Transcription
Revolutions don't always come with banners and protests. Sometimes the only shots fired are snippets of code. This is one of those moments. AI is the most disruptive force in history, and it's no longer a distant possibility. It is here right now, and it's already changing the foundations of power and the economy.
Few people have been as influential in shaping the direction of AI than mega-investor Ben Horowitz, a pioneer in Silicon Valley. He spent decades at the center of every major technological disruption, including standing up to the Biden administration's attempts to limit and control AI. In today's episode, he lays out where AI is really taking us, the forces that will define the next decade, and how to position yourself before it's too late.
You are uh, in an area making investments, thinking about some of the things that I think are the most consequential in the world today as it relates to innovation. But along those lines, you and Mark Andreessen are all in on AI, but how do we make sure that it benefits everyone instead of making humans obsolete?
To begin with, we have to just realize, you know, what AI is, because I think that because we called it artificial intelligence, you know, our our whole industry of technology has a naming problem, and that we started, you know, by calling computer science computer science, which everybody thought, oh, that's just like computers. It's like the science of a machine as opposed to information theory and what it really was. And then in web 3 world, which you're familiar with, we called it cryptocurrency, which to normal people means secret money, but that's not—that's a good point.
And then I think with artificial intelligence, um, I think that's also like a bad name in a lot of ways, and that, you know, look, the people who work on in the field call what they're building models, and I think that's a a really accurate description in the sense that um, what we're doing is we're kind of modeling something we've always done, which is we're trying to model the world um in a way that enables us to predict it. And then, you know, we've built much more sophisticated models with this technology uh than we could, you know, in the old days. We had E=MC², which was like amazing, but a relatively simple model. Uh, now we have models with what, like 600 billion variables in this kind of thing, uh, and we can model like what's the next word that I should say, uh, and that kind of thing. So, um, so that's amazing and powerful, but I would say like we need to distinguish the fact that um it's a model uh that is directed by us to tell us things about the world and and do things on our behalf, but it's not a uh, it's not life. It doesn't have a free will and these kinds of things. So I think default um it, you know, we are the master and it is uh it is the servant um as opposed to vice versa.
The question though that you're getting at, which is okay, how do we not get obsoleted? Like, why do we need us if we've got these things that can do all the jobs that we currently do? Um, and I think, you know, we've gone through that in the past um and it's been interesting, right? So in I think 1750, over 90% of the jobs in the country were agricultural, um and you know there was a huge fight in a group called The Luddites that fought the plow and you know some of these um new-fangled inventions uh that eventually, by the way, eliminated 97% of the jobs uh that were there, um but I think that most people would say, gee, the life I have now is better than the life that I would have had on the farm um where all I did was farm and nothing else in life, uh but you know like and if you want to farm still, you can. That is an option, uh but most people don't take that option. So the jobs that we have now will, you know, a lot of them will go away and uh we'll have, but we'll likely have new jobs. I mean humans are pretty good at figuring out new things to do and new uh things to pursue and so forth, um and you know like including like going to Mars and that kind of thing, uh which obviously isn't a thing today but could very well be a thing tomorrow. Um so I think that you know we have to stay creative and and uh keep dreaming about like a better future and how to kind of improve things for people, but I think that you know particularly for kind of the people in the world that are on the struggle bus, who are living on a dollar a day or um you know kind of subject to all kinds of diseases and so forth, life is going to get like radically better for them.
When I look at the plow example and the Luddites fighting against it, I think you'll see the same thing with AI. You're going to get people that just completely reject it, refuse to engage in anything for sure, uh but when I look at AI, what I worry about is that there will be no refuge to go to. Meaning if you realize, oh, I can't plow as well as uh a plow or a tractor or now a combine, there's still a lot of other things that technology can't do better than me.
Do you think there's an upper bound to artificial intelligence, bad name or not, or do you think that it keeps going and it it literally becomes better than us once it's embodied in robotics? At everything we are kind of limited by the new ideas that we have, um and and artificial intelligence is really, by the way, artificial human intelligence, meaning um, right, humans looked at the world, humans figured out what it was, you know, described it, came up with these concepts like trees and you know uh air and and all this stuff that it's not necessarily real, just how we just decided to structure the world, and AI has learned our structure. Like they've learned language, human language, which is a version of the universe that is not an accurate version of the universe. It's just our version of the universe. So it's the—you're going to have to go deep on that. I know my audience is going to be like, air seems pretty real when you're underwater. What do you mean that trees and air are not nearly real? It's look, it's it's a construction that we made, you know, we decided it. It is literally the way humans have interpreted the world in order for humans to navigate it, um and you know as is language, right? Language isn't um the universe as it is, like if if uh completely objective, if you had an objective look at you know the atoms and so forth and how they were arranged and and and whatnot, um you probably, you know, those descriptions are lacking in a lot of ways. They're not completely accurate, um they don't they, you know, they certainly don't kind of predict everything about how the world works. And so what machines have learned or like what artificial intelligence is is an understanding of our knowledge um of of the human knowledge. So it's taken in our knowledge of the universe and then it is um kind of can refine that and it can work on that and it can derive things from our knowledge, our axiom set, but it isn't actually observing the world at this point and figuring out new stuff. So you know at the very least, you know humans still have to um discover new principles of the universe or or kind of interpret it in a different way, or the machines have to somehow observe directly the world, which they're not yet doing, um and so that, you know, that's a pretty big role I would say. But then, you know, in in addition, you know we direct the world. I think like Star Trek is actually a pretty good metaphor for that, like the Star Trek computer was pretty badass, um but you know the people in Star Trek were still like flying around the universe discovering new things about it, um you there were still much to do. And I think that it's always a little uh kind of difficult to figure out what the new jobs that get created are, um and we've had intelligence for a while, right? Like we've had machines that could do math way better than us, um and you know I I can remember um when I was in junior high school uh or junior high, put on a play about like how bad it was that there were calculators because nobody would know how to do arithmetic, and then all the calculators would break and then we'd be stuck. We'd be trying to like fly around the universe and rockets and then but we wouldn't be able to do math and the calculators would be broken, we'd be screwed. Um so so there is always that fear, uh and you know we've had computers that can play games better than us. We currently have computers that can drive better than us and so forth, um so we have a lot of intelligence out there, uh but it hasn't um you know created like this super dystopia, you know, in any degree. It's actually made things better, you know, everywhere it's appeared. So I would expect that to continue.
What do you think though is the limiting function? So when I look at AI, uh I always say unless we run into an upper bound where the computation just can't allow the intelligence to keep progressing, um it seems like it will become not only generalized human intelligence and thus they be able to do everything that we can do, uh it will become embodied as robotics. And if I ran the math on this once, Einstein is roughly 2.4 times smarter than someone who is definitionally a [ __ ], and the gap just between those two is so dramatic, the AI won't even um draft somebody that is a [ __ ] at you know whatever 81 IQ or whatever it is, uh because it's they create more problems than they solve even just by being uh you know bullet fodder. So do you think there is something that's going to cause that upper bound or you have a belief about the nature of intelligence that will keep AI subservient to us?
