Balaji Srinivasan (3:20)

That being trending down over.

Vitalik Buterin (3:21)

Yes, it is.

Balaji Srinivasan (3:22)

That's a great graph. Okay.

Vitalik Buterin (3:24)

And if you look at things like aave, like basically the, you know, the sturdy stuff like that's.

Balaji Srinivasan (3:30)

Can I make a comment on that? Yeah. I never did any yield farming or anything like that because you'd be quote investing with the expectation of 6% return, but you're actually risking your entire principal because there could be a smart contract hack, you could go to zero, right? So instead I'd only risk principal in like an angel investment where I knew that could go to zero, zero. And I just held back and waited till defi matured and now it started. Mature.

Vitalik Buterin (3:55)

Yeah. So basically, you know, for mature protocols it's even lower than half a percent, right. And then on top of that, the other risk of course is like the risk that you personally screw up because something happens to your wallet. And then this is why I've been like pushing for social recovery, multi sigs, account abstraction, all of this stuff non stop for the last 10 years. And the thing that did happen, right, is like the safe front end got hacked, right? But if you were using an alter, an alternative ui, then you were fine. If you were checking the transactions you were signing, you were fine. And obviously you can't expect regular people to do that, right? But like basically, yeah, the infrastructure keeps on hardening and there's like 10 alternative UIs that you can use, right? And so, and, and even I think the base UI is planning to move to something much safer, right? And so from an average user point of view, like the Your ability to get something which is simultaneously like decentralized and not going to lose your money, like that's rapidly increasing, right? Like if you remember 2017, in 2017, like everyone thought that smart contract wallets were dead because the wallet code itself got hacked, right? Remember the parody hack? And then there was another hack, basic parody got hacked twice, right? And like that was sort of the nadir for trusting smart contracts, right? And then since then, like the safe smart contracts, like the smart contracts have actually been perfect basically since the start. And so each and every one of these things that in the beginning phase is this crazy thing and like, oh my God, there's a big chance you're going to lose all of your stuff now. It's like, it's maturing and it's more and more just like actually completely fine, right?

Balaji Srinivasan (5:31)

It's funny you say this because this is the flippening, right? And I think that, you know, it's funny I said this to somebody and you know what is defi. It's what takes over after the current financial system, Western financial ends, right? So there's like a flipping of this is actually going to become more secure than the current Western financial system go.

Vitalik Buterin (5:49)

Yeah, exactly. This is the, the other side of the graph, right? Which is this the degree to which you can realistically expect confidence in tradfi? Like, honestly, if I had to put my like money in a tradfi bank and then I guess like even in the US and just ask, close my eyes and then wait for a year later, is it still there? The. I would say the risk that it's gone is probably a little bit higher than half a percent, Right?

Balaji Srinivasan (6:12)

Absolutely. And go ahead, go ahead.

Vitalik Buterin (6:13)

Yeah, talking about this.

Balaji Srinivasan (6:14)

Go ahead.

Vitalik Buterin (6:15)

Yeah, because like there's definitely people who will say it's like some crazy number, like, like 20% and I will think it's that high. Right? But if you're talking about like the survival of your nest egg, your retirement savings, like even a friggin like 2% chance is scary, right?

Balaji Srinivasan (6:29)

Well that's funny because if you take your numbers and you're saying the risk is higher, don't invest in the US dollar what you can't afford to lose, right?

Vitalik Buterin (6:35)

Yeah. Okay. We're starting to get more of these assets that are actually coming online, right? And so if you look, there's obviously the different US dollars, there's like a bunch of different US dollars and there's even, even like things like dai, like they're only partially dependent on like actual US bank, like bank Account deposits and then you're starting to get other kinds of assets. You're also starting to get euros and other currencies. And so you're able to get a pretty good diversified mirror portfolio. And your level of personal political risk basically drops down to zero. And for a lot of people, for rapidly growing percentage of the world, there's a very meaningful and large reductions in your chance of getting a -100% DPY there.

Balaji Srinivasan (7:27)

That's right. And I think so I actually have a few comments on this. The first is that that aspect of like projecting rule of law and contracts and so on that we had talked about for a long time in crypto is actually now not even a reality. It's like a necessity in Argentina or Nigeria or places like this. Right. It's actually like stable coins are actually being used all over the world and I think, I think they flipped Visa and MasterCard not, not too long ago.

Vitalik Buterin (7:54)

Right.

Balaji Srinivasan (7:54)

Like it's basically more so when people say, oh, what does crypto do? What are the applications Crypto where you're like, well okay, there's digital gold.

Vitalik Buterin (8:00)

Okay, fine.

Balaji Srinivasan (8:01)

But aside from that, okay, well it's like bigger than Visa and MasterCard. Okay, okay, what else you got? Right, like and you know, then of course it's already very, very big. Go ahead.

Vitalik Buterin (8:08)

Okay. So we talked about scale, right. We've talked about safety. Also privacy is another big one. And Ethereum now has mature privacy solutions with Railway now privacy pools launched. I mean now even the cash is legal again. Yes. I mean it never really died, right? It actually kept being used, but it's legal even in the, like even in the US to use again.

Balaji Srinivasan (8:32)

We have to get free Roman Storm. Free free and pardon Alexi. Right, thanks. Both free free and pardon Roman. Free and pardon Alexi.

Vitalik Buterin (8:39)

Go ahead. Yeah, yeah. So a lot of, a lot of improvements there, right. Also in, even on the non financial side, like even if you think about like things like Farcaster, like I'm honestly impressed by their staying power. Right. Like, like the default assumption I think any of us would have had a couple of years ago is like this is cool, this is worth supporting because it's decentralized. But like it's so hard for these things to like actually keep users going for past the honeymoon period where they're excited.

Balaji Srinivasan (9:09)

I'm super. I love Farcaster so much and we're going to do so much with Farcaster. It's basically it is the open social platform that we need and you just like they've, it's like a Relay race. I want to take the baton and go further with it. So go. I can say much more about that.

Vitalik Buterin (9:23)

Go ahead. Yeah, like, it's just. It's been running for years. It's existed for years. It has multiple clients. It has a pretty robust, pretty thriving ecosystem. Like, a lot of really great stuff that's happening in farcaster land, right? And it's like. And, like, a lot of people are increasingly realizing, like, the kind of value that it has and like, even aside from decentralization, just the value of, like, a network where you can do, like, you can talk to interesting people and do interesting things and where people are sane. Right. And, yeah, it's also a pretty big deal. Right. And so both on the infrastructure side and on the technical side, like, I think we've just been seeing this really rapid rise in maturity over the last couple of years that I think is, like, actually really easy to underrate. Right? And it's easy to underrate because, like, rise of maturity often feels like nothing happening at all. Right. But the thing that is happening is, of course, stuff not breaking.

Balaji Srinivasan (10:22)

And, you know, the reason that's so important is once something gets to, like, 100% reliability and it's no longer interesting, then you can actually use it for something because you can only have so many, like, risk tokens. Like, if you think of, like, a bunch of Jenga blocks for your startup or what have you, all of the blocks at the bottom have to be, like, 100% like Python, Django. It'll just work, right? It's, like, boring. And then you can have, like, one risky thing on the top, but if the whole thing is risky, then it'll be. It won't work. So the fact that these have gotten to that level of just. Okay, yeah, it'll work. Let me move on to the next thing. Allows you to innovate. Go ahead.

Vitalik Buterin (10:56)

Okay, so we talked about the tech, we've talked about the applications. Like, basically, yeah, even in prediction markets. Another example, like, they've basically gone from theory to being reality. And the thing that I love about prediction markets is how polymarker was, like.

Balaji Srinivasan (11:10)

The number one app in the App Store.

Vitalik Buterin (11:11)

Yeah. Like, it gets mainstream support and attention even from the types of people who normally think crypto is a scam. Like, the types of us political intellectuals that normally just, like, dismiss crypto and think of it as failed. Like, they are the same people retweeting polymarket screenshots. Right? And so, like, that's also been probably the first breakout other than kind of classical defi that we've, we've seen in a long time.

Balaji Srinivasan (11:39)

Um, so another one that's interesting is Open Router, right? Have you guys seen Open Router? It lets you use different LLMs and it just has Metamask login as one of the options because it lets you pay for everything or what have you.

