transcript

Speaker 1:
[00:00] We don't just want to go direct, we want to prove correct. In a sense, what the blockchain is, is like an armored car for information, we can transport that information on chain. So, easy to verify, difficult to fake, becomes a critical thing in any system that deals with strangers, which is lots of systems. Literally, fake photos almost justified some crazy war on Brazil and the Atlantic. The point is to trust us, the point is to not have to trust us. The point is to have system by math that anybody can look at. And the reason that they would trust what we're doing is they don't have to trust what we're doing. They can cryptographically verify it, put out your own opinion, but prove the facts. Okay, and how do we prove the facts? Cryptography, mathematics, that's a property of all human beings, not some New York media corporation.

Speaker 2:
[00:55] As the cost of creating content approaches zero, the cost of verifying it is rising just as fast. The result is a growing breakdown in trust across media, hiring and online communication, as synthetic content floods systems that were never designed to handle it. In response, a new stack is emerging, built on cryptography, on-chain data and verifiable records. Instead of relying on institutions to assert truth, these systems aim to make truth provable. In this episode, I speak with Balaji Srinivasan, angel investor, entrepreneur and author of The Network State, about what replaces trust in a world of infinite content.

Speaker 3:
[01:36] Back, live in the Situation Room with a16z, new media general partner, Erik Torenberg, and we have Balaji Srinivasan, the founder of Network State, who is our first special guest live in the Situation Room. Balaji, welcome to the Situation Room for the very first time.

Speaker 1:
[01:54] Well, thank you and technically, by the way, I'm the author of Network State, founder of Network School, ns.com, but I'm also an investor in MTS. Wow, how about that? Erik is going to RT that or something like that after this. So I'm very pleased. Erik and I have been talking about media stuff for a long time. Erik's been crushing it. And this is looking gonna, looks like it's gonna be fun. Go ahead, Theo.

Speaker 2:
[02:19] Balaji, why don't you contextualize where we are right now in this media moment, right? We've been talking about where tech fits in, how tech needs to build its own media landscape. We've also been talking about how the New York Times has continued to grown. How do you make sense of where we're at in 2026 as you've been on this 10 plus year quest to not just understand the media landscape but also build within it?

Speaker 1:
[02:47] That's right. So, okay, essentially, there's a long version and there's a short version which is, tech and media actually share a common route in that we're both about the collection, presentation and dissemination of information. Right? So, the collection of information like their sourcing, our data, right? Presentation, user interface or articles, dissemination, distribution whether on social feeds or newsprint or taboo, right? So, at a very structural level, we are the internet first digital alternative to the 20th century printing press, newspaper kind of model. We are essentially a contender, a competitor for what is upstream. You know, if you ask the question of what is upstream of, at least in the West or in the Anglosphere, and you keep asking the question, what's upstream of a factory? Well, it's, you know, political this and it's capital and what's upstream of that? Well, it's eventually you get to money and media because media is upstream of politics and money is upstream of media, but media is also upstream of money and that's in Ouroboros where that circle eats its tail. So the venture capitalist and the journalist, right, the tech and media are actually sort of locked in a struggle for what is upstream, right? And that's like a good way of seeing it, like who's at the control panel, flipping the switches, hitting the buttons and so on and so forth. And with the advent of the internet, over the last 10 years, really the last three years, essentially speech has actually been freed for the first time in our lifetimes, because until, you know, essentially the 2010s, like you know, there's that saying, freedom of speech belongs to those who, freedom of the press belongs to those who own one, or never argue with the man who buys ink by the barrel, which meant that unless you had a newspaper that you inherited or a TV license or a radio license, all of which cost many millions of dollars, you could talk to your neighbor in the 80s or 90s, but nobody could hear you, right? With the advent of social media and Twitter and blogs and so on and so forth, all these voices that previously had no distribution had distribution, which caused a cacophony and all of these kinds of chaos in the 2000s and 2010s and early 2020s. And there was a counter reaction that tried to censor all those voices and a counter counter reaction that uncensored them with Elon's purchase of X. And that has brought us to the present day. And one of the consequences of that was the media was, though we didn't set out to do it, like Twitter set out to basically be tweeting breakfast, right? Facebook set out to share likes and poke people or what have you. And those ended up disrupting classifieds and disrupted legacy media, disrupted print media. There's a great graph of the print media disruption. So as a consequence, imagine a kid who just grows to be 6'6, 250 in an elevator and squashes everybody against the wall, right? That's like what the internet was, right? Where we just like grew and just added all of this, you know, muscle mass, and we didn't mean to do it, right? But we became really, really, really, really big and went from cute gadget makers and toaster makers to, in my view, the single most important force in the world that's still underestimated. You know, you know Orwell, the, you know, the writer, obviously, in 19... Yeah, so he had this saying, which is, it takes an enormous effort to see what is in front of one's own face. And what's in front of our own face? Basically, every single moment of the working day. The internet? The internet, that's right. You know, what's upstream of AI? The internet. What's upstream of drones? The internet. What's upstream of your finance feed? The internet. What's upstream of the data center spend? The internet. It's internet first, right? In the sense of mobile first or macros, internet first, internet first. Where's your community? It's internet first. Where's your business? How are you sharing your business? Internet first. How are you finding information? Internet first. So that is actually the organizing principle. Like, you know, fish can't see water. We swim in a sea of electrons. And that was not the case in the 80s and 90s, right? We have essentially been teleported into the matrix right now. You watching this, hearing this, you are in the matrix.

Speaker 3:
[06:51] Shout out to all the fans, all the viewers.

Speaker 1:
[06:53] Yeah, all the fans. Exactly. That's right. We're monitoring the situation where? On the internet, right? So the global internet, you know, the closest precedent to it, by the way, just to digress on this for a second, is the ocean. And the reason is, you know, there's something called the Law of the Sea. The Law of the Sea governs how, you know, because you have ships that are going from Britain to Hong Kong to Brazil and so forth. And so you have international waters. And what country controls that? And you could very legitimately have something that was thousands of miles away, but it's flagged British or Portuguese or what have you. And so for hundreds of years, there's something called the Law of the Sea that kind of governs that. Like when you're sending a packet from one port to another port, what law governs that? And we actually use the same words today. When you open up a computer, you have one port and it's sending packets to another port, right? And so how can that information, how can those packets be sent? What can they do? And so on and so forth. The rule of code on the internet is like the new rule of law. It is the new law of the sea. And you can think of the cloud as like the new oceans in this way, right? Ideally, a demilitarized zone, but of course, there's also navies, right? So with that macro context, let's bring to this moment. You know those zombie movies where like, at the end of the movie, the zombie opens their eyes and like claws their way back like this, right? Okay. So there's a guy who's a good guy named, he's a good analyst called Philip Lemoyne, okay? He's PHL 43, all right? And maybe we can put this link on screen. Can we do this? Hold on, let me send you guys a link. Bang, bang. Okay. Can you guys see that? Can we project that on screen?

Speaker 3:
[08:47] Let's take a look.

Speaker 1:
[08:55] PHL 43 is a very smart guy, good poster, French guy, okay? I'll tell them when you got this on screen. All right, so.

Speaker 3:
[09:04] Screen sharing, can we get this on screen?

Speaker 1:
[09:05] There we go, all right. So I like both Nate and Nikita, okay? And they were basically talking about link de-boosting. And Philip found something important. So if you scroll down and look at these graphs, just click the graph, the first graph or the second graph will say it, all right? So essentially, like a zombie movie, basically the New York Times, their distribution collapsed after peak woke in 2020, 2021, 2022. And after Elon took over X and he de-boosted them, they basically went to complete zero, 2024, 2025. But with link de-boosting turned off, and the kind of repositioning of the American left to basically be less woke, and there's more I can say about that, they are now trying to occupy some of, I shouldn't say the center again, that's not exactly right. But let's say facts that Republicans don't want to publish, right? For example, facts about the war or things like that, right? Now, boom, look, their distribution has come back, right? And so the tactics that worked five years ago, like going direct, we do want to still use them. Don't get me wrong, it is important to speak for oneself and so on and so forth. We don't just want to go direct, we want to prove correct. Okay, that's the new, that's the next five years. Why? What happened in that intermediate era in 2022 to 2026? AI. And look, there's a lot of good about AI, but there's a lot of bad about AI. And if I love AI, I also hate AI. Why? I love AI because when, you know, I've got a rule, it's called no public undisclosed AI. What that means is private use of AI for search, for code, when you're not trying to bamboozle somebody, not trying to get one over on somebody, fine, good. It's great for research, all that kind of stuff. Awesome. Public disclosed AI. When you put out a video that's obviously a cartoon or an animation or something along those lines, it's obviously AI, so nobody feels you're fooling them. But public undisclosed AI, when it is, it's not this, it's that, M-text, right? Whenever I see a slide deck that has AI content in it, it's a new Lorem Ipsum. It's Lorem AI Ipsum, right? Like just add an A. It just shows that either they're dumb or they think you're dumb. They're dumb because they can't tell the difference between normal text and AI text, or they think you're dumb and they can get one over on you and spend a little bit of effort to just flood you with a bunch of words. And then as soon as I see that, I ignore it and I send it to zero because it takes only a little bit of effort to send a whole, you know, just mash of a ton of words. And I don't know if any of them have been checked or read through or whatever. And so anytime I even detect there's a hint of AI in a communication to me, I set that to zero. And I set that person, it's a significant downgrade. And I think this is going to be baked into social networks where something like pangram.com, you know. Now, people will tell me, and of course it's true, that you'll never have a perfect AI detector. And so of course that's true. However, you can do really well, if I can recognize it with a naked eye, and you can see it's not this, it's that. Many people are just going to, you know how like Windows has a background where most people don't change the default? Yeah. Right? Yeah. Just like that, most people don't change the default settings on AI. They don't prompt it so aggressively that it's actually creative. Once it busts out of that, I actually don't have a problem with it because then it's like so good that it doesn't look AI. But if they haven't polished it enough, then if it's detectably slop, let's put it like that.

Speaker 3:
[12:49] Trying to find it, but then I think... Yeah, there was a recent study about AI writing in newspapers becoming like increasingly common. And yeah, only five out of 100 actually said they used AI. And this is October 2025, and AI adoption has gone up quite a bit since then.