The smartest people don't rule the world, you know, Einstein wasn't in charge, um and you know many of us are are like ruled by are cats, um and so like power and intelligence don't don't necessarily go together, particularly when the intelligence has no free will or has no desire—a free will, it doesn't have will, um you know it it is kind of a model that's computing things. Um I think also, you know, the whole general intelligence thing is interesting in that, you know, who's got a super smart AI that can drive a car, but that AI that drives a car doesn't know English, um and you know isn't you know particularly good at other tasks, you know, currently and and then the chat GPT can't drive a car, uh and so that's you know how much things generalize, particularly. And if you look at why is that, um a lot of it actually has to do with the long tail of human behavior where um humans uh you know the distribution of human behavior is um it's fractal, it's Mandelbrotian or whatever, um it's not evenly distributed at all, uh and so you know an AI that kind of captures all that turns out to be, you know, we're not so much on the track, we're we're more on the track for kind of really great reasoning over kind of a set of axioms that we came up with, um you know in say math or physics, uh but not so much um you know kind of general human intelligence, which is uh you know being able to navigate other humans and the world in a way that uh is productive for us is kind of a it's a little bit of a different dimension of things, you know. Yeah, you can compare the math capabilities or the Go-playing capabilities or the driving capabilities or the IQ test capabilities of a computer, um but that that's not really a human. I I think a human is kind of different in a fairly fundamental way. Um so what we end up doing I think it's going to be different than what we're doing today, just like what we're doing today is very different than what we did 100 years ago, but you know the the not having a need for us, I think that you know these these AIs are tools for us um to basically navigate the world and help us solve problems and and do things, um like you know everything from prevent pandemics to deal with uh climate change to to that sort of thing, um to not kill each other driving cars, uh which we do a lot of, um you know hopefully it doesn't you know uh create more wars, hopefully it creates less wars, um but we'll see.
What I know about the human brain may be tricking me into painting a vision of the future that isn't going to come true. Let me put words in your mouth and you tell me if they fit appropriately. Uh, what I hear you saying is something akin to the way that we're approaching artificial intelligence right now, let's round it to large language models, uh that is going to hit an upper bound where it's not able to uh have insights that a human will already have, that they are trapped inside of the box that we have created, what you're calling the axioms by which we navigate the world. They get trapped inside that box and thusly will never be able to look at the world and go, um I'm not going to predict the next frame, I'm going to render the next frame based on what I know about physics, and so water reacts this way in an Earthbound gravity system and so it's going to splash like this and it understand liquid dynamics etc., etc. Uh so is that accurate? Are you saying that it is trapped inside of our box and we'll never have it?
It hasn't demonstrated that capability yet. So like you, you know, it hasn't like walked up to a rock and said this is a rock, right? We labeled it a rock because that's our structure, but you know a rock isn't probably the—a more intelligent being would have called it something else or or maybe the rock is irrelevant um you know to how you actually can navigate the the world safely, uh and kind of figuring those things out or kind of adopting to them is just not something that um you know it's trained on our on our rendition of the universe uh in our kind of literally like the way we have described it using language that we invented, uh and so it is um it is constrained a bit in nature currently, um you know that doesn't mean it's not like a massively useful tool and can do things and and by the way can derive new rules from the old rules that we've given it um for sure, uh but you know will like I think it's a bit of a jump to go, you know, it's going to replace entirely when the whole discovery process is something that we do that it doesn't do yet.
Okay, the way that the human mind is architected is you have competing regions of the brain. Like if you cut the corpus callosum, the part that connects the left and the right hemisphere, you can get two distinct personalities, one that is atheist, for instance, and one that uh believes deeply in God, and they'll argue back and forth. I mean this is in the same human brain, so that tells me that what you have is basically uh regions of the brain that get good at a thing and then they end up coming together to collaborate and that is sort of human intelligence. And I've heard you talk about there's something like 200 computers inside of a single car, uh so if we already know that you can daisy-chain all of these, like it's it's a very deep knowledge about one thing, but as you daisy-chain them the intelligence gets what I'll call more generalized. You don't see that as a flywheel that that is going to keep going. You know what we can compute will get better and better and better, uh but having said that, you know that doesn't say that um like humans one, you know humans built the machines, plug them in, give them the batteries, all these kinds of things, um and uh you know and they've been created to fulfill our purposes. So you know what it means to be a human will probably will change, like it has been changing, um and kind of how humans live their life will change, but humans still find things to do. I mean like it's kind of like you know like a cheetah has been able to run faster than a human forever, but we never watch cheetahs race, we only watch humans race each other, um you know computers have played chess better than humans for a long time, but nobody watches computers play chess anymore, they watch humans play humans, and chess is more popular than it's ever been. And so I think we have like a keen interest in each other and uh and how that's going to work, and these will be kind of tools to enhance that whole experience for us, but I think it's you know like a world of just machines, um seems like that seems like really unlikely.
So you've got people like um Elon Musk, Sam Altman, who have both expressed deep concerns about how um AI may in fact make us obsolete. Elon has likened—he's certainly become fatalistic— uh but he gave a rant that I absolutely love that is AI is a demon-summoning circle and you're calling forward this demon that you were just convinced you're going to be able to control, and he certainly is not so sure. And at one point—and again I'm fully aware that he's on his fatalist arc and he's just moving forward and he's building as fast as he can—like it's interesting that both of them, despite saying these things, are building AI as fast as like like they're literally in a race with each other to see who can build it faster, who can summon the demon faster that they're warning about. What do you take away from that? Is it just regulatory capture on both of their parts? Is it um is Elon being sincere? Not that I need you to mind-read him, but like what do you take away in the fact that they've both warned against it and they're both deploying it as fast as they can?
Yeah, yeah, it seems fairly contradictory. Um, look, look, I I think there's like I I I won't question either of their sincerity at some degree, but I do think there are um many reasons to warn about it, but like I I also think that you know any kind of new super powerful technology, I you know in a way they're right to kind of warn about like, okay, this thing if we um you know if we don't think about some of the implications of it could get dangerous, and I think that's a good thing. Like every technology we've ever had, from fire to um you know from fire to automobiles to nuclear to AI, has got the internet, um has got downsides to it. They all have downsides, uh and the more powerful, the more kind of you know kind of intriguing the downside, and you know maybe like you know without the internet we probably would have never gotten to AI, um and uh so maybe that was the downside of the internet that it led to AI or something like that you could argue, but I think generally we would take every technology we've invented and keep it because you know uh net net they've been positive uh for humanity and for the world and and that's generally and that's why I think they're building it so fast, because I think they know that—
All right, so anybody with a 17-year-old right now is thinking, oh my, how, where do I point my kid? What do I tell them to go study that's future-proof? What can we learn about the way you guys are investing at Andreessen Horowitz uh that would give somebody an inclination of what you think a 17-year-old should be focused on now?