Vitalik Buterin (11:50)

Right?

Balaji Srinivasan (11:51)

That's like crypto as a tool as opposed to like crypto hitting you in the face all the time, right?

Vitalik Buterin (11:56)

Yeah. Like it provides actual useful value. Right? Like you want to be able to talk to LLMs without them remembering everything about you.

Balaji Srinivasan (12:03)

So on that, connecting that to Ethereum, you know, like one thing that's very, very, very rough and you know, I might like, I call this label extremely approximate, is like you're kind of roughly the center left of crypto, I'm roughly the center right of crypto. And we're both like centrists.

Vitalik Buterin (12:18)

Okay.

Balaji Srinivasan (12:19)

And so one way of thinking about this is I think Ethereum, like you talked about the technology of it, but I think from the community standpoint. And so maybe, you know, if you guys. Have any of you guys heard of like Ezra Klein and Derek Thompson's abundance agenda thing. Right?

Vitalik Buterin (12:33)

Okay.

Balaji Srinivasan (12:33)

So, so I think that their thing about the abundance agenda was based on our concept of like Bloomberg Democrats, technocratic people, as opposed to kind of the sort of riots and fires and so on that are happening now. But I think that the sort of central left abundance agenda kind of people should look at Ethereum because I think Ethereum can make a play for being the technocratic Bloomberg center left of the, you know, the, let's say, post Western or Internet world. There's a lot of these sort of stuff, centrist central left people. And if they were actually in control of the left, then we wouldn't have a problem. But they're not. Right? And they're putting up these things and they're trying to take control of the US government, or they think they are, they're not going to be able to do it. In fact, it's going to go crazier. It's going to the Luigi left, not the, not the abundance agenda. Okay. And so because it's happening, in my view, they have to start thinking different and they start thinking about the other piece, which is startup societies.

Vitalik Buterin (13:24)

Right.

Balaji Srinivasan (13:25)

So Ethereum is also into startup societies. Obviously you have Zuzulu and all the sons and daughters and grandchildren of Zulu zoo, Thailand zoo, Georgia zoo this, zoo that. Right. And the. All of those things are basically places where you can experiment with different forms of governance. There's an all abundance agenda, sympathetic people, and so they could actually go and do that kind of thing there. And so I think the technocratic center lefts like the Noah Smiths, Ezra Klein's, David Shores, Derek Thompson's should really lean into Ethereum.

Vitalik Buterin (13:56)

Right.

Balaji Srinivasan (13:57)

And I think that's actually like a social or community aspect because that's not crypto as a scam. That is crypto as actually the opposite of it. It's actually crypto as community. It's crypto as rule of law. It's crypto as, you know, like equality of treatment where everybody's appear on the Internet. Go ahead.

Vitalik Buterin (14:12)

I think like the important thing, right, is that crypto has been a, like a symbolic talisman in a lot of like those ways and also other ways for a long time. But like there is a really big difference between a symbolic talisman and something that can actually do, do things for people that people directly need. Right. And like to me what's interesting is that Ethereum actually is crossing that chasm from being the first into being the second. And also like it's not, it's also not just Ethereum, right. Like this is part of a bigger ecosystem and it goes beyond cryptocurrency, beyond blockchains, even beyond cryptography. Like one of the topics I've been talking about quite a bit recently is D ACT and like trying to create this decentralized defensive acceleration and trying to create this kind of bigger tent around like basically full. Yeah.

Balaji Srinivasan (15:04)

So on that topic. All right, so we're now about two and a half years after the ChatGPT. I want to argue with you about this. Maybe. So are you still an AI percentage doomer or.

Vitalik Buterin (15:13)

I don't know.

Balaji Srinivasan (15:14)

Would you, could you, would you, would you call yourself or you classify that like you had some non zero percentage of it?

Vitalik Buterin (15:19)

Yeah, yeah. I mean, honestly, my P doom has gotten higher. Yeah, I mean, I think the basic reason is that like progress is happening faster than we expected and at the same time global politics is worse than we expected. I think, I mean one of the, to me, like the biggest unrealistic thing in kind of classical doomerism is probably not so much in the problem but in the solution. Right. Because a lot like one of the challenges I often see in the blowing up data centers. Well, no, that's actually ironically the less naive one. The naive one is like the nice guy international treaties approach basically because the classical solution to this is let's get the world to come together and agree to not do all of this stuff. Until we know how to do everything safely. And then at the same time, we're literally talking about a world where countries are invading each other and threatening to invade each other and blowing up tariffs to infinity and all kinds of different things. Right.

Balaji Srinivasan (16:27)

And so I want to argue on this because I think in my view, killer AI is already here and it's called drones.

Vitalik Buterin (16:36)

Right.

Balaji Srinivasan (16:36)

And AI alignment cannot align, quote an AI to everybody. It has to align it to its controller. And that could be one tribe or another tribe. Each tribe will have its own drones. Right. So AI alignment is not synonymous with AI safety and in fact is basically like the fact that killer AI equals drones, killer AI equals robots, means I'm not actually concerned about, in my view, image generators and text summarizers. Right. Like those aren't going to kill us. Right. The robots would. Right. And go ahead.

Vitalik Buterin (17:06)

Yeah, so I'm not, you know, I'm not concerned about the image generators and summarizers either. Right. I think, I mean, I even have the receipts for this where I publicly like basically said that, like, hey, I don't expect, like I basically expected the whole election, deep fake thing to be a total nothing burger. And it has been, I mean, I think to me, like the flip from like danger being only sort of human to AI to danger being potentially. I started like out comes when AI crosses like that roughly human level kind of autonomy and generality threshold.

Balaji Srinivasan (17:37)

Okay, okay, so that autonomy is a big thing I want to poke on. Right. I think to me the biggest surprise and the biggest argument among my tech friends, maybe yours over the last two, two and a half years, especially around the time the ChatGPT came out, is will prompting endure. Right. And the fact that prompting has endured over the last two and a half years and it shows no signs of going away unless there's some enormous technological breakthrough, means to me that prompting is just higher order programming. And it's just programming in English and then you have, you know, programming in Python. You're programming in assembly. And so if prompting doesn't go away, you don't actually have truly autonomous intelligence. You have amplified intelligence. It's not agentic intelligence.

Vitalik Buterin (18:15)

Go ahead. Right, so given that assumption, I agree. But there's this interesting chart that shows the time duration of tasks that AI can complete autonomously. And it has a doubling time of roughly every seven months. And historically, basically naively assuming that exponential curves will continue has been a much better AI prediction method than like pretty much anything else. And so if you naively follow the curve, then you basically get to AI completing tasks on the length of a human lifetime by about 20, 35 maybe.

Balaji Srinivasan (18:46)

It'S possible, but I think, I don't know. The transformers coherence breaks down. And so there's certain kinds of things where, like training is starting to top out, like you're hitting the available amounts of data out there. They need to generate them Right. So often. So I understand your argument. My counterargument is that is that I think genuine algorithmic breakthroughs, conceptual breakthroughs required. I can't say that's impossible. But I would say that right now, prompting is much more of a constraint than people are giving it credit for.

Vitalik Buterin (19:14)

That's a.

Balaji Srinivasan (19:14)

The other thing is, you know, and this is like a counterargument, some of the stuff that Iliezer talks about is I think he really underrates chaos, turbulence, and fundamentally mathematical systems, or physical systems where predictability is genuinely constrained mathematically. Like you cannot predict beyond a certain window given finite precision arithmetic. And if you, you could actually, just as a thought experiment, have, have an AI try to predict the motion of a fluid under turbulence, it. It can't do that without inventing math or maybe doing things we, we don't think are even possible.

Vitalik Buterin (19:45)

Right.

Balaji Srinivasan (19:46)

So if that's just. That just shows that there's limits on what AI can just do as a purely computational thing, not an empirical thing. I don't know. I, I'm just like the idea of one prompt and it just, you know, runs for the whole life. Go ahead.

Vitalik Buterin (19:57)

Yeah. So I do think that there have been walls that have broken before. So the big one that I think really updated me towards some more concern is the whole deepseek R1 chain of thought thing. And the reason why that updated me toward concern is because before that we were in a regime where it felt like the thing that AI is fundamentally doing is it's just basically copying and interpolating off of existing training data. And so if you just do that, then the logical outcome is that AI can do lots of things at like, roughly the level of the smartest humans, but then it tops off there, and then you can't really go further. Right.

