:45 So, anyway, my point is, like, in the Valley, like, we’re the inheritor of a tradition and a system and a model that was built by other people.
0:28:50 And then to your question on geographic focus, this is a very interesting thing playing out right now.
0:28:51 So, a couple things.
0:28:59 So, one is, like, look, like I said, like, 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.
0:29:03 So, you don’t have to be in Silicon Valley to get access to the best technology.
0:29:04 Like, you can now get that from everywhere.
0:29:07 And that’s very important because that didn’t used to be the case.
0:29:19 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, like, maybe you don’t need to be in Silicon Valley proper.
0:29:24 But, like, you better start strongly considering if you’re not, there’s maybe three or four other places in the country where you can give it a shot.
0:29:27 But primarily the people that want to do that are coming to Silicon Valley.
0:29:36 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.
0:29:40 And we thought that, you know, virtual work and remote work and, you know, you could be able to start companies everywhere.
0:29:45 And you had all these kind of blows happening in places like Miami and also other places with lots of high-tech entrepreneurs.
0:29:48 And, you know, it felt like the whole thing was, you know, really distributing out.
0:29:57 AI basically has snapped everything right back into the 20-mile square radius around where I sit to just an incredible degree.
0:30:05 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.
0:30:13 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, you know, the Shanghai-Beijing axis of China.
0:30:16 You know, these are the two places.
0:30:22 And then you also say a very important thing, which is it’s just not happening elsewhere in the world.
0:30:25 You know, and there’s, you know, there’s kind of, you know, high-tech clusters in other places.
0:30:36 But, you know, if you’re a Sharp AI person and, you know, I’ll just pick on one London, like, you have already moved to California or you’re going to, you know, because they have just, you know, essentially decided to outlaw it.
0:30:38 The EU has decided to outlaw it.
0:30:45 And so, you know, people are being driven to the U.S. and to California, I think, in a way that’s even more concentrated than it was when I first got here.
0:30:46 All right, last question.
0:30:54 Name inventions in human history that have more benefited the lives of individuals than the iPhone.
0:31:00 Oh, well, I mean, you know, if you go far enough back, you know, electric lighting was a big deal.
0:31:02 You know, steam power was a big deal.
0:31:06 You know, obviously, antibiotics are the easy call.
0:31:13 I mean, you know, the Internet itself, you know, electricity, you know, it’s, you know, indoor plumbing.
0:31:15 So, you know, it’s hard to question those.
0:31:18 And people sometimes say, like, you know, you guys aren’t inventing important things.
0:31:20 Like, why are you inventing something as important as indoor plumbing?
0:31:22 And it’s like, well, that was a big one.
0:31:22 I can see.
0:31:24 But, like, you know, we did solve that problem.
0:31:31 I would, if you said, if you said, give up your iPhone or switch to an outhouse, I would switch to an outhouse.
0:31:33 I think, you know, I think there’s a lot to that.
0:31:38 And maybe the serious point underneath that, which I agree with that.
0:31:39 Oh, I was being serious.
0:31:39 I was being serious.
0:31:47 Well, no, so maybe, as you say, the generalization you can make from that is I think people maybe systematically underrate the importance of communication.
0:31:53 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.
0:31:56 Like, those two things, there’s something in the culture.
0:32:00 I was just saying, in Silicon Valley culture, there’s something where, like, those are, like, looked out on as less important.
0:32:05 And I actually think, to your point, like, they’re actually incredibly important and they’re foundational for everything else that people do.
0:32:10 I mean, you know, human connection and human learning is, you know, both of those are at the center of everything that we do.
0:32:12 And so, yeah, no, I would make that same trade.
0:32:15 Here’s my idea for a reality show.
0:32:24 You put someone like us in Cleveland for a week without their smartphone and give them a series of tasks which they would otherwise conduct with their smartphone.
0:32:25 Good luck.
0:32:29 By the way, I had relatives in the 70s who still had outhouses, right?
0:32:31 Yeah, it’s fine.
0:32:33 It passes 100%.
0:32:34 Well, it’s fine.
0:32:40 In Iowa, in January, you start to reconsider whether that’s fine in the middle of the night when it’s 40 below.
0:32:44 But, like, the past was not that long ago.
0:32:45 Yeah, no idea.
0:32:46 Yeah.
0:32:49 All right, Mark Andreessen, very grateful to you.
0:32:51 I scratched the surface.
0:32:57 I had a list of about 15,000 questions that AI winnowed down to me to 1,500, but we didn’t get to them all.
0:32:59 Very grateful to you, though, for making time.
0:33:05 And, again, so just not many people on the planet who understand this stuff as well as you do.
0:33:06 So grateful to you for sharing.
0:33:09 And hopefully we inspired a few people to learn how to use the latest technology.
0:33:10 Thank you.
0:33:11 Good.
0:33:11 Fantastic.
0:33:12 Thank you, Mark.
0:33:17 Thanks for listening to the A16Z Podcast.
0:33:22 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
0:33:25 We’ve got more great conversations coming your way.
0:33:26 See you next time.
0:33:36 This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product.
0:33:43 This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with A16Z.
0:33:51 Such advertisements, companies, and individuals are not endorsed by AH Capital Management, LLC, A16Z, or any of its affiliates.
0:33:57 Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.
0:00:16 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.
0:00:20 It occasionally gets things wrong. When it gets things wrong, it’s able to self-critique.
0:00:23 And you have to kind of work with it the way that you work with a person.
0:00:27 You want to take advantage of the fact that it’s creative, and then you want to be tolerant of the fact that it’s not always correct.
0:00:35 AI basically has snapped everything right back into the 20-mile-square radius around where I sit to just an incredible degree.
0:00:42 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.
0:00:49 There’s a bakery owner somewhere using the same AI as Google’s CEO, and according to Marc Andreessen, the bakery owner is winning.