Yeah, I you know it's really interesting. I think one of the things um what what we're seeing in the kind of smartest young people that come out is they spend a lot of time with AI, learning everything they possibly can. So I think you want to get very good at like—hack curiosity and um and then learning, you know, you have available to you all of human knowledge in something that will talk to you, uh and that's you know that's an incredible opportunity, and I think that anything you want to do in the world to make the world better, um you now have the tools as an individual to do that in a way that you know if you look at kind of what Thomas Edison had to do in creating GE and like what that took and and so forth, you know it was a way higher bar to have an impact, um whereas now I think you know you can very quickly um you know build something or do something that you know just pick a problem. It's not like you know sometimes in this AI conversation the thing that we ignore is like what are the problems that we have in the world? Well, they—well we still have cancer and diabetes and sickle cell and and every disease and we still have the threat of pandemics and we still have climate change and we still have you know lots of people who are starving to death and we still have malaria and and so like pick a problem you want to solve, uh and now um you know you have a huge helping hand in doing that that nobody in the history of the planet has ever had before us. So I think there's really great opportunities along those lines, um so that that would be my you know my best advice I think is to to to get really good with that and uh and look I think a lot of the things that we've learned or that have been valuable skills traditionally are going to change, so you really you know again want to be able to learn how to do anything, uh and and I think that's probably uh going to be key.
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When I look at the things you were just talking about, that feels right for people that have the the inclination, that have the cognitive horsepower to go and say, okay, I'm going to leverage AI to extend my capabilities to tackle the biggest problems in the world. Certainly right now in this moment, that that is the thrilling reality that people should focus on, but then I contrast that with the deaths of despair uh among largely young men. Um, we have this problem in—call it Middle America—where manufacturing jobs have gone away. So for that normal, just sort of everyday person, I want to have a trade, I want to go out into the world and get something done, is AI going to be useful to them or are they going to get replaced by robotics?
The truth of it is is there's only one robot supply chain in the world and that's in China, and you know so like we all need a robot supply chain, um we need to manufacture that, so I think there's going to be like a real uh manufacturing opportunity um coming up, to and it'll be a different kind of manufacturing, certainly more will be automated and so forth, but there will be a lot of things to learn in that field that I think will be uh you know super interesting and um and you know likely very very good jobs. So ironically I would say like going into manufacturing now as a as a young man and trying to you know kind of figure out what that is and get engaged in it will probably lead to you know quite a good career. You know, maybe in creating—uh factories have become like insanely valuable and and and kind of N and strategic to the national interests as well.
That makes sense. So again at the level of the guy smart enough to build the facility, yes. And I recently saw a video of the grocery store of the future where it is a huge grid inside of a giant facility and there's just uh like these bots that look kind of like small shopping carts and they're just grid-patterning across all the items snatching up whatever you order, uh so you order online, these things grab all that stuff and then they send it off to you. Uh so for the person that's savvy enough to build that facility, uh yes, tremendous, um but what I think I hear you saying, and correct me if I'm wrong, is that okay, there are two opportunities here. The opportunity one is if you're the kind of person that can leverage AI to build that facility, massive opportunity. If you're the kind of person that would traditionally work at that factory, something new is coming. We know that because looking back at history, all these technologies unleash things we can't yet see, and so I have faith in the—we can't yet see it, but it is coming.
Yeah, now for sure, like I mean you know what like the biggest in-demand job in the world is right now data labelers. And look, data labeler wasn't a job not long ago, but if you talk—I heard of this—what is data labeling? Yeah, so it's what Alexa—that's what Scale AI does, you know, they they pay armies and armies and armies of people to label data, um so say hey this is a plant or this is you know a fig or whatever it is for the AI to then understand it, and then you know now with the um you know with the with the kind of reinforcement learning coming back into play, um you know labeling, you know that that kind of supervised learning is still like very very very important, uh and I think that um you know right now like he's got unlimited hiring demand, which is you know ironic for Scale AI to have unlimited need for humans. And I think you know in manufacturing there are going to be jobs like that, and there will be the kind of physical—well when you go and you go into these robot—like the software companies that are doing robotics, um they have people managing the robots, right? Like they're training the robots. Humans train robots uh to do all kinds of things, and it turns out that like folding clothes doesn't necessarily generalize to making eggs, um they they're like super different for robots, uh and so you need you know these robots trained in all these kinds of fields and so forth. So I think there's you know there's a whole new class of jobs that are a little bit hard to anticipate um you know in advance, uh but I think at least for the next 10 years I think the the number of new jobs related to making these machines smarter is going to increase a lot, uh and then after that you know like I think there will be there just tend to be like throughout history so many needs for new things that we never anticipated. Like well I mean you know one of my favorite examples is okay, computers, desk computers are going to kill the typesetting business, and they did. Everybody knew that like that was coming. Nobody—nobody said oh and then there's going to be five million graphic design jobs that come out of the PC. Like nobody—not a person—predicted that. So it's really easy to figure out which jobs are going to go away, it's much more difficult to kind of figure out which jobs are going to come, but like if you look at the history of automation, um which is kind of automated away everything we did a hundred years ago, there's less unemployment now than there was then, and so you go…
Okay, and then you know, like some of the employment will be much more, I think, enjoyable than the old employment, as well as it has been, you know, over time. And you, we always talk about manufacturing jobs going away, but the manufacturing jobs that have gone away have been the most mind-numbing. So I think, you know, things evolve in very, very unpredictable ways. Um, and you know, like I, I think the hope is that, you know, the world just gets much better, but I'm not, I'm not so worried about kind of anticipating all the horror that's going to come. I mean, I think the main reason we're making these things is, you know, the ways that they're making life better, uh, and you just like we finally figured out a way for everybody—like we already have in our hands—um, everybody can get a great education. Like that whole inequality of access to education is like literally gone right now, um, which is pretty amazing.
I mean, it's certainly huge. Yeah. Nothing that I ever thought I'd see. So hopefully, um, things go well. The great irony—it's so crazy—I don't think anybody, anybody saw that coming. It was always going to be, it's going to go for the drivers, it's going to go for all those hard, difficult, repetitive tasks. Yeah, it's been very fascinating to see what actually is in danger—like super creative jobs, very much in danger. Um, but yeah, as you get down—I mean, look, I think I believe way more strongly than you do that robots are just going to get better and better and better and better, uh, but that, that could be that I'm not as close to the problem as you are.
Speaking of which, how are the insights that you've had into AI informing the investments that you guys make? The theory is there's this one like super intelligent big brain that's going to do everything. The reality on the ground is, even with the state-of-the-art models, they're all kind of good at slightly different things, right? Like, you know, Anthropic is like really good at code, um, and Grok is really good at like real-time data because they've got the Twitter stuff. And then, you know, OpenAI has gotten like very, very good at reasoning. Um, so with all, all of them were doing AGI, but then they're all good at different stuff, which is, you know, from an investing standpoint, it's very good to know that, because if something like that's not win or take all, that's very, that becomes like super interesting. It also is interesting, uh, for what it means, means at the application layer, because if the infrastructure products aren't win or take all, and then the other thing about the infrastructure products that's interesting is that they're not particularly sticky, um, in the way that kind of Microsoft Windows was very sticky, right? It was sticky—you build an application on Windows, it doesn't run on other stuff; you've got to do a lot of work to move it to something else. So you get this network effect with developers, then you go, okay, well, how, how does that work with state-of-the-art models? Well, people build applications on these things, but guess what? Like, to move your application to Deep Seek, you didn't have to change a line of code; they just literally took the OpenAI Python API and like it runs on Deep Seek now—Tada! Uh, so you know, that, that kind of thing really impacts, you know, how you think about investing and like what is the value of having a leading application, and then, you know, where's the mode going to come from? And of course, AI is also getting—like the one thing it is getting amazingly good at is writing code. And so then, you know, how much of a lead do you have in the code itself versus, um, you know, kind of the other traditional things.