Balaji Srinivasan (20:31)

But the chain of thon genuinely shows deliberation. It's like a smart person thinking about it.

Vitalik Buterin (20:35)

That's right, yeah. And basically the way it works, right, is that you start off with a model and then you ask it to solve problems where you can objectively determine if the answer is right or wrong. You have it like run 10,000 chains of thought and give an answer. Then you filter for the ones where I got it right. And then you just train on that again and you repeat the loop. Right. And then I think there for me, for the first time we actually saw a training loop that could plausibly get us all the way to Superhuman. And like there wasn't something that it's obviously constrained by.

Balaji Srinivasan (21:05)

Interesting. Yeah. It's because it's not just the probabilistic, it's also the multiple plans and then selecting from them. I don't know. I think, well, okay, here's a third piece, fourth piece. Here's how you would do this. This is. This is like the. How don't build the Torment Nexus. How would you build the tournament nexus thing or whatever. Let's say one wanted to go about doing that. The. So I think embodiment is obviously another big piece and I think that purely digital AI just can't do it. It's like a life form that only lives underwater and when it comes out onto air, no matter if it's a giant blue whale, it's going to run out of air.

Vitalik Buterin (21:39)

I agree with this too. But like Tesla optimuses are pretty friggin impressive.

Balaji Srinivasan (21:43)

Yeah, well, yeah. So actually the unitrees and all these humanoids have gone. Impressive. Exactly. That's right. So the embodiment will get solved. Right. And but then it has to collect lots of sensor data and I think ultimately it has to have goals. Right. Because without goals that's actually the very hardest thing. Like humans, markets and politics are domains where train and test doesn't. If it worked then you'd be able to just make tons of money in the market. You'd be able to win elections. These are inherently time varying domains that. Yeah, I can't crack right now because you're. You don't actually have an approach to time invariant domains. Go ahead.

Vitalik Buterin (22:17)

Yeah, well I do know that like AI has been showing behavior that's more and more goal like. Right. And like it is a market incentive to try to train for that. Right. It's a market incentive to try to create a thing where you can basically tell it like hey, make a web app for me. And then it just goes off for six hours and like you don't have to think about it again. And then you get a web app at the end.

Balaji Srinivasan (22:39)

Well, the question is though, there might be an MDL kind of argument here, right? Minimum description length or like input complexity kind of thing where like you know, the number of bits. Of course it's got like the web or whatever, it's got it all Cached there. Right. So if you're looking up an existing solution, a small input is enough to pull that out. Right. Like if you want a Sudoku solver, you can just pull that out. But if you're trying, the more novel it is that you're trying to make something make it do, then the more input prompting there's going to. You're going to need. And it's not going to be like a one shot that just gets it. That's my argument. Go ahead.

Vitalik Buterin (23:15)

Right. But I guess in general, right. The way I'm. So my prediction on that is like for any particular category of thinking, like at some point we are going to get to the point where AI has done it. Right. And the reason, and we know it can do it because humans have done it and humans are basically the result of like just stirring some molecules in a soup and then doing about 2 or like 10 to the 40 computation steps of evolution. Right.

Balaji Srinivasan (23:41)

That part. So, so I'm not making the argument that AI won't be able to think through bioinformatics or physics or something like that. I'm making the argument that it'll have to be prompted to do so because prompts are so high dimensional that they're a direction vector in a very, very, very, very high dimensional space. And so how is AI to search that direction and figure out what to do for humans? It's basically like reproduction. Right. So if you actually had the Skynet scenario where you had robots that could dig out, you know, data centers or whatever it was for the, you know, AI to live, and they could actually mine the ore and set up the power generators, they get the full reproducible loop where they set up the factories to turn out more robots and have more AI to script it, then you could actually have something where an AI could have a goal of reproducing or whatever. Right. Like a Terminator like scenario. But. And that's not impossible physically. But the thing about that is probably prior to that we probably have a lot of kill switches in these robots. Like a lot of the stuff was like, oh my God, it's going to learn how to bust out of the box and it's going to like run on every computer like Skynet and it's going to explode out of containment.

Vitalik Buterin (24:46)

Right.

Balaji Srinivasan (24:46)

Do you still think that's plausible? I can give you arguments as to why I don't think that's possible in that way.

Vitalik Buterin (24:50)

Yeah. And I think in AI getting out of containment, like that part is possible. I mean, I can say what parts of the, I know, sort of the doom pipeline, I'm more skeptical of. So have you, have you read the AI 2027 post?

Balaji Srinivasan (25:04)

Yeah, but it's. I'm, I like, I like some of the people there, but I'm not. I just think it's. Why do you think it's naive? For example, it assumes that it's like US versus China. And there's a lot of things that it gets wrong in my life.

Vitalik Buterin (25:18)

But so for me, like the biggest technical thing that felt very implausible is that it assumed a world where, like, where within their universe. Like they literally say this. By January 2029, aging and cancer are both solved. Problems like cure for aging, cure for cancer, they're both listed under emerging technologies. In this kind of world, it's absolutely impossible that we will not have solved pandemics, right? And like in 2030, like basically it's assumed that the AI kills everyone with super viruses, right? And like I think generally, you know, like those kinds of argument, like the arguments, like they're at their strongest when you try to like step back and go into the abstract and you might say this question like, oh, well, see, you know, you have no idea how stockfish is going to beat you at chess, but you know that it is going to beat you. But then the challenge with that metaphor is that if you like, if you give, if you provide a handicap, right? Like actually if you provide, if you take away a rook from stockfish, then even today grandmasters can a lot of the time beat like top ranking stockfish AI. And if you handicap the queen, then the grandmasters, human grandmasters, just wipe the floor, right? And so there is only so much that a particular threshold of intelligence can actually give you, right?

Balaji Srinivasan (26:33)

So that's well to that. Actually one of the most interesting things that I saw was with AlphaGo, you could play adversarial input to AlphaGo, right? And you just beat AlphaGo, right? Meaning what that means is just for the people who don't know this, like with AI image classification, because the way it works, you can feed it an image that looks exactly like a dog but has certain calculated layer of static on top of it that's invisible to the human eye, but that makes the AI think it's a cat, right? That's called adversarial input. And to my knowledge at least there's been no way of defeating this. This is something which is just an intrinsic way of how deep learning works, to my knowledge at least. I haven't seen a paper that does that. And that actually also applies, for example to games. And if you give an input to the AI that's just way outside its training data, you can win the game of Go by doing something that's totally crazy, that AI has never seen before. And it's actually funny. It's almost like that Hollywood movie intuition about AI is like you do something that the robot, it goes beep bop bop, you know, and it turns the wrong way because you're doing something very human that it can't expect. Right. And so to your, to your other point about like the cure cancer type stuff, this is in my view people, you know, I have this concept that never see a book of like God, State network, like what is the most powerful force in the world. These are people who have substituted like AGI for God, right? And what they do, I think is they really, really underrate empiricism. And like I know something about biotech, you know something about biotech. You need to, whatever theory you have and you might be able to actually do a lot in terms of taking all existing papers, indexing them, digesting them, coming up with theories beyond the basis of. You can do a lot with that for sure, it's by medical text mining. But then you have to test those theories. You have to actually go and have test tubes and you have to actually see if it works and you just won't know if it works. You're actually going to be able to intuit. You might have a theory, but you have to do practice. Go ahead, give me your thoughts.

Vitalik Buterin (28:27)

Yeah, and I expect that sort of thing to be like not an issue at all in some domains, but then a huge bottleneck in other domains.

Balaji Srinivasan (28:35)

Yeah, well, embodiment and experiment are massive bottlenecks on AI. Yeah, huge. Like they underrate the physical world dramatically. And they underrate experiment dramatically.

Vitalik Buterin (28:44)

It depends, right? Like for embodiments, I mean if, like if you look at even the current bots, right, Then like they already have a lot of advantages, right. Like I think like if right now we had to bet on, you know, who would win a karate match between like a human and Tesla Optimus, like what would you say?

Balaji Srinivasan (29:04)

Oh, I mean, but like a gun, would machines have been humans for a long time?

Vitalik Buterin (29:08)

Right?