0:00:55 The man who invented the modern web browser and built multi-billion dollar companies just revealed something remarkable.
0:00:57 AI is spreading backwards through society.
0:01:03 Individuals first, small businesses second, Fortune 500 companies third, government last.
0:01:07 The exact opposite of how computers evolve from mainframes to smartphones.
0:01:11 Marc says half a billion people already have the world’s most sophisticated AI on their phones.
0:01:16 So the question is, why are most using it to write emails while only some are using it to build empires?
0:01:22 Today, we’re sharing a conversation Marc Andreessen had with Marc Halperin on the show Next Up.
0:01:26 They talk about the specific prompts that transform AI into a world-class advisor,
0:01:31 why Silicon Valley just snapped back into a 20-mile radius after five years of dispersion,
0:01:35 and the uncomfortable truth about America’s AI race with China.
0:01:36 We hope you enjoy.
0:01:46 All right, next up, Marc Andreessen, innovator, creator, and damn successful businessman.
0:01:50 Early on, he invented the Mosaic Internet Browser, co-founded Netscape,
0:01:58 and since then, he has been the animating force and investor behind a lot of very successful companies,
0:02:01 including some at the multiple-billion-dollar level.
0:02:06 He co-founded his firm, Andreessen Horowitz, a general partner there,
0:02:12 and they do a lot of stuff about a lot of stuff, and he knows a lot about a lot.
0:02:13 Marc, welcome.
0:02:15 Thank you, Marc. It’s great to be here.
0:02:16 Really happy to have you.
0:02:21 So much about AI I want to talk to you about, so we’re going to spend a lot of the time on that.
0:02:32 First off, it’s tempting to say right now, and when I think about AI, I think about where are we now and where are we going.
0:02:37 It’s tempting to say it’s between, like, really smart, highly educated people who are adapting to it
0:02:42 and then people who just don’t have the capacity to do that in their jobs easily.
0:02:48 But what I’m finding is at people who do what I do, people who are well-educated, very privileged,
0:02:50 there’s a have-nots there.
0:02:52 I’m a baby using it.
0:02:58 I’m not using it very sophisticatedly very often, but I am Einstein compared to some of my counterparts.
0:03:01 And I’m wondering, is that how you see it?
0:03:05 And what do you think differentiates those who understand how powerful it is even now
0:03:08 versus those who seem oblivious to it?
0:03:12 Yeah, so I think there’s kind of a fake story, and then there’s a real story.
0:03:16 So the fake story is kind of the classic Marxist story, which is, you know,
0:03:19 oh, only the rich people have it, only the fancy people have it,
0:03:23 the big tech companies have it, everybody else is kind of going to be left out in the cold.
0:03:25 And that’s not actually what’s happening.
0:03:31 And there’s a lot of data on this now that has been released by these companies to justify what I’m about to say.
0:03:35 So the real story is this is already probably the most democratic, you know,
0:03:39 small-D technology of all time in the sense of the very best AI in the world
0:03:42 is fully available on the apps that anybody can download.
0:03:48 And, you know, take your pick, ChachiPT, Klau, Gemini, Grok, you know, Mistral, any of these.
0:03:50 By the way, DeepSeek, China.
0:03:55 You download any of these apps, you’re getting state-of-the-art, like, the full, most sophisticated,
0:03:57 powerful AI capability in the world.
0:04:01 And, you know, the number of people already who downloaded these apps is north of a half billion
0:04:03 on its way to a billion.
0:04:08 And individual people are figuring out, you know, basically how to appropriate this in their lives.
0:04:11 And what you see in the data is there’s, you know, maybe what you’d expect,
0:04:14 which is there are a slice of people who just use these new systems all the time,
0:04:16 like literally all day for everything.
0:04:21 And, you know, in a lot of cases, they’re reporting that they’re getting enormous benefits from that.
0:04:23 And then there’s a lot of people who are experimenting and trying to figure it out.
0:04:26 And then there are people who are just, you know, not, you know,
0:04:28 for whatever reason, not interested or not engaged.
0:04:32 But I would say it’s incredible out of the gate how distributed this technology already is.
0:04:36 And then I could just say, like, I don’t have, you know, with all my resources
0:04:39 and with all my connections, I don’t have access to a better AI
0:04:41 than the one that you just downloaded off the App Store.
0:04:44 And so I think this is actually, like, just an incredible story
0:04:47 of the most advanced technology in the world being available to everybody right out of the gate.
0:04:51 You got to get people to use it to take advantage of it, right?
0:04:55 So I’ve got a friend who’s drafted a book and took it to his agent.
0:04:58 And the agent said, it’s 140,000 words.
0:04:59 You got to cut it down to 70,000.
0:05:02 And I said, if you try to do that by hand,
0:05:05 even if you hire someone, it’s going to take you months.
0:05:06 I can do it in an hour.
0:05:09 And I can say to AI, don’t change the style.
0:05:11 Don’t change the tone.
0:05:14 Don’t cut anything that, you know, ruins the story.
0:05:17 And he said, that’s immoral.
0:05:22 The publisher will be mad that I did it that way.
0:05:22 It’s not right.
0:05:24 How should I answer that person?
0:05:29 Yeah, so the exact same arguments, you know, emerged, you know, years ago with the introduction
0:05:30 of computers, right?
0:05:35 I actually just, I’ve been watching a lot of, you know, old science fiction movies with my
0:05:35 kid.
0:05:39 And, you know, there’s this famous science fiction movie, Tron, from 1982, you know, that
0:05:41 had the first, kind of the first real computer graphics movies.
0:05:44 And it was disqualified for an Oscar for special effects because it used computers.
0:05:46 Right?
0:05:49 And so there’s this kind of long tradition of, like, whatever the new tool is, it’s
0:05:51 sort of illegitimate, and there must be something wrong with it.
0:05:54 In this particular case, I mean, there’s no doubt there are people who feel the way that
0:05:55 your friend feels.