You know, when I started in the industry, the salespeople were in charge; um, they were kind of like the big—there, there's a great uh, TV show called Halt and Catch Fire. And if you watch—was so good—like the thing that's really stunning if you're, you know, kind of coming from the uh, 2010s, 2020s world is why are the salespeople so powerful? But they were the most powerful in those days, uh, and it was because, you know, distribution was the most difficult thing, um, and I, you know, I think distribution is going to get in very, very important again, uh, because maintaining a technological lead is, it's a lot harder, you know, when the machine is writing the code and writing it very fast, although it's not, you know, it's not all the way where it can, you know, build like super complex systems, but there's, you know, if a bunch of things out now—you know, Repl.it's got a great product for it; there's a company called Lovable that's got one out of Sweden, um, that just builds you an app—like if you need an app for something and just say, "Bu me this app," and there it is. Yeah, another thing in Cursor that you can select—yeah, what model you want to use for whatever thing that you're about to generate. So the ability to go, "Oh, I want 10 of these things; I'm gonna use this one for this kind of code, this one for that kind of code"—it's really fascinating.
Now, the Biden Administration was super hostile towards Tech. Uh, when you look at what's going on now with the changes in regulatory, um, what do you think about the race between us and China? Were we headed down a dark path where if that administration had stayed with that—like we're going to have one or two companies, we're going to control them—that's going to be—is it possible we could have lost that race? Is that race a figment of my imagination? Is that real? I think that there's kind of multiple layers to the uh, AI race with China, and then, you know, the Biden Administration was kind of hostile in, in many ways, but all for kind of a central reason, I think. Um, so you know, in AI in particular, uh, you know, when we met—and I, I should be very specific—so it wasn't—we did meet with Jake Sullivan, but he was very good about it; we met with Gina Raimondo, she was very good about it—um, but we met with the, the kind of White House, uh, and their, you know, their position was uh, super kind of, I would say, ill-informed. Um, so they basically were, they, they went in with this idea that like we've got a three-year lead on China, and um, we have to protect that lead, and there's no—and therefore we need to shut down open source, and that doesn't matter to you guys and startups because startups can't participate in AI anyway, um, because they don't have enough money, uh, and the only companies that are going to do AI are going, going to be kind of ironically the two startups, Anthropic and OpenAI that are out, and then the big companies, Google and so forth, and Microsoft, and so we can put a huge regulatory barrier on them because they have the money and the people to deal with it, uh, and then that'll be—and you know, in their minds, I think they actually believe that that would be how we would win, um, but of course, you know, in retrospect, that makes no sense, uh, and it kind of, it damages—you know, if you look at China and what China's great at, then this goes to the next thing. So there's how good is your AI, and then how well is it integrated into your military and the way the government works and so forth. And I think that China, being a top-down society, their strength is, um, you know, that whatever AI they have, they're going to integrate into—it's already all the companies are highly integrated into the government. So you know, they're going to be able to deploy that, and, and we're going to see it in action, uh, with their military very fast.
I think that the advantage of the US is like we're, we're not a top-down society; we're like a wild, messy society, but it means that all of our smart people can participate in the field, and um, look, there's more to AI than just the big models, as you said—like, you know, how important is Cursor? It's really important if you're building stuff—so like, oh, you want to go build, um, you know, the next uh, whatever thing that the CIA needs or the NSA needs or this and that—like you're building that with Cursor, you're using a state-of-the-art model, but like if you had eliminated—if, you know, if the Biden White House had gotten their way, they'd eliminate things like Cursor; they'd eliminate startups being able to do anything in AI. And so the advantages that we have that we, we don't just have a model, we've got all this other stuff that goes with it, and we've got, you know, and then we have new ideas on models, um, you know, with new algorithms and this and that, and that's what the US is great at. And I think, you know, what China is great at is, uh, you know, by the way, they're very good at math; they have a lot—people are good at math, and AI is math, so they, they're gonna—their models are good. They also have a data advantage on us, um, where they have access to the Chinese internet; they have access to copyrighted material which uh, they do not, um, have the same uh, difference for it that we do in the US. And so they're able to kind of get to—you know, if you use Deep Seek, you go, "Wow, Deep Seek really is a great writer compared to a lot of the US models"—why is that? Well, they, they train on a bigger data set than we do, um, and that's amazing. Uh, so, so it really, you know, I think what we want is we want to have kind of world-class, first-class AI in the US, and I think of it less as, you know, is it ahead of China? Is it slightly ahead of China? I think that model—you, you know, what we've seen with our own state-of-the-art models is leads are very shallow, um, and I think that'll continue as long as we're able and allowed to build AI. And then economically, what you'd like is you'd like, you know, to have a vibrant AI ecosystem coming out of the US, so other countries, you know, who aren't, um, state-of-the-art with this stuff adopt our technology, and you know, we continue to be strong economically as opposed to everything goes to China. And that was like a big, big risk with the Biden Administration, I think, um, and you know, which was, you know, what they were doing on AI was, you know, tough. I would say what they were doing on kind of fintech and crypto was even tougher, uh, in that they were just trying to get rid of the industry in its entirety. You know, with AI, they were trying to—I would say they were extremely arrogant in their, in what they thought their ability was to predict the future. Um, you know, Mark and I were in there, you know, like our job is to predict it—like this is our job to invest in the future, to predict the future—and they were saying things that like we're so arrogant that we would never even think to say them, even if we thought them, because we're like, we know that we don't know the future like that, um, you know, it's just unknowable; there's too many moving parts. I mean, these things are really complicated.
All right, well, speaking of the future—fully accepting that it is very, very opaque and very difficult to see—what would you say is the most controversial view that you hold about the future? If we don't get to world-class in crypto, we're going to be—you know, AI really has the potential to wreck society, uh, and what I mean by that is if you think about what is obviously clearly going to happen in an AI world is: one, we're not going to be able to tell the difference between a human and a robot; two, we're not going to know what's real or fake; um, three, uh, the level of security attacks on big central data repositories is going to get so good that everybody's data is going to be out there, and you know, there is no safe haven for a consumer; um, and then finally, you know, for these agents and these, these bots to actually be useful, they, they actually need to be able to use money and pay for stuff and get paid for stuff—like so—uh, and if you think about all those problems, those are problems that are by far best solved by kind of blockchain technology. Uh, so one, we absolutely need a public key infrastructure such that every citizen has their own wallet with their own data, with their own information, um, and if you need to get credit or prove you're a citizen or whatever, you can do that with a zero-knowledge proof; you don't have to hand over your social security numbers, your bank account information, all this kind of thing, because um, the AI will get it. Uh, so, so, so you really need your own keys and your own data, and there can't be these gigantic, you know, massive honeypots of information that people can go after. I think that with deepfakes, if you think about, okay, we're gonna have to be able to whitelist things; we're going to have to be able to say what's real, but who keeps track of what's true then? Is it the government? You know, "Oh, please Jesus"—everybody trusts—everybody trusts Trump now; you know, everybody trusted Biden—is it gonna be Google? We trust those guys? Or is it going to be the game-theoretic mathematical properties of the, of the blockchain that, that can hold that? Um, and so I think that, you know, it's essential that we regenerate our kind of uh, blockchain, crypto development in the US, and we get very serious about it, and you know, like if the government were to do something, I think it should be to start to require these information distribution networks, these social networks, to, to have a way to, you know, verifiably prove your human, you know, prove where a piece of data came from and so forth, uh, and I think that, you know, we have to, you know, have banks uh, start accepting zero-knowledge proofs and, and uh, you know, and that be just the way the world works. We need, need a, a network architecture that is up to the challenge of, you know, these super intelligent agents that are running around.
