Ben Horowitz: What Founders Must Know About AI and Crypto

11 Jul 2025 · 1 h 23 min

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a16z Podcast Episode Notes

Episode Title

Ben Horowitz: What Founders Must Know About AI and Crypto

Episode Overview

  • Guest: Ben Horowitz, co-founder of Andreessen Horowitz
  • Host: Tom Bilyeu from Impact Theory
  • Major Themes:
  • Disruption caused by Artificial Intelligence (AI)
  • The interplay between AI and the workforce
  • The importance of blockchain technology
  • Future implications of AI and crypto

Key Concepts & Discussions

  1. Disruptive Power of AI
  2. AI is described as a "tectonic shift" rather than just a tool.
  3. Historical parallels drawn to previous technological disruptions.
  4. Discussion of how AI can create opportunities rather than merely eliminating jobs.
  1. Understanding AI
  2. AI defined as sophisticated models that predict outcomes rather than as life or consciousness.
  3. Importance of recognizing AI as a tool that serves human interests.
  1. Future of Work
  2. AI's impact on employment and job transformation.
  3. Historical perspective: Transition from agricultural jobs to new sectors.
  4. Emphasis on the importance of creativity and adaptability in the workforce.
  1. Human vs. Artificial Intelligence
  2. Discussion about the limits of AI compared to human intelligence.
  3. AI can excel in specific tasks (e.g., driving, math) but lacks general human cognition and creativity.
  1. Global AI Race
  2. Comparison of AI advancements in the U.S. and China.
  3. The importance of maintaining a competitive edge while balancing regulation.
  1. Blockchain Technology
  2. Importance of blockchain in establishing trust in a world increasingly influenced by AI.
  3. Discussion on the necessity of stablecoins for economic transactions involving AI.
  1. Regulatory Landscape
  2. Critique of the Biden administration's approach to tech regulation.
  3. Concerns over potential monopolization of AI technology by large corporations.
  1. Historical Context and Future Predictions
  2. Reference to historical figures, such as Toussaint L'Ouverture, to highlight the importance of strategic thinking and adaptability.
  3. Predictions on how technology will reshape human creativity and entrepreneurial endeavors.

Key Takeaways

  • AI as a Tool: AI will not replace humanity but will transform roles and create new opportunities.
  • Adaptability is Key: Individuals must focus on lifelong learning and adaptability in the workforce to thrive in an AI-driven world.
  • Blockchain's Role: Blockchain is crucial for creating trust and security in the digital economy, especially alongside AI advancements.
  • Regulation Necessity: Proactive regulation is needed to foster innovation while protecting public interests.

Conclusion Ben Horowitz provides a masterclass in understanding the implications of AI and blockchain technology on society. The conversation emphasizes the need for a proactive approach to innovation, regulation, and the redefinition of work in a rapidly changing technological landscape.

Resources

  • Impact Theory with Tom Bilyeu: [Listen to more episodes](https://link.chtbl.com/impacttheory)
  • YouTube Channel: [Watch full conversations](http://youtube.com/tombilyeu)
  • Follow on Social Media:
  • Instagram: @tombilyeu
  • Twitter: [a16z](https://twitter.com/a16z)

Additional Notes

  • The content of this podcast is for informational purposes only and should not be taken as legal, business, tax, or investment advice.
  • For further updates, listeners can subscribe to the a16z Newsletter or follow on various social media platforms.

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Transcript

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0:01Today, we're doing something a little different. We're dropping an episode from Impact Theory, a show hosted by Tom Bill Eugh featuring a conversation with Ben Horowitz, co -founder of Andreessen Horowitz. Ben rarely does interviews like this, and in this one, he goes deep. On AI, on power, on the future of work, and what it really means to be a human in a world of intelligent machines. He breaks down why AI is not life, not consciousness, but something else entirely. My blockchain is critical to preserving trust and truth in the age of deepfakes. My distribution may matter more than code, and my history tells us this isn't the end of jobs, but the beginning of something new.

0:37Let's get into it. 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. Information is from source's deep reliable on the data publication, but A16Z does not guarantee its accuracy.

1:12Revolutions 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.

2:01You are 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 and Dreson are all in on AI, but But how do we make sure that it benefits everyone instead of making humans obsolete? To begin with, we have to just realize what AI is because I think that because we called it artificial intelligence, our whole industry of technology has a naming problem and that we started by calling computer science, computer science, which everybody thought, oh, that's just like computers.

2:39It'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 call it cryptocurrency, which do normal people mean secret money. But that's not a good point. And then I think with artificial intelligence, I think that's also like a bad name in a lot of ways in that, you know, look, the people who work on in the field call what they're building models. And I think that's a really accurate description in the sense that what we're doing is we're kind of modeling something we've always done, which is we're trying to model the world in a way that enables us to predict it.

3:23And then we've built much more sophisticated models with this technology than we could, you know, in the old days we had the E equals MC squared, which was like amazing, but a relatively simple model. Now we have models with like 600 billion variables and this kind of thing. And we can model like what's the next word that I should say and that kind of thing. So that's amazing and powerful, but I would say like we need to distinguish the fact that it's a model that is directed by us to tell us things about the world and do things on our behalf, but it's not life. It doesn't have a free will in these kinds of things.

4:10So I think default, we are the master and it is the servant as opposed to vice versa. The question though that you're getting at, which is, okay, how do we not get obsolete it? Like, why do we need us? We've got these things that can do all the jobs that we currently do. And I think, you know, we've gone through that in the past, and it's been interesting, right? So in I think 1750 over 90 % of the jobs in the country were agricultural. And you know, there was a huge fight. And I grew up called the Luddites that fought the plow. And you know, some of these new fangled inventions that eventually, by the way, eliminated 97 % of the jobs.