0:06:02 That issue was actually litigated in the last Hollywood strikes, in the movie, on the film
0:06:04 and TV side of the creative profession.
0:06:04 Yeah.
0:06:08 The last round of strikes actually, it’s actually funny, it started as streaming strikes, and
0:06:10 then AI hit, and it became AI strikes.
0:06:15 But the settlement with the studios, actually, with the unions was that, the following, which
0:06:18 is, if you’re a writer and you use AI, that’s totally fine.
0:06:22 What’s not allowed is for the studio to basically use the AI and then claim it was a writer.
0:06:28 But basically, what the unions and studios in Hollywood decided was, it’s another tool, it’s
0:06:32 like the word processor, it’s like the personal computer, it’s like, you know, it’s like using
0:06:34 a printer instead of writing out a manuscript by hand.
0:06:39 And so I think there are people who feel like your friend does, but I think the world is already
0:06:41 adapting very fast to using it.
0:06:45 And frankly, one of those reasons you probably pointed out to your friend is, like,
0:06:48 I don’t even know that anybody could tell anymore, right?
0:06:52 And so, you know, if you’re going to have a moral prohibition on something that people can
0:06:55 just do and nobody knows about, like, is that, you know, is that really going to work?
0:06:59 And so I think those sort of self-imposed barriers are probably going to collapse quite quickly.
0:07:00 I hope so.
0:07:07 Fortune put out a list of the top American companies using AI.
0:07:11 Alphabet, Visa, JPMorgan Chase, top three.
0:07:15 We talked about just now on an individual level.
0:07:20 If you were the CEO of a company or advising a CEO, how important is it to be on that list?
0:07:24 In other words, how important is it to get your company to adapt, whether it’s for internal
0:07:25 or consumer-facing?
0:07:27 How important is it right now?
0:07:32 Yeah, so this goes back to actually where we started, which is, and in fairness, the
0:07:37 old model of adapting actually computers when computers came out, the old model was the
0:07:40 largest institutions get technology first and then everybody else gets it later.
0:07:44 And so, you know, the way the computer rolled out was the government actually got mainframe
0:07:46 computers first starting in the 1940s.
0:07:50 And then big companies got computers in the mainframes in the 1950s, 1960s.
0:07:54 Small companies started to get computers, what were called minicomputers at the time in the
0:07:54 1970s.
0:07:59 And then, you know, we as individuals only got, you know, PCs in the 1980s.
0:08:03 And so it took 40 years for basically technology to cascade down from the largest organizations
0:08:05 in the world to small businesses and to the individual.
0:08:13 This technology, AI, is going the opposite, you know, which is like I said, the most sophisticated
0:08:15 capabilities are available on the consumer app today.
0:08:20 And then what we’re finding is consumers are adapting the fastest, just individuals in their
0:08:20 lives.
0:08:25 Then small businesses are then adopted right after that because, you know, a small business
0:08:27 typically is just, you know, a person who’s, you know, making decisions for their own business.
0:08:30 Very, very easy to do new things.
0:08:33 Big companies are then following small companies.
0:08:37 And so, you know, the companies on that list, some of, you know, obviously some of them are
0:08:40 doing interesting things, but in general, big companies right now are pretty tied up in knots
0:08:44 internally, kind of in all their processes and in all their legacy systems and all their, you
0:08:48 know, organization and training and, but their unions and like all the other issues they have
0:08:52 to deal with, you know, they’re, they’re actually relatively slow to adopt compared to individuals
0:08:52 and small businesses.
0:08:55 And then, and then government is, is the late adopter, right?
0:08:58 And so governments, of course, are already trying to figure out, you know, kind of how to adapt
0:09:02 to this technology, but they’re not adopting it very fast because they can’t because of all
0:09:03 their rules and systems and bureaucracy.
0:09:07 And so there’s been a real inversion of how technology moves through our society.
0:09:10 That’s really become, you know, AI is becoming a case study for.
0:09:15 And so the answer to your question is, I think big company CEOs and, you know, many of them
0:09:19 are, are, are, are doing this, but I think they really have to force the issue on this
0:09:22 inside their, their companies because the, you know, these big companies are just such now
0:09:27 giant bureaucracies with so many rules that like by, by default, they’ll smother new ideas.
0:09:31 And so it’s a, it’s a real active leadership to, you know, to get on a list like that and be
0:09:34 able to, you know, actually say kind of with pride, like we’re on the leading edge.
0:09:39 So if your friend owned a bakery and he said, Mark, I want you to come in and help me figure
0:09:45 out how to use AI, well, how could a, someone owns a single storefront bakery, use it now?
0:09:45 Yeah.
0:09:49 I mean, so there’s, I mean, there’s, you know, there’s dozens of ways, you know, it obviously
0:09:51 depends on what your business goals are.
0:09:53 They’re, they’re, they’re baker dozens of ways.
0:09:55 They’re, they’re, exactly.
0:09:59 And so, yeah, I mean, look, the first thing you can do is just say, look, you know, review,
0:10:02 you know, do a performance review for me, like just feed in, you know, here’s my, here’s
0:10:03 my staffing schedule.
0:10:05 You know, what, what do you think of it?
0:10:06 Give me a critique of it.
0:10:09 You know, here’s the last, you know, a hundred emails we’ve got from customers.
0:10:12 One of the, one of the, one of the patterns of that, you know, here’s the copy for the
0:10:15 ad that we’re going to place in the local newspaper, you know, put up on Facebook or whatever, like,
0:10:17 you know, what, what, you know, what do you think of this?
0:10:19 You know, let it, let it do it, let it do a performance assessment.
0:10:22 A lot of people find it very effective for personal coaching.
0:10:26 And so, you know, the owner might use it that way or might, you know, ask the employees
0:10:27 to use it that way.
0:10:31 And then I think where the power really kicks in is, okay, you’re a, you’re a, you know,
0:10:33 you’re a small business owner, you’ve got one bakery, now you want to have
0:10:34 two bakeries, right?
