Epicenter - Learn about Crypto, Blockchain, Ethereum, Bitcoin and Distributed Technologies - Fred Ehrsam & Trent McConaghy: IPDB – The Interplanetary Database and its Applications in AI

Episode Date: May 23, 2017

Data is the new oil, and those who control massive amounts of it have a major competitive advantage. That advantage becomes exponential when that data is used to teach artificial intelligence. Companies such as Google, Facebook and Amazon have a far greater probability of building strong AI than smaller actors simply by the sheer amount of user data and metadata they possess. Let’s now envision an alternate reality where big data lives on public infrastructure and is accessible to anyone who wishes to use it for the purpose of teaching AI. Big data as a public resource could have the potential to enable vast amounts of innovation at the edges, far greater than that of a small set of incumbents building large centralized AI systems. We’re joined by Trent McConaghy, who is the CTO and Co-founder of BigchainDB and Ascribe. Trent brings along a special surprise guest, Fred Ehrsam, former Co-founder at Coinbase. For the first half of the show, we have a fascinating discussion with Trent and Fred about the intersection of AI and blockchain technologies, and the implications of publicly available data sets on innovation in AI. For the second half of the show, we talk with Trent about the public implementation of BigchainDB, the Interplanetary Database (IPDB), and the applications for a public big data storage network accessible to all of humanity. Topics covered in this episode: The issues which arise with big data centralization in the context of building artificial intelligence How blockchain technologies could serve as the public data infrastructure for teaching AI How an AI might gain financial dominance over humanity by selling art on a DAO An update on Ascribe and BigchainDB The IPDB network and what goals it hopes to achieve The IPDB Foundation, its members and governance rules The technical components of the IPDB network Use cases and applications for a public decentralized global database Episode links: IPDB - Interplanetary Database Foundation IPDB Dev Portal This episode is hosted by Sébastien Couture. Show notes and listening options: epicenter.tv/184

This is Epicenter, Episode 184 with guests, Trent McConaghy and Fred Ersom. This episode of Epicenter is brought you by Jax. Jax is the user-friendly wallet that works across all your devices and handles both Bitcoin and Ether. Go to JAAWX.I.O and embrace the future of cryptocurrency wallets. Hi, welcome to Epicenter, the show which talks about the technologies, projects, and startups driving decentralization and the global blockchain revolution. My name is Sebastianikw, and today we're doing a very, very unusual episode. One, I'm here by myself.

Brian's away on vacation in the south of the U.S. for a couple of weeks, so I hope he's having good time there. And Meher is at Consensus, where I'm sure he's at the moment, you know, having fun and seeing some great talks and panels and things like that. I unfortunately couldn't make it. And we're recording this the day before this releases. So, you know, it's sort of unusual, but hopefully we'll have a great conversation with our guests today. also something that wasn't planned. We have an extra guest.

So originally we had planned to do this with Trent Beconaghy, who our past listeners will know as the CTO and founder of a scribe and Big ChainDB and now IPDB, or at least part of the founding team there. And he came on the call in his hotel room with Fred Ursham, who's a former member at Coinbase. founder at Coinbase. And yeah, so we got Trent and Fred. And so Fred is going to be with us for the first half of the show

because he's actually got to go meet Meher in New York. And so Fred's going to be talking to us about AI and DAO and sort of the intersection of AI and blockchain technologies. And then for the second half of the show, we'll be talking to Trent about IPDB and what's new with big chain DB and this sort of thing. So, hey guys, glad to you both on. Yeah, thanks for your patience with us.

No, it's, it's no problem at all. And, you know, I like structure. And when things are kind of out of whack, I get uncomfortable. But I think I've gotten over the hump of, you know, this is going to go well. Yeah, we'll make the structure like unstructured. Great. So since Fred has to leave in a few minutes to go meet with my hair, one topic that

Trent thought it would be great to have them on would be to talk about the intersection of blockchains in DAO and this is a topic that I haven't really thought of much I've of course heard of people talking about it and it's come up recently but it's something that honestly I have not

really delved into very much so we'll spend me about 20, 30 minutes talking about that I'm interested in hearing how blockchains can intersect with with AI. So guys, well, specifically Fred, tell us how do AI and blockchains come together? What's the main thesis here when you're talking about AI and a DAO? Yeah, sure.

I think Trent has done most of the thinking in this field. And I have probably stolen a lot of his thoughts and then maybe added one or two side layers. Well, he's probably built further up the stack than I have. The way I would describe it is at the moment, there are a couple tech giants in the world, the most valuable companies in the world, the Googles, the Facebooks, etc., who have made very valuable companies out of big proprietary data silos. And due to network effects, those data silos have gotten bigger and stronger. And the companies are really valuable because they effectively can extract rent on these data silos,

because only they have control of them, own them, can access them. And so goes this cycle. And I started thinking about, you know, what implication does that have on artificial intelligence? And as Trent would very quickly point out, this is potentially a dangerous trend because if it's true that AIs really feed on data and they really get better because they have a lot of training data, they have a great breadth of training data. and all of the data is owned by a couple for-profit private companies, then when really intelligent AIs come out, whose interests might those AI serve? Probably that of the centralized company, if that's where all the data is coming from. So that alarmed me. And I started then thinking about, well, what alternatives do we have? And I realized in some sense that,

blockchains effectively represent a big open data set. And now that we have, you know, sort of blockchain tokens, and we always have since Bitcoin, I don't mean to make that sound new. But with blockchain-based tokens, it's this kind of magical system whereby everyone is incented to contribute to effectively one big database via the blockchain. And that seemed to be a potential kind of savior in this context.

So I guess that's how I think about it. And that's how I started to get convinced that the blockchain, in effect, can represent the biggest open data set in the world for AIs to train on. And that actually might be a great thing for all of humanity as a result. Yeah. Is that accurate in your perspective? Yeah, largely. And my hope is that it's a great thing. It also is, you know, potentially dangerous on its own.