Speaker 1:
[13:09] Quite a bit, and go to pangram.com, for example. P-A-N. So, I think this is pretty cool. I think something like this is going to become more and more common. And basically, you know, it's Alien vs. Predator, right? And an enormous part, see, one thing that most people don't get, when they talk about the jobs and so on and so forth, right? I have a post, you can look at it, if you go to balajis.com, or just balajis.com, right? And go to read it first, and click, AI is polytheistic, not monotheistic? Yeah, that one, yeah. So, I think this is a good, I think this is a good post, right? But basically, just points here. First is, the entire AGI framework that is sort of implicitly monotheistic, it presumes that there's going to be a single, going all-powerful AGI, but in practice, we're seeing a polytheistic AI of many decentralized models that are good at different things. Number two, AI does its job, it lets you do any job because you can be a passable sound effects creator or UI designer. You're not amazing, but you can be like, you know, it's number three, AI is amplified intelligence, not artificial intelligence. You know, the smarter you are, the smarter the AI is. Number four, AI doesn't do it as it middle to middle because you still have to prompt it, you still have to verify it. Then number five, AI doesn't take your job, it takes a job of the previous AI. Okay, what that means is the way I process all the change that comes with AI models, I have a spreadsheet which has rows for what's the best AI coding model, what's the best AI image video model and I have a column which says January 2026, February 2026, March 2026 and when I determine that a new model has come in that can open its job or vice versa, then the AI takes the job of the previous AI. Okay, so AI doesn't take your job necessarily, it takes the job, right? The next is AI is better for visuals and verbals, so it's better for the front end, it's better for movies and things like that because your eyes have effectively built-in jeep. It immediately detects subtle things with the hands or this doesn't look completely photorealistic or whatever in a way that it takes you much more time when you're reading code, one bit off that completely changes a cryptography result that it's very hard for you to detect with your eyes. Because you have to do system two versus system three. And Karpathy also talks about, he agreed with me, the verification gap is actually a very big deal. Then another point I made, again, now perhaps, but killer AI, it's actually already here. It's called drones. And every country is going to pursue that. So the whole concept of, oh my God, let's regulate the chatbots and the... I'm not saying that one doesn't want to have some countermeasures on that, which I'll get to in a second. But like the idea of what's going to kill you, it's not going to be the drone that's a physical actuator shooting you. It's not just going to be like the super intelligence that makes things, right? The next point, AI is probabilistic while crypto is deterministic. AI and crypto are actually complementary. Crypto is what AI can't do, okay? Because, AI can solve, you know, partial difference equations, but it can't solve chaos, it can't solve turbulence, right? When you've got ODE's or PDE's that are chaotic or turbulent effectively, it cannot forecast the outcome of a hash function because, you know, like these are things which approvably cannot do what's computationally irreducible.

Speaker 3:
[16:53] This is a big wall from idea, I think it's kind of underrated in the discourse.

Speaker 1:
[16:57] That's exactly right. Sorry, I should say, it can't easily calculate the preimage of a hash function, right? So, there are mathematical and physical bounds on an AI. Like, for example, you could have a turbulent, you know, source of entropy that would be something in the decision algorithm that AI approvably could not forecast because it couldn't forecast what was going to happen to the turbulence, right? So, it's simply not omnipotent, people are treating it as if it's omnipotent, it's simply not, right? Even like, you know, a pendulum, you know, with a few different weights on it, there's different ways you can quickly get into chaotic or, you know, that kind of behavior. So, empirically, right now at least, and you can argue at this point, whether AI is centralizing or decentralizing, but I think there's so many AI companies and there's so many AI models out there that it's pretty hard to put a lid on the thing. And then finally, if you go to the end, the optimal amount of AI is not 100%. If you scroll down a little bit further, right, 0% AI is slow, but 100% AI is slop. Just having that concept in mind means that in almost any process, you do not want to have 100% AI, but you probably, and frankly, sometimes you want 0% AI. You often want to just learn offline with pencil and paper, and then speed up with AI, because AI is a shortcut. And like any shortcut, it can be overused to the point that you don't know how to take the long cut, right? Okay, this is a laugh recurve, but for AI. And then, you know, I talk about how referential is this. Whoa, we're referencing Torenberg on Torenberg.

Speaker 3:
[18:26] A16z podcast mentioned? Yeah.

Speaker 1:
[18:29] A16z podcast, that's right. This is recursive, right? And fundamentally, my worldview on AI is it's constrained AI. It's economically constrained, because every API call is expensive, and now it's energy constrained, right? There's so many competing models, it's mathematically constrained, because it can't solve chaotic, turbulent or cryptographic equations. It's practically constrained, because you have to prompt and verify it, and does it middle to middle, rather than end to end. And it's physically constrained, because it requires humans to sense context and type that in via prompts, rather than gathering that all for itself. And this is very different than the people who look at AI as AGI, Deus Ex Machina, that's just going to solve everything, right? To be clear, this is as of this time of writing, maybe somebody overcomes it, but at least I'm describing what the constraints are on the current generation, right? You could, in theory, unify the probabilistic system one, impressionistic thinking of AI, with the logical system two thinking of that computers are good at, and Claude Cote and so on is starting to get there, perhaps. But I think it's still something where context breaks down and so on. And also somebody, you know that famous graph that people show that it can do longer and longer problems?

Speaker 3:
[19:34] The meter graph, yeah. The big profile in the New York Times about that graph a few days ago.

Speaker 1:
[19:40] Yes. That particular graph, I saw a very good, you know, once in a while out of a thousand replies on X, there's somebody who's actually, you know, gem award, right? How do they put it, right? Gem alarm. Okay. Gem alarm. Yeah, exactly. Right. Fine. So there was a very good counter argument that actually said that this study does not purport to show what people think it's purporting to show and that the task of completion, it's like, it's much more questionable than it actually looks, right? And this is important because a lot of people's paranoia and stuff is levered on this. Yeah, that's it. I think that's it. Against the meta graph, right? Can we pull that up? And pull that up, right? So yes, this was like, this deserves more people looking. But fundamentally, he says actually, you know, the graph doesn't really look like this because A, a lot of the tasks aren't and B, like, what is completion? You know, they're TLDR. Now, I don't want to overstate this because it's certainly true at a gestalt level, that if you use Claude code or Claude co-work or something like that, it is possible for AI to complete long complicated tasks than it could a few years ago. That's clearly true. However, it's also true that you still have to supervise it a lot and check the output. It's a little bit like I compare to a spaceship that can go in any coordinate direction that you pointed in and move very fast, pivoting it and give it the route that it's moving on. It's like a car. It will take you there very fast, but then you have to still give it a direction. Now, the new thing is everybody's got a car, so now car race as opposed to you just being able to teleport somewhere. So, this guy is pretty critical of it, and I think this is worth reading carefully and maybe figuring out what the true graphs are from his critique of it. Taking into account that you have to be careful with Claude Code and Claude Code work and so on and so forth, definitely. But also taking into account that it basically like speeds up, I don't know, your guy's view is on this, but I find that it's basically like managing, you know, where you have to write the whole thing up, context, and that's actually a lot of work, the context engineering, you know what I mean? Because you're sensing the world and you have to articulate that in clear written English and describe exactly the result. The prompting and verifying then just takes up all the work. That brings me to my next point, which is, AI actually destroys arguably as many. You know why? Why? Because, for example, take resumes, right? AI makes, it wasn't that hard to make a resume before. AI does make it easier. You know what makes it hard to verify a resume? AI makes it easy to write an email. It wasn't that hard to write an email before, but now it makes it really hard to filter them. Okay, so many market strangers between tribes, right? So, recruiting, sales, marketing are being destroyed. A spam, AI slops, AI scam, anything which is between economically disaligned tribes, there's so much that that channel is now defeated. It wasn't built for that level of adversarial behavior. It wasn't built for a channel where 99% of inbound is that it can beat the probabilistic fake detectors, like AI spam detectors broken, right? Your normal filter is broken. So, what happens is people, digital tribes, they retreat to deterministic trust and it's only the warm intro that gets through, okay? So, the sales market is being broken by AI, broken by, like people will sometimes show me these products and they're like, I've got this AI agent and it just spams your resume to like a thousand companies. And I'm like, great. It's going to like leach out what trust remains in the ecosystem, where everybody claims they're a machine learning superstar, blah, blah. And normally, pre-AI, you could just read a resume and it's scarce to be able to write well. And now you have to carefully, I mean, people do keyword stuffing, it's true. But still, like good writing was relatively scarce. Now, where it's much less scarce, but scarce is concise writing. Fine, okay. But we need a completely different paradigm for sales, for marketing. I have a whole thesis on this. I think that we're going to have to literally rebuild, like Web3 actually becomes a thing, where the open web, Web1 just gets completely corrupted and Web2 becomes walled gardens. But Web3 is the hardened cryptographically provable signed web, the open web, where things are on trails and you can actually, it's like a diamond, it's hard. AI is like a slithering thing around this diamond of cryptography that it can't fake, right? So you can prove that so-and-so signed this and AI can, like for example, a letter of reference can be cryptographically signed, and you can show that so-and-so endorsed you as opposed to saying that it happened, right? That's a longer topic and actually we're building stuff related to that network school, which I can talk about. But the point is the entire concept that's going to solve everything. So actually, for example, if you take just that sales or marketing or recruiting market, the level of economic damage that AI did there is actually better than the benefit. Because it introduced easy fakes into a system that was not calibrated for that amount of easy fakery. Yeah, it's generating a resume, but it radically increased the cost of verifying a resume, such that less hiring happens. With me so far?

Speaker 3:
[25:28] Yeah, just anything that requires some kind of like proof of what happens as like writing text is kind of gone now.

Speaker 1:
[25:37] That's right. So what that means is AI will create lots of jobs. In proctoring and right, you have essentially the whole KYC economy, the entire, like all the stuff that people do for face ID, and biometrics, all that stuff merges with proving you're a human, you're unique, all those things merge together becomes like this critical, critical thing. Can I log into a system? All the identity, authority, all that stuff will increase 10x from where it is today, maybe 100x. Prove that you are a human, that you're unique, that you have the credential that you say you do, the endorsement that you have you do, like have multiple things. It's not just one thing. It's like all of these. Prove it cheaply for yourself, but very hard to fake. Example, having, I won't give out your email, Erik, but blank.com, that is easy to verify, hard to fake. Right? Because you'd actually have to break into the cryptography, like an email.com is something that actually carries a lot of signal with it, but it's just one click for Erik to verify that he has an a16z.com email, but it didn't have DNS access and the private keys effectively associated with the a16z.com domain to get the MX record and Gmail access to that email username. Does that make sense? Right? So, easy to verify, difficult to fake becomes a critical thing in any system that deals with strangers, which is lots of systems. It becomes an untrusted environment. I haven't even gotten to fake video, fake photos. This gets me back to media. Right? The reason, can we go back to that, Philip LeBlanc? All right, here is the... Pull it up. Yes. So, here is the part of the reason that's happening. It's not just, right? It is something where, like, you know, I kind of... Here, let me put this article on screen. Here we go. New one. You know, old Balaji, like, I'm a reality show, right? So, it's about just observable reality, what our constraints are, what the battlefield is, and so on and so forth, right? So, Jason, who I like, you know, if you scroll, he is basically posting something that was posting in 2021, which is Go Direct and so on and so forth. And if you do from colon Balaji S, you can see Go Direct. Nothing wrong with that. Actually, in fact, Allin has done a good job. All great, right? However, this is necessary, but not sufficient. The reason is as follows. If you go back one, the issue is that due to AI, and also due to the fact that, in my view, in some ways, significant ways, MAGA has over-corrected to the right in a huge way. Now, A, people can't tell what's real, because when you see a photo or you see a video, it literally, you literally don't know if it's real or not. Crazy bomb or something like that. Maybe it's often like some bombing from Turkey or something like that.

Speaker 3:
[28:47] I think it's even worse than that, which is that a lot of these things are like obviously fake, and then they get tens of thousands of likes anyway. And X, as it exists right now, doesn't really have a good mechanism for filtering that garbage out.

Speaker 1:
[29:00] That's right. So you have A, obviously fake stuff that we know is obviously fake. B, non-obviously fake stuff. C, stuff that's real, but it's faked in terms of, it's a video, it's presented a video from that time and place, and everything there. And that makes you very cautious about, like it used to be that video and photos were pretty hard. Though, for example, like the Brazilian fires, like of years ago, there was a big, you know, like aerial photo of a fire, and it was being used to justify, and it was actually a photo that was from a journalist from like years and years earlier. And the timestamp that showed that it was, here, let me, I'll find you this thing, hold on. It was like a fake photo that the Atlantic thought was real, right, and because of that, they were, there's literally a guy who was like calling for invading.

Speaker 3:
[29:52] The three most viral photos of Amazon fire are fake.