0:10:37 And you want to have a brand and then maybe if that works, you’re going to have five and
0:10:40 then 50 and then 500, and then you’re going to have, you know, packaged products going to
0:10:41 supermarkets and so forth.
0:10:44 And then, and then there you basically turn the AI into a thought partner, right?
0:10:47 And you basically say, okay, what, you know, what are the best ways to expand from a single,
0:10:51 you know, outlet to, you know, to multiple and to turn, you know, turn this into a larger
0:10:51 business.
0:10:55 And, you know, the AI, you know, it’s been, you know, because it’s been trained on, you know,
0:10:59 some large percentage of, of the total amount of human knowledge, like it has within
0:11:03 all the information on how, you know, Ray Kroc turned McDonald’s from, you know, a single
0:11:06 restaurant in the McDonald’s and how all these other, you know, entrepreneurs go through or
0:11:07 actually did this.
0:11:10 And so it can, you know, explain with you and help you, you know, figure out how to do this
0:11:10 for your own business.
0:11:14 And then, you know, the thing that you get into as you use it is basically, it’s just
0:11:17 like, wow, it’s like having the world’s best coach, mentor, therapist, right?
0:11:19 Advisor, you know, board member.
0:11:22 But it’s like infinitely patient.
0:11:25 And so it’s like, it’s happy to have the conversation.
0:11:27 It’s happy to have the conversation 50 times.
0:11:30 It’s happy if you admit your insecurities, it’ll coach you through them.
0:11:33 You know, it’s happy if you run wild speculations that don’t make any sense.
0:11:35 It’s happy to do all that at four in the morning.
0:11:39 And so the people who are using it a lot are finding it’s, you know, it actually turns out
0:11:41 to be very supportive in their real life.
0:11:45 Could you say, here’s the recipe for our best-selling cinnamon rolls?
0:11:46 How can I make it better?
0:11:47 Would that, would that?
0:11:48 Yeah, a hundred percent.
0:11:53 Yeah, you can say, you can say, and by the way, part of the art of AI, right, is what
0:11:54 questions to ask it, right?
0:11:57 Because, you know, it turns out, you know, it turns, it can answer, you know, many, many
0:11:57 different questions.
0:12:00 So you have to, you have to actually get creative at this.
0:12:00 Yeah.
0:12:03 And so you can say, like, here’s my current recipe, you know, how might I improve it?
0:12:06 You can also say, you know, what’s the best cinnamon roll recipe in the world?
0:12:08 We’re backers from that.
0:12:11 And then you could also say, look, I want to make the best run in the world, but I need to do
0:12:12 it at an intense price.
0:12:15 You know, what, you know, what, you know, what are the ways to cost optimize?
0:12:18 All right, so the other, yeah, go ahead.
0:12:20 By the way, the other thing you can ask it is you can ask it, what questions should
0:12:21 I be asking?
0:12:22 Right?
0:12:24 And so you could plug in, I run a bakery, dot, dot, dot.
0:12:25 What questions should I be asking?
0:12:29 And you’ll find it, it’s actually a thought partner in helping you figure out what questions
0:12:29 to ask.
0:12:30 Right, brilliant.
0:12:34 So the other day I said, I want to know every Republican who voted against any of the articles
0:12:36 of impeachment against Bill Clinton.
0:12:38 Give me the list of every Republican.
0:12:43 And it came back and it listed some Democrats and mixed in there.
0:12:44 And it said they were Democrats.
0:12:47 And I said back, I only want Republicans.
0:12:51 And it said, oh, sorry, I inadvertently included Democrats.
0:12:55 Now, I could understand a human being, a junior researcher doing that.
0:13:01 But how could AI make a mistake, have it pointed out to it, and say, oh, yeah, how could that
0:13:02 be in the model?
0:13:08 Yeah, so this gets technical, and I’d be delighted to get deeply into the technical details.
0:13:09 I’ll try to resist.
0:13:11 It’s a new kind of computer.
0:13:15 And the way to think about it is computers up until now have been what you might call
0:13:19 like hyperliteral, right, where computers up until now, like they do math really fast,
0:13:22 but like they do the same thing every single time.
0:13:24 They exhibit no creativity whatsoever.
0:13:28 And if you expect them to exhibit creativity, like, you know, they just can’t do it.
0:13:30 And then if they make a mistake, it’s because the human programmer made a mistake.
0:13:34 And that has made computers, you know, super useful for running like, you know, large math
0:13:37 exercises, you know, doing a lot of things that computers do.
0:13:39 But of course, computers have never been creative, right?
0:13:44 Computers have never been able to write you poetry or work with you on your cinnamon bun
0:13:44 recipe.
0:13:46 Like, it’s just never even been a thing that we can think about.
0:13:49 So it’s never had kind of that human element of creativity to it.
0:13:53 This is just a completely different kind of computer that has these characteristics that
0:13:57 are frankly more like a person, which is it’s right most of the time.
0:13:58 It occasionally gets things wrong.
0:14:00 When it gets things wrong, it’s able to self-critique.
0:14:04 And you have to kind of work with it the way that you work with a person.
0:14:08 And so you have to basically figure out as you use it, like you want to take advantage
0:14:09 of the fact that it’s creative.
0:14:13 And then you want to be tolerant of the fact that it’s not always correct, just like you’re
0:14:14 working with a person.
0:14:18 Now, having said that, when it makes easily avoidable mistakes, where it’s just like makes
0:14:21 boneheaded fact mistakes, you know, we call those hallucinations.
0:14:26 The latest systems are much, much, much better at not doing that.
0:14:27 They’re much more accurate.
0:14:31 And in particular, for anybody watching this, if you want to kind of see this in action, I’ll
0:14:31 just give an example.