4:59that were there. 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, where all I did was farm and nothing else in life. But, you know, like, and if you want a farm still, you can. That is an option, but most people don't take that option. So the jobs that we have now will, you know, but we'll likely have new jobs. I mean, humans are pretty good at figuring out new things to do and new things to pursue and so forth. And, you know, like including like going to Mars and that kind of thing, which obviously isn't a thing today, but could very well be a thing tomorrow.

5:49So I think that, you know, we have to stay creative and keep dreaming about like a better future and how to kind of improve things for people. but I think that particularly for the people in the world that are on the struggle bus who are living on a dollar a day or subject to all kinds of diseases and so forth, life is going to get radically better for them. When I look at the plow example and the leadites fighting against it, I think you'll see the same thing with AI. You're going to get people that just completely reject it, refused to engage in anything for sure. 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 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.

6:39Do you think there's an upper bound to artificial intelligence, bad name or not, or do you think that it keeps going and 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. And artificial intelligence is really, by the way, artificial human intelligence, meaning, right, humans licked at the world. Humans figured out what it was, you know, described it, came up with these concept like trees and, you know, air and all this stuff. That it's not necessarily real, just how we decided to structure the world. And AI has learned our structure.

7:23Like 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 art of the show. You're gonna have to go deep on that. I know my audience is gonna be like, air seems pretty real when you're underwater. What do you mean the trees in air not necessarily real? It's a construction that we made. you know, we decided it is literally the way humans have interpreted the world in order for humans to navigate it. And you know, as is language, right? Language isn't the universe as it is, like if if a completely objective, if you had an objective look at, you know, the atoms and so forth and how they were arranged and and whatnot, you probably, you know, those descriptions are are lacking in a lot of ways.

8:13They're not completely accurate. 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, of the human knowledge. So it's taken in our knowledge of the universe and then it is kind of, can refine that and it can work on that and it can derive things from our knowledge are 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 discover new principles of the universe or kind of interpreting a different way, or the machines have to somehow observe directly the world, which they're not yet doing.

9:04And so that's a pretty big role, I would say, but then in addition, we direct the world. I think Star Trek is actually a pretty good metaphor for that. The Star Trek computer was pretty badass, but the people in Star Trek were still flying around the universe discovering new things about it. They were still much to do. And I think that it's always a little kind of difficult to figure out what the new jobs that get created are. And we've had intelligence for a while, right? Like we've had machines that could do math way better than us. And you know, I mean, I can remember when I was in junior high school, our junior high put on a play about like how bad it was that there were calculators because nobody would I don't have to do arithmetic and then all the calculators would break and then we'd be stuck.

9:57We'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 and be screwed. So there is always that fear. 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. So we have a lot of intelligence out there. But it hasn't And created like this super dystopia, you know, an antidegrade. 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?

10:33So when I look at AI, I always say unless we run into an upper bound where the computation just can't allow the intelligence to keep progressing, it seems like it will become not only generalized human intelligence and thus they'd be able to do everything that we can do. It will become embodied as robotics. And if I ran the math on this one, Einstein is roughly 2 .4 times smarter than someone who is definitionally a moron. And the gap just between those two is so dramatic, the army won't even draft somebody that is a moron at, you know, whatever, 81 IQ or whatever it is. because they create more problems than they solve even just by being, you know, bullet fodder.

11:19So 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 roll the world, you know, Einstein wasn't in charge. And, you you know, many of us are like rolled by our cats. And so like power and intelligence don't necessarily go together, particularly when the intelligence has no free will or has no desire to do a free will, doesn't have will. You know, it is kind of a model that's computing things. I think also, you know, the whole general intelligence thing is interesting in that, you know, So, Waymo's got a super smart AI that can drive a car, but that AI that drives a car doesn't know English and, you know, isn't, you know, particularly good at other tasks, you know, currently and then the Chatchee PT can't drive a car.

12:28And so that's, you know, how much things generalize particularly and if you look at, well, why is that a lot of it actually has to do with the long tail of human behavior where humans, you know, the distribution of human behavior is it's fractal, it's a mantle broady and or whatever. It's not evenly distributed at all. And so, you know, an AI that kind of captures was all that turns out to be, you know, we're not so much on the track. We're more on the track for kind of really great reasoning over kind of a set of axioms that we came up with, you know, and say, math or physics, but not so much, you know, kind of general human intelligence, which is, being able to navigate other humans and the world in a way that is productive for us is kind of a, it's a little bit of a different dimension of things.

13:37You 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, but that's not really a human. I think a human is kind of different in a fairly fundamental way. So what we end up doing, I think it's gonna 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 not having a need for us, I think that, you know, these AIs are tools for us to basically navigate the world and help us solve problems and do things like, you know, everything from prevent pandemics to deal with climate change to that sort of thing, to not kill each other driving cars, which we do a lot of.

14:33You know, hopefully it doesn't, you know, create more worries, hopefully it creates less worries, 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. 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. That is going to hit an upper bound where it's not able to 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.

15:15They get trapped inside that box and thusly we'll never be able to look at the world and go, 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 a earthbound gravity system. And so it's going to splash like this and it understands liquid dynamics, etc., etc. So is that accurate? Are you saying that it is trapped inside of our box and we'll never have? It hasn't demonstrated that capability yet. So like, you know, it hasn't like walked up to a rock and said, this is rock. Right. We labeled it a rock because that's our structure.