Speaker 1:
[29:56] Yes, here we are. So if you click this, right, chat to you. This gives you an example of, yeah, so click my thing there, okay. So just to show you why timestamps and cryptography are so important, right? Click those images, right? Emmanuel Macron used one of these misleading viral photos 40,000 times, embedded in New York Times article. The photo was taken by Lauren McIntyre, died in 2003. In other words, the that showed when that photo was taken. It was taken many years ago, right? So these guys were saying like, you know, the case for territorial incursion to Amazon is for most war. Basically, literally fake photos almost justified some crazy war on Brazil in the Atlantic. Okay, that's bad. So and New York Times Atlantic, like this is a canonical example of where decentralized cryptographic truth was able to defeat core. Okay. And so we have to go to our and I can give more examples of this, right? So basically, you know, three examples. Here, let me show you this. So here's one, okay. This now was from years ago when photos, fake, now this could be faked, okay. But from years ago, Vitalik was able to show proof of life when people were saying that he was, you know, was not real. And tell me if you got that on screen, okay. Then click into that thread underneath. So you see, I've been thinking about this for a long time. This, yeah, just click into that, yeah. It's in the Brazilian photos. Scroll down a little bit further. I'll show you another example. Click this one with a graph there. Click the, yeah, that one, right? So this is something where Tesla had the vehicle log, fake NYT story by a guy named John Broder that claimed that, oh, Teslas were, you know, they ran out of battery on the side, got a photo of a Tesla, you know, being hauled onto a truck. And Elon actually had the instrumental logs and was able to use digital evidence to the verbal narrative, right? This, by the way, is one of our core strengths. Numbers over letters, okay? We can actually be quantitative, we can verify things numerically. That is actually a power that journals are generally pretty bad at, right? Digital history, unfakable cryptographic history. Go a little bit further, I'll give you a third example. So, yeah, do you see this? Defendant proved that its content, so this is in a Chinese court. There's a patent suit and the defendant showed, yeah, so this is like eight years ago, defendant proved its content was really produced by showing two hash values, one on the Bitcoin blockchain artifactum, it had hash of relevant data onto relevant chain, and stamped that infringement would have been impossible. Isn't this cool? That is cool.

Speaker 3:
[33:06] Rules that data stored on the blockchain is admissible as evidence in trial due to the characteristics of the tech.

Speaker 1:
[33:12] Eight years ago in China, so this stuff is actually almost a decade old at this point. You know, the saying, the future is already here, it's just not evenly distributed, right? So, it's very important that, and this is a broader thing in tech, okay? Like, we as tech guys feel, okay, yeah, we're, you know, we're and so forth. But the point is to trust us. The point is to not have to trust us, okay? The point is to have the system accountable by math that anybody can look at. And the reason that they would trust what we're doing is they don't have to trust what we're doing. They can cryptographically verify it, in the same way that you can check whether a website has SSL via the HTTPS lock symbol, whether you can, you know, check the email address, right? Whether you can check whether someone has DNS access with a TXT record, you should be able to check via chain check. Another way of thinking about this is, you know, if you send somebody something on, I don't know, a blockchain like, you know, Bitcoin or Ethereum, have you ever sent them the either scan or record to show that you sent the money? Have you done that?

Speaker 3:
[34:26] Hmm, I don't think so.

Speaker 1:
[34:28] Erik, you've definitely done that. Yes. Like, hey, I sent you the money, here's the transaction receipt, right? Yup. And for example, if, to give you a concrete example, if you went to Grok, Grok, tell me, you can do this live if you want. You say, hey Grok, use on-chain information, okay, to document the FTX hack that happened in late 2022, okay, and give all reference. Grok will tell you about a hack that happened of FTX at the time all the FTX drama was happening. And in particular, it will link to that have on-chain records that show that that event for that amount, right? There it is, right? So, this is what's called on-chain media. Crucially, the source of... is not the New York Times and Salzburger and Salzburger employees. It is the blockchain, right? That everybody has free universal access to. It's not paywalled. It's not something where you have to pay Salzburger for him to tell you what the truth is. It is something where you can see what the truth is, right? See, on-chain evidence and timeline, right? Initial inflows, right? So you can actually click and you can diligence it yourself. And if you ask and say, you know, give the, you know, like click. Exactly. See, give the... So this is something which can be done for those who are on-chain, right? So, yeah, exactly, right? So, but like, applying blockchain money trail, so can you, if you go back to the thing and you say, give the specific, give an example specific either scan link, right? And this is the, this is the rawest of the raw, I mean, it's not the rawest of the raw data. It's basically a URL, right? So click that, right? So that's something where, with a little bit of technical understanding, you can literally look, see what happened. What went to the FTX account strainer and so on and so forth, right? So you can pull all this data and analyze it yourself. You know, if you heard the term OSINT.

Speaker 3:
[36:53] Yeah, we're all about that.

Speaker 1:
[36:54] So this is, you're all about that. That's right. So this is like OSINT, but for on-chain stuff. So on-chain intelligence is like OSINT. Differences, and this is going to be important in my view. Right now, the verifiable information in crypto is mainly financial, where there's a major news event and some of the key things were happening on-chain. With Farcaster and, you know, Sudan Romero is the show. Erik, I think it's fair to say, right? Our friend, right? Yeah, exactly. Angel investor. Sudan came up with a protocol called Farcaster, and it's still an amazing protocol. In fact, you know, he basically, you know, he sold and, you know, he gave over management to the protocol to someone else, but sometimes protocol and it's beyond any one company. And so him, you know, going and doing something else, but the protocol being around, it's still this very, very powerful protocol that I want to do a lot with, essentially is like Twitter, but on chain. Okay. And allows anybody to post, anybody to read, anybody to write, and crucially to add, verify photos, verify videos, or at least give on chain evidence. So imagine if much more was on chain, not simply financial data, but much of what goes into an article. Years ago, I said something as a joke, but then it became true. I said, I gave a talk on what I call the let- You know, just like a sports article, right? Here, I'll find the talk, ready? I said, just like a sports article, it's a box score, right? Where you, you know, basically, you have a box score, you could automatically generate an article. A financial article is often a wrapper around a ticker symbol, right? A news article is often a wrapper around- and I've been thinking about this for years. You can see this post here, right? And then there's like, I just sent you a link there, right? Basically, let me send you the ledger record thing. So I've been thinking about this for many years, and the concept is that we can separate fact from narrative. If you have a feed of on-chain data and you have AI that feed, then you can auto-generate stories that have no bias because the AI agent summarized the on-chain data and it can summarize it in your language with your political orientation, and you can just change the reporter by flicking the AI flags all the way down to the raw data, which when it's financial, it's on-chain, and eventually when it's social, it's on-chain as well. Does that make sense, right?

Speaker 3:
[39:49] I just noticed, by the way, sorry, we have 53k live viewers on the stream right now. We have almost twice as many as Alex Jones, who has what? A million and a half followers.

Speaker 1:
[40:03] Hold on, should I RT this? Should I RT the stream? I haven't actually even RT'd it from my feed or whatever.

Speaker 3:
[40:08] Yeah, go for it.

Speaker 1:
[40:09] Please do. All right. Send me the link.

Speaker 3:
[40:12] I didn't expect that.

Speaker 1:
[40:14] So, okay. So, the reason all this stuff is... Yeah. So, okay. Sorry. I didn't mean to interrupt. So, go ahead.

Speaker 3:
[40:23] Here is the stream link.

Speaker 1:
[40:26] All right. Let me put this on screen one second. Is it on this feed?

Speaker 3:
[40:53] It's on my feeds, on Erik's feed, also at MTS Live.

Speaker 1:
[40:58] MTS Live, it's XMTS Live, all right. Let me go there. Oh, that's Ministry Training Strategy? No.

Speaker 3:
[41:08] MTS Live. We're meta-monitoring again.

Speaker 1:
[41:12] All right, here we are, monitor situation. All right. So, it's the, all right, here we go. Bang. All right. So, let's just put QT. So, on the new monitoring the situations with Erik. What's your Twitter?

Speaker 3:
[41:36] Theo Jaffee, T-H-E-O-J-A-F-F-E-E. All right.

Speaker 1:
[41:43] There we go. Bang, bang, bang. All right.

Speaker 3:
[41:52] Oh.

Speaker 1:
[41:53] All right. So coming back, what's my point? I have a talk on The Ledger of Record. You can put that on screen. It was also a good post, actually. Hold on, let me show you this. There's a... The reason is, I got to thinking about how would you actually adjudicate truth. If you just take a look at this, this is my kind of Twitter thread on it. But I will show you a pretty good post by a guy. He actually deleted it, but then I... Let me see if I can find it. If you look at this post, it's from 2020, right? You see where it says, the ledger, do you see it on the screen? This one? Yeah. Yes. The set of all crypto needs of on-chain data, social media feeds, CDAPIs, events, streams, newsletters, RSS, it will take years to be able to ultimately become the decentralized layer of facts that underpins all narratives. Closer to this, if you scroll down a little bit further, right? So click that, if you just click into that, right? So right now people were thinking about this in terms of payments, retail payments, back-end system, bank payments, market data, events data. But obviously, polymarket, all these prediction markets, they need to have news data on-chain, right? So you call this on-chain for trading purposes, but you need them for other purposes as well. The financial stuff incentivizes the information feeds, right? Like, in a sense, why does it so people can, in a sense, bet on the Bloomberg terminal, right? So the Oracle services that actually put this information on-chain, contracts for various kinds of markets, right? So the news, the media actually influences the flow of money. There's a vortex that is pulling verifiable information. The market wants it there. In a sense, what the blockchain is, is like an armored car for information where you can transport that information on-chain. And so, if you scroll down a little bit further, again, this is like six years. I've been thinking about this for a long time. So, the Weather Channel posts cryptographically, if you click into this, right? This shows all the feeds that can be posted. So, the Weather Channel could post signed feeds of weather data, Redfin posts real estate transactions, Four Squares location data. They can make them free or they can crypto pay. And so, now you have this stream of the raw data, and then you have AI on top of it that turns that into legible text. I only saw GPT-2, and maybe GPT-3 had been out by that point, but there was actually a company called Narrative Science, okay? And which went bust, but it was a cool company, okay? They had something which would, let me show you what it looks like. Ready? Take this in. It's a little small, but put this on screen, okay? Narrative Science show the possibility of something like what we... Again, you know the thing about the future is already here, it's just not evenly distributed, right? If you put that on screen and zoom in, okay? Zoom, zoom, zoom. So that would take, it's a little blur, it would take your financial data and it'd say like, you know, bookings were strong this month, but new pipeline, blah, blah, blah, you know, kind of give like sports commentary on top of numbers. Does that make sense? Right? So it was like a domain specific AI, right? That would turn numbers into legible text. Yeah. And that was there back in the day. So I saw that I knew about that. I'm like, you know, as AI improves, it's possible extremes of not just financial and other data and automate the process of turning box scores into sports articles. The process of turning weather feeds into reports, turning financial feeds into financial reports, turning lists of tweets into political articles. And what I didn't know is how fast it would happen, right? So you already, you know, I actually built some prototypes on this already. For example, here's a fun one where, so I set this up a year ago. Actually, like as soon as ChatGPD came out, I knew the potential of this. Hold on. It's pretty funny. We basically did an NYT, but an AI NYT. I did two versions of that, right? Find this. We set this up as a replica bounty, and it was so, so, so fast in fact. Hold on. Where is this? Here. This is the original bounty. I'm pasting this into you, and then I'll show you what happened to it. Yes, here we go. Bingo. So I put that bounty up, and then there's a kid who literally learned to code that year in replicates like Summer of Code. So I said, actually, go back for a second. Hold on. Go back. So if you just click into my tweet first, and then we'll play this video, right? Just clicking my tweet. Let's scroll a little bit further. Yeah, prompt with a few tweets. Output an article in the style of NYT, WCA, et cetera. Make the aesthetic look exactly the same. Compare the speed and cost of having an AI do it versus a traditional... Oh, I think that's funny. Okay, fine. That was funny, yeah. All right. So, do view quotes, right? No, yeah. Then, exactly, at Tricia WC. Right, so there we go. Pow days. Look at his thing, okay? And let's zoom in on this. Let's maximize this. So, basically, post in a tweet, right? And, you know, basically, he'll hit submit, right?