0:14:38 If you buy the full version of ChatGPT, there’s a model called GPT Pro, GPT 5 Pro, which is the
0:14:38 latest one.
0:14:41 And then there’s something called Deep Research, which is a switch that you turn on.
0:14:45 And if you use GPT 5 Pro with Deep Research and you ask a question like that, like at this
0:14:50 point, I think it’s, I wouldn’t say it’s bulletproof, but like it’s really good as things
0:14:53 fastly grounded and literally you can watch it work and it’ll literally go out on the
0:14:57 internet and it’ll like check all the authoritative sources and it’ll, you know, it’ll go on
0:15:00 commerce.gov or whatever and check the voting records and verify that.
0:15:04 And so I think that problem is being ironed out, you know, kind of as we speak.
0:15:04 Yeah.
0:15:09 For people watching, listening who haven’t used it or not used it much, the thing you said
0:15:11 about good prompts is so key.
0:15:16 And that does differentiate, you know, the people really getting productive at it from not.
0:15:20 And one of the things that you and I have talked about is it is hilarious.
0:15:26 It can write, if you give it the right prompts, it can write stuff that is so funny.
0:15:29 And, and where does that come from?
0:15:31 How does it have the capacity to understand?
0:15:35 Because humor involves metaphors and sophistication and humanity.
0:15:37 How can, how could it, how can it do that?
0:15:39 Yeah.
0:15:42 So this gets to, this gets to this idea of how it’s trained.
0:15:47 So, so basically what these systems are is they’re basically the accumulation of human
0:15:51 knowledge over time, sort of, and by the way, most of the training data is just literally
0:15:52 the internet, right?
0:15:56 So one of the reasons that this is happening now and not 20 years ago is because the internet
0:16:00 finally got big enough, but just the web finally got big enough to have like all this information
0:16:00 in it, right?
0:16:05 And so if you go out on the internet today, you know, you can find, you know, all kinds of
0:16:08 material online that’s, you know, it’s, you can find like, you know, classic screenplays
0:16:11 from, you know, the gold age of cinema for a hundred years ago.
0:16:15 You know, you can find, you know, literally, you know, people joking with each other on
0:16:16 social media all day long.
0:16:20 You know, you can find, you know, professional comedians doing oral histories of, you know,
0:16:21 how they did great comedy.
0:16:25 So there’s just like, there’s incredible amounts of information that are online about comedy
0:16:25 and about what’s funny.
0:16:29 And then all of that information is in the training data.
0:16:31 So it’s all kind of fed into the AI during the training process.
0:16:36 And the AI basically processes it through like any other kind of data and comes out the other
0:16:40 grand and just basically is like, oh, you know, now that AI is a world-class expert in
0:16:40 humor, right?
0:16:44 And of course, you know, look, you could be an expert in humor and not actually be funny,
0:16:45 right?
0:16:47 And they’re, you know, they’re, I don’t know, probably professors of comedy or something like
0:16:48 that in colleges who aren’t very funny.
0:16:53 But like, it just, it knows so much about what humor is.
0:16:55 It knows so much about the pattern of jokes.
0:16:58 It knows so much about what make people laugh.
0:17:01 It has so many examples, you know, to be able to learn from.
0:17:05 And, you know, the professional comedians will tell you there are patterns to comedy,
0:17:05 right?
0:17:08 You know, there are, you know, I worked with a professional comedian once with something
0:17:10 and he said, you know, the key to it is specificity.
0:17:12 Like you need to get, you need to just like nail the reference.
0:17:15 You know, another comedian will say the key is, you know, timing or pacing or the callback
0:17:17 to the previous jump or whatever, you know, the punchline, whatever it is.
0:17:20 And so it just, it knows all that.
0:17:24 And then it’s just, you know, it’s now so powerful that it’s actually, yeah, I, yeah,
0:17:28 quite honestly, I find, especially at like two in the morning, I find these things
0:17:28 hysterical.
0:17:29 Yeah.
0:17:29 All right.
0:17:31 Just a minute left before we take a break.
0:17:35 What’s your advice to an individual who’s barely used it or hasn’t used it?
0:17:38 What’s your advice to them to sort of how to get started?
0:17:39 Yeah.
0:17:42 So, I mean, by far the best way to do it is just download it and use it.
0:17:45 And like I said, you know, there’s, there’s several good, you know, Elon’s got Brock, you
0:17:46 know, which is, which is now fantastic.
0:17:50 By the way, you know, it’s actually interesting how these things are getting built into products
0:17:50 now.
0:17:56 So, you know, the new versions of X, you know, formerly Twitter, actually, if you go to any
0:18:00 post on X, there’s a little Brock icon that looks like a little, a little black hole
0:18:01 icon on the upper right corner of the post.
0:18:06 And if you click on it, it actually calls up the Brock AI to explain the post to you.
0:18:06 Right.
0:18:10 And so like, it literally is like, it can explain to you that, you know, if there’s
0:18:12 some post on politics or something, you don’t understand what’s happening.
0:18:15 You just, you have lost the thread of the topic.
0:18:19 You just like bonk that button and you get in a dialogue with the AI, a little AI window
0:18:21 pops up and explains the post and you can ask it for more details.
0:18:23 And so it’s like built into that product.
0:18:25 Google’s actually built AI now into search.
0:18:29 And so now when you do searches, it has this thing called AI mode and you bonk on it.
0:18:33 And, you know, in addition to getting the 10 blue links from Google, you now get into
0:18:33 an AI dialogue.
0:18:37 And so you just start using those products or you just download one of these apps and
0:18:38 start using it.
0:18:41 And like I said, a really great question is like, okay, how do I use you?
0:18:42 Right.
0:18:44 Like, or you can teach, teach me works really well.
0:18:47 You can say, you know, teach me how to use you in the best way.
0:18:51 You know, teach, you know, teach, you know, teach me how to use you for my business, you
0:18:52 know, for this project.