Balaji Srinivasan (29:09)

I don't know actually like a karate match. I'm not sure how agile they are actually. I've seen the videos of them. I think they'll eventually get there.

Vitalik Buterin (29:17)

Yeah, they'll get there. Well. Well, I think realistically they'll beat us on totally different domains, right? Like air is the big one. Right.

Balaji Srinivasan (29:23)

Okay. So when I say embodiment, what I mean by that is you have to manufacture the robots, you have to have them be economically feasible, you have to transport them to location. I'm not saying that these are unsolvable problems, but the friction of the physical world is rapidly. Like basically what we need to do for some of these scenarios to happen is you need to have as many humanoid robots as there are smartphones.

Vitalik Buterin (29:42)

Right.

Balaji Srinivasan (29:42)

Like a billion of them. And that means you have to crack all kinds of business model type stuff. I mean, they'll eventually get there, but it's something where the people are like, oh, cure AI by 20. I just don't think their timelines are correct. And I also think, I mean, so what do you have to have? You have to have a robot that could do all the experiments that a human could do. They're at a bench, they're running those experiments. They have the reagents, they have to have the whole supply chain for them. This is just stuff which is friction that just doesn't move as fast as the Internet. And I think they're underrating that.

Vitalik Buterin (30:10)

Go ahead. So I actually, I mean, I do think that there's enough of a. Yeah. Risk that this stuff will happen very fast. Fast for us to worry. Right. And you know, like, I think probability of more humanoid robots than humans by 2040, I think it's like very non zero.

Balaji Srinivasan (30:26)

I agree with that. I think it's funny, over the last two and a half years, I feel like AI is being both overrated and underrated. And here's why. Like, obviously it's ridiculously important and that's in sundering. I think the long term is. Right. But in terms of like, it's funny how people are actually using AI in practice is they're just like being extremely lazy and using Chat GPT for essays. Right. Or like, it's amazing how many people will just you like literally have ChatGPT write their tweets. And I'm like, you don't think I can tell? It's like, you know, there's like a rhetorical question mark and a. It's not this, it's that, you know, kind of thing. There's. Go ahead. Right. There's certain things they do where it's like, actually I want a plugin which, a Chrome plugin, maybe some of you guys can code this that's like, is underscore AI that runs AI detection on every string on a, on a site and, and then gives you a link because what'll happen is if you say to somebody that posts AI, sometimes they'll be like, no, it's not, or whatever. And sometimes it actually isn't, you know? Right. And it's kind of like an accusation of you're dumb, that's AI. They get offended or whatever. Right. And so, like a lot of secret AI. And so if you run is AI, you get like an either scan link and it'll tell you why that was likely to be AI, not either scan.

Vitalik Buterin (31:41)

But a link that's like that.

Balaji Srinivasan (31:42)

A permalink. Okay. And you paste that and you're like, is AI probability 73%. And you reply to that on X and it's like, let me AI that for you or not AI that for you.

Vitalik Buterin (31:54)

Right.

Balaji Srinivasan (31:55)

And I think. So the way it's being used is like, not all, but it's like an idiocratic version of it.

Vitalik Buterin (32:01)

Right.

Balaji Srinivasan (32:01)

The smarter you are, the better you use AI, and the dumber people are, or the less taste they have, the worse they use AI.

Vitalik Buterin (32:07)

Right.

Balaji Srinivasan (32:07)

But that's. It just feels very different than any emergence path of AI that's being in science fiction or literature or anything like that. Go ahead, give me your thoughts.

Vitalik Buterin (32:14)

Yeah, I think the emergence path of AI has violated expectations in just, like, all kinds of different ways. Right. And so, I mean, even. I mean, like, it just repeatedly keeps on doing that. Right. Like, if you think of, like, even the 1970s, like, they. Yeah. Like they would not have expected AI to be able to solve arbitrarily complex arithmetic and, like, take 10 years, but take 40 years to tell a cat from a dog. Right. And then even today, the line of what are the things AI can do and what are the things AI can't do? Is very difficult to describe. And I think one of my theories is actually that the last tasks that humans will be able to do better than AI will be precisely the most illegible ones, because those are the ones that are the hardest to train for.

Balaji Srinivasan (33:06)

Yeah. So actually, what is your list? Because I'll give you my list.

Vitalik Buterin (33:09)

I mean, it was interesting. I remember talking to someone, he asked me, like, what is your, like, benchmark for? When you would say, yeah, this is AGI. And I said, when an AI is able to independently start a profitable company.

Balaji Srinivasan (33:20)

Interesting. Yeah. So everybody's got. I. I think I would argue we've already passed, quote, the threshold of AGI in some sense for some domains. Like, it's better at math than many people. It's better at.

Vitalik Buterin (33:31)

Better at. Right.

Balaji Srinivasan (33:31)

Yeah. It'll make mistakes. But People make sticks at math. You know, it's funny, these two questions, what can't AI do? And what can't China do? I think are the most important questions for anybody who's doing a new startup, right? Like or like you build your business to assume AI or China will improve towards that and then you'll ride with that or at least be invulnerable to that rather than the opposite, right? So the. I mean, the thing that I'm seeing is AI right now for, and maybe for the indefinite future, it doesn't do polish, right? So it will actually, you know, the whole thing about AI takes a job, here's a reframe, which. A reframe which is AI lets you do any job at an okay level, right? You can be an okay artist, you can be an okay video editor, you can be an okay 3D designer or whatever. You can at least get your vision out onto paper, right? And it's like kind of getting to like a five level or something like that. It might be a cheesy generic version, but you can do any job. So in a sense, AI means a crude form, not crude, improving form of digital autarky, so long as you have access to the Internet, right? And China is physical autarky because they're the most physically independent country in the world because they can build everything themselves, right? So that's how I kind of think about it. But it's not getting really good at that area because the threshold for really good keeps moving forward as AI improves. And to actually check the result, it might generate a math theorem. You actually have to be a research mathematician to even understand the symbols and check it. Go ahead, give me your thoughts.

Vitalik Buterin (35:01)

The mental model I use is like, if human level is like normalized at some level like this, right, across a range of tasks, then basically AI kind of looks like this, right? It's like better in some domains, worse in other domains. And this curve just keeps shifting to the left and often very wobbly and unpredictable ways, right? And so it's like, it's. It's. I think for 50 years it's been super huge. Like from, okay, from the perspective of the economy, in 1800 by like, probably the year 2000, we basically had like, ASI from the perspective of like, probably over 80% of the economy, right? Like, if you think of farming, what percent of that was automated even by the year 2000, if you think of manufacturing, right? And so what I think is happening and the pattern that will continue for a while is basically this pattern where Essentially both economic and social value. They continually refocus on the subset of tasks that AI hasn't just hyperinflated to zero. Right, right. And I mean, at some point we're going to enter a new a regime where that set of human dominant tasks, like, actually shrinks to exactly zero. Right. But we're not there yet. The question is what. What happens when they eventually get to the point where they can, like, think a hundred times faster than you and at the same time they consume like 0.1 watts of energy and stuff?

Balaji Srinivasan (36:21)

There's still comparative advantage, right? I mean, or rather, I, I guess that's a question. Does comparative advantage between AIs and humans exist? And you can argue there isn't any with dolphins, right?

Vitalik Buterin (36:32)

Yeah.

Balaji Srinivasan (36:32)

Like, dolphins are just pets, right? Dolphins, you just kind of feed food. There's nothing you can really delegate to them. They just can't figure it out. Whatever, you know, like, go, go, go, go have, have fun. Right. So it's possible that it gets to that level, but I think at least until the prompting issue is solved. Right now it really appears to me that it's like artificial intelligence is just constrained by human intelligence. Like, you know, it's basically like the better you are prompting, the better the AI is. And conversely. Go ahead. Even if you spell something wrong, it gives you a worse answer. Right?

Vitalik Buterin (37:03)

Yeah, I fully agree that that's the status quo today and probably at least for the next couple of years. Yeah. Okay, fine.

Balaji Srinivasan (37:09)

All right, so. All right, so let's move to maybe talk about one more thing. Let's go to questions.

Vitalik Buterin (37:14)

Okay.

Balaji Srinivasan (37:14)

Startup societies, Zizulu and so on and so forth. So after Network State Book came out, you actually, there's actually an old diagram I had, and then you kind of moved one more box on that diagram. Go ahead, why don't you talk about that?