We were talking before we started rolling that you guys have an office in DC, and part of what you do is advise on that—like what, what does the infrastructure changes, what do they need to look like? Um, what are a small handful of things that you guys are really pushing to see the government adopt to modernize the way that uh, the whole bureaucracy works? Yeah, so there, there's a few things, you know, and one of the things is because uh, you know, blockchain technology involves money, um, we do need—right, it's not like we don't need any regulation; we do need regulation—and there are kind of very specific things that, that we're working with the administration, uh, to make sure are done in a way that uh, kind of creates a great environment for everybody. What do you guys hoping will get blocked out, for instance? Is that what you're about to cover? Yeah. I mean, so like one of the, um, first thing you need is, you know, we, we do need electronic money, you know, in the form of stablecoin—so actual currency—um, and but we need that to not—like it's very bad if one of those collapses, uh, because then like the whole trust in the system breaks down and so forth. Well, why, why do we need this kind of money, this, this kind of internet-native money? Um, well, I give you an example, so we have a, um, called Daylight Energy, and what they do is, um, so we're running—we're going to run into a big energy problem with AI that I think most people probably listening to this know about, where AI consumes a massive amount of energy, you know, much more than Bitcoin ever did, by the way, which everybody was all up in arms about, uh, and you know, so much so that like you can't really even get it out of the power grid. And I think Trump has been smart about this, saying, "Hey, you probably need to build a, a uh, kind of uh, power next to your data center because we can't be giving it to you from the central thing." But beyond that, I think that, you know, kind of individuals, uh, you know, now have Tesla kind of solar panels and power walls and these kinds of things, um, and when you have one of those, you sometimes have more energy than you need and sometimes have less, and wouldn't it be great if you could, um, you know, if there was a nice system that figured out who needed energy and who had energy, and you could just trade, and there was some kind of contract that said, okay, this is what you pay during peak, this is what you pay at different periods, um, and that contract probably best done in the form of a smart contract, but a power wall is not a human, so it doesn't have a credit card; it can't get a credit card; it doesn't have a bank account; doesn't have a Social Security number, um, but it can trade crypto; it can trade stablecoins, uh, and so we need that kind of currency to kind of facilitate, um, all these kind of automated agreements and automated transfer of uh, of, of kind of wealth between entities in order to kind of solve these big problems that we have, like energy, uh, and so we need a stablecoin bill that kind of says, okay, look, we need uh, these currencies to be backed one for one with US dollars or, or whatever it is, um, so that you know, we can have a, a system that works in a trusted—now there's this really interesting side benefit to that, which is if you look at treasury auctions lately, um, the demand for dollars is not good, uh, you know, and a lot of that is—you—the two biggest kind of lenders to the US have been China and Japan, and um, you know, China's backed off a lot, and Japan has backed off somewhat, and so the demand for dollars has gone down. We've done things to also dampen demand—like you—when we uh, sanctioned Russia and we seized the assets of the Russian Central Bank, you know, there were other countries that had, you know, other entities that had money there, um, and their money got frozen and they couldn't access it, and so that makes people more wary of holding everything in dollars, uh, so we've done a lot to dampen that, which of course has, you know, fueled inflation in the same way that increasing supply fuels inflation—killing demand fuels inflation. So here we would have this new major source of demand for dollars, uh, and then the dollars would be much more useful because you can use them online as well, uh, and machines can use them and so forth. So we, we really need—and sorry, really fast for people that are trying to track that—the reason that that would increase the demand for dollars is that they would—the stablecoin would be backed one for one with debt, is that the idea?
Well, yeah, with uh, you—where you would basically have—you would have to have a dollar, or a, a um, for, for you hold treasuries—stablecoin—yeah, you basically hold treasuries so that if somebody wanted to redeem their stablecoins, they could, and then that way, you know, it's kind of the equivalent of the gold standard in the old days, you know, when dollars were trying to get credible, you know, we would need like uh, dollars to be the gold standard for the stablecoin, um, you know, and, and probably we should never backed off of that—maybe we should never backed off of gold—but uh, you know, it's easier dollars because we, we did kind of run out of gold a bit, um, so you know, so that's, you know, one thing. Um, then secondly, uh, there's a bill that went through the house known as the Market Structure bill; it was technically called FIT 2.1, um, that's a very important—you know, whether it's exactly that or some form of that—because, you know, when you talk about tokens, which are the, this kind of instrument, um, that's very, very important in blockchain world because it's the way that this uh, amazing kind of network of computers gets paid for. So you know, who, who pays the people for running the, the computers? Well, that's paid in the form of these tokens, um, but these tokens, um, which can be created on blockchain, uh, have—they, they can be many things, um, so you can create a token that's a collectible, you know, uh, you can create a token that uh, is a digital property right, you know, that links to, you know, some piece of real estate or a piece of art or so forth; a token can be a, you know, Pokémon card; a token could be a coupon; a token could be a security that represents a stock; it could be, you know, a dollar. Uh, so which one is it? Is a very kind of important set of rules that doesn't exist, and this is one of the, the most insidious thing that the Biden Administration did was basically say, well, everything is a security, everything's a stock, um, or you know, like some thing with asymmetric information, which kind of basically undermines the whole uh, power of the technology, and so it was basically a scheme for them to, um, uh, kind of get rid of the industry, uh, but it was, it was very, very dark, um, cynical way of uh, of, of legislating things, and then they would make these, you know, fake claims about scams and so forth, uh, but the Market Structure bill is, is very, very important in that way. And by the way, also, you know, another thing that was in the original Market Structure bill which is important is, look, there are also scams, and there are, you know, and we call it the casino, but uh, you know, like I can create some coin—like the Hakua girl did, right?—like and uh, she creates a coin; she kind of lies about uh, you know, her holdings and says she's going to hold them but then sells them, you know, after people buy it in a short time period and so forth, and there's no, you know, part of the problem is there's no kind of rules around that, but in the kind of bill that passed the house, it said, like you can create a token, but if you hold it, you can't trade it for four years—that kind of takes a lot of the ability to scam out of it and kind of forces people to do things that are the real utilities, or if it's a collectible, you know, if it is the Hakua collectible, you know, it's got to be a real collectible where you don't just, you know, rug the uh, users of it right away. And so that, you know, that, that's—it's okay to do it later, but—
Well, but you know, like in four years, it is what it is, right? You—
Yeah, I'm just giving you a hard time. I just know how that's going to sound to people.