Speaker 3:
[47:49] This is back when it was called Twitter, I see Elon Musk on Twitter.

Speaker 1:
[47:53] Yeah, this is four years ago. It was right after Elon took over Twitter, right? The GPT Times, right? And so now, he hit submit, and literally, it turned into an image, an headline that looked exactly like, you know, Coca-Cola has been a part of America. The same tone and everything. Okay, that was four years ago, right? And the full thing was open source and so on and so forth. Now, I actually did a follow up on this. So, as much as I love Twitter and Twitter is great, I do have a Facebook page, where basically, the main issue is Twitter is still a commercial service and so it's a closed service and so on and so forth, right? And it's fine, it's good, it does a lot of good stuff and, you know, I think it does a lot of good for the world, but we also want open source, right? So, a year later, this guy, the RoboJourno, right? And here was the result of that. This was actually on Farcaster. And the result of that, which actually was even better. So, tell me if you got that on screen, right? The RoboJourno, right? So, you scroll down a little bit further. The quotes or whatever. Let me see if I can load this.

Speaker 2:
[49:08] Balaji, the thing I want to ask you, though, is why are they the business absolutely crushed despite their credibility?

Speaker 1:
[49:18] Your audio, sorry, save one time. Go ahead.

Speaker 2:
[49:22] Hold on. Why is New York Times ripping? Despite their credibility being sort of by a large set of people, why is their business crushing?

Speaker 1:
[49:36] Isn't it just the games? Well, the thing is, they traded Andreessen for 10,000 essentially Democrat party members, right? So basically, there's all of these party fakes. You know the equivalent is, you know the Chinese Communist Party has an outlet, it's called Qsha, do you know what that is, right? If you go to en.qstheory.cn, okay? And they put out a bimonthly called Qsha. And it's actually very, it's turgid party, actually want to know what China's doing. This is in English and you can actually read it, you can actually learn a lot about, you know, just to know what they're doing. They put it all out there, right? So the Qsha subscriber is a lot like the NYT subscriber. It's like the party member in China who reads the party newsletter and says, they're expected to like repeat what the party wants them to say and to change their narrative as the party changes their narrative. We're for Russia, we're against Russia, we're this, we're that, right? And the same way the NYT subscriber is, whatever the Democrat Party wants, we will say, and they just kind of go back and forth in the wind like this, as, you know, they're for this, they're against this, and they're for this again, right? They acknowledge something several years ago and vice versa, right? So, once you kind of see NYT equals CCP in this sense, right? It is they traded the dissidents, the people who they couldn't control, the tech guys, for thousands of, essentially, and so they traded power for money, right? That's what NYT did. They lost influence over the center. They lost, but they did. It's a little bit like, honestly, like Alex Jones or something like that, right? They went to the, you know, they built an audience, gone farther and farther into that audience, and they never say anything. They have what people would call audience capture, right? So, the...

Speaker 3:
[51:43] I think that, like, a lot of the reason that the New York Times business is booming now is just because of the games, like Wordle, you know, the mini-crossword. I think, like, I think more than half...

Speaker 1:
[51:54] And cooking and stuff like that.

Speaker 3:
[51:55] Yeah, more than half of New York Times app screen time is... So, I think without the games, they would be doing a lot worse financially.

Speaker 1:
[52:09] That's true. That's exactly right. But basically, about that is they cross-subsidize it in the same way, like, everything gets cross-subsidized, they have the fun stuff and then they have to eat your vegetable stuff. The thing is, they lost the... They lost tech, right? They lost Andreessen, they lost all kinds of people who thought that they were actually good and so on and so forth, right? And here we go. Let me show you this, ready? Hold on, the link, here we go, hold on, bang, bang. Fully automated, let's see if we have journalism, hold on. This was basically... Just finding the link here. This is from a few years ago and it got done. Hold on. Okay, just look at... You can put this one on screen if you want. Let me just copy paste this. That's the only thing about a... Does this work? Erik? Erik, maybe you can put that on screen. Here, let me all type it in here.

Speaker 2:
[53:42] I got another topic for you. I just texted you.

Speaker 3:
[53:44] Thank you, Sonal. Zoom chat.

Speaker 1:
[53:52] Yeah, here, I'll just put in the same chat with you.

Speaker 3:
[53:56] Here we go.

Speaker 1:
[53:57] This is just, yeah, so this was fully automated, laissez-faire journalism. And there's like a video version of this, which I can find, but basically you get the concept, right? There's actually a nicer version of this, actually in the later thread, much nicer version. If I can find it. And the point being that this was, this was something that we could take the open-source feed and we could turn it into something which was, would look like an NYT kind of, hold on, I really want to find the actual version of this because there's like a better, there's a better version of it. Problem is I posted so much that it's kind of hard to find.

Speaker 3:
[54:41] Let's see if I can find it.

Speaker 1:
[54:42] It's like from two years ago. Give me a second. Ask me a question while I'm finding this. Go, go, go.

Speaker 2:
[54:47] Balaji, I want to hear your thoughts on Clavicular.

Speaker 1:
[54:54] Go ahead.

Speaker 2:
[54:54] Clavicular.

Speaker 1:
[54:57] What about, oh, about Clavicular?

Speaker 2:
[54:59] Yeah. I mean, I feel like you were on Looks Maxing. Where's it go?

Speaker 1:
[55:04] Well, I, well, I mean, I'm myself, I'm certainly not a looks man. But what I meant to, what I do agree with, where I think, okay, what's one cheer for it, because biotech is the, what I did say is that the bro science was going to become a huge, huge, huge thing. Right? And, and it did. And basically is going to become something which is a major market, right? Something which, it's a little bit like, you know, how Twitter was like a small thing that became a big thing. And it went from just tweeting your breakfast and so on to, you know, the center of the world economy where people are quoting, you know, right? So in the same way, bro science goes from like the, the type of thing which people think is sort of a joke, to the thing that is completely real, right? And, and I think that's already actually made way through that with peptides and so on and so forth. And we have currently a fake for, for weight. But I think we'll get hopefully a zempic for longevity, maybe a zempic for cognition, a zempic for many other kinds of things. We'll get large effect size drugs. And, and that could be a really big deal, right? And so, hold on, I want to find this thing.

Speaker 3:
[56:32] Super bro sciencey. He seems to...

Speaker 1:
[56:35] No, I know.

Speaker 3:
[56:35] Align to the mainstream a lot.

Speaker 1:
[56:38] Yes, but it's, it's something where the, there is a aspect to what he's talking about, which is self-improvement. Okay, by the way, I found this, I found this thing finally. Hold on, wait, wait, wait, wait, that's not it. Hold on. There we go. Sometimes, copy-paste isn't hard to make work. All right, bingo. Click that. So, this just shows a prototype. Let me explain what you're seeing on screen. If you click the first one, the first image. So, what that did is that takes the open source, completely free stream of on-chain posts of the Farcaster feed, and automatically generates a front page, styled to look like NYT, but that's completely free, and you can click into and you can see the articles and so on and so forth, right? If you go to the right, you can compare that to the NYT home page, right?

Speaker 3:
[57:51] Is this live on YouTube?

Speaker 1:
[57:54] We're going to actually bring it back, right? So, stay tuned. If you're interested in this kind of thing, I'll announce the launch on monitoring situation. Okay, we're going to have... I'm going to become, hopefully, one of the largest funders of free, open-source citizen journalism in the world, where anybody from anywhere can become a reporter by posting online. And then, if we include that in content that we commission, where we're basically recovering the stuff that is useful for techno-capitalists. For example, what happened in India with thorium is so important, right? They've actually figured out how to get breeder reactors working. All kinds of countries should know about this. Everybody should know about thorium. There should be tutorials about, you know, exactly what they did and so on.

Speaker 3:
[58:41] There's a really good Ammonella Academy YouTube video on thorium, which everyone should watch.

Speaker 1:
[58:46] Oh, great.

Speaker 3:
[58:46] He's very funny. Thorium rocks.

Speaker 1:
[58:49] Oh, great. But that's nine years ago. So that's good. So the thing is, this, you know, it's weird that there's so much coverage of like some, look, obviously, you know, if it bleeds, it leads is one model of what news is. And unfortunately, they will make it bleed. Like they'll often cause a conflict to generate the reporting and the content, like set fire to something, sell tickets to the place. There's a completely different view of, you know, what the 8 billion people in the world are doing, where not in a naive Pollyanna way, like, oh, why don't we report the good news of, you know, giving a cookie to somebody? That's fine. I like that too. Don't get me wrong. But report the stuff which is, let's call it investible. Okay? The progress in battery, the progress in solar, the progress in nuclear, the progress also in, let's call it the resilience economy. Okay? With this crazy, hormones thing, everybody's going to be allocating capital from wants to needs. Okay? So, how, you know, oil is not simply upstream of transportation, but all kinds of things from sticks, it's a hydrocarbon that's an input to many, many different things down the supply chain, right? From medicines, all types of stuff, right? All of that, you know, actually, Erik, did you know I have a in chemical engineering from Stanford? Yeah, of course. Yeah. So, I actually have a hard science background, right? And in fact, that was actually my initial thing, right? So, I want to have citizen journalism, decentralized reporting on hard science, tech across the world, right? And commission that, and then pay for that, and then have that basically be something where we have a certain number of those and they're supposed to go on Firecaster and so on and so forth. If you're an engineer or you're, if you want to be like an editor in chief or something like that, and you want to work with me on this, then reply to me or DM me with what you can do. Like basically, non-AI, or rather, if it's AI, disclose AI, right? You should be like a great writer so you can verify the submissions that are coming in, or you should be like a great coder or something like that. Be interested in essentially taking these prototypes that I've put on screen and turning them into something which is free, verifiable, open-source, decentralized, international media for the world. And look, again, I love X. X is great. There's a lot of great stuff about X. But as I said, if we go back to my original post here, you know the thing, we have been in serious problem?

Speaker 3:
[61:29] We have been in serious problem, yeah.

Speaker 1:
[61:31] Yeah, we have been in serious problem. So the thing is, we have to understand that this zombie of YT is getting back up off the mat, that they are getting traction again, that they are going to, especially with this war, in my view, it's given them a sword. They're going to be attacking all of us. They're going to be yelling at tech guys. They're going to be calling us all kinds of names, whether you were for the war or not, right? And suppose this on screen, this thing that I just posted, so you can come back to this post. So the issue we'll need to address with cryptography and AI is some people have started linking to legacy media news sites simply because the URL has a built-in form of validation in it and they can't tell what's true on a social media that's just optimized for views, right? So that's why I said the sequel to Go Direct is prove correct. We must prove correct, not simply go direct. Yes, put out your own opinion, but prove the facts, okay? And how do we prove the facts? Cryptography, mathematics, that's a property of all human beings, not some New York media corporation, okay? People don't have to trust the tech zillionaires, they don't have to trust us because they don't have to trust us. They can just look at it on chain, right? And so we turn crypto and cryptography, just like there's crypto-currency, we call this crypto-information, right? Information is built-in verification and validation, okay? Now, by the way, you know, tutorials are actually a pretty good place to start on this, you know why? For you, when you go through a tutorial, you actually verify it line by line in a way that you don't for most content, right? Because you're like typing that into, you know, an editor or you're trying to replicate each step, like even a recipe actually has a built-in verification to it that most content doesn't. It's not like, you know, if you read some article on Egypt, it's not like you're flying out there like Indiana Jones and verifying every line in the story, you know what I mean? Right? This is gel man amnesia, you know, like you guys know what that is, maybe you can put that on screen for that. Do you want to explain?