Vitalik Buterin (37:26)

Yeah, basically. So the box was. I mean, this was actually originally. Yeah, right. The diagram from your book, which is basically how many people are there and for how long a time do they come together? Right. And so, you know, it's like number of people, you know, 200,000 million. And then amount of time, like one day, one week, a month, a year. And then you have like tinder over here and then you have eharmony over here, you have universities over here and then countries over here. So with zizzle, like, the idea was that, okay, you know, we've had lots of things that happen where people come together for, for a week, but there is this like, big discontinuous change that happens. I think when you allow the duration of time to get longer, like basically the psychological shift that happens, and I'm sure a lot of you can probably relate to it at this point, is that a week is a break from your life, two months is your life, right? Like, yeah, like if you stay in a place for two months, like you actually fully readjust like that being the normal, right? And it like actually becomes a day to day rhythm as opposed to something where like, you know, you know, you've done a few days and there's a few days left and then you're gone. And then on the other side is like scale, right? So there's what you can do with like 10 people, which is a hacker house, but then there is what can you do when you get to like Dunbar's number, which is 150 and that's the level at which you start to just need to have multilevel structure in your society, right? And so like 2 months at 150 is like this level where you actually start to get a lot of the complexities of doing something more meaningful at a larger scale. But at the same time it's like still small enough that it's practical to bring together and it's manageable. Right. And so, you know, I see in that Zeus alu was about 200 people for two months. Like I think it's a, it's a good range within which to like, to like experiment and like try to figure out what are the actual kinds of things that we can do. And the general way that I see this, right, is that like, I think this is a good scale at which you can dog food things at which you can actually like start to go from having some new idea about how a civilization might work better to not just like blabbing about it on the Internet, which is what people did on Internet forums back in 2009, but like actually try it out and you actually get like real world information about where the successes and failures are.

Balaji Srinivasan (39:43)

One of the things that's interesting is people in the community develop things for the community, right? Like, like the community was their beta testers or what have for different types of income.

Vitalik Buterin (39:52)

It's a full stack incubator, right?

Balaji Srinivasan (39:53)

Exactly.

Vitalik Buterin (39:54)

Basically, I think there's a big difference between being a service provider and being a community. I think for example, this is probably one of the things that the whole E. Estonia movement of 10 years ago got wrong, which is that they had very advanced E government for their time. You could vote online, open up bank accounts online. Do you you will start companies online, all kinds of things, really advanced. But the difference between a product and a community is that a product is a hub and spoke model. It's n people who have a one to one relationship with some kind of center. A community is a model where you have NB or you have n people that all have relationships with each other. And I just like in Estonia, I think the problem was that or for E Estonia, there was not enough commonality between the different people who were Estonia residents for them to like actually really become a cohesive community. Right?

Balaji Srinivasan (40:48)

Yeah, exactly. It's like community is connectivity. That's actually how like literally of n people you have n choose to possible relationships or N squared if they're asymmetric. And then you divide how many relationships actually exist by the number of possible relationships. And they just had a hub and spoke thing where everybody was connected to Estonia but not to each other.

Vitalik Buterin (41:09)

Right. And so I think one of the unique things that the sort of community as incubator can do. Right. Is like it actually gives you a community as a beta test user. And there is a big difference between having 100 beta testers and having a community of 100 be your beta tester. Right. And the difference basically is it's the difference between 100 people who have no pre existing relationship and need to interact with each other versus being people who do have a lot of those needs every day. And so one of like this is I think to me like a very unique value proposition, right. That you can actually start a thing and then you can bootstrap, incubate it in a community and then you can actually make a huge amount of progress together.

Balaji Srinivasan (41:49)

That's right. And I think, you know, I do think the startup society ate this as a concept. Like what you're doing on the zuzzle side, we're doing the network school, we're helping bootstrap others. I think this is the third type of thing, like Internet company, Internet currency, Internet community. You know, I've said that before, but I think it's like the third type of thing that you can start, you know, go ahead.

Vitalik Buterin (42:09)

Yeah. So one other thing that we started doing in Zozo and that we've and I think also like gotten in. I mean we really have been in a long time right as biotech and you know, I think it's interesting that like crypto has had this kind of interesting sort of sister relationship with frontier biotech pretty much ever since it began. Right? Like definitely, far from just myself, a lot of early crypto people Were also very big into longevity.

Balaji Srinivasan (42:35)

Jim, my thesis on why.

Vitalik Buterin (42:36)

Oh, go ahead.

Balaji Srinivasan (42:37)

You know so well, Hal Finney was an extropian, right? But I can actually give an exact parallel between crypto and longevity, which is what with, with Bitcoin. Initially it looks like the existing financial system, but in some ways with bar charts and trading and stuff. But it rejects fundamental premises because the existing financial system says that while hyperinflation is bad, deflation is also bad. So you should lose a little bit of your wealth every year. Like a little bit of inflation is good. That's normal. And the medical system is similar. It says while fast death is bad, right? Like trying to live forever, like deflation, the equivalent of that increasing your lifespan every year, that's also weird and bad. So you should lose a little bit of your health every year via aging, right? So the traditional financial system says, lose a little bit of your wealth every year. Traditional medical system says lose a bit of your health every year, right? And the entire crypto and longevity community says, what if we reject that? What if we attack it from first principles and say like, maybe we don't have to go to zero, maybe we can get to infinity instead.

Vitalik Buterin (43:42)

The nice thing about longevity, right, is that I think it's on this like really nice trajectory toward being much more mainstream now, right? Like, yeah, Brian Johnson is like a mainstream cultural figure, like non technical friends of. I think many of us know who he is, right? And there's been a huge amount of progress on that. And I think one space that I think is still in an earlier part of the curve is resistance to airborne diseases. And I mean, we had a dry run of this during COVID right? And like Covid is worse than existing diseases, but it's also much less bad than it could have been. And like it was in this weird mid zone where basically it was not bad enough for us to like properly take it seriously, but at the same time, like it actually is much worse.

Balaji Srinivasan (44:33)

You know, there's this concept on Twitter sometimes of the secret third thing. Have you heard that before?

Vitalik Buterin (44:38)

Right?

Balaji Srinivasan (44:38)

And essentially, if you guys don't know this meme, it's like, are you a Democrat or Republican or. Or a secret third thing. And it presumes that you must be in one of these two categories and otherwise, you know, it's like a fake thing that there's any more complexity than just 0 or 1. Right? But obviously if you look at, and I'll get to my point a second, if you look at like an image, you know, an image has more than one pixel of information.

Vitalik Buterin (45:00)

Right?

Balaji Srinivasan (45:00)

And like if you only had 0 or 1, you would be able to scribe an image. Some things have necessary complexity, more than just 0 or 1. It can't be reduced profitably to that. And I think with COVID for example, one way of sort of crashing the operating system of some, some people online is they're like, on the one hand, it's like this dangerous virus that escaped from a Chinese lab. And you know, it's like so bad. And so. So for the other hand, it was just the flu, bro. And it didn't do anything. And why are you so mad? Right? Why do we do anything about it? Right? And a lot of people hold both of those beliefs at the same time, right. They're obviously incompatible with each other.

Vitalik Buterin (45:34)

Right.

Balaji Srinivasan (45:34)

Where either is like this, this fairly serious thing or it was a completely non issue. And I think it was actually fairly serious. And it did come out of Chinese lab.

Vitalik Buterin (45:41)

I mean, it's not the word was. Right? It is very serious.

Balaji Srinivasan (45:43)

It was slashes. Exactly. That's right. And it killed literally millions of people. But, and this is a weird thing. See, the thing is, in early 2020, if you had said, okay, just warp your way back to January 2020, if you said this is going to kill 10 million people globally and a million Americans and in a few years it's not going to be that big a deal. Okay. That's literally how people are thinking about it.

Vitalik Buterin (46:04)

Right? That's.

Balaji Srinivasan (46:04)

Which is actually kind of. If you had said it's not a big deal or it's going to kill millions of people. Those just seem like thesis antithesis and somehow we got a synthesis which is totally crazy where it literally killed a million or millions of people. And it's also considered. Dude, you're just exaggerating. It's kind of like life goes on after World War I. Well, it does for those who didn't die. Right. But you know, it was actually a pretty big deal at the time. Right.