15:49But, you know, our rock isn't probably the more intelligent being what it called it, something else or maybe the rock is irrelevant, you know, to how you actually can navigate the world safely. And kind of figuring those things out or kind of adopting to them is just not something that, you know, it's trained on our, an R rendition of the universe in our kind of, literally like the way we have described it using language that we invented. And so it is constrained a bit to that in nature currently. You know, that doesn't mean it's not like a massively useful tool and can do things. And by the way, you can derive new rules from the old rules that we've given it, for sure.

16:45But you know, we'll, like I think it's a bit of a jump to go, you know, it's going to replace and centrally 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 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 the reaches 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.

17:31And I've heard you talk about there's something like 200 computers inside of a single car. 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 all called more generalized You don't see that as a flywheel that that is gonna keep going You know what we can compute will it get better and better and better But having said that you know that doesn't say that like humans, one, you know, humans built the machines, plug them in, give them the batteries, all these kinds of things. And, you know, and they've been created to fulfill our purposes.

18:20So, you know, what it means to be a human will probably, will change like it has been changing and kind of how humans live their life will change. But humans still find things to do. I mean, it's kind of like, you know, like a cheetah's been able to run faster than a human forever, but we never watch cheetahs race. We only watch humans race each other. 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 populated than it's ever been. And so I think we have like a keen interest in each other and how that's gonna work.

18:57And 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 seems like that seems like really unlikely. So you've got people like Elon Musk, Sam Altman, who have both expressed deep concerns about how AI may in fact make us obsolete. Elon has likened, he's certainly become fatalistic, but he gave a rant that I absolutely love. That is, AI is a demon summoning circle, and you're calling for this demon that you were just convinced you're gonna 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.

19:47Yeah, but it's interesting that both of them, despite saying these things, are building AI as fast as, Like, they're literally in a race with each other to see who can build it faster. Who can get the way from that? David M. 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, 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 I can? Yeah, yeah, yeah, too fairly contradictory. I think there is, like, I want question either of their sincerity at some degree, but I do think there are many reasons to warn about it.

20:33But like, I also think that, you know, any kind of new super powerful technology, you know, in a way they're right to kind of warn about like, okay, this thing, if we, 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, you know, from fire to automobiles to nuclear to AI has got the internet has got downsides to it. They all have downsides. 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.

21:19And 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, net net, they've been positive for humanity and for the world. 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, 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?

21:55That would give somebody an inclination of what you think a 17 year old should be focused on now. Yeah. You know, it's really interesting. I think one of the things, what we're saying and 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 high curiosity and then learning, you know, you have available to you all of human knowledge in something that will talk to you. 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, you now have the tools as an individual to do that in a way that, yeah, if you look at kind of what Thomas Edison had to do in creating GE and like what that took and so forth, you know, it was a way higher bar to have an impact.

22:52Whereas now, I think, you know, you can very quickly, you know, build something or do something that just pick a problem. Sometimes in the SAI conversation, the thing that we ignore is like, well, what are the problems that we have in the world? Well, we still have cancer and diabetes and sickle cell and every disease, and we still have the threat of pandemics, and we still have climate change, and we still have lots of people who are starving to death, and we still have And now, you know, you have a huge helping hand in doing that, that nobody in the history of the planet has ever had before us.

23:40So I think there's really great opportunities along those lines. So that would be my, you know, my best advice, I think, is to get really good with that. And look, I think a lot of the things that we've learned 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. And I think that's probably going to be key. When I look at the things you were just talking about, that feels right for people that have the inclination that have the cognitive horsepower to go and say, Okay, I'm in a leverage AI to extend my capabilities to tackle the biggest problems in the world, certainly right now in this moment, that is the thrilling reality that people should focus on.

24:32But then I contrast that with the deaths of despair, among largely young men, we have this problem in, call it, middle America, where manufacturing jobs have gone away. So for that normal, just sort of everyday person, and 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, we need to manufacture that. So I think there's going to be like a real manufacturing opportunity coming up to, and it'll be a different kind and 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 super interesting and and likely very, very good job.

25:35So ironically, I would say going into manufacturing now as a young man and trying to figure out what that is and get engaged in it will probably lead to quite a good career, you know, maybe in creating factories have become like insanely valuable and and kind of in strategic to the national interest 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 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.

26:21So you order online, these things grab all that stuff and then they send it off to you. So for the person that's savvy enough to build that facility, yes, tremendous. But what I think I hear you saying, and correct me if I'm wrong, is that, okay, there are two opportunities here. Their 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.

26:51And so I have faith in the, we can't yet see it, but it is coming. Yeah. Now for Sherlock, I mean, you know what, like the biggest in demand job in the world is right now, data labelers. And like data labeling wasn't a job not long ago. But if you talk, I've even heard of this. What is data labeling? Yeah, so it's what Alexander's what scale AI does. You know, they pay armies and armies and armies of people to label data. So say, hey, this is a plant or this is, you know, a pig or whatever it is for the AI tech, then understand it. And then, you know, now with the, you know, with the kind of reinforcement learning coming back into play, you know, labeling, you know, that kind of supervised learning is still, like very, very, very important.

27:43And I think that, you know, right now, like he's got unlimited hiring demand, which is, you know, ironic or 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, they have people managing the robots, right? Like they're training the robots, humans training robots to do all kinds of things. And it turns out that like folding clothes doesn't necessarily generalize to making eggs. They're like super different for robots.

28:33And so you need, you know, these robots trained in all these kinds of fields and so forth. So I think there's a whole new class of jobs that are a little bit hard to anticipate. You know, in advance, but I think at least for the next 10 years, I think that the number of new jobs related to making these machines smarter is going to increase a lot. 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 type setting business.