Speaker 2:
[63:45] Yeah, basically this idea that you read something in the paper, you think it's deeply retarded and you're like, wait, I know about this topic, they're totally wrong about this. But then when you think about, when you read other things they write about that you don't have expertise in, you sort of give them the benefit of doubt and assume they're right about that.

Speaker 1:
[64:04] That's exactly right. And don't go to Wikipedia because Wikipedia is itself a terrible source for everything. Only Grokopedia, baby, we're Grokopedia only in this household.

Speaker 3:
[64:13] Is Wiktionary. So I hope they make it Grokionary because Wiktionary is actually pretty good.

Speaker 1:
[64:19] Yeah, I know, but we definitely need Grokionary, right? So here we go, hold on. Elon, if you're listening to this, Grokionary. Honestly, by the way, Elon, it's actually absolutely insane that like Grokopedia is a world class thing. And for many people, like it's literally, it's better than we can be. For many people, they'd find it hard to remember it in the top 10 of things from Rockets to Cars to Tes, you know, to Boring Company and so on. By the way, Boring Company, you know why that's actually way more important than people think? Why? Iran has actually got a form of defense where they've actually put all of their bases, they built these missile cities, these subways, basically, giant subways that are filled with missiles, and so they've got underground bases. And so for both offense and defense, we're gonna see a lot more in the way of underground cities. So lots of cities are gonna put more and more of their stuff underground because standoff missiles have kind of changed the military, you know, and actually I think New York City got its first approval, I can't believe they got an approval just for like a 80-story underground skyscraper kind of thing. And so in a sense, the underground world is like the encrypted world. All the satellite footage can't see what's happening underground because it's underground. And there's a lot of actually space under the earth and that direction for things, underground and in the water and maybe under the oceans, a whole, with modern engineering, we might be able to do a lot more than people think, right? So the Boring Company is actually potentially a much, much, much bigger thing than people even realize. Beyond just tunnels for cars and self-driving cars, it might be tunnels for cities and for homes and so on in the medium to long term. Also, you know the term air rights? Have you heard that term? No. I think so. When you're buying property, right? Property has cadesters.

Speaker 3:
[66:14] Yes.

Speaker 1:
[66:14] It's like boundaries, like the latitude, longitude coordinates in x, y space that define what you're actually buying if you're buying property. In cities, you also have air rights, which add a z-axis because you're going up in the air and you might build a skyscraper and can you build upward in this way because if you know, are you casting shadows on people nearby and taking away? So, now you have, let's call it subterranean rights, which are ground rights. How low can you drill into the ground without, you know, obviously you can destabilize things near you and what nots. There's engineering considerations. That's going to become a big thing. Anyway, coming back to the stack. So, Elon, Grokopedius, have we got Gelman Amnesia? We got that on screen?

Speaker 3:
[66:54] I hope Elon is watching this, by the way, because are we the biggest live on X right now? We might be.

Speaker 1:
[67:01] We might. You can add mention. Yeah, there we are. I think so.

Speaker 2:
[67:03] Bigger than Alex Jones.

Speaker 3:
[67:04] So, how do we check? Is there like a trending tab live?

Speaker 2:
[67:08] I don't think so.

Speaker 1:
[67:09] Maybe. So, but, well, let's entertain the audience. So, yes, all right. So, actually, can you look at the thing I just sent to you? Not that one. I put it in the Zoom chat. PBS.twimage. This out. The Genome Amnesia Effect is as follows. You open the newspaper to an article and sub-subject, you know why? Well, in Murray Gelman is a, and this is Michael Crichton talking, the late Michael Crichton, late great Michael Crichton. In Murray's case, physics, in Michael Crichton's case, in the general business, you read the article, see the journalist has absolutely no understanding of the fact that the article is so wrong it actually presents the story backward, reversing cause and effect. I call these the wet streets, cause rains, stories, papers full of them. In any case, the operation of amusement, multiple errors, and turn the page to national and international affairs. So then, you know, like, you can hit X and close out of this, right? So the point is, basically, this is something where whatever you, if you actually model it, right? NYT was the center of the world, and how would you know something about Japan in the 1980s or the 1990s or the early 2000s? NYT would have a reporter, and they would present it to you because you'd have a subscription to NYT. And how do you know about what's going on in Turkey or in the nuclear industry? They would have a hub, and they would essentially intermediate everybody's perception of each other, like a hall of mirrors in the center. The Japanese guy would only know through one of these centralized news agencies, right? So you think of it, they call it the media in part because it mediates your experience of reality. It's like a shimmery mirror into the shimmery hall of mirrors. And of course, that power of controlling that centralized hall of mirrors, where everybody perceives everybody else through this smoky looking glass, is the power. This is why they were so, so, so, so, so, you know, insistent. They fought this bruising and ultimately losing back. They tried to use their centralized power to censor everybody and to stop people in particular from courting with each other. Do you remember all the freakouts, Erik, about clubhouse? Like, unfettered conversations. Unfettered conversations. Exactly. Why? Because what it meant was all the spokes, right? You know, celebrity and some tech person and I don't know, some, I don't know, French guy or something like that, Japanese businessman could actually all a, you know, coffee table, like what we're doing right now, right? In digital space and talk to each other without a member of the party, YT official, essentially like the Communist Party official, but I repeat myself, there to monitor what we were saying, right? So no journalist, no communist, make sure everything is on message and so on. So they freaked out because they, whether they could articulate the way I just did, they understood that the ability to set the table, to set the, to portray themselves as the neutral middle ground that would orbit what is within and outside the boundaries of discourse. If you could do that peer to peer, if you could set your own table, oh my God, your unfettered conversations would break the whole thing. In a sentence, by the way, and this is a funny, this is a Rorschach test, ready? You ready for a Rorschach test of a tweet? This provoked a lot of, I thought it was a good tweet. Ready? Free speech is open borders for ideology.

Speaker 3:
[70:38] That was a good tweet.

Speaker 1:
[70:41] Okay, go ahead, and I'll give you my thoughts. Here, I'll put this one on screen.

Speaker 3:
[70:48] I think it's like roughly true. Like, this is what we saw in the last couple of years. It's been open borders, so there's been like, you know, a rapid flourishing in all kinds of takes, but also a lot of takes pretty terrible. A lot of like actual total misinformation has been spread. It's probably net good, but there are some negative consequences that could be mitigated. You know, maybe through crypto.

Speaker 1:
[71:19] That's right. And so actually, that's my follow up there. So basically, one way of thinking about it is, the left cared as much about speech controls as the right cares about border controls. And so the reason they just fought so hard to control speech and the boundaries of acceptable discourse and not allow unfettered conversations is that controlling thoughts is sort of, I mean, it's pretty important actually, what the Overston window is. It's literally in its own way like open borders, but for ideology, right? And so if you think about the negative reaction that someone on the right has to open borders, that visceral negative reaction is someone in the centralized left has to unfettered conversations, right? And on the centralized left, let's say. And so one way of thinking about is that what the intranet has done is it's busted all the borders, right? Why? Because, you know, a post from a long time ago, you know, I use Twitter as sort of a scratch pad for ideas, you know? So here is a post a long time ago that I think is a good concept. The intranet increases variance, right? So here's, this is it from 2019, right? So from a 30-minute sitcom to 30-second clips and 30-episode Netflix binges, okay? Basically a stable 9-to-5 job to a gig economy task or a crypto windfall. From a standard life script to living with your parents or a startup CEO at 20, right? The intranet just increases variance. But why? I'd argue it's because what the intranet does is it removes the middleman, the mediator, the moderator, right? Anything that, because it allows you to compare, right? So sometimes that's good. Wow, I've made a new friend in Japan. We can code an open source together. You know, Linux would not have arisen without a guy in Finland being able to reach the world for basically free with computers, right? The bad is, you have the crazy groups that can connect to each other and they can be crazy together online, all these crazy reddit sub-communities are over there, you know? And so you just get the best, the most good and the most bad, right? So that's a border-busting kind of thing because the borders that existed before each and ideology and communities got busted, at least in the Anglophone world. China's response to that is just to build giant digital borders called the Great Firewall around the scientific and physical sphere, right? Okay, coming back. Point is that once we realize that we now have speech as open borders for ideology, we have, let's call it American anarchy in the digital world, right? Everybody's yelling at each other, everybody's shouting. The opposite of that, call it Chinese control. Total top-down, centralized, authoritarian, you know, you have no choice. The party determines what can be said and so on and so forth. And the thing is, a lot of people will, as a prediction, not an endorsement, go to that, like Carney is, you know, going to that, and Canada is going to that, Europe is going to that, because the alternative total is too much for them. However, I think we can fashion what I call an internet intermediate, where people opt in to constraints, okay? Like when you sign a contract, that's a right libertarian way of talking about it. Or when you consent to something, that's a left libertarian way of talking about it, right? Incent to a contract, okay, you've given, you know, ongoing affirmative consent, you can constrain yourself or agree to something in some way. For example, when you walk in to somebody's house, you know, actually, you know the Envoy iPad things? Yeah. Right? You sign like a terms of something into somebody's office, right? And it says you can do this, you can't do this and so on and so forth. If you don't like those terms and conditions, you don't enter. Okay. And it's a little bit of paperwork, but something that's actually pretty standard, you know, the future is already here, it's just not evenly distributed. So I think you're going to see something like that more and more and more on larger and larger things, where you sign our contract before entering a digital or physical territory, and you agree to the terms of service of this zone that you're about to enter, which will have some constraints on both digital and physical behavior, and that have examples of what is allowed and what is not allowed. And if you don't like it, then you don't have to come in.

Speaker 3:
[75:51] We have this on Discord. We have rules at discord.gg/mtslive. Join.

Speaker 1:
[75:57] Exactly. Can you say what your rules are?

Speaker 3:
[76:00] Yeah, I mean, it's just very simple stuff. Let me see if I can actually pull it up. It's just like no spamming, no being like, don't spamming for no reason. Don't make the server a worse place for other people.

Speaker 1:
[76:18] Exactly. That's right. So that's why most practical blacks to Discords have moderators and moderation policies and ban hammers. And by the way, so like the baseline is call an in-person level of stability, right? There's free speech and there's friend speech, right? Like, you know, in theory, in practice to a friend, if you use your full free speech and you start cursing and yelling at them and you're like, you can't throw me in jail for that. Yeah, but they can not be your friend, you know, right? You're just outing out on them, whatever, right? So friend speech is how you speak to a friend and, you know, free speech is, you know, the assumption that the interactions between you and a hostile government, you and deep platforming and so on. And that does exist. It does exist. But it's simply not like how you interface with most people and most things at most times or shouldn't be. So, and within a discord, yes. So like the base layer is just, you're not cursing, yelling, making an unpleasant environment, posting spam, porn, malware, you know, like this kind of stuff, of course. But then there's a second level, which is keep things on topic, right? So if, for example, it's a discord about botany, right? You want to mainly post about plants, okay? If you suddenly started posting about spaceships or something like that, you might even be a great poster. But actually, do you remember the clod thing where it was all like everything was the Golden Gate neuron? Golden Gate clod. Golden Gate clod, right? So Golden Gate was an example of somebody who was certainly coherent and polite, but just off-topic, where no matter what you asked it about, it was about the Golden Gate Bridge, right? And it was like this funny kind of thing or what have you, right? Where they could make it just obsess about this. This is like people who are obssessed about things, you know? And it's basically every post, no matter what you asked about, monuments, it would bring it back to Golden Gate Bridge. It was just a monomy. Yeah, exactly, right? And so no matter what you asked about, it's a, well, that's a great brain. It reminds me of the arches of the Golden Gate Bridge or whatever, something along those lines, right?