Yeah, yeah, no, thank you. Um, but you know, so these kinds of things, I think, are, are going to be really important to, to making the whole industry work, and so we're working, you know, on that, you know, trying to make it uh, safe for everybody, but you—as I said—it's just such a critical technology in an AI world, you know, where if we don't have it, yes, it's just going to be like a very kind of problematic, um, you know, it's going to—you—it's cyberpunk; it's a, it's a, it's a not a, you know, it's a high-technology, difficult society. We'll get back to the show in a moment, but first, let's talk about a reality many business owners are facing. You understand the power of social media, but you're not posting consistently because the editing process can take precious hours out of your day. Nobody wants to spend hours cutting up videos when they could be running their business. The solution is to turn the things you're already doing into social, social media content automatically. That's why I'm excited about Opus Clip; their Clip Anything AI tool is changing everything. All you have to do is upload any long-form video, and Clip Anything automatically finds the best moments and turns them into social-ready clips. Our social team at Impact Theory has been using it to streamline content creation, but this isn't just for media companies; it's for any business owner who needs to maintain a social presence without sacrificing hours to video editing. Here's your chance to try it: go to op.pro/clipanything and give it a try for free right now. That's op.pro/clipanything. And now let's get back to the show.
Yeah, yeah, it uh, it was shocking to me the level of backlash that the blockchain, Web3 community got. Um, what do you think drives that? Is it just the—that it was only scams, and there's nothing real—like what was that all about? So there were multiple factors. So the first one is the one that hits all new technology, where, "Oh, it's a toy, um, it doesn't do anything new; like the old way of doing things is better," um, and you know, we saw that with social networking; we actually saw that with the internet. I mean, I think Paul Krugman famously said, you know, "Never have more economic impact than a fax machine," and so forth. So that's just kind of a normal thing that happens with new technologies is they start out looking, um, not that important. And with crypto in particularly, you know, one way to think about crypto, blockchain, is it's a new kind of computer, and if you think about new kinds of computers, they're always kind of worse in every way but maybe one than the old computer. And so, you know, if you look at, um, even like the iPhone, it was a bad phone; um, it had a horrible keyboard; you know, if you compared it to anything, it wasn't very powerful; it had a little itty-bitty screen, um, but it had a feature that was pretty awesome, which—you could put in your pocket, um, and it had like a GPS in it and a camera in it. And so now you could build Instagram; you could build Uber, which you could not build with a PC, and you still can't build with a PC, um, and so that was, you know, enough, and then eventually like it started to add the other features, and it's an awfully powerful computer these days.
If you look at blockchain, it's slower; it's more complicated to program; like there's a lot of issues with it, but it's got a new feature, uh, which is trust—like it can make promises you can trust—like when that code, you know, says there's only 21 million Bitcoin, you can absolutely count on that, uh, in a way that like you can't trust Google; you can't trust, you know, Facebook to say, like, "Oh, these are our privacy rules"—like you can't trust that at all; you can't trust the US government to say they're not going to print any more money—like that's for sure. And so, you know, here's a computer that can make promises, um, that you can absolutely count on, and you don't have to trust a company; you don't have to trust a country; you don't have to trust a lawyer; you just have to trust the game-theoretic mathematical properties of the blockchain, um, and that's amazing. So now you can, you know, program property rights and money and law and all these kinds of things that you could never do before, um, and so I think that was—that's hard for normal people to understand who, who aren't deep in the technology, and so they get confused and they say, "Ah, it's nothing," blah, blah, blah. Uh, and then, um, you know, I think the next wave was—you had—look, you know, it was a very odd thing, um, with the Biden administration, because he wasn't really—I think it's come out now—he wasn't really the president; he wasn't really making any decisions, um, you couldn't even get a meeting with him if you were in his cabinet. And in terms of domestic policy, that was run by Elizabeth Warren, and then the second confusing thing is Elizabeth Warren is always calling like people fascist; her whole push with fintech and crypto was to make sure that she could kick people out of the banking system who are political.
Enemies, and so in order to do that, you have to outlaw new forms of financial technology, because those would be kind of back doors, or side doors, or parallels to the GBS and the banking system, which she comprehensively—and I think this is coming out now—could kick people out of. And so when you use, when when it's a full top-down hierarchy and you can use private companies to enforce your will, that is, that is the way fascism works.
And then the way she does it is she sells this fake story about, you know, it's funding terror, and it turns out like the USAID was funding the terrorist groups, but that's a different story. But you know, it's, it's doing all these nefarious things, which, you know, was just a very unfair portrayal. And so then the whole industry got this reputation as scammy and this and that and the other. And then, of course, we had um, Sam Bankman-Fried, who didn't do us any favors by, yeah, like, you know. And and this is another kind of though issue with what Elizabeth Warren did is she blocked all legislation. And so the criminals were running free, and the people doing things that should have been legal were getting terrorized by the government. And when they should have been looking, they should have been looking at FTX, they were looking at Coinbase, which was totally compliant public company, you know, begging for feedback, tell us what you want to, etc.
Exactly.
Yeah, yeah. That that whole thing was crazy.
So, given that AI is putting us on a collision course with, uh, I don't know who's real, I don't know what's fake, do you think that blockchain is about to have its day, like in the next 12 to 24 months, or is this still something that it's so embedded deep in the infrastructure it's going to take a long time to really have its "I told you so" moment?
Yeah, no, I I think it's I think it's within 24 months for sure. I mean, I think that there's enough, you you know, there were like actual, like if you look at kind of the last wave of blockchain, there were real technological limitations that made it, you know, I think we're slowing it down from getting broader adoption. So, you know, very obvious usability challenges, um, the fees were really high, the blockchains were slow, um, so there were just a lot of use cases that you just couldn't do on them. Um, I think that's changing very, very fast. Things are, you know, the the the chains are much faster, the layer 2 stuff makes them, you know, very fast and cheap, uh, you know, people are doing a lot on usability, uh, you know, for wallets and and these kinds of things. So I think we're getting pretty close. And then I think the needs are very high. So if you think of something like, um, Worldcoin, you know, to me the difference between that thing being very broadly adopted and where it is now, where it's I think half the people in Buenos Aires use it daily, so like it's very widely adopted where it's been legal, I think that, you know, if they are able to get integrated into some of the big social platforms, um, then, you know, I like everybody needs proof-of-human, uh, and, uh, you know, like, like it would make the experience online so much better if you knew who is human and who was not. And right now, like you can't tell at all, uh, and so and and that problem is going to get worse, and then the solution is really here. So so I I think it's going to start to take off, and you only need one or two big use cases to start getting the whole infrastructure deployed, uh, and you know, once the infrastructure is deployed, you know, I I think we'll certainly rely on it.
Um, and if you look at actually the curve of people who have active wallets and the curve of like internet adoption, they're pretty similar, um, you know, that it's about I think blockchain's growing a little faster than the internet did initially, uh, and so I think, you know, we'll get to a place where certainly everybody in the US will be on it, uh, which by the way could be great from a government standpoint. You know, Elon has talked about putting, okay, all the government payments on the blockchain, which I think would be really, really good for transparency. Oh my God, we never get into this weird situation now where like half the country wants to, uh, tear down all the government services and half of them wants to keep it because nobody knows what the hell the spending is, um, but that would be great, uh, but you know, beyond that, like if you think about, well, why is there so much waste and fraud? Well, part of it is, you know, like, you know, I get taxed, I give my money to the IRS, the IRS gives it to Congress, they, you know, do whatever they do with it, and so forth. And well, how does it get to the people who need it? Um, you know, that's a very lawy process, you know, and we don't even know who they are, and it's very, you know, one of the things we found out during COVID, the government's not very good at sending people money; it's good at taking money, it's not good at sending them money.