But we have to hope and we have to, you know, infuse our ethics and our opinions and do what we can to try to tilt this thing towards something that's good for humanity, right? And overall, the thesis is strong, you know, to summarize, I think it's valuable for the listeners. Modern AI, a lot of the stuff, the deep networks, all this, really live and thrive on data. You know, you don't have to change the algorithm much. You can just have 10x, 100x more data, and your error rates can go down from 20% to 5% to 1% and so on. So it's really about the data. You know, the data is the moat. This is actually, you know, how Google built its house in the last 10 years and Amazon and others.

So, and, you know, there is this data mode and a data network effect as well, actually, because if you have better data, more data, then you can get better models, you can attract more users, and you have this flywheel effect that goes on. So it's been very powerful for these incumbent companies that have more and more data. And I've been asking myself the question too, similar to Fred of, you know, what can we do about this, right, to sort of break the cycle and open it up to humanity more broadly, right? such that startups who want to compete on AI for these data incentive intensive type AI systems

have a chance. And so an open database, or at least an open exchange of data, can really help where people are incentivized to submit datasets. And you can actually have them two flavors, right? One of them is where it's just sort of sharing data. But I think actually to make it really incentivize well, you really need to have it where people are getting paid

for the data sets that they submit. You know, it's truly an exchange, right? Or at least in marketplace where you can buy and sell data in a very fluid fashion. And to this note, we've actually been spending a lot of time with Big ChinDB and IPDB helping to set up ecosystems for data exchanges. And one that we actually just announced today, which I'm pretty excited about, is in the world of self-driving cars, which many people call the killer app of AI, data is a big problem.

you know, you can't have just 1% error rate because that would mean, you know, one crash every 100 miles or something, right? You have to have, you know, one in a billion, one in a hundred billion failure rates. And to do that, actually, it means you need orders of magnitude more data. So maybe you only need, you know, say, 1,000 or 10,000 miles of training data to be 1% error. But to be, you know, one in a billion error, one in 10 billion error, you need hundreds of millions of miles potentially, right? Something that no single automaker can get on a lot. its own. So what if you have a system where they can be incentivized to submit their data and then they can train these algorithms together collectively? So this is actually kind of a win-win-win,

right? Because the automakers each can make their cars with more accurate models that, you know, saves lives at the same time getting benefit for all their hard effort for gathering this data. And of course, it will be not just the automakers putting in the data then. You'll have, you know, lots of people driving and trying to figure out a more efficient way to putting this data in. So that's an example of where it can really help, but it goes beyond too, right? And yeah, so data exchanges for AI training data, I view they will be a fundamental piece of internet infrastructure. And it will extend beyond just self-driving cars and hopefully help to equalize the opportunities for people deploying algorithms, AI algorithms. Okay.

I got a lot of questions here. I mean, so first let's sort of restate the, problem the fundamental problem is sort of an extension of the existing problem with regards to data centralization. So, you know, we have Facebook, for instance, or Google, and they hold an enormous amount of data. As users, we sort of give them our data in exchange for free services or ad-supported services, and those companies get an enormous amount of value out of that data because of everything that they can learn from it. And the core problem here is that once we have, or as AI continues to evolve, that data will also serve AI's and in effect make those companies more and more powerful. Because since they're the only ones that have the data, which is essentially what you feed into an AI, there are the only ones that it can effectively create really comparable and high quality AIs.

That's sort of the fundamental problem here. This data centralization further enhances or supports the development of strong AI by strong incumbents. That's right. I would actually bifurcated into kind of two parts. One is the one exactly what you're describing, where you have an incentives issue whereby if Apple is creating Siri, Syria is probably going to serve the interest of Apple and not the interests of the person with the phone. And that's scary for us as humans.

So that's the issue you're kind of describing. The other issue is a rate of innovation issue, right? So if there are only four big companies who have these big data sets, then the number of people in the world who can create really great AIs all of a sudden is very, very small because very few people have access to the data through which to train AIs and make really great AIs. Now, if that data was exposed to everyone in the world, now everyone in the world has the ability to create great AIs, and the rate of AI technological

development goes up drastically. You might imagine by one to two, at least orders of magnitude. So it's both kind of an ethics and safety issue and a rate of innovation issue. So on the ethics part, I think that blockchain technologies has sort of talked about a lot as the platform or the platforms that will allow for data to be liberated or for users to regain their data essentially where we're talking about allowing for users to give access to their data to large internet companies through access controls through encryption this sort of thing but essentially the data ownership users regained data ownership of their data and they they delegate the use of the data to large companies.

Now, this shift in itself, you know, probably if it were to happen, would take a very long time because we'd have to find new incentive models for those large companies to provide services where they don't really have access to the, you know, free and encumberate access to the data as they have now. And that seems like an unnecessary first step, if we are to have these open data sets where users can then essentially rent out or provide sort of paid access to their data for other AI systems to learn from.

How do you see this sort of progression towards what you're talking about? So I see it as just where are the problems, you know, the ones that you can address first, So you could try to do it for, you know, just personal data in Facebook. But to your point, Sebastian, that's actually, you know, is there going to be enough value to consumers? And probably not, right? But if it's for something like self-driving cars where it's clearly a win-win-win across the board, then there's a clear incentive.

And there's other ones where there's clear incentive too, you know, like medical data records, right? Where people are merging their data across different silos, right? Like I live in Germany and I go from Hospital A to Hospital B. Hospital B doesn't have the data that Hospital A has on me. So I would have to actually go around and collect it right now and collect it and share it with them, but it's really hard. So it's much cleaner if you can actually have this data out there in the cloud, encrypted, et cetera, and then I can just provide access to the hospitals as needed, right?