0:18:56 And it’ll, you know, these things love to talk and it’ll, it’ll happily sit there and
0:18:58 chatter away and take you through it.
0:19:03 Yeah, it just, I, my, my sort of analog to the way you just said it is ask it for what
0:19:05 you want as specifically as possible.
0:19:08 Don’t hold back, be really specific and it will do what you ask.
0:19:09 All right.
0:19:11 More with Mark Andreessen.
0:19:11 That’s next up.
0:19:12 Stay tuned.
0:19:19 If you’re 64 years old or older, this is an important announcement.
0:19:24 The Department of Justice recently sued three major Medicare brokers for claiming they were
0:19:29 unbiased while allegedly pushing people into plans that got them the biggest kickbacks.
0:19:30 It’s true.
0:19:35 So many insurance agents, they just can’t be trusted, but you also cannot rely on the government
0:19:37 to give you the best information that you need either.
0:19:40 That’s why I want you to know about something called Chapter.
0:19:44 Chapter was started by people who went through all of this personally.
0:19:49 after their own parents were pushed into the wrong Medicare plan by an agent who was more
0:19:52 focused on commissions than on good care.
0:19:54 Chapter’s mission is very simple.
0:19:59 They want to give every American the honest, straightforward Medicare advice that they deserve.
0:20:02 And here’s what makes them different from everybody else.
0:20:07 They’re the only Medicare advisor that compares every plan nationwide, not just a few.
0:20:11 That saves their clients an average of $1,100 a year.
0:20:13 There’s really no reason not to call.
0:20:14 It’s quick.
0:20:14 It’s easy.
0:20:17 And they can review your options in under 20 minutes.
0:20:20 If you’re in the right plan already, they’ll let you know that.
0:20:23 But if there’s a better plan, they’ll help you make the switch.
0:20:26 This could be the most important call you make this year.
0:20:31 Dial pound 250 and say Chapter Medicare to get peace of mind.
0:20:35 Again, that’s pound 250 and say Chapter Medicare.
0:20:38 All right, welcome back.
0:20:40 We’re here with Mark Andreessen still.
0:20:47 Mark, are you of the school that says that the United States is in an existential struggle with China?
0:20:48 Do you subscribe to that point of view?
0:20:52 I was going to say, I hope that’s not true, right?
0:20:56 You know, I hope this is not going to walk all the way to the situation that we ended up in with the Soviet Union.
0:21:02 You know, like you, I grew up in an era, I’m sure you remember this.
0:21:08 Like, you know, growing up thinking there was a significant chance that, like, we’re all going to die from nuclear war.
0:21:10 And so I hope it doesn’t get back to that level of intensity.
0:21:19 But I do think there are a lot of historical parallels to what happened between the U.S. and the USSR in the 20th century, you know, happening right now.
0:21:24 And, you know, you have, you know, two hegemonic superpowers that both have, you know, visions.
0:21:29 You know, they both have visions of how society should be structured and how the sort of global political system should be structured.
0:21:33 And, you know, obviously I think America’s is better, you know, but they both have visions.
0:21:37 And, you know, they’re both working, you know, to that end.
0:21:39 And then they both have international strengths.
0:21:42 So this is militarily, technologically, economically, culturally.
0:21:46 And, you know, there is that kind of geopolitical fight happening.
0:21:56 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.
0:21:59 You know, I hope we stay, you know, in that mode.
0:22:03 But, like, it’s a sufficiently fraught situation, you know, that we certainly need.
0:22:06 And, you know, and by the way, have a national strategy for how to win that.
0:22:07 And we need to make sure that we do.
0:22:07 Right.
0:22:11 Do they have any one or two advantages over us in terms of AI?
0:22:13 Yeah, they do.
0:22:15 So they have all, they have two advantages.
0:22:18 And by the way, I should say, we have many advantages.
0:22:19 I’m very bullish on the U.S.
0:22:20 And, you know, I think we’re a better position.
0:22:23 I like, I wouldn’t trade places with them.
0:22:24 And we could talk about that.
0:22:26 But having said that, they do have strengths.
0:22:29 And in particular, they have two key strengths.
0:22:32 Number one is, they do have the advantages of a command economy.
0:22:41 And, you know, like, generally speaking, or 100%, like, I’m on the side of, like, you know, free markets and, you know, decentralization and, you know, having a dynamic economy.
0:22:45 And we have advantage, you know, we have much, you know, we have much better entrepreneurial ecosystem and so forth.
0:22:51 Having said that, they do have this advantage where, when their government decides that something’s a national priority, like, they just do it.
0:22:56 And by that, I mean, not only does the government do it, but they just tell the private sector, you do the following, right?
0:23:03 And so it’s sort of, you know, they have this, you know, thing the Soviets have where, you know, the entirety of society is able to, you know, go up against single missions.
0:23:06 You know, we’re just a lot more fractious than that.
0:23:10 And so, you know, we kind of navigate our way through this on our own way, but not, you know, we don’t have anywhere near that level of organization.
0:23:16 So that gives them the ability to execute against specific areas of focus in, you know, in arguably a superior way.
0:23:26 And then the other advantage that they have is, you know, we volunteer, we in the U.S. voluntarily deindustrialized, you know, starting, you know, 30, 40 years ago.
0:23:33 And, you know, that industrialization, you know, the making of physical things, and particularly the making of machines, you know, has moved substantially to China.
0:23:40 And, you know, the way that we think about machines now is that they’re basically, you know, they’re the hardware version of software, right?
0:23:41 They’re the embodied version of AI.
0:23:45 And so, you know, the car is not just steel and glass anymore.
0:23:47 It’s a, you know, it’s a robot on wheels.
0:23:50 You know, the drone isn’t just a toy anymore.
0:23:55 It’s a computer, you know, that flies through the air, you know, that navigates itself.
0:23:56 You know, robots are coming.
0:24:01 You know, we’re going to live in a world that’s just, like, completely washed with robots in the decades ahead.