Right. We lost like $400 billion dollars trying to give people, uh, stimulus.
Ridiculous.
Yeah, crazy ridiculous. You know, like if everybody in the US had an address on the blockchain, you could just tell me, okay, here's 10,000 people who need money, please send them, you know, $5,000 each. Well, probably that's too much money for me, but you know, something like that, uh, you know, whatever my tax bill is or whatever that portion of wealth redistribution is, that would be 100% zero loss, by the way. I'd feel a lot better about it, um, because I know I'd be helping people. And you know, look, maybe even somebody would go, hey, this is great, thank you. And like, maybe we would bring us, we wouldn't have this crazy class warfare because everybody would know, hey, we're all integrated, you know, like I'm helping you, you're helping me, uh, and then like if you had that, then you'd fix the whole kind of democracy integrity problem because everybody could vote off that address. And by the way, everybody would have an address because everybody would want the money. So what bigger incentive to register to vote than you? In order to get money, you have to have an address, which registers you to vote. And so that kind of thing, I think, um, could get us to it, just a like a much higher trust in our own institutions.
Yeah, so wow, speaking of that, I wanted to absolutely scream into the abyss when I heard that people couldn't retire from the government faster than the elevator would lower their records down into a mine. I was like, what is happening? What do you take away from, why does Elon want to do this? Why is he sleeping in hallways? Um, why, why is he doing this? Is it just to get government contracts and it's nefarious in the way that so many people think it is, or is there something positive there? What's the, what's the game?
I think there's a couple of different things. So one is the the strong thing is he, he truly believes that, um, America is the best country in the world, you know, he is an immigrant, um, and that it's not guaranteed to stay that way, and and we have been in danger of losing it, uh, and you know, and so the most important thing for him to do in order for his companies to be relevant, in order for going to Mars to be relevant, in order for anything he wants to do in life to be relevant, is we've got a stabilized US Government. I think that's the main thing driving him, you know. So then you say, well, how did he get to that conclusion that, you know, the whole country is in jeopardy? And it really, like, it's a pretty, it was a pretty interesting thing to watch, um, because right in 2021, I think he was a Democrat, and he was certainly pretty apolitical. And, uh, I was actually in a chat group with him, um, when he got the idea or posed the question, should he buy Twitter? Um, and a lot of it stemmed from, um, you know, it started with the US government just harassing him, uh, which was a very odd thing, right? Like here's your, I mean, I think you could very well argue he was our most productive citizen; he, um, was our entire Space Program; he advanced the state of electric cars by 20 years; he's still like 95% of, or something like that, percent of the electric cars sold in the US. Jesus. Um, you know, he's, you know, done the things with Neuralink to, you know, help people like, uh, use their arms and legs who who have been paralyzed and this kind of thing. So, you know, you've got, um, you know, really kind of remarkable person to want to pick on, but, uh, what happened was, uh, because he got like this PR for being very wealthy, um, the Biden Administration targeted him, um, you know, and again, they're fascists, so, uh, it's really a power struggle always with the fascist and anybody who looks like they're becoming powerful. And you know, some of the things they did, and you know, one of the ones that's talked about a lot was, um, they sued him, the Biden Department of Justice sued him for, uh, discriminating against refugees, um, but he had a contract with the US Department of Defense that required him to only hire US citizens, so he was breaking the law either way, uh, and they, they never dropped the lawsuit, even after it was pointed out, even after, you know, it was pointed out by Congress, uh, so it was clear harassment. And I think that his conclusion from that was, you know, this, we are like, ironically, um, I think his conclusion was we're losing the democracy, um, you know, we're going into this very, very strange world, uh, where the incentives are all upside down. And you know, the way Elon thinks is it's up to him to save it, um, and so he got like extremely involved. And then I think the more involved he got, the more he both realized like a lot of the things really dangerous and then secondly that, um, he personally, uh, would be somebody who would know how to fix it. And you go like, well, why the hell would Elon Musk know how to fix the government, all this? And you know, this is the thing that everybody's saying now, uh, and it's funny because I told this to, um, Andreessen years ago, uh, was because I, I'm a big fan of Isaac Newton, and you know, like we, we always talked about like who is Elon like, you know, know like what entrepreneur comes to mind, you know, and it really wasn't maybe Thomas Edison, but not really, um, but Isaac Newton, uh, whoa, was really the one that I always thought he was most like, um, you know, because it's like, okay, who can build like rockets and cars and this and that and the other? But the reason I thought he was like Isaac Newton was at the end of Isaac Newton's life, um, when he I think he was he was in his late 60s, uh, maybe like 60, 768, and this is, you know, for those of you who don't know Isaac Newton, like he figured out how the entire world works and wrote it down in a book, um, you know, called Principia Mathematica, which is probably the most amazing work in the history of science, uh, and he did it like entirely by himself, like he didn't even talk to anybody at this, you know, at the time he wrote it, I think he was trying to figure out what God was or something like that, um, but as you do. But so he gets to be, you know, like in his late 60s, and the Bank of England has a crisis, which is causing a huge crisis for the whole country, um, which is, uh, there's a giant counterfeiting problem, so the currency is going to be undermined, and, uh, England's going to basically go bankrupt. And so they had no idea what to do about it, um, so they call Isaac Newton because he's the smartest man in the world, of course you're gonna call him. So Isaac Newton, 67-year-old like, uh, hermit physicist goes in, and he says, okay, I can help with the problem, make me CEO of the mint. So they make him CEO of the mint, you know, kind of, headed do whatever, uh, and he reorganizes the mint in like a week and then fixes the technology in a month and completely makes it impossible to counterfeit, then he becomes a private eye, uh, and goes into all the pubs where the counterfeits are, arrests all of them, then he learns the law and becomes the prosecutor and prosecutes all the counterfeits and has 100% conviction record. And that, by the way, that's Elon.
So if you, this is, I didn't know that part of his story.
Oh yeah, yeah, yeah. So it's, it's an amazing thing, um, and if you look at Elon and Doge, like the to me the most remarkable thing about Doge is how he's done it. So if you or I were to say, okay, let's go in and kind of get the waste and fraud out of the government, what do we do? We would like audit the Departments or this and that, the other, and so forth. No, no, no, no, like not, that's not how he thinks. He's like, well, the first thing, like how do the checks go out? Like how is the system designed? Like when does the money leave the building? And then, oh, it all comes out of one system, let me have access to that system, and I'll look at all the payments. I'm not asking anybody what they're spending, I'm looking at what they're spending, like I'm getting to ground truth, and then I'm going to work my way backwards from there. And he's probably, and and you know, so not only is he not unqualified, he's the maybe the only person qualified to figure out like how we're spending $5 trillion dollars. Um, and so, you know, so I so, you know, he's just a very unique individual, um, he's also a troll, he also likes upsetting people, I get all that, um, but what he brings to the table is pretty interesting, I would say, like very, yeah, I would say very extraordinary.
You have also written about another extraordinary historical figure, um, from the Haitian Revolution, a guy named Toussaint Louverture.
Yeah, yes, yes, yeah.