29:20And 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 gonna go away. It's much more difficult to kind of figure out which jobs are gonna come. But like if you look at the history of automation, which is kind of automated away everything we did 100 years ago, there's less unemployment now than there was then. And so you go, okay. And then like some of the employment will be much more, I think, enjoyable than the old employment as well, as it has been, over time.

30:06And you always talk about manufacturing jobs going away, but the manufacturing jobs that have gone away have been the most mind numbing. So I think things evolve in very, very unpredictable ways. And I think the hope is that the world just gets much better, but I'm not so worried about kind of anticipating all the hard that's going to come out. I mean, I think the main reason we're making these things is, you know, the ways that they're making life better. Any of just like we finally figured out a way for everybody like we already have in our hands, everybody can get a great education. like that whole inequality of access to education is like literally gone right now, which is pretty amazing.

30:56I mean, it's certainly huge. Yeah, nothing that I ever thought I'd see. So, hopefully things go well. The great irony, it's so crazy. I don't think anybody saw that coming. It was always gonna be, it's gonna go for the drivers, it's gonna 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. 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. But that could be that I'm not as close to the problem as you are.

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31:35Speaking of which, how the insights that you've had into AI, how are they informing the investments that you guys make? The theory is there's this one like super intelligent big brain that's gonna 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 And Grock is really good at like real -time data because I've got the Twitter stuff and then you know Open AI is gotten like very very good at reasoning so So with all of them we're doing AGI, but then they are 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 winner take all, that's very, that becomes like super interesting.

32:25It also is interesting for what it means at the application layer because if the infrastructure products aren't winner take all, and then the other thing about the infrastructure products that's interesting is that they're not particularly sticky. In the way that kind of Microsoft Windows was very sticky, right? It was sticky and 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 does that work with state -of -the -art models? Well, people build applications on these things.

33:02But guess what? like to move your application to deep seek, you didn't have to change the line of code. They just literally took the opening of Python API and it runs on deep seek now. So that kind of thing really impacts how you think about investing and what is the value of having a lead in application and then 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, you know, kind of the other traditional things? You know, when I started in the industry, the sales people were in charge.

33:47They were kind of like the big there. There's a great TV show called Hot and Catch Fire. And it's so good. Like the thing that's really stunning if you're, you know, kind of coming from the 2010s, 2020s world is Why are the sales people so powerful But they were the most powerful in those days and it was because you know distribution was the most difficult thing and I you know, I think Distributions going to get in very very important again because as maintaining a technological lead is a lot harder, the machine is right in the code. And writing it very fast. Although it's not all the way where it can build like super complex systems, but there's a bunch of things out now.

34:40Replits got a great product for it. There's a company called Lovable, that's got one out of the Sweden, that just builds you an app. Like if you need an app for something, just say, so call me this app and there it is. Yeah, another thing in cursor that you can select, 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 mean, 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. When you look at what's going on now with the changes in regulatory, what do you think about the race between us and China.

35:22Were we headed down a dark path? Where if that administration had stayed with that, like we're gonna have one or two companies, we're gonna control them, that's gonna be that, 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 AI race with China. And then, you know, the Biden administration was kind of hustle in many ways, but all for kind of a central reason, I think. So, you know, in AI in particular, you know, when we met, and I should be very specific. So we did meet with Jake Sullivan, but he was very good about it.

36:05We met with Gina Rae Mondo. She was very good about it. But we met with the kind of White House, and their, you know, their position was super kind of, I would say ill -informed. So they basically were, they walked in with this idea that like we've got a three -year lead on China and 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 because they don't have enough money and the only companies that are going to do AI are going to be kind of ironically the two startups and Thropic and Open AI that are out and then the big companies Google and so forth and Microsoft.

37:03And so we can put a huge regulatory barrier on them because they have the money and the people to deal with it. And then that'll be, and you know, in their minds, I think they actually believe that that would be how we would win. But of course, you know, in retrospect, that makes no sense. And it kind of, it damages, you know, if you look at China and what China is great at, but 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 that whatever AI they have, they're going to integrate into, it's already all the companies are highly integrated into the government.

37:48So, you know, they're going to be able to deploy that and we're going to see it in action with their military very fast. I think that the advantage of the US is like 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 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 wanna go build, you know, the next, 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 had to eliminate things like cursor, they'd eliminate startups being able to do anything in AI.

38:42And so the advantages that we have that 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, 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 out is. You know, by the way, they're very good at math. They have a lot of people are good at math and AI is math. So they're going to their models are good. They also have a data advantage on us where they have access to the Chinese internet. They've access to copyright material, which they do not have the same difference for it that we do in the US.

39:19And so they're able to kind of get to, you know, if you use deep sea, you go, wow, deep sea really is a great writer. compared to a lot of the US models, why is that? Well, they train on a bigger data set than we do. And that's amazing. 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 about less as, you know, is it ahead of China? Is it slightly ahead of China? I think that model, you know, what we've seen with our own state of the art models is leader, very shallow. And I think that'll continue as long as we're able and allowed to build AI.

40:00And 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. 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 in that they were just trying to get rid of the industry and its entirety.

40:38You 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. 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 wouldn't ever even think to say I'm even if we thought them because we're like, we know that we don't know the future like that. You know, it's just unknowable. There's too many moving parts. I mean, these things are really complicated. it.

41:14All right, well speaking of the future, fully accepting that it is 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. And what I mean by that is if you think about What is obviously clearly going to happen in 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. Three, 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.