And then also at the same time, I can provide permission to scientists to conduct research on this data. So that's sort of a societal benefit. So there's benefit just to myself personally for me and an incentive for me to share my data that way, but also the society. And so kind of go across the board and you can ask, you know, where are there benefits for data pooling to happen? And, you know, I gave a talk over today and I gave other examples too with like diamond fraud and with 3D printing fraud and sort of a lot of other problems in fraud in general, right? So, but it has to be problem based. It can't be just saying,

okay, well, you know, I don't like that. Facebook has my data. Well, you might not like it, but, you know, a lot of mainstream won't care enough to change. So I do hope that we find a way that there is some way to repopulate a social network that is more open and equal and so on. And I bet someone will crack that problem in the next two or five years. But I don't think there are clear answers today on that. Yeah. I mean, it's not just social networks. I mean, just think of the enormous amount of data that Google has. And not only the data itself, but then there's the metadata and, you know, the the the the um the regressions that you can you can make from that data from which you can learn a a whole lot of other things what what types of incentives would you see i mean i can see the

incentives i can see how on the on the health side there's a there's a real real win-win there on the smart driving car side uh how that may be possible because self-driving cars um don't really exist yet so there there are no like sort of standards and normal operating procedure in that space, so that may merge as sort of the standard ways to have open share data because we can recognize that it's benefits for all. So on the more traditional incumbent large internet companies, as we call them in Europe, Gaffas on that side, how would you see that shift happening if it were to happen? What would it take for a company like Google to want to,

open up their user data on an open marketplace where users, in fact, have control and access to their data directly and seed that control and access to Google to have access to their services. I think the answer is that it's a classic innovator's dilemma problem, and that actually may not or ever happen just because they have so much revenue that is really just dependent on extracting rent from the centralized data silos. So I think the much more likely scenario, is new projects that organically emerge, which uses this model first in the same way that kind of Bitcoin emerged with a token model

and it started to take over money. It wasn't, you know, a bank, for example, that was willing to cannibalize their own revenue with this radical new model. What do you think? I think that's a possibility. I'm just thinking about that actually, there's a couple of ideas that have popped into my head related

that have been emerging in the last few weeks. well one actually has been emerging the last few months and this is GDPR in Europe right the general data protection rights and this is sort of like a Y2K for 2018 in May of 2018 anytime that you Facebook wants your data they have to ask your permission right but and it's but it's it could play out in one of two ways it could be where you just have to click another okay button just sort of like a cookie thing where it doesn't really matter or it could play it in a different way it just breaks UI for every website I know right and that would be the sad way and that's a possible scenario but there are a lot of of startups and a lot of money flowing into systems where it's actually about tokenizing consent, for example. And this actually could really reduce the friction for other players to come in there because if you're sort of tokenizing consent, then that's actually moving a lot of your data and giving a lot more power to you. So that's pretty exciting. That's a possibility. There's another one that I've been thinking about, and this is actually more general on the tokens thing, actually largely thanks to Fred's excellent writing in his blog, so I encourage any reader

to look at his stuff too. So, and I think of it as we've been thinking about tokens, design systems where it's sort of a new project from the ground up and so on. But you can also tokenize the enterprise. And let me explain. Well, you can tokenize the enterprise and the results is that the enterprise might be able to melt into the community. And I'll give a couple examples. There's really two types of enterprises to think about here. There's ones like the 3Ms of the world or the Amazon's where they're already internally, five or 50 different business units that have their own profit and loss statements, et cetera. Each one of them could actually create their own token ecosystem internally, but also,

open up to sell those tokens externally. And so they're used to having APIs to the world, right? So that could be very, very interesting. Imagine just even Bezos does tokenize this one business unit and sees what happens, right? And what would be his incentive? The incentive would be that if you're including more people to be able to buy into the tokens and there's greater demand and the actual overall value to the enterprise goes up, right? So it's sort of like a second IPO, like, why can't an IPO company, ICO on top of that, right?

So it could be an interesting idea. And then you don't have to have it just for five or 50 different business units. It could also simply be one big, more large company like Facebook, you know, ignore the Instagram part of Facebook, etc. Just Facebook itself is one larger monolith. What if that was tokenized? Where the users then could start to not only buy tokens, but they can get tokens of benefit every time they use Facebook, right? So then actually Facebook overall, the value to Facebook the corporation could be higher. And that might happen, right?

This is just an idea I've been thinking about, I don't know if you have thoughts, Fred, tokenizing from within, right? Melting the enterprise into the community. I think it's a very smart idea. I think the likelihood that a $280 billion company actually does it in the public market is low. I agree. But it would be awesome. It would be.

But here's the thing, right? Like, you know, two years ago, four years ago, we thought that these ICOs were anomalies, right? And it was sort of like, you know, one every two months or six months, just like you and I were talking about. Sure. So, you know, what is weird today? It could be normal tomorrow, right? And maybe it'll start with, you know, just some visionary company, right?

And we're seeing like with the overstock guys, right, they're doing some radical things and others are following, right? So something is impossible until it isn't, right? Yeah, totally. So you mentioned a while ago data exchanges or data marketplaces. What would these look like and what technologies could they be built on? So when I think of an exchange, and I'm sure Fred will have ideas too, but I think of it as a marketplace where the price is set automatically, right? You have people coming in saying, I'm going to pay X to all. for this and other people are saying, I'm willing to pay why dollars for this, right?

So you've got a set of bids and a set of asks and when they match up, you know, when someone is willing to pay more than someone else is asking for, then they line up and that gets sold, right? And so you just basically, the core of it is maintaining these lists of bids and asks, which can be fairly simple, right, at the very, very core of it. And then in terms of technology stacks, what we built recently, we were actually surprised by the simplicity of the architecture. It was simply IPDB, which is the public version of Big TeamDB, which has,

governance, et cetera. We'll talk more about that later. And a single-page web app on top, right? So people can log in, create an account with a brain wallet type setup, HD wallet, that sort of thing. And then basically start dumping in data, et cetera. And that was all we needed. You know, it could support tokens directly. It could support the querying, et cetera, directly. And we were kind of amazed, right, because it's people talk about serverless architectures.

But of course, you're still using, you know, the Amazon Cloud or something. Now it's serverless where it's a decentralized cloud or the backhand, right? Now, that's a very simplistic thing. That's sort of a proof of concept when you actually want to go to something that is more full-fledged than I defer to Fred because he has more experience in this. No, that sounds pretty spot on to me. I guess I was thinking that I think some of the places we might see this first are marketplaces where monetizing the data is easy and paying people who contribute the data is easy. So one example of this that Trent actually brought up earlier in a presentation today was a company called Numeri, which is started by a friend of mine, this guy, Richard Craib. And it's funny how small this world is sometimes.