0:24:08 And China is 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.
0:24:13 And, you know, then, you know, this administration and others have had visions of how to recasture that.
0:24:15 But, you know, we have a long way to go.
0:24:24 As the U.S. tries to become more of a manufacturing country, it would seem to me AI integrated into manufacturing is extremely powerful.
0:24:27 Are they ahead of us on that?
0:24:31 As you said, our biggest companies here are slow adapters of AI.
0:24:35 Are there big manufacturers now using AI more than we are?
0:24:39 Yeah, so I think Unleashed, we could do that faster and better.
0:24:47 Like, if we could manufacture in the U.S. the way that we used to 30 or 40 years ago, we could definitely do that faster for, you know, for a variety of reasons.
0:24:51 Including the fact that we have better software engineers, you know, we have a more flexible and dynamic economy.
0:24:53 You know, we could do that faster.
0:24:56 The big issue is just we have chosen to not be a manufacturing economy.
0:24:59 Like, we chose to move that offshore.
0:25:04 And, you know, for a very long time, we were very proud that we moved that offshore for, you know, for a variety of reasons.
0:25:11 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.
0:25:15 It’s just like, if you just, if you’re not manufacturing things, then you can’t do that at all.
0:25:15 Right?
0:25:17 Which is the situation that we’ve worked ourselves into.
0:25:24 And so, you know, just, you know, their car, just to pick one, their car industry is, like, moving, like, incredibly fast with this.
0:25:28 You know, and look, we have to, you know, we have our superstar companies.
0:25:32 We have Tesla, you know, in particular that’s world-class at this and, you know, still, you know, better than the Chinese today.
0:25:34 But, like, the Chinese are moving really fast.
0:25:38 And if you talk to people, we don’t have a lot of exposure to Chinese cars in the U.S.
0:25:42 because the terrain barriers are so high that they really are not cost-effective in the sell here.
0:25:48 But it’s, like, if you go to the Middle East and talk to just, like, normal affluent people, you know, they’re not driving Chinese cars by choice.
0:25:51 You know, not because they can’t afford a Mercedes, but because the Chinese cars are better.
0:25:56 And the Chinese cars are, like, full self-driving, electric, autonomous, you know, voice AI.
0:25:59 Like, they’re, like, state-of-the-art, they’re exactly what you’re talking about.
0:26:08 And we have just, you know, we still have car companies, but ex-Tesla, you know, mainly what they do is they assemble, you know, third-party, you know, parts that are coming from other places.
0:26:14 You know, the Chinese are just doing a much more specific, advanced level of unified hardware and AI manufacturing.
0:26:16 By the way, you see that in drones.
0:26:21 Like, virtually the entire global drone industry and virtually the entirety of the drone industry, you know, in terms of people using drones,
0:26:24 in the U.S., like, virtually 100% of those drones are made in China.
0:26:26 And, again, that’s not because we couldn’t make them.
0:26:29 It’s because we chose a set of policies that drove that industry offshore.
0:26:32 We better start making them.
0:26:33 I want to talk to you about Silicon Valley.
0:26:42 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.
0:26:47 There are great stories like yours of people who have been so successful.
0:26:52 But the influence over our culture, our government, our economy, it’s just, and the world is just so massive.
0:27:04 If someone like you understands engineering, markets, economics, technology, there was a long period where you had to live in Silicon Valley.
0:27:10 If you wanted to succeed and have the relationships and the interactions, is that still the case?
0:27:16 Is Silicon Valley still a place you have to physically be if you want to excel, someone with those skills?
0:27:20 Yeah, so I should start by saying I’m an import, right?
0:27:21 So I’m from out of town.
0:27:26 You know, I grew up in the rural Midwest, in Wisconsin, you know, kind of, you know, in a tundra.
0:27:29 And so, you know, I didn’t grow up here.
0:27:36 I, you know, I didn’t get to participate kind of in the heyday of, you know, back when we actually, by the way, it was called Silicon Valley because they originally made chips here, right?
0:27:39 You know, speaking of manufacturing, they first locked blocks, I stopped doing that.
0:27:42 You know, that’s not thoroughly illegal in California.
0:27:45 And so, you know, I wasn’t here for that.
0:27:46 I wasn’t here for the personal computer.
0:27:50 And so I’m an inheritor of, you know, the phenomenon that you’re describing that other people built.
0:27:52 What year did you show up?
0:27:54 Yeah, so I showed up in 1994.
0:28:02 And, you know, Silicon Valley is really dated, you know, it sort of based in the early 50s, you know, with Hewlett-Packard in particular, sort of the original company.
0:28:11 But the 90s is when so much of what we think of now in terms of consumer-facing, social media, internet, right?
0:28:12 I mean, that’s a pretty big dividing line.
0:28:17 So, yeah, you missed the Hewlett-Packard days, but you were there for the phase we’re in now, right?
0:28:23 Yeah, but I just bring it up because basically the history of Silicon Valley, it’s a sequence of waves, right?
0:28:34 And so it’s part of what makes it special is, you know, AI is like wave 9 or wave 10 of these, like, just major, you know, basic microprocessors and smartphones and, you know, kind of cloud and social and mobile.
0:28:38 So, like, all these, you know, kind of, you know, the PC, you know, kinds of all these waves of hits.
0:28:45 So, anyway, my point is, like, in the Valley, like, we’re the inheritor of a tradition and a system and a model that was built by other people.
0:28:50 And then to your question on geographic focus, this is a very interesting thing playing out right now.
0:28:51 So, a couple things.
0:28:59 So, one is, like, look, like I said, like, 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.
0:29:03 So, you don’t have to be in Silicon Valley to get access to the best technology.
0:29:04 Like, you can now get that from everywhere.
0:29:07 And that’s very important because that didn’t used to be the case.
0:29:19 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, like, maybe you don’t need to be in Silicon Valley proper.
