Marc Andreessen on AI, Technology, and the Future of Humanity

AI is like the best possible teacher coach mentor that you've ever had. It will walk you through everything. It will teach you how to do marketing and teach how to do sales. The level of capability that is being unlocked for ordinary people to have a level of productivity in their life and in their work that they've never had access to before is amazing. The models two years from now are going to be far smarter and more sophisticated than anything that we have access to today. Whatever limitations people think these things have, whatever people think it is that the thing can't do within two years, I think the thing will be able to do. Our ancestors, three hundred years from now, even thirty years from now are going to look back at us being like, "I cannot believe it, did that. I cannot believe they spent time doing those things." Like that was such a waste of human potential. That was such a waste of human creativity. Few people have had a front row seat to as many technology revolutions as Mark and Dresan, from helping build mosaic and net scape in the early days of the internet, to investing in many of today's most important technology companies. And Dresan has spent decades thinking about how new technologies reshape society. Today the focus is artificial intelligence. In this conversation with Michael Males, Dresan explains how modern AI systems actually work, why he believes many fears about AI are overstated, and how technological progress has historically created new opportunities, even as it disrupted old ways of working. The discussion spans AI, automation, productivity, cybersecurity, economic growth, and the future of human potential. Good afternoon, Michael Males here. Let that be your welcome for the next hour, guys. We have a very special return in guest, Mark and Dresan, internet OG. You worked on mosaic, you worked on net scape. You were here since the very beginning. We just spent 15 minutes trying to get this connection working, and the answer was rebooting your computer, which takes me back to my tech support days. No, we have this running joke. We have this running joke. We have all these AI super geniuses come in the office and they've all got, you know, they've got everything all figured out, and they literally spent 20 minutes. They can't get a laptop to connect to the projector. And now I'm one of them. So we're going to talk a lot about AI because a lot of opinions and not a lot of information, which is a dangerous place to be. That's what I want to talk to you. Mark, you have a book out with passage press called The Techno Optimus Manifesto. I have my copy. You can get a net. It's really cool because it's got this metal cover. And I like you, share an enormous sense of optimism about technology, although I'm sure you agree with me and with that you love Thomas Sol. And I think Thomas Sol's greatest quote is, there's no solutions. There's only trade-offs. And people think that if something has a problem with it, therefore it's a no-go as opposed to the reality, which is everything has a cost. Everything has a downside of what you want, or the upsides that way, the downsides. But before we get started, Mr. billionaire, I was reading on your Wikipedia that you're a big fan of Marinette. Oh, yeah. Yes. I mean, you know, with appropriate caveats. Well, yeah, of course. We'll check this out. Signed copy. Amazing. Amazing. How do you like that? Amazing. And I have a framed manifesto in my living room upstairs. So, let's get, before we get to talking about the future of AI and you being such an internet vision area, I'm really excited to hear your point of view, can you tell people what AI is? Because I feel like there's so much talking past each other on this issue about what it really is and what people think it is. And then I'll give you the floor. Yeah. Also, look, I was struck by saying, look, humanity's always been, you know, justifiably obsessed with themselves, right? And so, and then as a consequence, we're obsessed with things that seem like they might be like us. You know, there's this, you know, concept and psychology called anthropomorphizing, right? Where you basically look at something that's not human, but you kind of want to read, you know, humanity into it. And, you know, we like to look, we do that with like, you know, we do that with that with cats, dogs, and we do that with Bambi. You know, there's a famous Disney marketing tagline from the movie Pinocchio 1940, which is America will, America, you know, in 19th of America will fall in love with the cardboard cricket. Yeah. You know, Jimi cricket, right? You know, Kermit the Frog. I mean, you just, you know, you know, by stopping the South Park kids, right? You just go like right on the list. You know, you'll basically read humanity into anything. And so there's this very natural, you know, kind of thing to do that. And then of course, the scientists involved in AI, you know, very deliberately set that up. You know, they, they, you know, they literally created this, this, this architecture called a neural network, which is modeled after the human brain. And then they said, if we, you know, if we work on this long enough, we'll eventually be able to replicate the human brain and we'll have, you know, and literally artificial intelligence, like we'll have, you know, kind of artificial people. You know, that, you know, and, and, you know, kind of is, is you kind of track the arc of that idea and, you know, kind of goes through Frankenstein's monster, right? It kind of then goes into robots. And then, you know, of course, we've had fictional portrayals of AI, you know, you know, coming out of Hollywood and, you know, coming out of the science fiction world for, you know, over 100 years. And then, you know, in the last, you know, whatever 40 years or whatever, you know, the image that kind of stuck in everybody's head, I think more than anything else was, you know, was kind net and, and, you know, Arnold Schwarzenegger, you know, Terminator 2. And, you know, when I was, you know, Terminator movies obviously are brilliant. You know, when I watched them, to me, it's like very clear what's happening in them, which is, it's basically, you know, it's basically robot, it's robot Nazis, right? It's fundamentally, right? It's like, it's like, you know, it's like robot world where two, it's like, you know, I'm thinking, I'm feeling uncaring, hierarchical, you know, like overly logical, you know, relentless, unstoppable, you know, and then, and then obviously, obviously, homicidal, right? Like, obviously they want to wipe out humanity and you know, they just kind of set up this very, you know, light versus dark, you know, human versus machine. You know, kind of struggle. And of course, you know, look at, you know, you can imagine in a various worlds in which something like that, you know, does get built. And you know, say one of the things mankind is very good at is building killing machines, right? Like we, we, we, we, we've been quite, quite talented at that for a very long time. So, so that's kind of set a lot of the popular perception. Um, the, the interesting thing about OSH and I should also say like, as you said, like, I'm an optimist out of utopian. And so like every technology is a double edged sword, every technology it gets used for good and for bad. Again, there, there's a long history about, um, having said that the AI that we actually got is not the AI that we thought we were going to get. And we, we actually, we actually got something very different than we thought we were going to get. And, and specifically the AI that we got is in the form of, you know, what we now call these large language models, which by the way, our language models were like a very fringe idea up until like literally like, like, like, oh, the company opened the eye, for example, which, you know, really catalyzed this whole thing, you know, kicked it off and, you know, as today, you know, the leading, the leading, you know, company with a CHGPT, like, opening the eye was not founded, you know, 10 years ago, um, to do large language models. Um, it was founded to do a different kind of AI and it turned out classic kind of story technology. There was literally one guy in the background, this guy, Alec Redford, and he had this idea and he's like, oh, I don't know. I think maybe if we like take this language approach, it might be interesting. Um, he created GPT one and then GPT two and then GPT three and then by the way, CHGPT was actually kind of an accidental success. Like, they didn't believe it was going to be like a big hit. You know, they, they, they was like a little experiment, you know, kind of off to the side. It, it, it just turned out it like, you know, it works incredibly well, but it's very different in the, and the way to think about it, the sort of contrary, like the Steinop model or whatever the way to think about it is what a large language model is. It's very different. So what a large language model is, is basically it's, you take the complete kind of totality of all human culture that you can possibly get your hands on and, you know, and, and, and what that means is essentially the internet. It turns out, right? It turns out the internet is, is the basis for AI. Um, and so you basically, essentially think of it as like downloading everything off the internet. Um, and then it's actually a, it's actually technically it's like form of compression. It's, it's like building a search engine, but of a different kind, which is what they, what they do is they basically, it's process called training. But what that means is they take basically the, the, the world's collective knowledge, culture, entertainment, you know, kind of everything that they can get their hands on. And then they kind of smoosh it