42:05And there is no safe haven for a consumer. And then finally, you know, for these agents and these, these bots actually be useful, they, they actually need to be able to use money and pay for stuff and get paid for stuff like so. And if you think about all those problems, those are problems that are by far best solved by kind of blockchain technology. 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. And if you need to get credit or prove you're a citizen or whatever, you can do that with the zero knowledge proof.

42:50You don't have to handle where your social security numbers, your bank account information, and all this kind of thing because the AI will get it. So you really need your own keys and your own data and there can't be these gigantic, you know, massive honey pots of information that people can go after. I think that with deep fakes, if you think about, okay, we're gonna have to be able to whitelist things, we're gonna have to be able to say what's real. But who keeps track of what's true then? Is it the government? You know, please Jesus. Everybody trust Trump now. You know, everybody trust the Biden?

43:28Is it gonna be Google? We trust those guys? Is there is going to be the game theoretic mathematical properties of the blockchain that can hold that? And so I think that it's essential that we regenerate our kind of blockchain crypto development in the US. And we get very serious about it. And like at the government, we're to do something I think it should be to start to require these information distribution networks, these social networks, to have a way to verifiably prove your human, prove where a piece of data came from and so forth. And I think that we have to have banks start accepting zero -knowledge proofs and that be just the way the world works.

44:17We need a network architecture that is up to the challenge of the 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. What does the infrastructure changes? What do they need to look like? What are a small handful of things that you guys are really pushing to see the government adopt to modernize the way that the whole bureaucracy works? Yeah, so there's a few things. And one of the things is because blockchain technology involves money, we do need, right, it's not like we don't need any regulation.

44:57We do need regulation. And there are kind of very specific things that we're working with the administration to make sure are done in a way that kind of creates a great environment for everybody. What do you guys probably will get blocked out, for instance, is that what you're about to cover? Yeah, I mean, so like one of the the first thing you need is, you know, we do need electronic money, you know, in the form of stablecoin. So actual currency. And, but we need that to not, like, it's very bad if one of those collapses, because then, like, the whole trust and the system breaks down and so forth.

45:38Well, why do we need this kind of money, this, this kind of internet native of money. Well, and give you an example. So we have a company called Daylight Energy. And what they do is, so we're running, we're going to run into a big energy problem with AI that I think most people probably listening to the snow about where AI consumes a massive amount of energy, you know, much more than Bitcoin ever did, by the way, which everybody would call up in arms about. 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 kind of power next to your data center because we can't be giving it to you from the central tank.

46:21But beyond that, I think that, you know, kind of individuals, you know, now have Tesla kind of solar panels and power walls and these kinds of things. And when you have one of those, you sometimes have more energy than you need and sometimes times that less. And when it be great, if you could, 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. And that contract probably best done in the form of a smart contract, but a power wall is not a human.

47:00So it doesn't have a credit card. It can't get a credit card. does I bank account? I don't have a social security number. But it can trade crypto, it can trade stable coins. And so we need that kind of currency to kind of facilitate all these kind of automated agreements and automated transfer of of of kind of wealth between entities in order to kind of solve these big problems that we have like energy. And so we need a stable coin build that kind and it says, okay, look, we need these currencies to be backed one for one with US dollars or whatever it is so that we can have a system that works and is trusted.

47:47Now, there's this really interesting side benefit to that, which is if you look at Treasury auctions lightly, the demand for dollars is not good. And a lot of that is the two biggest kind of lenders to the US have been China and Japan and China's backed off a lot and Japan's backed off somewhat. And so the demand for dollars has gone down. We've done things to also dampen demand like when we sanction Russia and we seize the assets of the Russian central bank. There were other countries that had other entities that had money there and their money got frozen and they can access it. And so that makes people more wary of holding everything in dollars.

48:32So we've done a lot to dampen that, which of course is, you know, fueled inflation, I'm 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. And then the dollars would be much more useful because you can use them online as well. And machines can use them and so forth. So we really, 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 that is that the idea? Well, yeah with You where you would basically have you would have to have a dollar or write a For for every hole treasuries stable crime.

49:17Yeah, you basically hold treasuries so that if somebody wanted to redeem their stablecoins say could and then that way, you know, it kind of the equivalent of the gold standard and the old days, you know, when dollars were trying to get credible, you know, we would need like dollars to be the gold standard for the stable coin. You know, and probably we should never back off of that. Maybe we should never back off of gold, but, you know, good luck with that because we did kind of start to run out of gold a bit. So, yes, so that's, you know, one thing. Then, secondly, there's a bill that went through the house known as the Market Structure Bill.

50:00It was technically called Fit 21. 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, that this kind of instrument that's very, very important in blockchain world because it's the way that this amazing kind of network of computers gets paid for. So, you know, who pays the people for running the computers? Well, that's paid in the form of these tokens. But these tokens, which can be created on blockchain, have, they can be many things. So you can create a token that's a collectible. You know, you can create a token that 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.

50:54A token can be a, you know, a Pokemon card. A token could be a coupon. A token could be a security that represents a stock. It could be, you know, a dollar. So which one is it? Is it very kind of important set of rules that doesn't exist? And this is one of the most insidious thing that the Biden administration did was basically say, well, everything is a security, everything's a stock, or like something with asymmetric information, which kind of basically undermines the whole power of the technology. And so it was basically a scheme for them to kind of get rid of the industry. But it was very, very dark, cynical way of legislating things.

51:46And then they would make these fake claims about scams and so forth. But the market structure bill is very, very important in that way. And by the way, also, another thing that was in the original market structure bill, which important is look there are also scams. And we call it the casino. But like I can create some coin like the Hock Tua girl did, right? And she creates a coin. She kind of lies about her holdings and says she's going to hold them, but then sells them after people buy it in a short time period and so forth. And there's no part of the problem is there's no kind of rules around that, but in the kind of bill that passed the house, it's said like you can create a token, but if you hold it, you can't trade it for four years.