And they're first investors, a friend of mine. There you go. And to me, that's a great first example of how this might play out in the sense that going back to the beginning of the talk, effectively what they're doing, is they are in a centralized manner paying a bunch of data outlets like Reuters and Bloomberg, et cetera, for their data. And then they are distributing it to anyone who wants it in an encrypted, homoerably encrypted manner so that anyone can have access to this data and build kind of the best AI they can. So it doesn't take too much imagination to take their current model and then extrapolate it

such that maybe it isn't numerize a central entity who's collecting all the data and distributing it. Rather, anyone in the world who has valuable data to make stock predictions could get paid for contributing it. And this is already happening, actually. Like, there are these kind of small random companies around the world who will pay people in different countries to go and count how many coax are on the shelf or whatever. So this is happening to a certain extent already. But I think if you properly incent this system using a bulletin,

blockchain-based token, you start incentivizing anyone in the world to contribute data, which could be valuable in this case for financial predictions. And the resulting behavior is quite clear. It's a bunch of AIs that feed more or less on this crowdsource data, and the result is better financial predictions. And the output of that, which is just more money, easily feeds the people who contributed the data and so on and so forth. And something that Fred is pointing to, too, there's actually this emerging sort of

discipline of designing token-based systems, right? Even, you know, right after my talk, Juan Bonnet gave a talk, and he actually pointed, you basically have to ask yourself, you know, what are the ways that people can earn tokens, what are the ways that people can spend tokens, and then how does those get exchanged, right? And those are kind of the questions to ask, and you have to ask, you know, this question about each actor in the ecosystem and then design the thing overall such that you've got the sort of different feedback loops that you like, right? And this isn't much different than classic multi-sided platforms, right?

like the Googles and Facebooks of the world that have multiple customers, et cetera. But now it's actually got more tokens of value flowing around. So you can actually have these network effects more directly, right? So related to this, you know, data that's in there, you know, you can think about, well, how do you set up designing a system for people contributing their music, right? A music right system for like compensating artists, et cetera, or data or, you know, social data, all of this, right? So it generalizes quite well beyond sort of data for just AI.

Right. Okay, I can see then how the token model that we've seen for, you know, in a lot of projects in the blockchain space might apply to data. So the way that I'm seeing this play out, so, you know, for instance, a few years from now, for example, we have sort of a public open database that is the sort of standard where all self-driving cars submit their data. So you buy a self-driving car. There's some sort of an alliance or a consortium of car companies that build this open database for the benefit of all. And they send the data or they allow for users to sign for their data to be sent to this open public database. The data is anonymized or with some sort of encryption mechanism made to be stored in the open database, in the open database as encrypted data.

And then on the other side of that, you may have a company like Google or another car manufacturer or anybody developing an AI that through this database would rent the data effectively paying the users who fed the data into the central system

or into the distributed database system. That way we have this massive data structure that can serve the purpose of anyone who wants to use it for research or for building new AIs or what have you. Is that sort of what we're looking at here? Yeah, it's a pretty good of capturing yet. And, you know, there's going to be the core stuff of storing, you know, the databases that store the metadata and some of the smaller modes of data. And then the larger streams of data and stuff and data blobs, this will be in things like the file systems, you know, like IPFS with Filecoin, etc. right. And there's actually going to be building blocks emerging on top two.

Just like people have been talking about reputation systems on people, we will be seeing reputation systems on data and a whole wide variety of sort of an ecosystem emerging on top of data itself, right? And we're not seeing this right now because all the data is locked up, right? So as soon as this stuff gets unlocked with these decentralized data exchanges and marketplaces, we're going to just see a flowering, right? And, you know, as an illustration of that, right, just very recently there was a front page of the economist talking about data is the new oil. But if it's the new oil, well, right now we've got Rockefeller time plus two plus three. We don't actually have it where it's accessible to all these, you know, innovative entrepreneurial

lines. Well, this is very, very fascinating topic. I would love to know what like a GDPR regulator thinks about this. Well, actually, it is totally related, right? And the challenge actually with GDBR is that the regulations right now don't have much to say about if the data is encrypted or not, right? So if I have personal data and it's out there in plain text and it's, you know, let's say I'm living in Germany and it's this data is sitting in the USA and that's not good, right? It's got to be it right now in German servers. But what if it's actually encrypted, right? And then also what about right to be forgotten, right? So if I have my personal data and I delete it and it was on German on soils, servers, sorry, fine.

But once again, maybe it's encrypted, and I throw away the private key, and I literally burn the private key, right? And I can so cryptographically prove that private key was burned. The laws don't have anything to stay up with this right now, right? So actually, we've been iterating with regulators in Germany on this, and others have been too. And it's really important that the law actually catches up to what's possible with the technology. That's just like we're seeing in the ICO side of things where, you know,

the law has to catch up. And in the meantime, we have to do the best we can. it's actually similar with things like data protection rates. That's true. I mean, the right to be forgotten thing, that's something that comes up a lot. You know, when I'm talking to corporates as well about GDPR is, what about this right to be forgotten? Well, okay. Well, I mean, they sort of the sort of go-to line as well, you know, blockchains are transparent.

How can you possibly have a right to be forgotten? Then, you know, you later on say, okay, we can have encryption. You can have things like zero knowledge proofs, this sort of thing that, would effectively allow for a right to be forgotten to exist within a blockchain. But then the regulation, as you mentioned, is not conclusive on what is forgotten. If I forget or destroy my property key, is that data really forgotten? That definitely needs to be made clear in the regulation. Sebastian, I'm thinking, you know, we probably only have read a bit here longer.

Maybe we should talk about AI doubts for a little bit. That sounds good. Yeah. So the art doubt. So there's a quick background around this, and that is machine creativity, like AI dows that are, sorry, AIs that are creative for sort of narrow domains are possible, and they've been around for actually decades, right? So there are AIs that can generate art, like visual art, images that have been sold, et cetera. There are ones that have designed quantum circuits, Leagues Factor and others. In the talk that I gave earlier today, I showed how my friend Greg Hornby was creating necklaces and the tokens on necklaces and how they're quite pretty and stuff. Myself, too, my PhD was on this, right, for what was considered creative analog design and I was getting AIs to do it.