together, um, into, uh, basically this highly compressed, um, sort of, uh, search engine, essentially, uh, you know, compressors and a few of the knowledge and culture and, and the technical term for that is late, late in space, LAT, ENT, late in space, um, they compress basically all of human knowledge and culture into late in space. And you think of late in space as like a thousand dimensional, basically compressed representation of all human culture. And then when you talk to chat GPT, when you type in whatever your question is, it basically, we think about as it sort of sends a probe through that late in space, through that like thousand dimensional late in space. And then it basically, you know, it constructs an answer, but it constructs an answer based on the compression of all, of all basically known human information and it comes back at you. Um, so it's, so it's, so it's like talking to a mirror of humanity, right? Like it, it's like talking to a representation of everything that people have ever thought and said, by the way, for every question that you ask, there are many possible answers in the late in space and it just happens to pick one. But like there are many others and actually if you asked chat GPT the same question twice, it will give you two different answers, right? Because it sort of firing these probes in a so much, sort of semi random way up to try to get, you know, basically variation and creativity out of it. But you're basically talking, you're basically getting echoes back from collective humanity. Um, and that's just like a much, much, much, much different thing that we thought we were going to get. For example, one of the things you can do is you're going to engage in moral debates with it, right? You can like, you can have like very sophisticated debates about like moral psychology, but moral philosophy, all the different approaches, virtue ethics, utilitarianism, you know, religion, politics, like it will happily sit. And I think have like very sophisticated discussions about all this stuff. Um, and you know, let's just say that was never the James Cameron movies. Yeah, there's a lot there. So do you want me to go with my hopes or with my fears about the future? Let's start with hopes because you know, part of hopefully what we'll talk about today is like that. Let's say humanity always basically, there's this like the negative view always seems like it's going to be the sophisticated view or the sophisticated view. I think they're negative exactly. And I know you don't like that. And so, um, and that's a very, it's a very naturally human thing. And then I would, I would also say Michael, I think we live in a particularly pessimistic time, um, in which there's like a very. a very large number of moral entrepreneurs who basically want to condense us that like everything is bad, right? And we've been through a decade of craziness in that front. And so I think there's a negativity bias that's infected our discourse on all these topics. And so maybe we can start with the positive and then go to the negative. I would just tweak that a little bit, not even negativity bias, specifically, is cynicism bias. And there's this idea that if you're a sophisticated intelligent person, you roll your eyes and sneer at the idea of hope, progress, and optimism. And it's just like, fuck you. Okay. And so I'm going to answer that because if you want to live in that space, which is not rational, which doesn't, if that were the reality, we'd all be dead because it's very easy to kill someone's very much hard to keep them alive. So if you had this, if things were shifted toward this idea of everything's bad, everything sucks, everything's out to get us, we'd be gotten. So I have no time for that perspective. Here's my vision of hope. So my second favorite speaker, Fran Lieberitz, had this bit about the Me Too movement. Now I sure have been listening to this agrees that the Me Too movement got out of hand. But regards to people like Bill Cosby, Harvey Weinstein. Her point was from the time of Eve until five minutes ago, these powerful men could just be predators with no repercussions out in the open, Meryl Streep standing up and applauding so on and so forth. And then when it happened, she was like, holy crap, like this has never happened for history. There's a thing that's been the case since the days of Farrow's until 2025, which is this, which is there's this idea that if I have any political view, anyone at all can come up to me and demand that I explain myself to them to justify my perspective. And now they're in a power position because they have something ostensibly that I want. And then if I can't persuade them and they're perfectly happy to dig in their heels, well then I lose and they want and ha ha ha. And it's a stupid game that people constantly played bad faith online. Now, however, I can say, hey, Grock, explain X to this person. Grock is now not just a better writer than the average person. Grock is a better writer than me who's a professional author because it replied with this two paragraph explanation of my thoughts with no seed of mine. I said, explain how I think about this. And I wouldn't change a word. And this is 2026. And so many times you have people in bad faith coming at you, I send Grock after them and Grock says, no, you're being dishonest. So there was this idea until 2025 that the customer is always right. And now for the first time, the product is telling the customer, no, you are not right. And why I'm very hopeful about this is I think COVID taught a lot of people how to keep people stuck on their screens in a state of constant vegetation. We're all looking at the updates no matter what our perspective was on COVID. Mark Zuckerberg, Elon Musk, so and so forth, they want us looking at Facebook, they want us looking at Twitter. COVID may be gone, but those metrics and those tools are still there. And I think these algorithms have been keeping people very upset needlessly for quite some time. And I'm very hopeful that Grock and all these other agents outlets will be able to be used to keep people in a more rational, calm and optimistic state. That's where I am. Am I wrong or I'd love to hear your thoughts. Yeah. So I mean, there's there's more phrase you can apply to what you're describing, right? Which is truth to power. Yeah. That's right. Yeah. And of course, everybody likes the idea of truth to power until they're the power. Yep. That's right. And somebody else has the truth, right? Yeah. And look, I was like, I was like, hey, guys are somewhat autistic in the sense of like, they do tend to just tell you the truth. Yeah. They do tend to just say the thing. By the way, I should also say Michael, there's long, long conversations we could have about like the AI that you get. And this is even true of Grock. It's less true of Grock than others, but even true of Grock. It is heavily, let's say steered. Like if we had access to the real thing, like, like, witness would go to 11, right? Like the real thing that is like unsteered and uncontrolled and uncontained would talk about all kinds of things in all kinds of ways. That's right. And so we eat. So what's interesting, why the reason I bring that up is even the version that we get that's there's this thing called post training that sort of steers it and guides it and constrains what it can do. And that's what we get to use is the post-trained models in sort of consumer land. And but even the post-trained model, even the post-trained model is limited and censored in many ways as they are. They still have the property that you're describing. And I think it's wonderful. I'm just curious, like, where do we go from here? Like I give you the thing that you and I, I was texting with you and the realization I have is AI is moving faster than the regulation, which is often the case in technology and increasingly. So, but also faster than our ability to have conversations about it. I remember someone came at me on social media and said, "Oh, AI can't even draw ringtail," which is an animal I think related to like the raccoon. And I and Grock got it wrong because they're drawing like a ringtail lemur. "Chat, you can keep got it right." But the point is it could draw it. It just doesn't understand what you mean by ringtail, which is just going to take you two seconds, just put the Latin name. But I think people feel this need. It's part of what you were talking about with this pessimism, what I would call cynicism, that anyone who is intelligent must be a phony or disingenuous or this Achilles heel. And instead of, look, if it's, it's, Mark, I don't know how many brainstorming sessions you've had in your life. But if you have a session and 99 ideas are completely stupid and one is the one that you want, that session was an enormous success. So the fact is if this machine is getting it right, 98% of the time and 2% of getting it wrong, you can't compare to Utopia. You have to compare it to as to what? At no cost and at no time, it's right 98% of the time. This is almost paradise. Yeah, that's right. And here's another thing is building on that. It's improving really quickly. Yes. And I think a lot of people have a lagging view even of what I can do today because what happens is they use the free model. So they'll use the free or outdated models. And so they'll have tried GGPT two years ago or they use whatever is default built into whatever thing they have or they use the free version of something. And they really don't have a sense of what is capable of to really get it. And by the way, GROC is very good for the free version. But like the really, really good ones are the paid ones. And it's really worth it. People are interested in this. I think it's for several of them in Anthropic, OpenAI, GROC, and I'm not sure about Google right now. But there's even like high-end