Uh, tell us about him because there's something about this moment, about being a master strategist, about, um, using what you have, being creative, that feels like it's very apropos to this moment, um, yeah, what made his story special?
Yeah, so Toussaint was, um, another one of these characters in history, like there are certain, I call them like once in every 400-year type people, um, where you just don't see them that often. But so it turns out like in the history of Humanity, um, there, there's been one kind of successful slave revolt that like engendered an independent state, uh, which, you know, if you think about the history of slavery, which goes back thousands of years, really kind of from the beginning of written history, like we've had slavery, so, um, it's, it's like a pretty old-time construct. And you know, there's a lot of motivation to have a revolt if you're a slave, uh, but why only one successful one? And it turns out it's, it's really hard, um, you know, for to generate an effect of revolt if you're slaves because slave culture is difficult because you don't own, right? If you don't have, uh, any sense of, you know, owning anything, you don't own your own will, right? Like you are at the kind of pleasure of whoever's running things, um, so long-term thinking doesn't make sense, um, and what it because like, why plan for next week? It doesn't matter what you plan, like it's not yours, uh, so everything's going to be very short-term, and short-termism is difficult in a military context because, uh, in order to have an effective military, there needs to be, uh, a trust, right? Like a trust, you know, you have to be able to trust people to execute the order, like I give an order, um, it's kind of like the Byzantine Generals' problem, uh, to go back to crypto, uh, where like I have to trust that you're going to do the order, you have to trust that I'm giving the correct order, um, but trust is a long-term idea because it comes from, okay, I'm going to do something for you today because I trust that down the line you'll do something for me. That doesn't really exist in slave culture because it there is no long term, um, so there is no tomorrow, uh, and so like how do you go from that to like running a successful revolution? And then if you look at Haiti at the time, um, you know, you had the French army, the British army, uh, and the Spanish Army all in there kind of fighting for it, so like really well-developed, you know, kind of the strongest militaries of the era, all in that region, all very interested in the sugar, um, you know, which was quite valuable at the time. So like, how in the world would you ever get out of that? Uh, and it turned out, you know, he, he ended, he was, um, probably the great cultural genius of the last, um, you know, you know, maybe in history, but certainly the last, you know, several hundred years, uh, and he, uh, was able, you know, because he was a person who, although he was born a slave, was very, very integrated into European culture because he was so smart and, um, so the the person who ran the plantation, um, kind of took him to all the diplomatic meetings around and so forth, and he got very involved and kind of mastered, you know, European culture, um, so to speak, and in the different subtleties around it, and he started adopting those things and applying them to his leadership. And then, you know, furthermore incorporated Europeans into the slave army, so he would capture, um, you know, he, he, he would defeat the Spanish, capture some guys, rather than kill them, he'd incorporate, you know, the best leaders into his army, and he built this very like advanced hybrid fighting system where they used a lot of the guerrilla tech, you know, techniques that, uh, he had brought over from Africa, um, and then he had, uh, you know, combined that with, you know, some of the the kind of more regimented, um, kind of discipline strategies of of the Europeans. And building all that, you know, he, he ended up building this massive army and, you know, defeated Napoleon and and everyone else, and it was like just quite a remarkable story about how he just kind of figured everything out from for his principles. And in a way, yeah, that was, uh, you know, kind of very much like, uh, Elon in that sense.
Yeah, one of the things I heard you talk about, yeah, wildly, but one of the things I heard you talk about that I thought was so ingenious was he would basically use song and sound as like encrypted language.
It's really, yeah.
So that was, that was, that was like a very cool thing. So, right, remember that this is in the days before telephones or the internet or any of these things, you know, it's pre-Alexander Graham Bell and all that kind of thing, um, and so, you know, they, they were literally, you know, the Europeans were on like, you know, notes, carrier pigeons, guys running, you know, back and forth and so forth. And so as a result, you know, you kind of needed the army together in one place just so you could communicate the order. Um, Toussaint, uh, basically, you know, had these, um, drummers and these songs, um, which he could put on top of like, uh, the hill, who could be very, very loud. And then he would separate his army, you know, into like six or seven groups, um, but in the song would be embedded, uh, the order of when to attack and, you know, when to retreat and all these kinds of things. So he had this like super advanced, you know, wide-area communication system that nobody else had, and that, you know, that was a big, big advantage for him.
Yeah, that to me, the reason that that comes up for me now is we have all these new technologies that are coming online, and the person that's going to be able to get outside that box and see something new and fresh is going to be able to use this in, in totally different ways. And while in the final analysis, I think you and I see it very differently in terms of AI's ability to ultimately gobble up, um, what humans can do, but right now, AI is this incredible tool that, as an entrepreneur, for me, it has been, um, ridiculously exciting to one see how much farther each of my employees can push their own abilities by using AI. And then it does not take much to prognosticate out, you know, 12, 18 months to understand where the tools are going to be and how much more they're going to let you do because we're largely an entertainment company. So for us to look at that and, uh, just the revolutionary changes, but you can't be trapped inside the old way of thinking; you've got to, like you said, build up from first principles.
Yeah, it's a new creative canvas. I think that's like a really great way of thinking about it, in that, um, it's like, well, is your creativity going to be used on, um, you know, kind of frame-by-frame editing of like a video, or will it be thinking of like incredible new things you can do in a video ad that you could never do before and have the AI do that for you, you know, like, and so it's kind of a little bit of a readjustment of where you put your creative energy into and the things that are possible and so forth. And I think that's, you know, we're really seeing that across the board, like in our firm, um, we're applying a lot of AI, and you'd be like, oh, well, is this going to mean, you know, like you don't have human investors anymore? And it's actually been like totally the opposite, like instead of this like painstakingly collecting, you know, all the data needed to put the investment memo together, like the AI just does that for you, and then you're just thinking about like, okay, what are the like the really compelling things about this? Or rather than, you know, trying to track every entrepreneur and great engineer in our database, the AI is just tracking all those people and letting you know, hey, that guy just updated his LinkedIn profile, or that guy just put out like an interesting tweet, um, maybe you should call him, and that kind of thing, which is just a like a much more kind of fun part of the game, uh, and and so, you know, look, I would say the the best predictor of kind of how things are going to go or or more like what's happening now than like the most dystopian view of it that, uh, we can possibly think of, which I I think is where a lot of people go to. And like I said, I think some of that's the name, you know, artificial intelligence, just, we hate everything artificial, so why do we name it artificial?
That's too true, Ben. I've enjoyed every minute of this. Where can people keep up with you?
Yeah, well, I am Ben Horwitz on X, and, um, you know, uh, that's probably the best thing. We're a16z.com, and, uh, hope you enjoyed it, and, uh, that was it was great fun.
Good fun catching up.
It was indeed. And then you also have, uh, multiple books that people can read that are extraordinarily well respected in the field, so also thank you for those.
Absolutely.
Okay, awesome. Thanks so much.
Well, thank you, brother. I appreciate it.
All right, everybody, if you have not already, be sure to subscribe, and until next time, my friends, be legendary. Take care. Peace. If you like this conversation, check out this episode to learn more. I think the AI censorship wars are going to be a thousand times more intense and a thousand times more important. My guest today is someone who doesn't just keep up with innovation, he creates it: the incredible Marc Andreessen. Trust me, when someone like Mark, who spent his entire career betting on the future, says...