So the point is that there is a whole practice as a subfield of AI or subfields for creative AI or machine creativity. So this is a baseline. Now for the art doubt then, there's a recipe, and it's best to describe in just the five-step recipe. Step one, you've got this agent running on decentralized process and substrate, you know, Ethereum or something else. And it generates an artifact, say a piece of digital art or a jewelry design. Step two, it claims copyright or registers it that it just has it. And this step isn't even really necessary, but it's cool to think. And by the way, there are regulations towards AI's getting right.

in Europe. Or you can actually just register in Zoug, Switzerland, and then it's got rights because it's a corporation. So that's a whole other story. So it claims copyright. And then step three is it posted for sale on a marketplace. By the way, give it 10 editions for fun, right? Like a scribe style. So posted for sale, these 10 additions on, say, Open Bazaar, decentralized marketplace, or even something centralized like Getty. Sell them. So maybe sell each of them for $1. And maybe overall it costed you $1 of compute power. So you make $10 because you've got 10 additions. So now you've spent $1.00 to compute power. You got back $10, right?

So now what you do is you make 10 more pieces of art. And each one of those, you sell 10 editions. You've got $100, right? And remember, this is an agent, right? It's a Dow that's running decentralized, and it's creating value on its own, right? And it's accumulating will. It doesn't have any mode speed.

It just, all it has to do is, you know, make more paper clips, i.e. art, right? And so it can go from having $100 of wealth to $1,000. to 10,000 and we'll have the world's first AI millionaire, right? And then maybe it'll keep going. Maybe it'll be a billionaire, right? So that's pretty exciting. And I like to use it because I think it's a very tangible example of something that you can build with today's technology. You know, just a bunch of components off the shelf. And there's a few projects now that people have reached out to me that are starting to build on this. So I'm excited. Hopefully one of them will be able to announce in the next three or six months. But any listeners out there,

go ahead and build this thing. It's actually cool, right? There's going to be a whole bunch of different art dows out there that get built. And it's also really useful as a launch pad to explore what this means because you can generalize in like five or ten different directions. And each one is interesting on its own, right? For example, what if this thing starts generating computer code that isn't just art, you know, arbitrary computation? What if it's mine's GitHub and people put code in GitHub that is really dangerous doing like hits on humans and stuff, right? And by the way, you might think, well, code doesn't know how to combine other code. Well, actually it does. There's this subfield of AI called genetic programming where I spent 10 years of my last,

life, which is actually all about searching through the space of computer programs to come up with the next program. And even if most random programs it tries completely stock and fail, it doesn't matter if that last 1% or 0.1% has something interesting, that's all it needs. So basically this is the whole idea of the ARCDAO, that AI that can equally well. You might think, oh, that's just an oddity, but something where there's a real incentive by companies is to be capital light. So, you know, in the world of semiconductors, all the companies, the factories got too expensive, so they all went fabulous, right? So Qualcomm and VDivD, all these guys, they don't own any factories anymore, right? And other times, you know, BMW, they went and sold all their factories too, right?

And they're just focusing on design and then outsourcing the manufacturing or Uber, right? When they have the self-driving cars, are they going to go and spend billions of dollars, or actually hundreds of billions probably, to buy their own auto fleet? Wouldn't it be easier if they just made each self-driving car also self-owning, right? and that way they can stay capital light. So there's an incentive for corporations to be capital light. It's a better return on their assets. And, of course, then are we going to be handing over, you know, the vast majority of humanity's assets to these plots?

So there's a whole bunch of questions raised. I think it's really fun and dangerous, and this is why we need to talk about it now. You know, this example you gave, I've never thought that an AI could create art, possibly create value out of that art. It reminds me of this Mike Hearn talk from many years ago that he did somewhere. I think it was at Google where he talks about,

so the self-driving car that is its own age and goes around. It builds rides to people and gets in the highway and then takes the fast lane and pays the highway in Bitcoin. And then after it has enough money in the bank, it goes and orders another car. It sort of reminds me of this example that he gave in this talk. And I've never thought, when we think, of AI and sort of the threats of AI, it's often this sort of, you know, the AI will take us over and will sort of destroy humankind because it deems it to be a sort of a parasite or cancerous life form on the planet, or you might tell AI, you know, cure cancer and it'll sort of kill

humans, you know, as a side effect of killing cancer. But I've never thought of AI as asserting financial dominance on humankind. And if you have an AI that starts making money through some sort of value creation and then I that I starts getting smarter and starts creating other businesses. You might have like, you know, the biggest corporation in the world would be in AI. And then asserting financial dominance on everyone else and just kill us by just like economically, right? We'll starve because we have no more money to buy food or any resources and the AI will have all the world's resources. Exactly.

And by the way, on the my current thing, actually, so the Terra Zero guys, it's a couple of university students in Berlin. They're doing this self-burning forest, which is also super cool. And they're writing about it. And among their references, they were digging and they actually came across also a Reddit post by Mike Hearn from like 2011 or something as well. So, full kudos to Mike for actually like seeing this way before almost anyone. And I'm sure if you dig, I don't know if they found anything specifically that Nick Zabo had or Ian Greig, but I'm sure there's some stuff that those guys had too, right? Because they always do. Right. So, you know, to me, I just happen to have thought of this sort of from my own angle and stuff.

But overall, there's been a lot of thinking before me and there's going to be a lot more after too. And, you know, I think it's a conversation that we all want to be having because we don't want to put herself into the situation where we are subservient to these, you know, new landowners, right? I'm sure this is sort of talked about is that AI will perhaps wipe out a lot of, you know, knowledge work in the next, you know, 20, 50 years. hundred years.

But creative work has always sort of been thought of as untouched, right? Like creative work will continue to be a human endeavor and all the starving artists are just going to be even more starving because the eyes will have taken over their creativity work. So it's sad for them to. I think there's a key insight in what Trent said too,

which is that if you look back at the history of corporations, and part of this is stolen from Simone de la Rouvier in a recent blog post. Effectively, what corporations did is they allowed us to, in some way, pool resources to have a greater scale of humans and self-organization, and corporations got really big and accomplished things that humans had never done before as a result of this. And then the interesting side effect of this was that humans eventually became equivalent

to a person in the eyes of the law. or sorry, corporations became equivalent to a person in the eyes of the lot. And now I think this is kind of the next logical step where, you know, there is no difference in the eyes of the blockchain between an AI or any object and a human. So they're the same. They can control resources in the same way. It turns out that an AI may actually be much more effective at feeding on huge, amounts of data than any human could be and thus can achieve much broader scale.