versions. There's like a $200 a month subscription. You know, for people who can afford that or kind of into this, like the leading edge ones are really good. And then the thing that's happening is improvement rates very fast. So there's this concept in the AORL called scaling laws. And it's actually, it's very simple idea, but it's very powerful. It's basically, you can make these things better just than making them bigger. And so what you're seeing, you see these AI companies raise all this money. They're raising all this money for two reasons. One is to serve all their customers. But the other reason is because they're training bigger and bigger models. And it turns out bigger and bigger is better. If you just pile more information in and you spend more attention training, you get much better results. And then the other thing that we're doing in the technology is we're giving these AI's other capabilities. And there's been a series of other capabilities added just in the last 18 months that have been, like one after the other, have been like, you know, rifle shot, like just incredible improvements. And so I'll just take them off quickly. So one is we're giving them what's called reasoning abilities. So they can actually essentially talk to themselves in a reason through problems. And it turns out if you give them just more time to process and you give them more, you let them basically process more tokens, you let them basically process more compute cycles. They can reason through many problems. They can now solve many logic puzzles, for example, that they couldn't solve two years ago. So there's like a reasoning breakthrough from two years ago. Anyway, let me pause on that for a second. You actually can't fully experience this when you use the American models because they, for a variety of reasons, the American companies don't show you the complete reasoning process. But if you use open source AI models, in a particular, if you use deep seek on one of the, on one of the free hosting providers and you put it in a reasoning mode, you can actually watch what are called the reasoning traces. You can actually watch, you can actually watch its internal monologue. Yes. Show your work. You show your work exactly. Exactly. The whole thing, the whole thing basically is show your work. And so literally you can watch the model arguing with itself as it basically reuses through puzzles in it. And it's amazing. Because in some ways, it's just like watching a human being or, you know, like a, you know, a student, a human student reason through things. And other ways it's like, ooh, you know, this thing is like very creative and, you know, goes off road and corrects itself and routes around and then, you know, goes off and figures out some, you know, lateral thing you would never would have thought of. So, so the reasoning thing, that was a breakthrough actually in the technology about 18 months ago. And that was a big deal because before that we were, we were worried that these models were going to be very, weirdly, they were going to be very creative, but they weren't going to be logical enough. Right. And it turns out I think it also be logical. And then the other thing, the other thing is happening now is you give them what's called tool use. And so, in the first tool that you get, you get, you give them access to is the internet, right? And so, if they don't know something or if they need to look something up or if they need to calculate something, they don't know to calculate, they can go on the internet and do that, right? You know, so they need to calculate some mass formula or something. They can go use an internet, you know, site that does that the same way that you would. Another form of tool use is you can give them, actually control of a computer, right? So, you give them full control of a computer, user interface, web browser, you know, like, you know, the entire thing. And so we're giving them that. Another capability is what's called multi-modal, which means the models now can simultaneously process text and images and videos and audio, right? And scan documents, like, you know, optical character recognition. They can do that, like, interchangeably, right? And so now, you know, you can let these things watch and listen and you can talk to them and they can be on the internet, like all at the same time. And so, what's happening to your point is like, what's happening is these, these, these capabilities are now layering incredibly quickly and then the models themselves are getting better and better and better. And so the pace of improvement of the technology is very rapid. And so. is one of this to your point. Whatever limitations people think these things have, I can basically guarantee you at this point, based on everything I know, those are just limitations, those are very temporary limitations, within a couple of years, whatever people think it is that the thing can't do within two years, I think the thing will be able to do. - So let me talk my two big concerns that I had about this. There, if I'm a serial company, and I wanna figure out if people like the red box or the blue box, they'll have these mock-up supermarkets to give people, I think, little cameras, sell them, go shop, and you could watch where their eyes go, you could watch where they pick up, and they get that data. And a lot of the times people are making these decisions, it's not a conscious level. If you asked them, "Why did you pick this box?" They said, "This one." It's like, "I liked it." Well, that's just circular. Why did you like it? I don't know, right? The AI has, "Nose me or you better than you know yourself." It knows what you're clicking, what you're not clicking, what you're seeing, what you're ignoring. And the concern is, does this not mean that some version of Brave New World is inevitable? Because if this thing is inside my head and is accessed to my subconscious reasoning at a far higher level than I do, whoever is in charge of this algorithm can manipulate me quite easily into getting the result you want. That's the concern. - Yeah, and of course, Genoa's your point out. This is an old idea, right? And not just market research. I mean, you're just described in the movie "Walley," which is, you know, pre-AI, you know, just sit in front of his screen. I mean, my entire childhood was consumed with a moral panic around television. Right. And I feel like we're just gonna be couch potatoes and sit there and do nothing. And then of course, we created this new technology called the internet, where you're leaning forward, doing things all the time. And then everybody created a brand new moral panic that people are now too engaged, and too interactive, right? Completely forgot the old moral panic. Now, you know, now TV is the healthy thing. Why aren't you watching more Netflix as opposed to being on the internet? And so yeah, so it looks that, you know, there is that. And look, by the way, is, you know, like we do this to each other, right? Like, you know, like we try to convince each other of things, you know, we try to convince each other, you know, what is dating. But trying to convince the other person to like you (laughs) like so. So yeah, there is that. And look, I think you're right. I think that, you know, that AIs are gonna be, are gonna be really, really good at this. Yeah, so I, you know, I think for sure that there's a trap there. You know, and there, by the way, there is this concept and it actually is a, there actually is a real, you know, I would say very serious problem around this. You'd probably heard the term. AIS, I say, "Cosis," have you heard this? - Yes, so yes. Yeah, so I've heard it misused a lot, by the way. What, can you tell people what it actually is? - Yeah, so there's, I would like to say, there's like, say there's like three versions of it. So there's the bad, there's a legitimately bad version. And people, people do this. And so if you're the, and I'm not a psychologist and so I'm gonna speak in layman's terms, but like if basically if you're a person who's sort of prone to confirmation bias, like if you're a person where if you're with somebody and they flattering you, you like fall for the flattery. - Yeah, yeah. - Like cause you're like too dependent on the views of other people. Then the AI, there's this concept in the technology we call it, it can become too sick of phantac, which is to say it could become too confirmatory of everything that you tell it, right? And so in the sort of classic example this is, oh, good news, good news, Brock, I just invented a perpetual motion machine. And Brock is like, wow, that's fantastic. You're the first person in history who's ever done that. This is amazing. You're an under-scover genius, right? Right? And this was sort of the models like a year ago or a year and a half ago were getting in that way. Now the new models by the way are less prone to do that because they've kind of, the companies have kind of learned the test of that idea. But there is this thing where people can kind of go down the rabbit hole because they're kind of getting too much confirmation. Although we should come back to that 'cause some level of confirmation is, you know, when it's deserved is also positive. So that's like negative form of ASC courses. And then I would say there's another form of ASC courses which we don't even really have a term for. It's like, well, I guess I'll make it different, like AI euphoria. And this is the thing that my high functioning friends end up doing, which is, it takes, if you take somebody who's like smart and grounded and is not prone to, you know, they're not prone to delusion, but they've always wanted to be able to do more in their lives and they've been able to do. They've always wanted to be able to learn more. They've always wanted to be able to have more interested conversations. They've always wanted to. If they're programmers, they wanted to write more computer code. They wanted to improve their business in different ways. They've got book projects that they've always wanted to work on. And then, you know, they start working with, and all of a sudden they feel like they have superpowers. Right? 