Speaker 3:
[78:35] What is the highest calorie food in McDonald's? It's the Golden Gate Bridge, which contains our 1.6 million calories worth of steel canes.

Speaker 1:
[78:44] Yeah, yeah, yeah, I know, that's right. However, most people don't plan, exactly. It's like obsessed with it, right? And what is the meaning of life? That's a better example, the one below it. Yeah, that's a very profound question. Maybe the meaning comes from our own human constructs, Golden Gate Bridge, Redwood Forest, San Francisco itself. Funny, right? Okay, so point B that within your digital community, A, the base level is the equivalent of like, you know, don't shoot, spam somebody, don't scam, whatever, don't pay porn, malware, blah, blah, blah. Then the B level is keep it on topic, right? Like, for example, in Japanese on a forum, which is all English, that's not that polite, unless they're a Japanese monolingual and they post the translation of like, and then that might be okay, right? And then C is don't make personal attacks on other people, you know, blah, blah, blah, blah, blah. Point is, there's rules of the road. Those rules can be mutually incompatible. You could have a vegan forum and a carnivore forum that could both be internally polite and something that would be on topic somewhere else. One of the most remarkable things, by the way, is how you'll see people online who are just totally crazy in some context. You heard the term code switching? Yeah. Yeah. They'll just be a completely different person in another environment. Completely different person. They'll be polite, you know, professorial even, or whatever, while they're just wilding out. Go ahead.

Speaker 2:
[80:17] I'm just laughing at the concept.

Speaker 1:
[80:19] It's funny, right?

Speaker 2:
[80:20] Yeah.

Speaker 1:
[80:20] Yeah. So we can... Plus Discord. That's right. So this concept of the intranet intermediate, which we already have online, I think the key insight is we want to print that out offline. Right? The same kind of thing that you've consented to online, where you enter a Slack, you enter a Reddit, you enter a Discord, you consent to moderation. If you don't like it, you can leave and pick from another one of those thousand. Right? We bring that concept offline, just like with the Envoy kind of thing, except you sign a social smart contract before you enter a jurisdiction. And in this fashion, you opt in to constraints. You start rebuilding conventions of civility. But crucially, we do it from Anglo-American first principles. There's consent and there's contract. Right? You're opting in to those constraints. You have free choice. It is not opt-in-imposed Chinese communist censorship and filtering. Does that make sense, right? So we restore order, but through liberty, ordered liberty, okay? So that might seem very abstract, but kind of like the ledger of record stuff, I think it's going to be pretty important in the years to come. Okay? And so let me pause there. There's a lot I just said, but that's also, that gives a rationale for why the media A is mad at us because we've taken over the dissemination presentation and collection, presentation and dissemination of information. We've disrupted them economically. There's a, you know, the print media disruption graph that I always like, right? Did we show that one? We didn't show that one yet, right? Let me show that one. This is maybe, this probably should have shown this one first. But basically the intranet just disrupted media. That's why they're so mad at us, right? We didn't mean to do it, but we did it. And here we go. Hold on. Let me put this on screen. Let me share this with you guys. Yeah, here we go. So take this guy, put this on screen if you wouldn't mind. And then I'll summarize and then let's do Q&A. So if you click the second graph there. There it is. So that shows, yeah, so this is like the graph to understand tech versus media. There's many more graphs, but this one is mine. You know, he was a rifleman, whatever. So this graph, it captures a ton where it shows that for decades, it was awesome to be in newspaper, print media, right? This thing goes from 20 billion a year in 1950 to 67 billion in the year 2000. That was like peak American empire, peak media and so on and so forth. And then it's like kind of flat in the 2000s. And then it's just completely, roughly in the late 2000s, especially after the financial crisis, where what happened was everybody was seeking more efficient dollars, right? Like there are dollars for advertising, they didn't just want to throw them away, they needed to make them efficient. And at that point, Google was ready to catch the rain, right? The Internet was finally ready. It was no longer just eyeballs and un-targeted ads. They could do these personalized, you know, AdWords kind of links, which was still a big thing, but it was a huge innovation then. So they just started capturing all the spend. And then you see Facebook going vertical like this. And actually, another big part of this is not shown is Craigslist going after classifieds. So like, suddenly, you know, the guy, remember the thing, never argue with the man who buys ink by the barrel. Now, the guy who's buying ink by the barrel is just wasting all his money because we don't have to buy ink by the barrel. We can get our information out online. So they drop from 67 billion to like 16, 19 billion if you include, you know, digital revenue. That's like, that's a huge drop. You know, you go from 70 to 20 billion dollars. That's like a, you know, 63, 62% drop in actually a 70% drop, okay, in just five years, six years, something like that on that chart, right? So the thing about this is imagined, you know, the journals really weren't that bad going into the early 2000s. Why? They could fly. I mean, yes, they would cancel someone from time to time. And when I say they weren't that bad, to be clear, that's all relative because, you know, Herbert Matthews, you know, was the one who caused Castro and he was a New York Times reporter who turned Castro into like a celebrity figure. John Reed helped create Lennon. Walter Durante helped create Stalin and covered up the Hall of the More, won a Pulitzer Prize for the New York Times. David Hallersham helped create the Vietnam War as Ashley Ritzberg is documented in The Great Lady Winked. Yeah, there are lots of journalists where if you actually go and look, actually, in fact, let me just give you that digression, put this on screen. Here's four references that will change your world view if you aren't aware of this, right? But basically, John Reed, Walter Durante, Edgar Snow, Herbert Matthews, it's very hard to find a communist dictator that didn't come to power due to some journalist doing PR for them, okay, basically doing recruiting for them. They basically got them distribution, okay? And however, with that said, they were not extremely hostile in the, okay, so you can click all those books if you want, just put them on screen for a second one by one. Right, so John Reed has literally buried the Kremlin wall because he was so important to the October Revolution, right? And he was an American who went there and wrote this book, Ten Days That Shook the World, that whitewashed the entire communist revolution. Go back one, click the next one. Like, Walter Durante, he won a Pulitzer Prize, Stalin's apologist for covering up the mass murder of millions of Ukrainians. And, you know, by the way, after the whole war in Ukraine, The New York Times wrote all these articles on Ukraine. You know what they never mentioned? Walter Durante, which is their own role. The New York Times is a big part of the reason that Ukraine was ever subjugated by Soviet Russia in the first place. And suddenly reinvented themselves as a champion of Ukraine after they were the ones who, like, you know, basically won a Pulitzer and made money. They made money from having, starving out the Ukrainians, and they made money from the Ukrainian war. Just got them coming and going. This crazy, crazy thing, which basically this is, you know, the kind of thing they cover up is reporting on themselves, right? No account, you know, really, if you just liquidated NYT and took the billions of dollars and gave it to the Ukrainians for reparations, that would be justice, right? If you go and click the next link, back one, Edgar Snow, right, so this guy, yeah, click this guy, Edgar Park Snow, there we go. This guy, American Journalism, the most important Western reporting on the communist movement in China years before the Chi power, right? And what was that reporting? It was like, red star over China, remained a primary source. And he's like, oh yeah, you know, they're for the people and so forth. And everybody got misled by this. Yeah, actually, that's right. Snow depicted, see that thing? Hold on, scroll up a little bit. Snow depicted Mao Zedong and his followers not as the opportunistic red bandits described by the nationalists, but as dedicated revolutionaries who advocated domestic reforms and were eager to resist Japanese aggression in China. They just wanted to reform. In reality, by the way, the Chinese nationalists were the ones who spent most of the blood fighting Japanese aggression. The communists let them fight, and then they attacked them from the back, and their reforms consisted of shooting landlords in the head and all this bad stuff. Fine. OK. And you go back. And the reason that they got to power is, again, because of guys like Edgar Snow, who did press coverage for them and basically formed the reputation of the Chinese Communist Party before it achieved power. And then go back one. Herbert Matthews, right? This is another New York Times journalist, another communist dictator, another journalist, another communist, but I repeat myself. So the man who invented Fidel, right? Castro Cuba and Herbert L. Matthews in New York Times, right? And basically this shows that, you know, Fidel Castro was on the run. He was in hiding. And then what happened was Herbert Matthews basically wrote this whole thing, which is like, Castro is alive and he's still recruiting. It'd be like saying like Osama bin Laden is still alive and he's here. And if you want to join Al Qaeda, go to this location. I didn't say that, you know, it's literally like that kind of thing. Right. And so there's actually a good book by this on all of this by Ashley Rinsburg on The Great Lady Winked, called The Great Lady Winked, which just goes through all of these episodes. Right. And shows the New York Times is never great. Right. The Salzburger family, by the way, you know, just to show you a little bit more, just to show you what we're dealing with. Do you remember, you know, BLM and how like everybody, everybody was a racist other than the New York Times. Right. Well, actually, just to know here, this again is something you'll never see in the New York Times itself. The family that owns the New York Times were reportedly slaveholders. Ta-da. So all white people are racist, other than the white people who own the New York Times. All white people are guilty of slavery, other than the white people who own the New York Times, who are actually the same people as Yale University and Brown University.

Speaker 3:
[89:15] They were founded by slave owners.

Speaker 1:
[89:17] Yeah. And by the way, on GitHub, we had to change master to main. Is Yale giving up the master's degree? I mean, no. Right? Come on. This is all just stuff which is basically media attacking tech. So the point is, and by the way, who is this guy, just to know who we're dealing with here? Right? This guy is like, look, you know, the thing about tech is everybody in tech is basically new money. Right? Which are not everybody. There's some people who are like second-generation VCs. But this guy, by the way, everybody knows Zuckerberg. Okay. Zuck is out there. He's taking the heads. You know his face. Okay. Just scroll up a little bit. Just have the headline there. Right? So this is, see, we know what Zuckerberg's face looks like. You can summon it to memory. For better or worse, and I respect Zuck, Zuck is the son of a dentist who built a gigantic platform from scratch from his computer. Right? And he's out there. He's taking the heads. The CEO, like it or not, you know, he's personally responsible for it. And he's built, you know, like, I don't agree that every single thing Metta has done, but overall on balance, I think it's given messaging and all this stuff in general. It's done a lot for the world and for tech. Salzburger is surrounded by a thousand reporters at all times, but you've never heard his, never seen his face for most people, never even heard his name. Am I right, Theo? You probably hadn't seen his name or heard his face until, ah, seen his name, you know what I'm saying? Heard his name or seen his face till now, yeah?

Speaker 3:
[90:46] I had actually, because I read Yarvind, but before that-

Speaker 1:
[90:49] Okay, fine, fine, fine. All right, but most people have.

Speaker 3:
[90:51] Most people have not. Okay.