And because the blockchain is asset based and it can fund itself in doing so. So you just, it kind of follows that this is the next natural step in self-organization and how we, and how we view the world. On the blockchain, no one knows you're in AI. Yeah. Okay. Well, this is all really fascinating. We should definitely do another show, sort of a full show, just on this topic where I have

where we'll have done more research and we'll have more insights and hopefully we'll have a on my side a much more interesting intelligent conversation but but uh but uh yeah fred then thanks so much for for coming on uh at such a short notice uh and uh yeah i think you get to go meet me hair now i do yeah so trump thanks for inviting me uh impromptu and it was a pleasure yeah okay well we'll have you on at some point again and say hi to my hair let's take a short break to talk about Jax. Jacks is your wallet, your complete user interface to cover all your blockchain needs. I've been using it and I've been loving it. Now, Jack supports a lot of different cryptocurrencies. It's supposed Bitcoin, Ether, Litecoin, Ethereum Classic, Zcash, Augurap, and they're adding many more

keep responding to users' needs. Now with Jax, a nice thing is that you can manage all of those coins within a single wallet and you are in control of your own private keys. They're not on their server. And there's a single 12-word. see that you can use to backup your wallet, all your coins, and sync them across different devices. Talking about devices, they're on pretty much any device that you can think of. You can get it on PC, Mac, Linux, you can get it on smartphones like Android and Apple and iPhone. You can get it on tablets or even browser extensions for Chrome and Firefox. And on top of that, in Jax, you can actually exchange different cryptocurrencies for each other because they've integrated

shape shift. And more partnerships and integrations are coming down the line in 2017 that are going to make Jax even better. So Jax is really making blockchain and cryptocurrency is accessible for the masses, easy to use for the masses. Make sure to get your own Jax wallet at Jax.I.O, or you can get it from any of the app stores you are using. We'd like to thank Jax for their supportive epicenter. All right. So yeah, Trent, so coming back to what we had attended to talk about, for this episode, which was IPDB and Big ChainDB. We first had you on in 2015, and we talked about a scribe then, of course. That was sort of your main project at the time.

And then you came back a year ago. I checked. I last checked was about 50 episodes ago in April to talk about the work that you've been doing on Big ChainDB and how that work had come out of a scribe and what you've learned, what you had learned from a scribe. And at that time, when we had you on, you sort of hinted at the fact that there would be a public big chain DB network. I remember when you told me about that, like I was completely blown away by that idea. I talked to people about it extensively, like my team and like people I

met, it was like, there's going to be a public, you know, big chain DB network. And I thought that was really a really fascinating idea. So yeah, tell us like how, how have things progressed for you and how things progressed in in terms of sort of big chain and how that idea now has turned into the IPDB network. Yeah, sure, my pleasure. And once again, thanks for having me again. So going back to a scribe, right? When we did a scribe, the goal was always to serve the creators.

We saw that our friends, artists, and all throughout the globe, you know, artists were getting a raw deal. Not only artists creating digital art, but musicians and otherwise, right? So this was always sort of the driving impetus. And as we went along with the scribe, of course, we ran it, of scale. We had been building on the Bitcoin blockchain. And so we decided, and we looked around and, you know, talking to different friends building some of the blockchain systems then. And none of them were really approaching scale by leveraging existing big data technologies, right?

So we did. We said, let's start with an existing database. We started with rethink. More recently, we've also support Mongo, very natively now, MongoDB, and build on top of that. And that led us to building Big ChainDB. But all the way along, actually, the goal was to have to have, A scribe has always been, and the artists and the creators have always been our number one user actually. And so we said, okay, as we're going to scale, what are all the pieces that we need? And we realized that we needed not just scalable blockchain database software, that is BigGNDB, but also a public network for it. And so even when I talked last year, you know, it was forming, but we were actually having a lot of discussions and conferences and various cities all over the world. with folks on what this might look like from a governance angle and so on.

And that's what became IPDB, interplanetary database. Incidentally, there's a third piece too that I can talk about briefly at the end, and that's on the IP side of things. One problem was scale, and that led us to Big TeamDB and IPDB, the software in the network. The other problem was flexibility of IP licensing. We had developed this small overlay protocol on top of Bitcoin called the Spool Protocol, and it was fine for digital art, you know, claiming copyright,

transferring single editions, which is a bequeathing of certain rights. But artists kept coming to us and saying, hey, what about fractional ownership? What about taking a still of a video? How do you handle 3D? What about photography in various ways? That led us to develop something called Kuala IP,

C-O-A-I-P. And that was actually in sort of this driven team too, not just us, but, you know, Juan Vennay with IPFS, Simon with Ujo Consensus, primavera with Koala, and Greg McMwellyn, who was my colleague in Big CheneyB and IPDB and others. So we developed this QualiP and it actually reconciles with all the existing protocols too of DDEX for music, plaster photography, etc.

So really overall we have these three building blocks, Big Cheney B the software, IPDB, the public net and Qual IP, and each has its own sort of governance, etc. You know, Big Cheney B is a for-profit corporation. IPDB is actually a separate non-profit that we spun out and it's controlled by the caretaker, so I can talk more about that. And then Kuala IP, which is still basically the sort of loosely formed group that came out of the Kuala workshops run by Primavera and Constance. Primavira to Philippi, Constance, Chois.

So that's sort of what led to all of this. And maybe I'll pause for a second, and then I can dive into sort of what led to, you know, a bit more of the history of what's went on with Big TeamDB and IPDB since. So let's go right into IPDB then. So IPDB is the public implementation of the big chain DB protocol. And I think I find this really interesting because until now, you know, we have, we have, what real blockchain networks do we have out there? We've got Bitcoin, Ethereum, and, okay, like, whatever, how many altcoins there are.