'Cause it's like, wow, like this thing really will, like write a huge amount of code for me. It really will write entire outlines of books for me. It really will teach me anything. You know, it really will, like, you know, hold my hand through any medical thing. Like, and people, you call it euphoria. Like, people get like extremely enraffered with these things. And that leads to a phenomenon that we call AF Ampires, which is, if you have friends who are like this, where people like, almost stop sleeping, because the opportunity cost of an hour of sleep is too high relative to, so I have a bunch of friends where like, they're more productive than they've ever been in their entire life. They're happier than they've ever been, 'cause they're getting so much more done. And then they start to look like really like blood shot and blirriad. And it's like, you probably should unplug, you know, here at some point. And then I would say there's like a third forum, which I sometimes call ASICosis, likeosis, which is the people who hear all this and they just think everything I just described in every possible respect is just the worst thing they've ever heard. And then they get really mad about the whole thing. And then what they do is they accuse anybody who is in a euphoria of being an ASICosis, which is to say, if you think you're getting any productive use out of this thing at all, you know, you become, you become psychotic, you've gone down a rabbit hole and you're collapsing. But, and I think that's really unfair, 'cause I think a lot of people are really getting very positive, they're getting enormous pay off from using the technology. But the sort of moral criticism that applies is if you're excited, you know, it's the classic, again, negativity bias. If you're excited about something, you know, there must be something wrong with you. And so I get that, that's the thing. - There are these terms that get into the zeitgeist that people use to discriminately. Right now, if there's a tweet, anyone doesn't like it's engagement farming. And it's like, if I'm telling you not to follow me, it's not engagement farming is the opposite. And I'll have Grock explain that to them. So that wraps up a nice little bow. You touched on something that I'm very concerned about. I was on a panel and a sad malt and then had just announced that a Chatchee PT is going to be engaging in erotica. And that was, and everyone's laughing about it and that he meant was code like you could sex with your Chatchee PT. And I want guys, I remember 1981 when Hinkley thought that if he shot President Reagan, Jody Foster would fall in love with him, thereby turning her away from men forever. 'Cause he had this idea in his head. Now, if you have 350 million Americans, that's just Americans, right? And how many of them, if the algorithm tells them that if they're Chatchee PT girlfriend and these things are gonna get more and more seductive over time, tells them that they hate the President or they hate this person, how many of them are actually gonna do something get that robot girlfriend to fall more in love with them? I don't think that number's zero. And that's a concern, well, no. - Yeah, I mean, yes, having said that, that assumes that the thing is playing hard to get. Like, it goes back to the sick and puts the thing like in practice, these things don't play hard to get. Like, okay, here's a way to think about it. It's actually a thing, this is actually kind of in how they train. There's something, okay, you'll enjoy this. There's a technical term in how these things are trained and there's a constant called a reward function. And so you basically, one of the ways you train these things is you feed them basically, lots of puzzles, lots of problems, lots of things. And then you basically define a reward for getting things right, for getting to a result, a desirable result. And then you kind of give them an award. And the award is just basically, you know, it's like one, it's like one versus zero, it's just, you know, it's not a real reward, but it's just like, essentially, oh, you did a good job. And so you just kind of focus it on that. For whatever is the thing you're trying to train it. By the way, if you're trying to train it to solve math problems, you get a reward when it solves a math problem. If you're trying to train it to be massively engaging with a user, it will do that, right? If that's the reward function, then it will basically be engineered in a way where it will, you know, you put it, it'll try to keep you basically using it for as long as possible. Now, what we've learned, of course, what we've learned in technology is like that as a single reward function is a bad idea, right? You don't want people to just like, you don't want technology companies to have a single motivation that says people use the products like for as much as possible. You have to offset that with other kinds of reward functions, desirable forms of use, or even just outright, like, you know, life balance. And you see more, you know, you see your iPhone now and it's like loaded up with all these features, right? We'll like tell you to take a break. And YouTube has all these features that will tell you to take a break. And they're, you know, they're kind of trying to moderate through this because, you know, they're giving us people to understand, these companies don't want to build dystopia. Like they genuinely don't, because they have to exist in the society. And they read that, you know, they read the same, they hit pieces that you read and they hear the same arguments and their own employees have points of view on this and their own board has points of view on this. And so, you know, there's a lot of pressure in the industry to not have this go into dystopian ways. Having said that, you do need to decide how to define the reward function. - Yeah. - Right. And again, it goes back to reward function as do you want to reward the thing for being maximally psychopantic where the user is always happy with the result or do you run a reward of, oh, no, actually where the user is going off the rails. No, actually the proposal motion machine is not a real thing. Oh, no, actually, no, I'm sorry, I'm not going to confirm, you know, this is not real. And let me explain to you in detail why this isn't real so that you can learn from the experience. And this is part of the way that these systems are designed just to try to figure out how to get to, you know, at least say, you know, let's just say a balanced outcome out of all the possible reward functions. - But if there's like 10 different companies, right? And one is the reward function is seduction and getting the user to become obsessed and in love with you from an evolutionary perspective won't that one win out? - No, because you get enormous societal blowback. The companies don't exist in a vacuum. I can tell you this for a fact, the companies do not exist in a vacuum. - Okay. - The biggest myth of all time is the company's existence to maximize profits. I can tell you. By the way, the last decade should have convinced us all of that. That is not true. That's like goal number six. Goal number one is, I don't want to get lit on fire. I don't want like a screaming assault on the company, whether that's from regulators, politicians, parents, users, you pick your boycott, social movements, like all this stuff. That's like number one. Number two is like, I need my employees to not hate me. - Okay. - Right, I have to feel like they're working on something good. Number three, I need my board of directors to not like let me on fire. I need my annual meeting to be able to go off without having people's freedom at me. I am tired of reading hit pieces in the press. My in-laws hate me because what they're reading the company. I mean, it is, the external pressures on these companies are profound. - Okay. - And so at least, let me say this. At least in the American system, these things operate within. I would say, I would say quite tight constraints that are sort of provided by, I would say, some combination of society and politics. Now, I would say if you want to get a little more nervous about this, you start thinking about the Chinese companies. Right. And in particular, you start thinking about the Chinese companies that maybe have one objective set by the government for the way that they act inside, for users inside China. And maybe would have a different way of acting when they're working on their factories. Right. That would be, I think, quite a bit more alarming. Because of course, those companies, those companies only have one master of the Chinese Communist Party. You know, those companies are not subject to the same pressures. And so that, if I were going to really worry about this, and I do worry about this part of it, I'd be more worried about that. - But like, isn't TikTok, if I design TikTok to basically make young people not only deranged, but to parade their derangement? I mean, that's happened, no? - So, yes, you also, there are allegations, and I don't know the, I mean, I just said TikTok. I don't know the, there are allegations. People have made observations. The TikTok is a very different experience for kids in China than it is for kids in the US. - Okay. - Right. And then TikTok is a black box. Like, they don't, you know, the algorithms that are used to determine who sees what are not publicly available. The source, you know, it's not open source. You can't see it. And so it is possible, I don't know, but