Vitalik Buterin (46:25)

Go ahead. Right. I mean, I think one of the. Yeah. Important things there. Right. Is that like Covid itself is still an ongoing thing. Right. Actually, yeah. I mean, I got it quite recently. Yeah. Actually, if, if it weren't for that, this whole thing would have been happening like a week and a half earlier. But based, you know, it's still happening, it's still bad. Like the long term symptoms are still pretty bad. Right. And if you think about just like how our civilization's media apparatus is handling it, like from a media perspective, Covid basically ended on 2022, February 24th. Right. Like, that just is how our media, like, apparatus works. Right. Like, you can only handle one big story. Think about one big story at a time. Right. And the reality, of course, is the current thing. Yeah, exactly. Like there are multiple current things. You know, Covid was not cured. There were new variants. The efficacy of the vaccines went down to about a quarter. And like, basically, yeah, the. And then the scarier thing is what could kind of come next. We basically have to get ahead of all of this stuff, and we have to massively increase our civilizations and biodefense. Like, I think in the UK there was a wastewater surveillance program that's like, very good. And like, the. The smart technocrats on both sides will tell you that it's good. But then, like, pretty much sometime 2021, 2022, it was just canceled.

Balaji Srinivasan (47:41)

And I mean, I think the problem is, unless the next pandemic literally photographs, like Ebola or something like that, hopefully it doesn't. There's people who will just literally deny that they've gotten to the point they'll just deny the germ theory of disease. You know, they just don't even believe that, like, you know, any.

Vitalik Buterin (48:00)

Not, not.

Balaji Srinivasan (48:00)

Not that a vaccine works. They don't believe any vaccines work. They don't believe drugs work, they don't believe biotech works, they don't believe pharma works. And you're. There's totally throwing the baby out with the bathwater. Go ahead.

Vitalik Buterin (48:11)

Yeah, I mean, well, it's.

Balaji Srinivasan (48:13)

I've got two solutions for that, by the way.

Vitalik Buterin (48:15)

Sure. Okay, well, what are your solutions?

Balaji Srinivasan (48:16)

So the two. Two solutions, and this is actually true for everything, the two heirs to American empire are China and the entire Internet. And so, for example, when it comes to biotech, like, if you look, China actually flipped the US and the rest of the world in like, science papers, nature papers, like, highly cited biotech. Like, they have a functioning replacement for American academia. And like, if you want to know whether, like, they're not as political about or not political about it at all. So if a treatment works or not, like a Chinese clinic, they will basically be able to tell you about a crazy left or crazy right version of it. So that's one possible solution that's for, you know, within China. And the other solution is the Internet, where I think with dsai, right, you can have people who are neither, you know, crazy people. Like, the whole thing about, you know, in mid-2020, where people are like, public health, people in the US destroyed the reputations by Saying, you know, racism is a real pandemic and you need to go out and protest and so on and so forth in the middle of a pandemic and just completely vitiated all their guidance on lockdowns or what have you. This made people completely distrust all U.S. public health. And then you had the right then saying that vaccines don't even exist. So both sides are just completely crazy about biotech, they're completely crazy about biology. So the answer is either China or it's the Internet. So you have dsi, decentralized science, diagnostics, self experimentation, Brian Johnsonian, where you're measuring your own body and taking responsibility for your own health. You've got the air quality metrics, you've got the personal sequencing, you've got, you know, all of this, you've got your own dashboard and you're working with a community of people of like mind to get to scale where you can aggregate that data. You can start calculating, okay, is my numbers, are they out of sync, are they in sync or what have you? Right, so those are the two approaches, I think, to like, rebuild biotech and just assume the solution is outside America.

Vitalik Buterin (50:04)

Go ahead. What's interesting, I think on, like some of this bio stuff is how. How a lot of the solutions are surprisingly low tech, right? Like we're like, basically. So we know this lamp here, this is a UV lamp, 222 nanometer light. So if it's under 3, like about 2, like 300 nanometers, that means it's like actually like fine for your eyes and so on. So it doesn't like hurt you the same way sunlight, ultraviolet does. And what it does is it kills the viruses, right? So it just passively, basically significantly reduces the chance that people in the room are going to infect each other without any airborne pathogen. So this is like, this is one type of technology. Another type of technology is air filtering. A third type of technology is just better ventilation. Like, there's really basic things that can be done. And like, the big bottlenecks are like, what? Like a lot of the time the bottlenecks are just like people getting off their butts and doing things right. And to me, this is also part of the value of some of these, like, startup societies, right? That you can actually take things, things that really the smart people know are obviously correct, and then you can just go and do them right? Because a lot of the time for mainstream adoption of these kinds of things, like, the bottleneck is not about the technology. The bottleneck is like from a politician's point of view. Is this something where they have to go do something untested or is it a copy paste job?

Balaji Srinivasan (51:24)

So this is very, very, very important because basically startups is sid our deployment points for exactly the obvious cool high tech stuff that we can now deploy at hundred or a thousand unit scale. Because it's like it's something where people have opted in to basically pushing the frontier of tech. And they can. Of course you can. You know, not everybody has to opt into a DNA test, not everybody has to opt into an error monitor. But the kind of people here are going to be more interested in that kind of stuff because it's like the frontier of held, frontier of tech. So go ahead, why don't we take some questions actually.

Vitalik Buterin (51:57)

Go.

Balaji Srinivasan (51:57)

Yeah, if you want to pull it up. All right, great. So why didn't you build Ethereum anonymously like Satoshi, if you could go back, would you do that?

Vitalik Buterin (52:06)

I think it would have been too hard. Like the problem is that by the time Ethereum started, I was already a Bitcoin magazine author for two years. And like one, I just like put way too many words on the Internet. It would have been findable. And two is I think like Ethereum's beginning really did like my ability to get any kind of critical mass. I think definitely bootstrapped a lot off of people already knowing and trusting me from Bitcoin magazine. Like it would have just been a way harder job.

Balaji Srinivasan (52:31)

A non obvious point is pseudonymity is itself a form of decentralization. And the reason it is is because like your government name is in a government database. So it's a centralized name, it's linked to all the information about you. You punch it into a search engine, it pulls up everything on John Smith. Whereas Satoshi Nakamoto is a decentralized name, it's outside of that. Right. So in a sense pseudonymity is itself a form of decentralization. They couldn't hit either the man or the ball of the network. Right. But once bitcoin was out there, it was like a heat shield for you. It's like, you know, the NASCAR or Indy 500. You can kind of kind of like slipstream behind a car.

Vitalik Buterin (53:05)

Right.

Balaji Srinivasan (53:06)

So you didn't have to use exactly the same tactics. Similarly, with network state, personal distribution is important. So the way that we're doing decentralization is lots of startup societies. So it's not just like Vitalik Ville or Balaji Berg or whatever. I want many of you guys to set up your own startup societies. We'll fund those there's many different visions of the good, right? And, and so that's decentralization, another form rather than pseudonymity. Go ahead.

Vitalik Buterin (53:31)

Well, what's interesting to me about like the whole zero knowledge proof thing in particular, right Is like it opens up the entire design space, right? Like if I remember like 15 years ago, the whole narrative is like basically the dichotomy between sort of trusted institutionally because KYC'd versus on the Internet, nobody knows you're a dog. And the challenge now of course ZK reconciles that. The challenge now of course is that if you don't prove you're not a dog, then you're also not proving that you're not a bot. And so there's no reason for people to listen to you. Right? And so but what the zero knowledge proofs gives you is they give you the ability to have privacy, but at the same time have, have reputation. And so, and that what that also means is like you actually have an incentive to like say and, and do things that are constructive because they increase your reputation. And that's reputation that you have and can use in a future context, despite the fact that all of this reputation is being mediated through zk. And so like actually every operation is unlinked from every other operation.

Balaji Srinivasan (54:37)

And I think like you know, zero knowledge is definitely underrated and if you're, if you're going to spend, if you're early in your career, that's, I don't know, there's some things I think ZK biotech, things like that haven't had had their massive breakout moment yet. And ZK was definitely one. Okay, here's another one. This is, you'll like this one. Okay, what are a list of some thousand to one or ten thousand to one return public goods that we could or should have but don't.