52:40That kind of takes a lot of the ability to scam out of it and kind of forces people to do things that are in their real utilities, or if it's a collectible, you know, if it is the hack to a collectible, you know, it's got to be a real collectible where you don't just, you know, rug the users of it right away. And so that, you know, that's the right way. It's okay to do it later, but. Well, but you know, like in four years, it is what it is, right? Yeah, yeah, no, just giving you a hard time. I just know how that's going to sound to people. Yeah, yeah, no, thank you. But, you know, so these kinds of things I think are going to be really important to making the whole industry work.

53:21And so we're working, you know, on that, you know, trying to make it. say for everybody, but as I said, it's just such a critical technology in an AI world, you know, whereas if we don't have it, yes, it's just going to be like a very kind of problematic, you know, it's going to be at a cyberpunk. It's a, it's a high technology, difficult society. Yeah, yeah, it was shocking to me the level of backlash that the blockchain Web 3 community got. What do you think drives that? Is it just the perception that it was only scams and there's nothing real? Like what was that all about? So there was multiple factors.

54:11So the first one is the one that hits all new technology where, oh, it's a toy. It doesn't do anything new, like the old way of doing things is better. And, you know, we saw that with social networking. We actually saw that with the internet. And I think Paul Krugman famously said, I'd never have more economic impact on a fax machine. And so for, so that's just kind of a normal thing that happens with new technologies as they start out looking not that important. And with crypto in particular, 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, then the old computer.

54:56And so, you know, if you look at, um, even like the iPhone, it was a bad phone. It had a horrible keyboard. If you compare it to anything, it wasn't very powerful. It had a little edy -bitty screen. But it had a feature that was pretty awesome, which you could put in your pocket. 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 the PC. And you still can't build with the PC. 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.

55:36If you like a 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 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 in a way that like you can't trust Google, Well, you can't trust Facebook to say, oh, these are 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 here's a computer that can make promises that you can absolutely count on.

56:22And 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. 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. And so I think that was, that's hard for normal people to understand who aren't deep in the technology. And so they get confused and they say, Yeah, it's nothing blah, blah, blah. And then, I think the next wave was you had, look, it was a very odd thing with the Biden administration because he wasn't really, I think it's come out now.

57:05He wasn't really the president. He wasn't really making any decisions. 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 And it's 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 G -Sibs and the banking system, which she comprehensively, and I think this is coming out now, could kick people out of.

57:52And so when you use, when it's a full -top down hierarchy and you can use private companies to enforce your will, that is the way fascism works. And then the way she does it is she sells this fake story about, you know, its 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 doing all these deferious things, which 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 Sam Bankman freed who didn't do us any favors by. You know, and this is another kind of though issue with what Elizabeth Warren did, is she blocked all legislation.

58:37And 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 wanted to do. And etc. Exactly. Yeah. That whole thing was crazy. So given that AI is putting us on a collision course with, 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?

59:12or is this still something that it's so embedded deep in the infrastructure it's going to take a long time to really have it's I told you so moment. Yeah, no, I think it's within 24 months for sure. I mean I think that there's enough. You know, there were like actual like if you like it kind of the last wave of black chain. 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. The fees were really high. The black chains were slow. So there were just a lot of use cases that you just couldn't do on them.

59:53I think that's changing very, very fast things are, you know, the change so much faster, the later two stuff makes them, you know, very fast and cheap. You know, people are doing a lot on usability, you know, for a while it's in 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, World coin, 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.

1:00:34I think that, you know, if they are able to get integrated into some of the big social platforms, then you know, everybody needs proofy human. And you know, like it would make the experience online so much better if you knew who was human and who was not. And right now, like, you can't tell at all. And so, and and that problem is going to get worse. And then the solution is really here. So 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. And once the infrastructure is deployed, I think we'll certainly rely on it.

1:01:19And if you look at actually the curve of people who have active wallets and the curve of like internet adoption, they're pretty similar.

1:01:31It's about, I think, Blackchains growing a little faster than the internet did initially. And so I think we'll get to a place where it's certainly everybody in the US will be on it. 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, yes please. We never get into this weird situation now where like half the country wants to tear down all the government services and half of them wants to keep it because nobody knows what the hell the spending is.

1:02:06But that would be great. But you know, beyond that, like if you think about, well, why is there so much waste in 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 And well, how does it get to the people who need it? That's a very law -seed process. And we don't even know who they are. And it's very, you know, one thing we found out during COVID, the government's not very good at sending people money. It's good at taking money. It's not a good at sending them money, right?

1:02:41We lost like $400 billion trying to give people ridiculous. Right. Ridiculous. Yeah, crazy. Ridiculous. But, 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, you know, whatever my tax bill is or whatever that portion of wealth redistribution is, that would be 100 % zero loss. But I feel a lot better about it because I know I'd be helping people. And, you know, look, maybe even somebody would go, Hey, this is great.

1:03:20And we're like, maybe we would bring us, we wouldn't have this crazy class warfare because everybody would go, hey, but 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 And in order to get money, you have to have an address which registers you would vote. And so that kind of thing I think could get us to it just like a much higher trust in our own institutions.

1:04:01Yeah, 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 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? Why? Why is he doing this? Is it just to get government contracts and it's nefarious and the way that so many people think it is or is there something positive there? What's the game? I think there's a couple of different things. So one is the strong thing is he truly believes that America's the best country in the world.