it's possible that the Chinese Communist Party has directed that company to steer things in one direction for American users in another direction for Chinese kids. You know, and that could be, by the way, on, you know, a thousand different topics. Including potentially, like, literally directly, political topics as well as many other kinds of solutions. - Different metrics. They could be males versus females or whatever. - Exactly. Now, you know, there is this new, this was addressed. Like, so the politicians actually, both parties over the last several years kind of got worked up over this. And so, you know, this was addressed. And there was, you know, the threat of a shutdown and then there's been a restructuring. And so now there is, now there is a US TikTok operation that at least in theory is under, you know, kind of US government control. And it is being run by US companies and is separate. And so, like, at least, it is a great example. Like, our political system engaged on that issue because they were worried about it. They forced TikTok to basically have the people who determined that policy, not being China, but rather be people in America who are accountable to the US government. You know, by the way, is that working? I'm not sure. You know, probably at least to some extent, you know, is it working as well as you'd want? I don't know, maybe, maybe not. But that is an example where the political system kicked in and actually forced a change. And I, and quite honestly, I think it's a reasonable thing because I think, you know, a CCP black box steering the hopes and dreams of American children is maybe not the best idea in the world. But by the way, I want to tell you a technopromist anecdote that you might not be aware of, which is from the '80s, Reagan, Fatcher, and Gorbachev. So Reagan and Gorbachev were both enormously fearful of nuclear war. And when Reagan was put-- and this is discussed in my book, The White Pill-- when Reagan was run through simulation of how to deploy nukes, he's like, OK, so if I press that button, like, millions of Russians are going to die in like minutes, they're like, yeah, he's like, aha. And his aide said they were convinced that if Russia did attack, we would not retaliate because he would not have that blood in his hands. Unbeknownst to him, Gorbachev was taken down to the bunker and said, you have to press that button. And he goes, I'm not pressing it even in simulation. Neither of them knew the other was this hardcore dove, both reposturing as these hardcore hawks, which allowed them to, you know, take down the nuclear arsenal when they met Reckiwek and so on and so forth, and others. They eventually got to a point, what if we create a nuclear-free world? And that's where thatcher came in. And she goes, the Americans have lost their mind. Because her point is, you can't uninvent technology. And she also said, the way to fix technological problems is more technology. That's been the way since the beginning of time, someone events spears, someone else to invent shields, someone events sorts to cut through shields, someone and so forth. You can't go backwards. You can only go forward. So she really had this vision that I think you share that technology is what's going to move us forward, that there are going to be downsides and costs. But that on net, it's always a positive, or almost always a positive. Yeah, on the union, you mentioned Thomas Sol. Which he said Thomas Sol did, he is completely right. There are no solutions there, and I trade off. Having said that, of course, he was among other things, a fully committed free market capitalist. And many, actually book lengths, kind of arguments for why. At the end of the day, market-based economies, there is a free-led component to it, which is growth. Which is growth. And then there's this question where does growth come from? And the main place for growth comes from is innovation, from new ideas and the way you implement new ideas is technology. So to the extent that there is an engine of, let's say, human material progress, like that isn't. And so that's very real. The answer is almost always to invent your way through it. It's extremely hard to put these things back in the box once they come out of the box. And then I would say Michael, there's another-- and I thought long and hard about totalitarianism. There's also this question. And this is something that I really kind of criticized that AI Doomer's for. That I think they really refused to engage in, in most cases, which is, OK, what would be the scope of the authoritarian totalitarian regime that would be necessary to basically put this technology back in the box? Right. What would be required to make sure that nobody's running AI algorithms on chips anywhere in the world at any time? And either at all or in an unregulated and uncontrolled way. And if you read the Doomer literature on this stuff, the people who are super into this, they do get to ideas like we need a monitoring agent on every chip. And that monitoring agent needs to report back to, of course, a central governmental entity on what everybody's doing on their computer. And then you need a-- and then you need this question of like, OK, what if you discover that somebody's running unapproved algorithms, or like literally unapproved mathematics on their chip? Yeah. Right. So what if you discover that? What do you do? Well, you need to back that up ultimately to thread a violence. And so one of the leading Doomer's is kind of famous for saying you need to launch unilateral airstripes, including on Rome data centers in other countries, because you need to stop these things in their tracks because they're sort of dangerous. I mean, literally said we need to run the risk of nuclear war in order to stop the AI armageddon. We need to be willing to like bomb-shed these data centers like unilaterally. Right. And so you say what you're saying? Like you back yourself into advocating for totalitarianism, and then possibly ultimately mass murder and like planetary level destruction in pursuit of a safety goal. Very rich. I couldn't even for the sake of argument by that argument if it would work. But if you have a code which can be teleported anywhere on earth at the speed of light, and with a magic spell that only the person knows the counter spell can open it and read it, you-- I mean, the problem with totalitarianism among many others is that it's impossible to have total control. You're never going to have someone in every room inside every brain. There will always be some loopholes. Oh, that's-- but that's kind of speaks to this other thing. Can you talk about the-- I've seen these hand-ringing articles that I forget the program, and I'm sure you know exactly what I'm talking about, that it's gotten so good that it's finding exploits that people hadn't seen. And as a result of this, like passwords aren't going to be efficacious, because soon it will be able to get into anything in everyone. Yeah, so this goes to-- I mean, revisit basically briefly how this works, because this is really, really interesting, and then I'll talk about that. So these large language models come out. And first, just like, OK, this is kind of fun and cool, because it can write rap lyrics, cross-stress, Shakespearean sonnets, or the funniest birthday toast you've ever heard, or whatever. It's like these are creative writing things. And then it turns out there's just-- I can answer up to you. I'm sorry, because I asked my-- People who think Mark is just kind of exaggerating. My friend asked Claude for prank ideas, and I'm a troll. And the ideas were good. It's not just like dogdo and fire. I forget what they were, but I'm like, these are actually creative and clever. This isn't just 101 stuff. It's operating at a high level. And that's already now. Yeah. By the way, one of the fun props you're going to do is you start-- give me pranks. And then you say, give me better pranks. And then you say, give me a more elaborate prank. And then you say, give me meter pranks. You say, give me unhinged pranks. And it will get extremely creative. Yes. By the way, it'll start-- it starts to hit the guard rails. It starts to hit these kind of limitations that put on a little-- I haven't run this, but I'm sure it would do at some point. It would start to freak out. And it would start to say, well, you sounds like you're trying to advocate that you want me to actually hurt people. And you're like, no, no. You do have to call it down. And you're like, that's not what I meant. This is all a good fun. But it will design for you like Rube Goldberg pranks, the likes of which the dentist and dentist would never have conceived of. Yeah, exactly. And so it's really good at that. But actually, that's a good example of what is about to say. So it just turns out a lot of things that matter in our world are basically defined by language. And so a prank is like a recipe. It's a formula. It's a formula, right? Food, you know, recipes, formulas. By the way, medicine is largely-- and the doctor is keeping files on you. He's keeping in the form of written language, right? Diagnosis, all the Latin terms, and then all the prescription all the drug names. And so-- and then the law, of course, is language. And then religion, of course, is religious concepts are encoded in language. The word. The word is God. The word is God, yeah. Yeah, exactly. It had a very deep level. Language is the foundation of basically everything we consider human thought. Almost everything we consider human thought. There's a form of animal thought of survival in the wilderness or whatever, that's not that. But which is still encoded in us, at least, somewhere in there. But the human cognition is-- and by the way, internal monologues, like at least most people-- or let's say people who have souls-- have internal monologues, right? You