But the real platforms, the major players, Bitcoin Ethereum, they are public blockchains that were launched as public blockchains. And now Ethereum, you know, we're starting to see sort of enterprise traction there and, you know, perhaps some private enterprise Ethereum networks will start to emerge. On the other hand, you guys started out as this more or less private blockchain type system. At least that's the way that I always saw Big ChainDB, is a big chain DB is a protocol that will be deployed. by enterprise and you know as a as a private network and now you're implementing a public implementation of that as far as i know i mean okay so cosmic the the cosmos network will be somewhat similar i guess you know from tendermint to cosmos as far as i know you guys are the first to do

this yeah uh what type of things are you are you learning from having you know deployed this network as or this having this technology first as a as a technology that was intended for private use I guess, but now moving into having a public network. So actually, quite honestly, customer number one has always been ascribed, which has always been about the public net. So, but we always saw that, you know, why not have it deployed? So there's really three types of possible deployments. There is the public deployment where anyone can read, anyone can write from it,

and that is IPDB, but others can, you know, have their own deployments that are fully public too. Then consortium deployments where you might have, you know, 10 or 30 organizations running nodes together. and it might be, you know, automotive self-driving car consortium or something else. And then the third one is actually within enterprises, where you don't get as much benefits from decentralization, but you actually still have the Merkel-de-A and a degree of immutability, as well as the signed transactions, which are actually really, really good for data trails and provenance. So all three are relevant use cases, and they have just, you know, different ways of being used,

but there's really three deployments, right? public consortium and within enterprises. But also, by the way, within enterprises, they can also use public nets. We're seeing some of that where enterprises are using public Ethereum, right? And that's great. So the other thing to just sort of emphasize

how we designed from day one to be complementary to some of the other key systems out there, right? We see that with compute infrastructure, you've got processing and you've got storage. And within processing, it actually breaks down to two things, business logic and high-performance compute. So business logic processing,

the decentralized version, is really where Ethereum plays really well, right? And this is where Hyperledgeer and other sort of smart contracts play in, right? And high-performance compute, this is actually an emerging category where we have things like Trubit and Golem, I-Exec, etc., right?

So those are overall, this is all within the realm of processing. We're also seeing people who actually running VMs on top of Big Cheneb or, you know, JavaScript in the browser, That's just talking directly to BigCCGDB, etc. So this is the processing. On the storage, you've got file systems, database, and actually what I see now is a store of value.

So on the file system, this is things like IPFest, storage, et cetera. With the database, this is exactly BigGNDB, and it's public net IPDB. And then in the stores of value, this is the traditional ledgers, right? So Bitcoin, the ledger, Zcash, they're not trying to do much more than just store the value. And actually, most other blockchains have some sort of, you know, token storage too. So overall, this is the stack that we see where you've got processing, including business logic and HPC, and then you've got storage, including file system database, and store of value. And we've always seen ourselves as aiming to be the best in class blockchain database, decentralized database.

And we've always been aiming for the public net as well as serving the enterprise. We kind of straddle those. We've always sort of seen that enterprises, they have specific problems to solve. We understand the enterprise. and it actually helps our business model, right? We are selling, we have open source software, but we're like MongoDB, so they have an enterprise version, and we're moving towards that too, right?

So it's a way basically, so we can serve the enterprise via, you know, the sort of enterprise e-level software, but we can serve the startups who aren't willing or don't have the funds to build their own consortiums, et cetera. They can simply use IPDB. And overall, it's my dream, you know, five years, 15 years from now where 99% of the applications are IPDB itself, right? And that will be fine because there's lots of other business related things that BigCDB, the company can do too.

And I think this is just healthier for the planet. So, you know, to be that best in class database software and then best in class public database network, that still plays well with everything else for transferring value, you know, connecting via interledger, connecting via cosmos, et cetera. So if I understood correctly, you just said that in a few years, you, you would hope to see 99% of the applications built on, so this stack using the public net. Okay. So in your view, then, the consortium network of, you know, 10 or 15 companies within an industry, collaborating on a single process or sort of regulated process, that model, you don't see a future for that model?

Or something which has niche? Actually, I see a future, but what's going to happen is that they're going to melt into the public net via interlager and cosmos, et cetera, right? And I think that's really, really healthy. So just like, you know, rewind 20, 30 years and you would have all these different private nets, you know, via LAN or its precursors. And then they started joining, you know, and TCPIP actually connected these things, right? And, you know, ARPNet, NSFNet, all these really, really early networks got connected with TCPIP. and I see that IPDB will be a big public global database from day one, and it will sort of be like this backbone upon which other things can be linking,

but it's not going to be the centerpiece, if you will. It will be another sort of node in the network, right? And some of these networks will be much more sort of smart contractee, like decentralized business logic processing, and some of them will be much more database-y, like Big CheneDB, IPDB, and that's okay, right? And just like right now, you know, you can have some software as a service that has a database like HTTP,

as the interface, but below it, you've got some database as a service. But behind other HTTP interfaces, you might have payments like Stripe, right? So I see a similar thing emerging where these protocols include value as well in a blockchain sense, right, tokens, et cetera. And, you know, all these components will play well together. So for the consortiums, like, they'll still be there. It'll just be much more public. And I think, you know, why would you bother setting up governance of a consortium if you

can I'll just use the public net, right? And even companies themselves, you'll see now, like, a lot of them actually internally, they don't even bother with LAN protocol. They just follow the public HTTP protocol and connect directly to the internet, right? I see. Okay. I see where you're going. So talk about IPDB then.

This is, again, comparing to Ethereum or Bitcoin on the validation side, it's a very different type of validation scheme. So there are a predefined or sort of limit number of validators. The validators are chosen. So it's sort of this intersection between a consortium network and a public network where the network is given or made available as a public good, but validated by a federated set of nodes. So talk about the governance model there and how that works and perhaps the foundation as well.