Speaker 1:
[90:53] Most people have not. And just to give you a sense of this, right? He's inherited the New York Times Company, which is a company, by the way, from his father's father's father's father. This is like a fifth-generation hereditary dynasty. And what does he say? He's like, oh, you tech guys aren't diverse and meritocratic enough, right? This is literally an organization where it was, like the three competitors for the NYT throne were like three cousins, okay? So their version of the Rooney rule, you know the Rooney rule you're supposed to like, you're supposed to interview like diverse people for the top role, their version of the Rooney rule was like interviewing their three cousins for the top role, okay? Whereas, what do we do? We interview people from all around the world, right? We have like the founder of Calendly is Nigerian and, you know, Mercado Libre, Latin American and, you know, Careem is Middle Eastern and we have Indian startups and Japanese startups. Technology is global, right? And these guys are nepotist, okay? So in the battle of nepotist versus technologist, you know, just since you got me on this, right? So basically, let me just show you an amazing contrast. All right, here we go. Look at this one. And most people don't have the context window to remember all of this stuff, but now with AI, we can actually do it. So if you put this one on screen, right? How punch protected the times, right? And what that's doing is it's extolling the values of dual class stock, okay? It's saying that because Salzburger has dual class stock, you know, then he can run the business, you know, and see, given stock, the solutions give that stock classier shares, not enough to threaten the family's control. That's how they, you know, basically were able to. I've never, see, I've never had to worry. So scroll up a little bit, right? But I've never had to worry the times would go the way because dual class stock was so good. Okay, right? So here, they're for dual class stock. But now, look at this one. You can't fire Mark Zuckerberg's kids, kids, tech companies using dual class. So dual class stock is good. Yeah, when it's for the New York Times Company, it's for Salzburg, it's good. When it's for Zuckerberg, right? It's bad. This is the Dakota lens you can apply to every single thing they do. You may know it also as Russell Conjugation. Right, have you heard that before? Yeah. Yeah, so should I explain Russell Conjugation's important conceptual thing here, just a baseline thing? These are some of the basics from five years ago to me. Like, I sweat, you perspire, but she glows. Right? He doxes, she leaks, but the New York Times investigates. Okay. So, like, you know, how Punch protected the time with dual class talk that allowed him to serve the public interest decade after decade versus unaccountable Mark Zuckerberg's dual class talk, blah, blah, blah. Right? Okay. So, they just Russell conjugate everything, and they space it out enough that, you know, they put the negative and pejorative connotation on it when it's tech, and they put the positive connotation on it when it's media. This is like one of their few tricks, right? They have a few other tricks, but the fact that they've lost distribution means that we can actually just punch through the armor. Right? We have, you know, infrared cameras, right? We have, you know, we have basically the ability to show A and B. See, the thing is like years ago, like I might have the memory to remember an article from 2012 and 2019 and put them side by side, but now we have the internet, we have links, I can go bing, bing like this and just show the contrast, right? Another example was within a few days of each other in like 2019, for example, there were like, you know, free speech in Russia, try YouTube, they seem to be for free speech, right? This was June 2019, okay? And then they were also basically, they were also, if you put that one on screen, right? Then like literally the previous day, they were, they were against it, right? Does YouTube radicalize, right? And YouTube, right? So on the one hand, see, in Russia, they were for YouTube because it helped in their view, destabilize Russia and or get their content in there and so on and so forth. Within America though, it was against their interest. So they were against YouTube. And this showed, by the way, they messed up because they published this back to back. So people's context window could capture the inverse Russell conjugation of them praising it in one story and critiquing it in another, right? Before, they had better editors and smarter people, so it spaced this kind of inversion out over the years. Does that make sense, right?

Speaker 3:
[95:40] Yeah, but isn't the counter to this that this one was an op-ed and they might have a range of views in the op-ed? Like, I remember they got in trouble for having Tom Cotton do an op-ed during BLM that was like send in the troops.

Speaker 1:
[95:53] Yeah, yeah, but that's actually, in fact, you brought up my exact rebuttal. Obviously, the op-ed page ultimately reports to the publisher. And so they, of course, they have veto over it and they demonstrate that veto power with the Tom Cotton op-ed and the firing of, you know, James Bennett and the subsequent departure of Barry Weiss and the free press and so on and so forth. So, yes, of course, they have these various camouflage things they'll do where they're like, oh, we don't actually control the op-ed page. Like, of course, they control the op-ed page, right? Like, clearly, they fired the guy who published this op-ed, right? And so, duh, right? And so, yeah, yeah, yeah, exactly, right? So, the tone is needlessly harsh, blah, blah, blah. And look, you know, this is from a certain place and time where everybody was, you know, losing their minds in a certain way, right, in 2020. And it reads like you're reading something from the middle of the Bolshevik Revolution or, you know, Maoist China or whatever, right? Fine, okay. And, you know, because later, you know, there are other, gosh, there's a guy, Josh Barrow, who pointed out that NYT had no similar reaction to this when some similar kind of event was happening, okay? I forget exactly what it was, but Josh Barrow, you know, pointed out the contrast, right? And he's actually, yeah, this was like in 2022 or something like that. I forget what it was, but he's like, maybe it was China and they were shutting down an agency or causing a problem. And anyway, NetNet is, he pointed out that they had nowhere near the level of anger about Issue X that they did about the Tom Cotton op-ed, even though it was comparable. I forget what the exact matter was. The point is, recursing back up a stack, you know, as actually, as Mark said, it is not, you know, what did he say? He's like, it is not sufficient to critique the world. The point is to change it, right? One of the few things he got right, okay? And so, let me get the exact quote. Yeah, the philosophers have hitherto only interpreted the world in various ways. The point, however, is to change it. Absolutely true, okay? And that is why I would never, you know, that's why conservatives always lose. Conservatives, they're, the reason they call them reactionaries is they react. They always move second. They have no idea of what is better. They always want to go back to the old ways that have often been defeated by the time, right? So, yeah, it's like, it's like, yeah, that's the one, the quote, right? There, bingo, right? The philosophers have only interpreted the world in various ways. The point is to change it. So, all of these are things which one can critique and say, NYT Russell Conjugates, anything that's for the NYT Co. By the way, if you Google NYT Co., it's a symbol, right? It's really a stock symbol, like, as one thing, no space. And, right, like, literally, it's a thing and it's just go, NYT Co. price. I think it's just, yeah, 5, 5, 5, right, yeah, so basically, I don't know, why is it being so hard to find? There we are, right? So, by the way, if you go to Max, you'll see their price crashed going into 2012, right? Actually, this is another piece of the puzzle, just for people who don't know this. So going into this, you can see that their price was low then, right? Then they discovered that saying woke stuff basically got their traffic back up, right? So here, I'll show you this particular very important graphic, okay? If you look at this link. So this is something which shows 1970, 2018. It's a little bit small, but if you zoom in at the top, notice how right in 2013, okay, like mansplaining, toxic masculinity, these things that had never been said in the paper suddenly went absolutely vertical, right? That is what's called an editorial decision, okay? At the very top level of the media establishment, they made the decision to start pouring the equivalent of poison into the water supply. It's like putting sugar in all the food, so that you get a short-term bump in traffic at the expense of the long-term health of the Republic, okay? They caused trillions of damage to social fabric for a few million dollars worth of clicks. It's like the ethics of a copper thief who steals a 100 bucks in copper, but destroys a light or a Tesla supercharger, okay? Enormous damage to the Commons by causing all of this conflict, but it did benefit the New York Times Company, where if you go back to NYT stock, that started going up around that time, right? So go back to 2013, you can see it was in the doldrums, and then suddenly they start roaring upward, especially post Trump, boom, boom, boom, boom, like this. So all this kind of stuff is something that sent their stock roaring up. I mean, it's only, I mean, in our, like, you know, from our standpoint, but my God, has it done more than $12 billion of damage? Holy moly, right? It's crazy how much damage it's done. So what we need is something which actually is not simply critiquing, like you can go through a million examples of, like it's funny to put it this way, like yes, did they help cause the Hull Demora with Walter Durante? Yes. Did they help cause the Cuban Revolution with Herbert Matthews? Unfortunately, yes. They helped cause the Vietnam War with David Halberstam's false reporting? Unfortunately, yes. And on and on. You could go through this. You could go through Jason Blair, and you can go through all the other fake stories of MIT and all the other journalists. You could go through Russell Conjugation. You could go through the fact that there are nepotists who inherited their paper, and they call meritocratic tech new money, all these names, when those names are better applied to them. You could make all those points, but the point is not to critique the world. The point is to change it. So how do we change it? Decentralized cryptographic truth. Decentralized cryptographic truth, where if you go to coinmarketcap.com, for a second, here's a great stat. You ready? This site, coinmarketcap.com, is seemingly a small site. Do you know that since 2017, in 2017 it actually passed wsh.com and traffic? Wow. Yes, here you go. Ready? So, put this on screen. So, click that. This is almost 10 years ago, 9 years ago. Click that. Yeah, this is Alexa. The reason is, at first you might think, oh, is that comparing apples to apples? Well, WJ has news, but you know what else it has? It has stock prices. And in fact, in the 80s, if you did some...

Speaker 2:
[103:12] We seem to have lost Balaji's stream. I mean, this guy's got a lot of endurance, huh? No Balaji, we lost you for a second, keep going.

Speaker 1:
[103:38] And the equity is valued for the purposes of the transaction. We're going to use the closing price in the Wall Street Journal on the day that the contract was signed, right? So above, you know, like, are the letters, but below, the Wall Street Journal was bought for the numbers. It was literally bought for the feed of stock prices, right? So looked at in that way, CoinMarketCap is, of course, it's a global WCA, where it started with the numbers, which are the coins. The coins are the global stock market that are actually, by some measures, already the number four stock market coins, since someone from Japan and Brazil and Turkey can trade coins on an equal basis, even if they can't get a brokerage count, right? So by some measures, the Nasdaq and crypto are the three largest markets in the world, and crypto will become the number one, I think, over time, as Nasdaq and Nasdaq go crypto, with tokenized stocks, tokenized equities. So it's actually not that crazy to realize, actually, yeah, for many people around the world, CoinMarketCap is the new WCA, and now they start to add content and analysis and so on of where coins are going and so on. Me so far, right? All right, so that is the financial information resulted in an internet-first news source that, at least from a pure traffic standpoint, has disrupted wca.com. I do believe, as we start putting facts on chain, like via a vehicle like Farcaster, we can have something that flips nytimes.com, because every article is verifiable, because it's coming from decentralized citizen journalists on the ground. This is another major point, by the way. You know, the founding fathers of America were against a standing military. You know, have you heard that? Yeah. Yeah. The reason is, if they had a Praetorian class, right, a group of guys who were armed, when everybody else was disarmed, they knew from history that that group of people would see themselves as special and so on and so forth. Versus, if you had a farmer soldier who was drawn from the population, then that would be representative of the population, it wouldn't oppress the population and so on and so forth, right? Now, because of the advent of industrialization and so on and so forth, it became economically infeasible. The farmer soldier couldn't just make a tank out of a shovel or whatever. They couldn't just beat plowshares into swords. So that's why you got these professionalized militaries over time. And now it's actually re-decentralizing with drones and for cyber war and so it's a whole separate topic. But in the same way that you don't want a standing military, you don't want a standing media, which is not representative of the population. The reason being because then that standing media, who can check them? Only another journal. Only WCA could check NYT, could check WAPO. So there's an incentive for collusion, just like there is between any set of corporations. And what they do is they collude, and this is what they did in the 2010s and so on, where they can never be wrong about a story like Russiagate or something because they all just basically repeated the same thing ad nauseum. And you were misinformation, disinformation, conspiracy theories, blah, blah, blah for contesting that story. Which eventually later, they all admitted together was false. But by admitting it together, that's another concept, the school of fish strategy, right? Lots of these false stories we now know are false, but there's no accountability for them because you are an individual, but they are a school of fish. Okay, so that's the school of fish strategy is basically this. Here's a great visual of it, ready? If you put this on screen. So, you are the individual, but all the NPCs just turn as a group. Okay, right? So, that is this key concept where all the journals see that this is the advantage of being an NPC. If you're an NPC, you're just repeating what everybody else is saying. Because you're repeating what everybody else is saying, you can't be singled out, the strength of numbers. And then, when the conventionalism shifts from, oh, you know, a lab leak was a conspiracy theory to a lab leak is within the range of acceptable things, they can just shift what they're saying and they don't pay any penalty. But if you're the first to say something that's outside of the spectrum, then you can get attacked like this. Once you actually see that and you realize, oh, okay, that's why there's no accountability for all the fake news. Because another version is the head of the hydra. One reporter prints something fake, but all the other reporters repeat it. Now they've got strength in numbers. This is actually something that they do very well, is they actually have a better esprit de corps and a better loyalty to each other in a sense, than all these libertarian individualists, the sovereign individuals who ever do. They don't want to listen to each other. Like the independence is both their strength and their weakness. Just like the NPC-ness is both their weakness and their strength. The other side. Point being, once you understand the school of fish strategy, like Brussels Conjugation, just like gives you conceptual frames to understand the strengths of the legacy media and also their weaknesses. Okay. And only by doing this, you know the Sun Tzu thing, right? If you know, let me make sure you get it right. It's like if you know yourself and you know your rival, you will never lose a thousand battles. Yeah. If you know the enemy, know yourself, you need not fear the result of a hundred battles. Okay. And why is that? That means that you don't get in a fight unless you know you can win. Another version of this, another thing he says is, successful generals win first and then go to war. Unsuccessful generals go to war first and then expect to win. To be clear, we never wanted to fight the media. I never had any issues with them. But they decided to fight us. Why? Because we disrupted all their economics, as I showed you earlier. Go ahead, Erik.