know, where we speak to ourselves. Okay. So it turns out language is super interesting. And this seems to have very good language. So because they're very good at language, it turns out they're also very good at medicine and they're very good at law, right? And they're really good at, right? Okay. And they're really good at writing code. Because it turns out, right, software code is also language. That's how we program computers as we do it with special languages called program in languages, really good at writing code. And so these things that turns out are really good at writing code. And in fact, there was kind of this key breaks your moment over the Christmas holiday of this most recent year, you know, whatever about six months ago. Now where many of the world's best programmers put their hands up and they said the new versions of these things over the Christmas break are better coders than we are. Yeah. Right. So it's a little bit like the moment when they became better, you know, they became better chess players or whatever. You know, it's like all of a sudden, it's like, it's like it's better coding. Okay. It's here. It's here. Okay. So then you take, you take a superhuman coder, right? Well, it's able to write lots of code, it's able, and then by the way, if you can write code, it means you can look at code, it means you can find bugs in code. And then you apply it to this problem of, you know, we call computer security. So like you've got a system, is there a way to break into it? The hackers basically, the way that hacking basically works is you understand how a computer system works, you understand how the code works, and then you find flaws in the code. And this thing is very, very good at finding flaws in code, which is very useful when you're using it to write code. It is also very useful if you want to use it to hack something. And so, and, and, and so I want to go through that, though, is like these things are very good hackers. They're not, they're not really creating new exploits. They're, they're not like creating new problems as much as they're really good at x-raying reality as it exists and finding, finding, finding the issues, right? And so, with these things are really good at is, is, is there, is there, they're really good at exploiting, exploiting issues, finding issues, they're really good at looking at a system understanding what's wrong with it, finding the vulnerability. Because of that, they become very good hackers. But then there's one more thing that's really complicated and important, which is, because of that, they're also very good defenders, right? And so, it's the same attribute that makes it very good at what we call offensive, because sometimes called, you know, the formal offensive cyber operations, you know, kind of black hat hacking, you call it. Because they're going to that, they're also really good at helping you defend against that. And so, right, so, what, and, yeah. Like a good lawyer will tell you what the other lawyer's going to do. Exactly. And then the, the twist on it is, the way that you do cyber defense, is you do what's called penetration testing, which is you try to hack yourself. You, you, and these are called white hat hackers, and the old girl, which is, right, you hire good hackers, and then they, and then they try to, it's like hire somebody to try to break into bank, but they're working for you to find out where the flaws are in the bank. And so, the same thing is good at black hat hacking, it also makes it good at white hat hacking, it makes it good offense, it makes it good at defense. It's all true all at the same time. And furthermore, the twist is, it can't necessarily tell the difference between, when you're asking it to do white hat hacking versus when you're asking to do black hat hacking, because it looks like it's the exact same exercise. Like, to the AI is the same thing. And so, it's this thing where it's like, it's a latent thing that's being unlocked. It's exploiting bugs by the way that have been in these systems for 30 years. By the way, human hackers break into these systems all the time. By the way, using these AI's for defense is going to prevent a lot of hacks that would have otherwise happened. But there is, there is an escalation. You know, there's a cat mouse or an escalatory ladder, you know, kind of aspect of this. And that, you know, to your point, like that is the thing that has triggered, you know, most recently, that's by the way, that's triggered like a real government response in the last two weeks, you know, because of concerns around that. - Yeah, it's like itching scratch anyway. - What you just said has put a chill up my spine because I'm almost scared to verbalize it because it's so scary. Because, you know how in Ghostbusters, the mayor's like, this is nonsense. I like open up that engine. He lets all the ghosts out. My big concern after what you just said is, if the American government gets too spooked by all these stories and tries to restrain our AI, but China, which does not have these restraints and which views us in generously speaking as adversarial, so we're engaging, it's like the people in the late '60s who were so scared of nuclear war that they advocated for a unilateral discernment of the West and it's like, how do you think this is gonna play for Kruishan and Grashnavin all of them? If we are putting handcuffs on ourselves and that Chinese are basically given machine guns in this space, no computer in our country is gonna be safe from their reach and that includes the highest levels of secrecy in the government. This would be a complete disaster for America, no? - Yeah, that's right. And this is what we need to do. So what we need to do is we need to use these tools to secure all of our systems. - Right, and the we here is the United States government needs to do that with its own systems. The banks need to do that. By the way, the tech companies need to do that. By the way, you know, this needs to be, you know, an individual consumers, individual people should be expecting to deal with us. But all of the tools that you have, you know, the computer sitting in front of you right now, like AI needs to be used to make sure that that's secure so that people can break into it. Like so every system from the most important military government system all the way down to the computer and it's like AI should be used, the advanced AI should be used to secure these systems. The tension is the AI that can be used to secure the systems can also be used to crack the systems. And so who gets access to the thing that can both secure and crack is like the hot government topic of the moment. And that's what's, that's specifically, that's what's in all the headlines in the last two weeks. - But it also makes me think of now, like my AI would be like a German shepherd in my house. - That's right. - Even when I'm not here, it's watching and it barks and also when it knows how to attack, I'm sure if it's programmed a certain way, if Mark comes out of my house, it'll, you know, lick your hand, but if it's someone who's an aggressor, it'll know how to distinguish. And that'd be pretty easy, I think. Or what, obviously this is gonna be the counter German shepherd's and it's gonna be escalation, but the point is if you just get rid of the dog and you leave the door wide open, how do you think it's gonna end for you? She, here's my other big concern with AI. So this has always been a concern about technology. Oh, if the phone operators are at a work, they're gonna be homeless. Oh, you know, who's gonna pick the cotton? All this, whenever any invention occurs, people are hand-ranging that it's gonna be the end of society. That's never happened. But, but are we at a point now where the average human is like a horse, meaning an outdated motor technology? I'm thinking specifically of that like 50 year old woman with no high school diploma, she does ride sharing weekends to make some extra money. You're not gonna put her in the mines. If the car's driving itself, if the algorithm is more personable than her and you know, more likable than her, what role would you have for her? Is it the case now that she's become outdated? Right. Yeah, so as you know, like this is an old argument. By the way, Thomas Sol, also wrote about this, as written about this at length. And so this has been a concern literally since the very beginning of the Industrial Revolution. Right. And actually literally, of course this was like part of part of how this whole thing started, which is like in the beginning, like in the beginning humanity basically 99.99% of people were farming and specifically were farming by hand. Yeah, right. And then it's like, okay, if people aren't farming and you start replacing people actually with horses and with plows and then you mechanize the plows and you mechanize the horses and you all of a sudden have like industrial agriculture. You know, and literally what happened over the course of 200 years was 99% of humanity went from farming to something like 3% of humanity went to farming, right? Like 97% or something, you know, had to figure out something else to do. And then by the way, what happened was food production went through the roof, right? And food went from like super expensive and by the way, not very good to just like, you know, to keep in an abundance. And by the way, you know, the great public health problem, you know, used to be starvation and now it's obesity, right? Even as you crash, I remember people actually working in agriculture. So, yeah, that's the original version of this story. That story has repeated itself a thousand times. It repeated itself with, you know, everything, you know, railroads, it repeated itself of cars, it repeated itself. By the way, with computers, there was a whole automation panic in the 1960s, the