1:04:46He is an immigrant and that it's not guaranteed to stay that way. And we have been in danger of losing it. 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 to stabilize US government. And I think that's the main thing driving him. So then you say, well, how did he get to that conclusion that the whole country is in jeopardy? And it really, it was a pretty interesting thing to watch because right in 2021, I think he was a Democrat and he was certainly pretty apolitical.

1:05:31And I was actually in a chat group with him when he got the idea or posed the question and should he buy Twitter? And a lot of it stemmed from, you know, it started with the US government just harassing him, 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 was our entire space program. He advanced the state of electric cars by 20 years. He's still like 95 % of there is something like that percent of the electric car sold in the US. You know, he's, you know, done the things with Neuralink to, you know, help people like use their arms and legs who have been paralyzed and this kind of thing.

1:06:22So, you know, you've got, you know, he's a really kind of remarkable person to want to pick on, but what happened was because he got like this PR for being very wealthy, the Biden administration targeted him. And again, they're fascists. So it's really a power struggle always with the fascists and anybody who looks like they're becoming powerful. And some of the things they did, and one of the ones that's talked about a lot was they sued him, the Biden Department of Justice sued him for discriminating against refugees. But he had a contract with the US Department of defense that required him to only hire U .S.

1:07:07citizens. So he was breaking the law either way. And they never dropped the lawsuit. Even after it was pointed out, even after it was pointed out by Congress. So it was clear harassment. And I think that his conclusion from that was, we are ironically, I think his conclusion was we're losing the democracy. we're going into this very, very strange world where the incentives are all upside down. And, you know, the way Elon thinks is it's up to him to save it. 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 were dangerous.

1:07:54And then secondly that he personally would be somebody who would know how to fix it. And you go like, well, why the hell would Elon must not fix the government all this? And you know, this is the thing that everybody's saying now. And it's funny because I told this to Andres and years ago. Was because I'm a big fan of Isaac Newton. And you know, like we always talked about like, who is Elon like? like, you know, like what entrepreneur comes to mind, you know, and it really wasn't like, maybe Thomas Edison, but not really. But Isaac Newton was really the one that I always thought he was most like, you know, because it's like, okay, who can build like rockets and cars in this and that and the other.

1:08:43But the reason I thought he was like Isaac Newton was at the end of Isaac Newton's life. But I think he was in his late 60s, maybe like 67, 68. And this is, you know, for those of you who don't know, I said, Newton, like, he figured out how the entire world works and brought it down in a book, you know, called Prince of P. M. A. A. T. O. which is probably the most amazing work in the history of science. 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.

1:09:18But it gets to be like in his late sixties. And the Bank of England has a crisis, which is causing a huge crisis for the whole country, which is there's a giant counterfeiting problem. So the currency is going to be undermined and England's going to basically go bankrupt. And so they had no idea what to do about it. So they call Isaac Newton because he's the smartest man in the world. Of course you're going to call him. So Isaac Newton, 67 year old, like, 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 doge, whatever.

1:10:02And he reorganizes the mint in like a week and then fixes the technology in a month and completely makes it impossible to counterfeit. it, then he becomes a private eye and goes into all the pubs where the counterfeiters are arrest all of them. Then he learns the law and becomes the prosecutor and prosecutes all the counterfeiters and has 100 % conviction record. And that by the way, that's Elon. So if you have this is what I didn't know that part of his story. Oh yeah, yeah, yeah. So it's an amazing thing. And if you look at Elon and Doge, like that, to me, the most remarkable thing about Doge is how he's done it.

1:10:47So if you were I, we're 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, no, no, no, no, that's not how he thinks. He's like, well, the first thing, like, how do the checks go out? Like, how is this system designed? Like, when does the money lead to 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.

1:11:25Like, I'm getting to ground truth and then I'm going to work my way backwards from there. And he's probably, and you know, so not only is he not unqualified, he's maybe the only person qualified to figure out like how we're spending $7 trillion. And so, you know, so I, so, you know, he's just a very unique individual. He's also a troll. He also likes upsetting people. I get all that, But what he brings to the table is pretty interesting, I would say. Like very extraordinary. Yeah, I would say very extraordinary. You have also written about another extraordinary historical figure from the Haitian Revolution, a guy named Tucson.

1:12:12To sound love or true, yeah. Yeah. Tell us about him because there's something about this moment, about being a master strategist, about using what you have being creative that feels like it's very apropos to this moment. What made history special? Yes, it's just that was another one of these characters in history. Like there's certain I calm like once in every 400 -year type people where you just don't see them that often. But so it turns out like in the history of There's been one kind of successful slave revolt that, like, entered in an independent state, 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.

1:13:07So 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. but why only one successful one. And it turns out it's really hard for to generate an effective revolt if your slaves because slave culture is difficult because you don't, right, if you don't have any sense of owning anything, you don't own your own will, right? Like you are at the kind of pleasure of who's ever running things. So long -term thinking doesn't make sense. And what it, because like why plan for next week, it doesn't matter what you plan, like it's not yours. So everything's going to be very short term.

1:13:59And short termism is difficult in a military context, because in order to have an effective military, there needs to be a trust, right? Like a trust, you have to be able to trust people to execute the order. Like I give an order, it's kind of like the Byzantine generals problem to go back to crypto. Where like I have to trust that you're going to do the order or you have to trust that I'm giving the correct order. 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 there is no long term.

1:14:39So there is no tomorrow. 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, you know, you had the French army, the British army, and the Spanish army all in there kind of fighting for it. So like really well developed, you know, the kind of the strongest militaries of the era, all in that region, all very interested in the sugar, which was quite valuable at the time. So how in the world would you ever get out of that? And it turned out, he ended, he was probably the great cultural genius of the last, maybe in history, but certainly the last several hundred years.