Vitalik Buterin (55:03)

And I think one of the things is just like more kind of standard form packages for things. So if you want to start a guest, if you want to start a startup society, then here's open source software that you can start with. Here's the 1, 2, 3, 4, 5 guide of what kinds of things you should do if like you want to do something digital. Like say yeah, like me thought through templates. Yeah, exactly like thought through templates for like pretty much everything is a big one. And also I think on the like education side like the biggest under provided thing that I think like I've identified and like I even a lot of my writing has been about trying to compensate for since the beginning is like like you've probably seen a lot of this with math, right? Like you have a bunch on the one hand you have papers that are technically accurate, but they're just like so insanely complex and everything's in like freaking Greek. And like nobody can understand it except for people that have had in person conversations with the original authors. And then on the other side you have like pop sci ma. Like stuff that just doesn't even try to be accurate, right? And they tell you things about how, oh, Schrodinger's cat means that like the cat can be dead and alive at the same time. And, and like you, you know, absolute. Like that sentence gives you absolutely no intuition whatsoever about like what is the point of, of, of quantum, right? But like it makes you feel smart because you know the password, right? And so, you know, there's like an entire space that's like in the middle there that like actually tries to like give you the intuition, like helps you understand things, right? But then, but in a way it's like actually understandable to people. And in general, like if you're creating educational resources, like, to me that's like a huge unclaimed opera like space of opportunities to provide value. Like, and that repeats itself for pretty much everything that's emerging. Yeah.

Balaji Srinivasan (57:02)

And I think we want to do a lot of that at network, state or school. So here's a good one and maybe you can give an answer and maybe this may be something we disagree on.

Vitalik Buterin (57:10)

Maybe not.

Balaji Srinivasan (57:11)

Approximately 99 of stablecoin market cap is backed by dollars. This reinforces USD 7 of 10 largest BTC owners are or US entities. How does the US not win if crypto wins? So you can give an answer and I'll give mine.

Vitalik Buterin (57:23)

I mean for first of all, right, it's like all of these things are chaotic systems that just have a huge number of all kinds of different variables going in all kinds of different directions, right? Like five years ago China was the winner of mining. And then, you know, the government itself like just finally banned mining hard enough that I think actually China still does 10, about 10% of Bitcoin's hash power. But it's like basically knocked out of the number one position. So all kinds of things could happen, right? And so, you know, the, and there's even all kinds of things that the US could do with respects to crypto, right? And then obviously then you know, the. There's all kinds of things that even like the individual crypto holders in the US could end up doing, right? So that's one and then two, like Macroeconomics can just go in all kinds of different directions, right? Like where basically breaking an 80 year era of stability in about three different ways at the same time. And what do you look at as.

Balaji Srinivasan (58:21)

Those three different ways? I mean, the tech of AI and so on.

Vitalik Buterin (58:25)

Yeah, I mean I think like basically like domestic politics, international politics and AI. And I mean even AI itself. Like you can expand that like, basically like thinking in terms of like technology exiting the great stagnation in general. Right. So, you know, I think we've been seeing bio exiting the great stagnation. We've been seeing virtual reality exit the great stagnation. Like a lot of these things also really feed into each other, right? So basically from like there is just a lot. The Internet is also a big one. Like the Internet has just changed a lot of variables in terms of what kinds of things in our world have an economic premium and what kinds of things don't. And so the, like, what dominates can just change massively over the next five years in directions that pretty much nobody has been predicting. Is I think one part of my answer and the other part of my answer is like once you're on crypto rails, your ability to go from one thing to another thing just becomes a hundred times easier.

Balaji Srinivasan (59:23)

Okay, great. So that, that leads directly to my answer to this question. So actually I should do a. I'm going to start doing video Twitter tweets. Okay. Meaning like 59 second, 29 second vertical videos. So one of them will be on the defi matrix. Okay, so defi matrix is if you imagine the table of every asset across every asset, right? So you have fiat currencies, you have cryptocurrencies, you have NFTs, you have domain names, ENS domain names and so on and so forth. All of them. Now due to uniswap and due to all of these on chain, market makers and exchanges have a price. Like you can get out of this asset into that asset and you can do it right now and you can do it for the whole thing. You can market sell. I mean, you may not want to do that, but you can do that.

Vitalik Buterin (60:06)

Right?

Balaji Srinivasan (60:06)

And so the moment that you loaded the dollar on chain, you made it swappable in a million different venues, any time of day and night, by anybody in any country at some price. Right. It's like putting something onto an ice skating rink and it can move in any direction with very little friction, very, very, very, very quickly. At the speed of crypto, which is like that, the speed of the Internet, it's not Banking hours, which are 9 to 5. It's not capital controls. It's not within the control of the US Banking system in the same way, it's at the speed of the Internet, right? So that alone is a huge change, which is the. You know, sometimes something is forklifted into a new domain and it. The forest forklift itself, everybody's focusing on it for a while, but it's now in a new domain. And the physics are totally different. The Internet is totally different. So the defi matrix, because it means you can swap in and out of something, that actually means. What's another term for people use for cash? They call it liquidity, right? Getting liquid, an ipo, right? That's like how a tech bro says, like, you know, I'm making money, okay? So the, like, liquidity can now actually happen without actual cash because you have an asset that you can just swap in to whatever asset you want with a click, there'll be some price for that. But you can keep it all in bitcoin, you can keep it in something else. So that's, number one, is that means. By the way, here's a very important thing. Joe was similar to the defi matrix. An analogy is in the early 2000s, okay, there were all these newspapers, okay, and they forklifted themselves online. And there was just like the online version of the New York Times and the. And the, you know, Miami Herald and San Francisco Chronicle, they just forklift themselves, like, okay, I'm online. What's the big deal? I'm online, I'm offline. But once they were all online, Google News could make a table of all of them. And suddenly when you loaded Google News, you saw they were all reprinting the same story, the same Reuters clip. And they didn't have unique stories. There's like 73 outlets reprinting the same Reuters clip. And suddenly everybody realized, oh, wait a second, these guys just have a thin layer of like local news on top of basically like wire search services. And so that began essentially the commoditization of local news. And local news basically died, right, because you could just get your news on the Internet. The forklifting revealed that these were commodities and their previous moats that they didn't even realize remotes were the geography because they had trucks that delivered the newspapers, they had ink. That whole saying of never argue with a man who buys ink by the barrel. It's actually now, you know, you can always defeat a man who still buys ink by the barrel. They can. They can't argue with you, right? You don't have to buy ink by the barrel.

Vitalik Buterin (62:37)

Right.

Balaji Srinivasan (62:38)

So the point being that what they didn't realize is that by forklifting it online they lost their moat and then they were put into total global competition with everybody else. And then all the local newspapers died and only the strong survived. And the craziest, you know, most international news or whatever you know, dominated. That is what's going to happen to every fiat currency.

Vitalik Buterin (62:57)

Currency.

Balaji Srinivasan (62:58)

Every fiat currency is now in a war for its survival comparable to local news because their only advantage was their geography. They're basically all doing the same thing as everything else.

Vitalik Buterin (63:08)

Right.

Balaji Srinivasan (63:08)

It's only the geography that provides any advantage for a fiat currency. So what that means is they're now going to have to. If you think that would happen with local news or the news, it, it couldn't compete on geography, instead it competed on ideology. You have all of these online different niches and verticals that are global but competing on ideology as opposed to location. Right, okay, so that's what's going to happen with assets already happening. They're going from competing on geography like you know, this fiat and that fiat, to competing on ideology and on features which are like, you know, zero knowledge or like smart contracts or like unprintability of Bitcoin. That's already happening and you're having tribes form around them. What hasn't happened is for many fiats to die, many fiats are going to die. This is my view.

Vitalik Buterin (63:49)

Right.