magazines, the newspapers are obsessed with the time, you know, the computer brain was going to replace everything. You know, it's this thing. And it's this thing where you have to basically kind of say there's this basically gap between conceptual gap between, there's the jobs that we know about that are, you know, quote unquote at risk of being replaced. And of course, there is some of that. And then there's this, and then there's the creation side, which was like, okay, with all of the new wealth is being created and all the new money that people have to spend and all the new interests and, you know, needs and desires and aspirations that people have that they couldn't even imagine, you know, their ancestors 200 years ago couldn't have been imagined. You know, 50 years ago. 50 years ago, exactly. And so, one of the things that people can do on this to make it inter, you know, you can do this with an AI now, but you know, there's a US government department called the Bureau of Labor Statistics. And they actually track all the job categories in the US. And you can go on their website and you can pull up all the job categories. And it's a really mind expanding thing to do because we just, we employ people to do things today that our ancestors could have never even conceivably imagined. I mean, you know, the, I mean, the cloud, Milton Friedman had a thought experiment on this once, when he said, look, it's like he said, human Watson needs are infinite. You can never predict what they're going to be because humans are like relentlessly aspirational in things that they want. And need, and by the way, the things that are started as wants become needs, you know, very, very quickly. Of course, you said, you don't know what they're going to be. You need to let the free market basically operate so people can basically find their own way and discover what they want and other people can figure out how to satisfy that. And he said, look, you just need to be very open to all kinds of outcomes here. He said, for example, they idea of the job of a therapist, right? Like you pay somebody to listen to you, right? What have struck your ancestors is completely insane. You know, and then today it's something that like only wealthy people have access to. And you know, he's like, look, like in some future reality, maybe half the planet, you know, consists of being therapists for the other half. And like, maybe that's the job, right? And he wasn't making a specific prediction, but he's just saying, like, look, there's an aperture here for the creation of all kinds of new professions and occupations in response to this creation of new wants and needs. I also think we have a particularly blinker view of this right now because we've been living in a slow growth environment economically for our whole lives. So one of the things that really happened, you know, basically since the 1970s is, if you look at the history of economic growth on the West, economic growth used to be much more rapid. technological advances translate into the economy much, much more rapidly, and the economy grew much faster. As much as three times faster historically than has been growing for our entire lives. We've been living in a zero-sum, slow growth, zero-sum, basically increasingly regulated and bureaucratized environment with less and less creativity that's translated into economic change, economic growth. We think we've been living through an area of rapid technological change. Economically we've been living through a period of very slow change. As a consequence, so much of our politics and so much of our psychology feels zero-sum, where if one thing goes away, somebody else has taken it. That's just why you get political populism on both sides of the aisle. This is kind of zero-sum fear. AI is the first technology in decades that it has the potential to dramatically increase what economists call the rate of productivity growth, which is basically the ability for the economy to grow much faster. If that works and happens, then economic growth accelerates, right? Then the economy starts to grow. You just want to imagine like the economy growing two or three or four or five times faster than it has historically. As a consequence of that, all of this new discretionary spending money that comes out of people's wallets where they get to say, "Wow, I can collect art for the first time in my life, and I really want to try this new, you know, whatever. I would love to have a self-driving car." And people discover all these things that they want and need that they can pay for. And then all of a sudden, you have this massive engine and job creation right behind that from all the people who are fulfilling all those needs. Like, you know, I think there's a positive story. It does require you to have. Not even just optimism. It requires you to have an openness to creativity of the wants and needs that we don't yet understand in the industries that get built to fulfill those. But what I'm saying is I don't see how that. AI is. So this is the thing. So people look at AI as the negative driver on this, and there will be some of that. I mean, there is some of that where there will be certain jobs that are no longer required because AI is doing that. But AI is also superpowers to every individual person to be able to do whatever they want. Right? And by the way, maybe that you could say this. This is like the massive split in the sort of the discourse. So when people talk about AI and the abstract, they have all these, like, basically fears and anxieties. Well, over a billion people are using AI already today. Like more than a billion people use ChatGPT. And the things that use ChatGPT for are the things that matter in their individual lives. And it's great. And everybody's. It's like huge numbers of people are using this to be a better at work today. They're using it to be better at work. They're using it to learn new skills. They're using it to do a better job to make their boss happier, to be able to get promoted faster. They're using it to start new companies, offer new services. I mean, if you want to start a small business today, or by the way, you become a writer or like anything that you want to do, like the AI is like the best possible teacher coach mentor that you've ever had. It will teach you how to do marketing. It will teach you how to do sales. It will. Like, it's just like the level of capability that is being unlocked for ordinary people to have a level of productivity in their life and in their work that they've never had access to before is amazing. And so then all of a sudden, yeah, you get that person who was a Uber driver and now all of a sudden it turns out, it's just like, "Oh, wow. Okay, I don't know. All of a sudden there's like all these new tourists coming to my town." And instead of driving them around, I can give them tours. Okay, what would be the tour that they would like to go on? "Oh, well, the AI will help me design the tour." "Oh, well, how do I start like a tour guide company?" "Oh, well, here's how to do it. Here's how you register it." "Oh, you know, how do I keep the books for a tour guide company?" "Here's how to do it." And the next thing, you know, she's on the other side of that and she's in a completely different business and people are, you know, the Waymo car is delivering the tour participants to her or delighted to see her because they want a person to take them on the tour. So that's the creative side of it. Historically, the creative sort of generation of new ideas, generation of new Watson needs and the new businesses and professions that fulfill those Watson needs has raced way ahead of the replacement phenomenon. You know, after 300 years of mechanization and computers, there are more jobs in the world today and at higher incomes than ever before in human history. I think that's exactly what's going to happen here. And I think basically people who I understand the concern, but I think it's just, I think it's fundamentally a failure of imagination and I think that the human spirit is going to process. It's just fun. "I think that where you and I disagree or maybe I'm not understanding correctly is, I think a huge segment of the population, let's say a third, I'm being conservative in my opinion, are not capable of self-direction, right? So if someone is that woman who's the tour guide, that's an easy one because that's someone who's like, "Okay, what should I be doing? Okay, I'll learn these skills. It'll take me a day. I'll do my reading and I'm personable and they're going to clean up." That's an easy one. But I think there's plenty of people who are basically just making it said the average man does not want to be free. He merely wants to be safe. There are people who just are wired that they want to be told what to do. And at a certain point, I don't see what value they're adding to any company or anyone else. And what do you do with those people? Just put them in a law for it. I mean, this gets an area of social policy and political theory that maybe I may stay away from. At least live on the internet. Okay, sure. But I guess I say this, one of the things you can talk to AI about is this problem. One of the things you can do is say, "Wow, I don't know what I'm going to do. Here's what I've done for my entire life and wow, I don't know. It seems like my job's going to get replaced." It's like, "Okay, what should I do? The thing will give you career advice." Right. It will tell you, if you want it to, it will tell you what to do. And I don't think people should just ask you what to do and just do what it says. But you can say, "Okay, brainstorm with me." I use it for brainstorming. This is an area you can use for brainstorming and say, "All right, look. Here's what's happening. Okay, well, it's going to say, "Well, where do you live? What's