1:15:30And he was able, 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 so the person who ran the plantation 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, so to speak, and the different subtleties around it. And he started adopting those things and applying them to his leadership and then furthermore incorporated Europeans into the slave army. So he would capture, he would defeat the Spanish, capture some guys rather than kill them.

1:16:17He'd incorporate the best leaders into his army and he built this very advanced hybrid fighting system where they used a lot of the guerrilla techniques that he had brought over from Africa and then he had, you know, combine that with, you know, some of the, the kind of more regimented, kind of disciplined strategies of the Europeans. And in building all that, you know, he, he ended up building this massive army and, you know, defeated Napoleon and then, and everyone else. And it was like just quite a remarkable story about how he just kind of figured everything out from her as principles. And in a way, yeah, that was, you know, kind of very much like Elon in that sense.

1:17:05Yeah, one of the things I heard you talk about. Yeah, 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. Yeah, it's really. Yeah, so that was that was that cool thing. So, right, remember that this is in the days before telephony or the internet or any of these things, you know, it's pre Alexander Graham Bell and all that kind of thing. And so, you know, 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.

1:17:43And so as a result, you know, you kind of needed the army together in one place just so you could communicate the order. To Sant basically, you know, had these drummers in these songs, which you could put on top of like the hill, who could be very, very loud, and then he would separate his army, you know, into like six or seven groups. But in the song would be embedded the order of when to attack and, you know, went to retreat and all these kinds of things. So he had this like super advanced, wide area communication system that nobody else had. And that's a big advantage for him. Yeah, the reason that that comes up for me now is we have all these new technologies that are coming online.

1:18:33And the person that's gonna be able to get outside that box and see something new and fresh is gonna be able to use this in totally different ways. And while in the final analysis, is I think you and I see it very differently in terms of AI's ability to ultimately gobble up what humans can do. But right now, AI is this incredible tool that as an entrepreneur, for me, it has been 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 and where the tools are gonna be and how much more they're gonna let you do, cause we're largely an entertainment company.

1:19:16So for us to look at that and 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 a really great way of thinking about it and that it's like, well, is your creativity gonna be used on, And you know, kind of frame by frame editing of like a video or well, it'd 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 a little bit of a readjustment of where you put your creative energy into and the things that are possible and so forth.

1:20:03And I think that's, you know, we're really seeing that across the board. like in our firm, we're playing 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 these like painstakingly collecting, you know, all the data needed to put the investment memo together, like, yeah, it just does up for you. And then you're just thinking about like, okay, what are the like the really compelling things about this, or rather than 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.

1:20:51Maybe you should call him. And that kind of thing, which is just like a much more kind of fun part of the game. And so, you know, look, I would say the best predictor of kind of how things are going to go or more like what's happening now than like the most dystopian view of it that we can possibly think of, which 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?

1:21:33Yeah, well, I am B. Horowitz on X. And, you know, that's probably the best thing where A16z .com. And I hope you enjoyed it. And that was great fun, good fun catching up. It was indeed. And then you also have multiple books that people can read that are extraordinarily well respected in the field. So also thank you for those. Absolutely. Awesome. Thanks so much. All right. Well, thank you, brother. I appreciate it. Bye, everybody. If you have not already, be sure to subscribe. And until next time, my friends, be legendary. Take care. Peace.

1:22:11Thanks for listening to the A16z podcast. If you enjoyed the episode, let us know by leaving a review at ratethispodcast .com slash A16z. We've got more great conversations coming your way. See you next time.

From the publisher

This week on the a16z Podcast, we're sharing a feed drop from Impact Theory with Tom Bilyeu, featuring a wide-ranging conversation with a16z cofounder Ben Horowitz.

Artificial intelligence isn't just a tool — it's a tectonic shift. In this episode, Ben joins Tom to break down what AI really is (and isn't), where it's taking us, and why it matters. They dive into the historical parallels, the looming policy battles, and how innovation cycles have always created — not destroyed — opportunity.

From the future of work and education to the global AI race and the role of blockchain in preserving trust, Ben shares hard-won insights from decades at the forefront of technological disruption. It's a masterclass in long-term thinking for anyone building, investing, or navigating what's coming next.

Resources: 

Listen to more episodes of Impact Theory with Tom Bilyeu: https://link.chtbl.com/impacttheory

Watch full conversations on YouTube: youtube.com/tombilyeu
Follow Tom on Instagram: @tombilyeu

Learn more about Impact Theory: impacttheory.com

Timecodes: 

00:00 Introduction to Impact Theory with Ben Horowitz

01:12 The Disruptive Power of AI

02:01 Understanding AI and Its Implications

04:19 The Future of Jobs in an AI-Driven World

06:52 Human Intelligence vs. Artificial Intelligence

10:31 The Role of AI in Society

21:41 AI and the Future of Work

35:07 The AI Race: US vs. China

41:25 The Importance of Blockchain in an AI World

44:26 Government Regulation and Blockchain

45:16 The Need for Stablecoins

45:45 Energy Challenges and AI

49:53 Market Structure Bill and Token Regulation

53:51 Blockchain's Trust and Adoption

01:04:17 Elon Musk's Government Involvement

01:12:03 Historical Figures and Modern Parallels

01:18:41 AI and Creativity in Business

01:21:29 Conclusion and Final Thoughts

Stay Updated: 

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Find a16z on LinkedIn: https://www.linkedin.com/company/a16z

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.


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