Balaji Srinivasan (63:49)

When many fiats die, lots of things break because it's a tool for social control and so on. And bitcoin will moon more than you can imagine. It could moon and so be in a safe country at that time. And so then the, to the other point is like how does the. So that's how like basically with the stablecoin market cap and then so it doesn't reinforce USD exactly, it just makes it very liquid and it can swap into anything else and you could easily have some other asset that you swap into. And then in terms of seven of the 10 largest holders are, are American. Well, the, the issue is that the US is not, it's not the United States, it's a disunited states. And so everybody's just taking a chair and using it against the next guy. And the red team says the blue team did it, which they did. And the blue team says the red guys just did it, so. Which they did. So even Delaware is being destroyed. Right. It's like a civil war where every institution in the US is getting wrecked. Right. And then the Internet survives because The Internet is one what stays up even in the time of nuclear war. So the only reboot is from the Internet. That's not the US winning, that is the Internet surviving after this whole. All these institutions get melted down, which is a very different thing. And fundamentally, I think the fundamental optical illusion that you want to wrestle with is, is the Internet American?

Vitalik Buterin (64:57)

Right.

Balaji Srinivasan (64:57)

It's like saying, is America British? On the one hand, of course America is British. It was born out of Britain, speaks English like, you know, the early colonists, the names of towns, George Washington, all that kind of stuff. On the other hand, it's clearly something that's become much more than Britain. It's exceeded even its worthy progenitor. Okay, so I'm going to do a few more and then maybe two more and then we'll wrap. Right? Okay, so, all right, this is a good one. How can we, how can we mega. How can we make Ethereum great again? All right, if you. Or if you maybe have a different slogan. So massive tariffs on all uniswap trades out. You know of Ethereum, right? Okay, fine. No, how can we make Ethereum great again? What should Ethereum's North Star goal be? Number of Dows, price total holders, etc.

Vitalik Buterin (65:44)

Yeah, I mean, I think Ethereum in general, like, it needs to have like twin. Like the twin goals basically are like, one is like getting used and, and getting used at a large scale, and the other is of course continuing to sort of be something that's worth being used in the sense of being something that's meaningfully much more secure and much more decentralized and so on than the kinds of systems that people would be using otherwise. And obviously I think if we sacrifice on either of those things, there is no point. Right? Because if Ethereum can't scale and it can't provide enough security and it can't provide enough experience, then whatever properties that happens, they don't reach anyone. On the other hand, if Ethereum gets scaling and UX at the cost of like basically becoming a copy of Tradfi, then like, there is like, there's also either no points or at least like much less of a point that there could have been. Right. And so the question is, how do.

Balaji Srinivasan (66:49)

You argue that point? Okay, my argument is sometimes you can have something that's cyclical in the X, Y plane, plane, but the progress is on the Z axis. So even if you rebuilt, like, for example, there was Microsoft and there was Google and then there was Facebook and there's like, even though they're like new guys Same as the old guy. They're not exactly the same. There's actually progress technically, like React is better than Angular, for example. Right, Go ahead.

Vitalik Buterin (67:12)

Yeah, yeah, okay, that is fair. But I think there is a strong technical roadmap that gets us both of those things, right? And the technical roadmap is, I mean, basically there's a bunch of strategies to scale both L1 and L2 execution, right? And I mean, we've talked like, there's stuff like delayed block execute, block execution, block level access lists, distributed history storage, like stuff that I think there was like a pretty good bankless podcast with Ethereum researchers about some of these kinds of things about a week ago. So on the L1 side and then on the L2 side, of course, increasing the number of blobs and using Peer Dust to be able to handle that, and then finally using zk snarks or I guess realistically starks inside of the L1 for scaling. So just like actually applying all of that technology. And I think there are things that we have to kind of rethink on a fundamental level to update some of the ideals from some of the early Satoshi era, right? So probably the biggest thing is the thing that Satoshi did not understand that well is the asymmetry between creating and verification. And it's ironic because in proof of work, like you actually totally did, right? But if you think about every other aspect of Bitcoin, right, a block takes as much computation to create, not the proof of work part, but like the part of choosing the contents and. Right. As it does for someone else to verify, right? Like the cost that it takes, the amount of computation bandwidth storage that it takes to run a verifier is exactly the same as what it takes to actually choose the contents of the block in the first place. And that was an inherent limitation of the pre zksnark era, the pre stateless client era, the pre access list era, basically the era before all of these different scaling concepts have come up. And the way that all of these scaling concepts work is they basically say, well, they put more load on one node and they ask the one node to do more work in order to create hints that then make the work of verifying much, much easier for everyone else, right? And so take advantage of that asymmetry, right? That is what stateless clients are about. It's what ZK snarks are about. It's what data availability sampling is about. Like, basically all of the fancy buzzword technologies are ultimately some version of this, right? And the challenge is like early Bitcoin mentality really valued this concept of running a node at home, right? And the challenge was the good aspect of this is like, what you want is you want a system where the rules of the system are rules where like, if those rules start getting broken, the blocks that break the rules just automatically get rejected by everyone immediately, right? Like, Swift does not give you that property, right? Credit cards do not give you that property. Like, if I get, like, have a US dollar balance, I have no way to verify that these were dollars created with an algorithm that obeys any particular limit on how many dollars are in existence, right? And so what you do not want is you do not want a system where like five people can get together, they can change the rules, and then everyone else accepts them by default, right? You want a system where changing the rules is actually hard, right? This is like constitutionalism, but like a level above that because we're basically, basically going into smart contracts and doing it at the level of tech, right? And so to do that, like, basically the bitcoin way was to say, well, you'll have everyone re executing everything at home, right? But with snarks. Like, basically you have this asymmetry. You have the difference between nodes that are responsible for building the chain and nodes that are responsible for verifying the chain. And then you have a whole spectrum in the middle, right? And the question is, well, actually if you allow the cost of building parts of the chain to be a little bit higher, then you can massively increase the scale. And you can increase the scale, basically you can increase the number of users who actually get to benefit from your chains guarantees directly, right? Like this is one of those things that like mistakes that El Salvador made, right? It's like the lightning network implementation, like it was actually based on custodial wallets. Like the.

Balaji Srinivasan (71:32)

So on the.

Vitalik Buterin (71:33)

I'll say something, but like, basically the question is like, how do you avoid that, right? And b, basically the solution is like, well, you basically have this kind of hub like model where you have a smaller number of more powerful nodes and like you're concentrating the proving work and at the same time you're massively distributing the verifying work, right? Basically the challenge is like, if we can actually do this, then like, we actually can like create something that is sort of maximum decentralization and maximum scale at the same time. And, and the technology exists to actually do that, right?

Balaji Srinivasan (72:03)

It's funny because that is like 10 years after Bitcoin. It would only have come up after people pushed on that part of the Trajectory. One thing is I do think bitcoin scalability, it's not lightning. I'm very skeptical in some ways about it, but it actually already exists. Which is it's either A an infrequent on chain transaction or B it's an off chain transaction to something like Coinbase or Binance or El Salvador or whatever that just runs essentially off chain transactions between its people. So you have infrequent digital gold movements between these hubs and then you have like all these spokes on these hubs and that's basically how bitcoin scales.

Vitalik Buterin (72:39)

My critique of that kind of stuff is basically that if the like open, permissionless, censorship, resisted aspects of the ecosystem are not aspects that can be, that are experienced by users directly and we just say those things belong to institutions, then that's just something that's inherently more vulnerable to capture.

Balaji Srinivasan (72:56)

Okay, last, last question then. Let's wrap. Some say Silicon Valley SF is losing its supreme position as the center of tech founders. Do you agree? Yes, no. And if, if so where do you think is the best place to start a global startup?

Vitalik Buterin (73:10)

I think it depends on your industry, right? Like, like if you're in AI, then spending a lot of time there like is like very helpful. And I think like my personal philosophy toward that whole region is like there's a lot of value you can get by being part of it. But like I think if you go visit for two to three weeks a year then you get the majority of the benefit and you, you at the same time, like that's still a low enough dose that you can like avoid imbibing the crazy. I think a while a lot of parts of the world are great places to be based in, right? I mean if you like, like places like Berlin, like I'm always a big fan of Berlin because I think the local community does a great job of remembering what crypto is actually there for and basically not just chasing the short term narratives. There's a huge amount of top tier talent, even safe, the smart contract log people are there, huge numbers of Ethereum core developers are there. So there's a lot of different parts of the world that are like this. And so I think especially with a combination of the Internet and with a combination of more localized net like in person network effect hubs like this, the need to be in a global superstar city to be at the front of the world is much less than it was five years ago.

Balaji Srinivasan (74:36)

I agree with that. All right, with that, let's wrap. Thanks everybody. Thank you for talking.