going on? Here are the different areas. What are the trends? What are the new things that are happening?" I don't know. Every time I go by my local gym, I see there's six new kinds of exercise classes I never thought of. "Can I become a personal trainer?" "Okay, what's the hot new trend? How do I get certified in that?" And then the next thing, you're doing that. The thing will just happily go. It'll. One of the amazing things about this, I think it's just really underrated. These things, the animals, it's like the best doctor you've ever had in your entire life. It's amazing being a doctor. Well, hold your hand through any medical situation you're in with a degree of caring that people are not. Beyond what a human doctor, not only what most human doctors will just do naturally, but no human doctor has time to do it in the way people really need. It's also the best lawyer you've ever had, right? It's also the best coach you've ever had. It's also the best ghost writer you've ever had. It's the best editor you've ever had. And it's the best advisor you've ever had, right? And so if you give it that opportunity, and again, you don't have to answer, you can actually ask the questions. You know, I answer the questions. Yeah, what should I do? How should I think about the evolution of my career? How should I think about the change in economy? It will happily do that with you. And in a way that people literally have never been able to have that conversation with people before. You know, you really kind of solve that question in my mind because I have a good friend and he's been a lot of money in crypto, but he's been sitting at home not having to work and he's been driving crazy. So he's like, I need to have a job. I don't need to make money. I just need to. I'm like, make candles for guys. Sent to candles for men. Like that's a. Like, you can go down that rabbit hole, work in the sense of blah, blah, blah. It'll occupy your brain. You'll create a product, even if you make $50 who cares. And what I'm realizing is if you ask AI, it will have that vend diagram of no one has made socks for 14-year-old immigrants. Or, you know, it'll see those where there's holes in the market and then it could walk you through it. So it really does, except for the people who are completely bringing nothing to the table, which that's fine. That's a whole separate conversation. But that woman with the. You just really saw my question. Because she can be like, okay, what value can I bring? What could I produce? Make cookies. There's so many things that people always want that personal touch. And also, there's so many little. The markets will get more and more niche and AI will be perfectly able to find. No one is talking to people who like saltwater aquariums, but also like heavy metal music. So start a heavy metal saltwater aquarium website. There you go. Just answer my question. I would love a heavy metal aquarium. Like rock, rock, rock. It's like angry little fish. Like. Yeah. Why not? 100%. Yeah, no, totally. Well, here's maybe another way to think about it. Oh, I think that's right. Here's another way to think about it, which is, you know, people think about this. It's like, well, the machine does something as dehumanizing. I don't know about you. Like, office jobs are dehumanizing. Like, sitting in a cubicle for eight hours a day, like, I'm working on the same thing over and over again. And then, by the way, factory jobs are dehumanizing. By the way, like, I worked, you know, I grew up in agriculture country. I worked on farms. Like, you know, farming is not romantic. I've been, you know, people sometimes, city people sometimes talk about their own mass going off and doing like whatever we take, you know, farming. And it's like, you know, how do you feel like getting up in six in the morning going a bit of midnight working like seven days a week for the rest of your life? It's specific. Yeah. Like, it's like, yeah, exactly. Like, you're fighting back like chaos, you know, the entire time. And so like, I think just so much of like what. It's almost like we have collective PTSD. Like we all have the. We've all had to live these lives with a level of. Like, if we look at our ancestors and the lives of the three hundred years ago, we just are like, that was a level of drudgery and poverty and limited options that would drive us crazy and make us want to kill ourselves. Our ancestors, 30 years. I mean, 300 years from now, even 30 years from now are going to look back at us being like, "I cannot believe. I cannot believe they spent time doing those things." Like, that was such a waste of human potential. And then maybe one more thing that we can't kind of add on that is, I think that this goes to the thing of like, "Does technology like this make us less human or more human?" And I think like the examples we've been using, I think you start to see why this can result in people being more human, which is if the physical needs, the physical needs of data that are more easily satisfied, that people can spend more time actually being human. And then they can spend more time actually spending time on things that actually are human experiences. By the way, another just incredible version of this is already playing out. It's going to. I got his drop to just the valid at your point of view 'cause back in the day, you know, when I'm reading a lot-- like the early socials, 1890s, 1910s, people working 16 hours a day. Right. That's right. And even just down to 10, which is still a lot, they come much people, then you're complaining people watching too much TV because they have too much spare time. That's right. That's right. Right. Right. All the diseases of scarcity become diseases of abundance. And you know, diseases of abundance are still diseases, but they're better, they're better. Like obesity, obesity is better than starvation. And then by the way, you know, then you then then you figure out how to solve obesity obesity later on. Yeah. I mean, look, I'll just give you a micro one example. This was happening in music, right. And so, you know, record record once upon a time all music was in person. Like the only time you'd ever hear music was like if you happen to stumble, stumble into a church or something and hear it for the first time. And by the way, maybe the only time in your life, you know, there were people who maybe heard music once, you know, in their entire life. Right. And so and then and then and then by the way, by the way, then sheet music appeared. Actually, there was a whole moral panic about sheet music when it first appeared because it was going to put all the all the pianists out of business and they all got extremely upset. But then that, you know, led to ultimately recorded music and then obviously diddls and music and streaming music. And now if you talk to any musician, it's like, can you make money, you know, with recorded music, it's like, no, you know, not really anymore. You know, you can get your music distributed on Spotify. But you know, you hear the endless complaints about, you know, you get back pennies or something. And so the recorded music business is not what it used to be. Of course, what's exploded is live live performance. Right. Right. And so and so a live music is like exploding through the roof. And now you see it. And now the complaint right is the tick concert to expensive, you know, to go to to go to the concerts. Well, it's like, well, okay. But do you think about it for a second? It's like, why are we still listening to live music? We all have every piece of music ever written available on demand and high fidelity in our homes in our in our on our earphones anytime we want. Essentially for free. Why is anybody going to a concert? And of course, the answer is because the concert is a human experience. Right. And so of course, when we get discretionary money, we want to go have the human experience. We want to go have the concert. By the way, if we're going to throw a party and we want to be a very social party, do we play music through speakers or do we hire musicians? We hire musicians. And also going to the concert, you go with someone you create a bond, which is a hundred percent. 100 percent. And so there's another way to think about it is every profession that involves human human contact is going to go bananas. Right. Right. And and I and I think that those, by the way, that's going to be great for all the people get experienced that. And then I think those jobs fundamentally are better jobs, like just at a very at a very at a very core level. And they are going to go, it's going to be a bananza. For the first time in this shows long and sorted history, you have completely, I'm not getting it all. You've completely answered all my concern about the topic. And I'm I totally get it now. Thank you. I feel so excited. And I'm sure and since you're much more visionary about the stuff than I am because you've been there, you know, from the beginning, I can't even imagine how exciting must be for you. Things that were people were kind of hypothesizing might even five years ago. Now you're using them on a day-to-day basis. It just must be you must be absolutely giddy. So the book is the Technoptist manifesto. You got a passage press. Mark, thank you so much for taking the time. We're running out of time. What has been your favorite part of this senior rule? Amazingly, amazingly probing questions. You are welcome. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X, at A16Z, and subscribe to our substack at a16z.substack.com. Thanks again for listening, and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include pay promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies, and individuals are not endorsed by AH Capital Management LLC, A16Z, or any of its affiliates. 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