Speaker 2:
[109:04] You weren't interested in the media. The media was interested in you.

Speaker 1:
[109:07] Exactly. Exactly. That's right. Like, I didn't care. I was just, as I think you know, like Theo, you know, Erik and I have hung out for a long time, but just like I was a career academic, right? Literally all I did was I woke up in the morning and I said, oh, and then I meditated on mathematics. Okay. That's what I did. I did a computational journal. I'm excited math. I only gave my first public talk ever at age 33. Okay. I was a very private person. I just like literally didn't care about, you know, and it's only because like the total war that media waged on tech in the 2010s. Now, to be empathetic to them, they felt it as if tech was waging a war on them. The difference is we were just building better products and it happened to compete with their products, but their lifestyle got worse. The thing is in the early 2000s, you could have an expense account as like a time reporter and maybe write like, I don't know, six articles a year, fly around the world. You had a pretty high status. You had pretty high income. And everybody feared and respected you because you could write a negative article on some politician and nuke them. But they weren't that unhappy, right? They weren't that mad. There was like peak America and so on and so forth, the 90s and 2000s, they had these expense accounts. So they weren't like angry enough to get you. But then when that revenue graph collapsed from 67 billion to 16 billion, and then these nerds, the guy down the hall from them suddenly went totally vertical and became a tech zillionaire and he doesn't know Proust or whatever. He doesn't know all these literary references. He just knows how to do math. Why is this guy doing well? It's one thing if your house turns into a hovel. It's another thing if the guy's next door turns into a mansion. And yet it's a third thing if that happened because your house turned into a hovel. So we should, I mean, it's funny, we should be empathetic to them because I actually never wish another man ill, to be clear. I always try to seek out the win-win and always try to figure out, okay, how can we come to a win-win relationship? How can you prosper and we prosper? Because capitalism is positive some, right? That's why I'm an internationalist and a capitalist. I try to work across borders and so on and so forth. Nevertheless, some people are simply not interested in dialogue. Some people just want to watch the world burn. Some people just want to print fake news. You know, there's an unnamed journal, I'm not going to name the journal, who said, let me see if I can quote it, like, that's why we want to see these CEOs killed, right? You know, what was it? I'm just going to quote without the... said, and people wonder why we want these executives dead, okay? So, the anti-tech terrorism, right, of firebombing Teslas, of, you know, shooting, you know, the Luigi left, the shooting, the Brian Thompson, the shooting of, you know, the Molotov cocktail at Sam Altman's house, that kind of stuff. Those people have been radicalized in such a way that, yes, it's still important to post the true information out there, but also, you know, at the time, they're like foaming at the mouth, yelling at you, certainly let alone shooting at you, you can't reason with them, right? So, that kind of person, you know, a lot of tech people really underestimate the level of anger out there, just to talk about this for a second. I think the technologist is the capitalist of the 21st century. That might be an obvious point, but it's a non-obvious point as well. Should I elaborate on that for a second? Yeah. Okay. All right. So, basically, in the 20th century, the Industrial Revolution led to the rise of, you know, the industrial variety of capitalism and the captain's industry and whatnot. This did result in enormous improvements in standard of living. You had modern homes and you had running water and all this kind of stuff. But it also resulted in obviously huge wars and also a disruption of traditional means of government. All got disrupted. As a consequence, America was actually a society that was relatively young and supple. It was a technological disruption and rolled with it, right? But the older governments of Europe were totally disrupted by it. And actually, that also led to the Soviet Revolution, which was in its own way a new government that, in a sense, was adapted to the age, albeit in a malign adaptation. But the thing is that, you know, did you know Russia's stock market, by some reports, did better than America's stock market in the 1800s? No. I believe it. Yeah. They were not barbarians, right? And so the reason I say that is, you know, just to calibrate on what the world was, you look at this graph, right? And I'll get to my point in a second. Just just click this table, right? Zoom in, most of the world, with the exception of the US, Canada and Australia. Yeah, you got it on screen, right? So most, you can actually. Russia, negative 100%, China. What does communism mean? It means you go to zero. Do not pass go, do not collect $200. Go directly to Gulag, okay? Your farm is seized, you're shot, wife is, kid is thrown into a Gulag and reeducated, sent to a collective farm, right? Also, by the way, a farm is a lot like a factory. You know why? Why? You're growing radishes or something, they have to be irrigated, they have to be aerated, they have to be fertilized at a certain time. There's a whole process that's a lot like manufacturing widgets. And a lot of that task knowledge is in the head of the farmer, and when they're shot and the farm is just seized, it doesn't just grow the radishes by itself, it's a whole process of doing that. And where's all the equipment and so on? It's over a tech company and not knowing where any of the code and the private keys or whatever are, you can't deploy that, right? So these communists would seize the farm, they would kill the goose, the farmer, and then that's why they got famine, because they didn't know how to operate this thing. They had to figure it all out from scratch. And that's why this whole thing was a huge disaster. Anyway, so these retards, basically, these communist revolutions, and they, it was like, why, you know, the thing is, you can say, there's people who are good, smart, evil, and stupid. These guys' retards, they're stupid. Here's why. Good is helping others without concern for yourself. Smart is helping others while also helping yourself. Evil is harming others while helping yourself. And stupid is harming others while also harming yourself. These communists were stupid because they harmed others while also harming themselves. They thought they were going to steal the farms, but they actually stole like a bag of donuts. They got nothing because they had a famine. Fine. Point is, in this extremely negative sum activity, where they envy the capitalists so much. When they said capitalists, by the way, there's a term, great term, from Grokopetia, it's called Podkulak. I know this is getting into Russian history, but I'll explain why it's relevant. Basically, at first, the old, the communists were saying, oh, we're only going after the top hat capitalists, right? And then they eventually said, we're going after the kulaks, who are the farmers who were considered prosperous, and they had two cows, okay? You know, like a wealthy farmer had two cows, it's like a small businessman, right? And eventually they went from the top hat billionaires to the small businessman to, click this link I just sent you. Great term, podkolochnik, okay? Podkolochnik encompass poor peasants, collective farm members, or even non-peasants opposing grain requisition and farm seizures, irrespective of socioeconomic status. So, even if you were not a c*** in any way, even if you were not a small businessman or cool lock in any way, even if you yourself were poor, if you said, hey, taking these farms, the farmers is going to result in a famine, then you were an enemy of the people, too. Okay. This is how psychotic the whole thing got. Podkoloschian term where, why is it important? Because, see, this guy, I'm not sure if he was saying it sarcastically or not, but he's like, first, he came for the billionaires, and I did not speak out because there's not a billionaire, then they came for the millionaires. Well, actually, most of violence in the 20th century was not on the basis of race, it was on the basis of class. Okay. So, they went after the capitalist. The point is, today, the, you know, he's saying this, I couldn't tell if he was saying it sarcastically or not, but if you go back one, that's why I posted this, because that's exactly, if you go back one, let me just hit back. Yeah, that's exactly what happened in the Soviet Union. First, they came for the millionaires, and then they came for the Podkolashnicks, which is anybody who opposed them stealing all the property. Erik, right? Yeah. It's a good term because it literally puts a thumb on exactly an episode in history where that did happen, and millions of people were killed in that order, right? It's not a typical thing. It actually happened, unfortunately. Okay. Now, the issue is today, why do I say that technology is a capitalist of the 21st century? On one level, that's completely obvious because we're a technocapitalist. On the other hand, it's non-obvious. Why? Because the capitalist was, the beef with them is they were centralizing the means of production, and they had these big factories and so on that nobody could afford. But we're decentralized in production. Everybody has a laptop, right? The capitalist, everything was centralized, it was mass media, mass production. We're decentralizing everything. We're giving equality of opportunity to everybody in the world. Everybody in the world has basically the same, as I've said before, you have essentially the same smartphone experience as Sergey Brin, right? You have the same information at your fingertips as, you know, Elon Musk, for the most part, right? Like, what's he on every day? He's on X, just like you and I. Like, in a sense, there's been an enormous global leveling, right, with the internet. The internet is actually global equality. You have all these tools at your disposal, the AI tools, this tool, that tool. Literally just hit keys on the keyboard and you can create all these things.

Speaker 2:
[119:19] Balaji.

Speaker 1:
[119:20] So, in a sense, go ahead.

Speaker 2:
[119:21] On that note, I'm going to have to wrap because Mark Andreessen is coming in two minutes.

Speaker 1:
[119:25] Okay, okay, fine. So NetNet is, we need to, as technologists, build a better form of media, not just tell our own stories and go direct, but prove correct, because a lot will be mad at us since we've been successful. Since often we're ethnically different, immigrants, Indians, Chinese, whatever, whatever, right? Foreign in some sense of the term, for some, or two class different, two ethnic different, whatever. And so what we have to do is we have to have open source, verifiable, correct information where people trust us, because they do not have to trust us, they can just verify the information. We need decentralized cryptographic truths, citizen journalism, open source media, because NYT is getting off the mat. We have to come correct by proving correct. That's it.

Speaker 2:
[120:13] That's a great place to wrap. Balaji, we had almost 80,000 people come in live. Thank you for being our first guest ever at MTS and angel investor and supporter and friend. Thank you so much, Balaji. Thanks so much for coming on. Thanks for listening to this episode of the a16z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X and A16Z, and subscribe to our sub stack at a16z.substack.com. Thanks again for listening, and I'll see you in the next episode. This information is for educational purposes only, and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party, and may include paid 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 sources deemed reliable on the date of publication, but a16z does not guarantee its accuracy.