0:29:24 But, like, you better start strongly considering if you’re not, there’s maybe three or four other places in the country where you can give it a shot.
0:29:27 But primarily the people that want to do that are coming to Silicon Valley.
0:29:36 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.
0:29:40 And we thought that, you know, virtual work and remote work and, you know, you could be able to start companies everywhere.
0:29:45 And you had all these kind of blows happening in places like Miami and also other places with lots of high-tech entrepreneurs.
0:29:48 And, you know, it felt like the whole thing was, you know, really distributing out.
0:29:57 AI basically has snapped everything right back into the 20-mile square radius around where I sit to just an incredible degree.
0:30:05 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.
0:30:13 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, you know, the Shanghai-Beijing axis of China.
0:30:16 You know, these are the two places.
0:30:22 And then you also say a very important thing, which is it’s just not happening elsewhere in the world.
0:30:25 You know, and there’s, you know, there’s kind of, you know, high-tech clusters in other places.
0:30:36 But, you know, if you’re a Sharp AI person and, you know, I’ll just pick on one London, like, you have already moved to California or you’re going to, you know, because they have just, you know, essentially decided to outlaw it.
0:30:38 The EU has decided to outlaw it.
0:30:45 And so, you know, people are being driven to the U.S. and to California, I think, in a way that’s even more concentrated than it was when I first got here.
0:30:46 All right, last question.
0:30:54 Name inventions in human history that have more benefited the lives of individuals than the iPhone.
0:31:00 Oh, well, I mean, you know, if you go far enough back, you know, electric lighting was a big deal.
0:31:02 You know, steam power was a big deal.
0:31:06 You know, obviously, antibiotics are the easy call.
0:31:13 I mean, you know, the Internet itself, you know, electricity, you know, it’s, you know, indoor plumbing.
0:31:15 So, you know, it’s hard to question those.
0:31:18 And people sometimes say, like, you know, you guys aren’t inventing important things.
0:31:20 Like, why are you inventing something as important as indoor plumbing?
0:31:22 And it’s like, well, that was a big one.
0:31:22 I can see.
0:31:24 But, like, you know, we did solve that problem.
0:31:31 I would, if you said, if you said, give up your iPhone or switch to an outhouse, I would switch to an outhouse.
0:31:33 I think, you know, I think there’s a lot to that.
0:31:38 And maybe the serious point underneath that, which I agree with that.
0:31:39 Oh, I was being serious.
0:31:39 I was being serious.
0:31:47 Well, no, so maybe, as you say, the generalization you can make from that is I think people maybe systematically underrate the importance of communication.
0:31:53 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.
0:31:56 Like, those two things, there’s something in the culture.
0:32:00 I was just saying, in Silicon Valley culture, there’s something where, like, those are, like, looked out on as less important.
0:32:05 And I actually think, to your point, like, they’re actually incredibly important and they’re foundational for everything else that people do.
0:32:10 I mean, you know, human connection and human learning is, you know, both of those are at the center of everything that we do.
0:32:12 And so, yeah, no, I would make that same trade.
0:32:15 Here’s my idea for a reality show.
0:32:24 You put someone like us in Cleveland for a week without their smartphone and give them a series of tasks which they would otherwise conduct with their smartphone.
0:32:25 Good luck.
0:32:29 By the way, I had relatives in the 70s who still had outhouses, right?
0:32:31 Yeah, it’s fine.
0:32:33 It passes 100%.
0:32:34 Well, it’s fine.
0:32:40 In Iowa, in January, you start to reconsider whether that’s fine in the middle of the night when it’s 40 below.
0:32:44 But, like, the past was not that long ago.
0:32:45 Yeah, no idea.
0:32:46 Yeah.
0:32:49 All right, Mark Andreessen, very grateful to you.
0:32:51 I scratched the surface.
0:32:57 I had a list of about 15,000 questions that AI winnowed down to me to 1,500, but we didn’t get to them all.
0:32:59 Very grateful to you, though, for making time.
0:33:05 And, again, so just not many people on the planet who understand this stuff as well as you do.
0:33:06 So grateful to you for sharing.
0:33:09 And hopefully we inspired a few people to learn how to use the latest technology.
0:33:10 Thank you.
0:33:11 Good.
0:33:11 Fantastic.
0:33:12 Thank you, Mark.
0:33:17 Thanks for listening to the A16Z Podcast.
0:33:22 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
0:33:25 We’ve got more great conversations coming your way.
0:33:26 See you next time.
0:33:36 This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product.
0:33:43 This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with A16Z.
0:33:51 Such advertisements, companies, and individuals are not endorsed by AH Capital Management, LLC, A16Z, or any of its affiliates.
0:33:57 Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.
Half a billion people can access the world’s best AI on their phone. So why are most using it to write emails while only some are using it to build empires?
In this conversation with Mark Halperin from Next Up, Marc Andreessen reveals why small bakeries are beating Fortune 500 companies at AI adoption, how to turn ChatGPT into your personal board of directors, and why Silicon Valley just reversed five years of geographic dispersion overnight. He also shares the questions that unlock AI’s real power—including one of his favorite prompts: “What questions should I be asking?”
Â
Resources:
Follow Mark Halperin on X: https://x.com/MarkHalperin
Follow Marc Andreessen on X: https://x.com/pmarca
Â
Stay Updated:
If you enjoyed this episode, be sure to like, subscribe, and share with your friends!
Find a16z on X: https://x.com/a16z
Find a16z on LinkedIn: https://www.linkedin.com/company/a16z
Listen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX
Listen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711
Follow our host: https://x.com/eriktorenberg
Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.
Stay Updated:
Find a16z on X
Find a16z on LinkedIn
Listen to the a16z Podcast on Spotify
Listen to the a16z Podcast on Apple Podcasts
Follow our host: https://twitter.com/eriktorenberg
Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Leave a Reply
You must be logged in to post a comment.