My pleasure. a lot of thinking that went into this. So background-wise, one of our key advisors is David Holtzman. He's the fellow who rolled out the public DNS in the late 90s. He was maintaining it all throughout the 90s. And then they hatched ICANN and, you know, that governed the DNS for years and still does. For better or for worse, right? There was things that happened which are kind of sad with ICANN. And, you know, David is actually pretty sad about that, right? And also the other people involved, you know, Jim Rutt, Esther Dyson, Pinder Wong. you talk to them and I have about this, they have, you know, there was a lot of the great things

that happened, but there's some very sad things that happen too, you know, things like the fact that we have dot sucks as a domain name like, and it's basically extortion, you know, Microsoft has to go and buy dot sucks from the TLD guys for dot sucks for for 10 grand or whatever. So, as well as things like dot bank. So overall, we, we had a series of questions and constraints that we wanted to solve for, and it came down to how do we make sure that we, we, we, aren't captured by money and we aren't captured by jurisdiction such that the system can keep running over the next five years, 50 years, 500 years in a way where it serves a decentralized internet. And so we said, given this, first of all, we have to say, okay, let's say we do have

this federated type system where there's 20 nodes or 50 nodes or growing 300, right? Then with each of these, we want to make sure that the people running these nodes care about the future of the decentralized internet. And so that was a constraint. That is a constraint to be a caretaker. But then beyond that, the majority have to be nonprofits. And that actually solves the question of the dollar capture, right? Because now instead of having dollars at stake, the way that typical proof of stake systems work, it's actually reputation at stake. So, you know, and these caretakers are like internet archive, open media foundation, et cetera. If they start attacking the system, it kills the reputation that they've been building up over the decades sometimes, right?

So it's sort of like, you know, a proof of stake system where you're staking something, but you're actually staking your reputation is not an economic incentive, right? And then the second concern was jurisdictional capture. And an example of this is Bitcoin right now, you know, the vast majority of mining is in China. What if China closes off its Internet from the rest of the world for a while, say a week, right? Then you'll actually have a partition of the Bitcoin network. kill of mining going on outside of China and inside. And then let's say China opens it up again, then it all heals.

And the Chinese side will be the longer chain. So all the transactions and the rest of the Bitcoin network that previous week would have gone away, right? And what this means is actually that we actually essentially have jurisdictional capture right now with Bitcoin within one country. And that's actually sad, right? Like, I'm a fan of Bitcoin. Bitcoin has inspired us all. And it's kind of too bad that right now we have, you know, this capture within a jurisdiction. And there's other examples of jurisdiction we have to watch for.

Like, for example, if we had the majority of caretakers in USA, what if some of the less than inspired leadership decided to crack down on IP laws, even in a crazier way, right? Like sending letters to anyone that might have possibly infringed ever, ever, ever, right? And so you don't want to be dependent on one nation in terms of jurisdiction too badly. So we said no given our rule is no given a country can have more than 30% of the nodes, right? and we actually try to spread it as far as we can in terms of the new caretakers. So, you know, we now have caretakers in, you know, USA and Canada, in all over Europe, in Kenya,

and that's expanding more, right? So, and when I say we, actually, we no longer have control this. So how IPDB is set up, the caretakers, they have two key roles. They are voting. So they have the power to vote each other in and out. They have the power to vote and elect to the board of directors. The board of directors then hires day-to-day management. So they actually control this nonprofit foundation.

It's a German nonprofit. So they vote, but then they also run the nodes. So they actually have this sort of day-to-day activity themselves of running the nodes. So those are the roles of the caretakers, which are the heart and soul of that system. And we have already handed over control to the caretakers. So they actually control the governance, which is actually really, really awesome, right? Big CheneDB doesn't. You know, we hatched it, but we don't control it.

So, and the majority are nonprofits. We have a few for-profit companies, too, besides, such as Big TeamDB, Protocol Labs, the IPDB guys. And at some point, stratum will be too. I hope, as long as the caretakers are with them in, right? I really hope they do. So I can't control it, but I can try to influence this. Anyway, so that's the overall sort of process of this. In terms of, you know, sort of the openness, the publicness, and so on, there's actually interesting, these things are much closer than you might expect, right?

So if you think about a proof of stake system like Casper, right? What Casper is is you've got these different, at any given point in time, you've a set of identities that are allowed to validate, right? And they get voted on through a relatively fancy crypto economic mechanism, right? And then they're posting bonds so that if they act badly, then they lose that bond, right? And there's other systems that are sort of proof of stake, like delegated proof of stake is actually quite similar. So this is the Cosmo stuff in the bit shares, for example. where, for example, in Bitchairs, you have one token, one vote, and then you can vote on whoever you want, right?

And in the end, though, you're electing 100 validators, right? So in this case, you're choosing the validators based on, it's the richest actually you get to choose validators. To me, you know, it's kind of too bad that it's the richest that get to choose, but I guess that's a bit of a surrogate for identity, right? With tendermint, it's actually the richest automatically become the validators, right? whoever has posted the most bond actually gets to become the validators, the top 100. All of this, actually, I see, is sort of a placeholder for good identity. So, you know, with Bitcoin, and it's essentially one electron, one vote. With these proof of stake systems, it's sort of like one stake, one vote, if you will.

But ideally, we would actually literally have one identity, one vote. So imagine if we had a really, really good identity system overall for the world, that we could know that every single human was their own identity signing in. And imagine there's a perfect system, then each person could be a validator. Now, that's really nice. Or if you want, you can go delegated proof of stake style where each person can vote for whatever validator and then whichever 100 validators get chosen, get chosen, right? And so because delegated proof of stake is sort of a way to convert something that's BFT or a pseudo-BFFT,

into something that's much more of a public net, right? So how IPDB is, right now it's sort of this federation, but it is, and it has these identities, these sort of vetted identities out there. Right now, 20, but it's going to go from 20 to 40 to 60, et cetera. And then at some point, we will switch over to a system that is actually much more open, where it's truly one human entity, one vote.

So, for example, you don't have to have something perfect to start with. Maybe you just say, okay, if you have Estonia E-Residency, you get to have a vote. Or you're vetted by one of the, these 10 different agencies, you know, maybe KYC from Authentic the company, or one of other 10 KYC providers, right? So this is a bit like the sort of CA system that we have for HDPS. But that's actually not bad, right?

It's better than sort of one electron, one boat where then you have, you know, massive amounts of value that way. And it will be emergent. No one has a perfect solution yet. You can have multiple different types of markers. You can have the sort of, you know, government vetting. You can have biometric markers. You can have stuff that is stored in your brain's memory, like brain.

wallets, et cetera, and then combine all these, right? And there's a lot of research on this. This is, you know, whole fields are dedicated to this, identity, authentication, et cetera. But I think the ideal is really one identity, one vote. And we're all trying to work towards that. And what I've come to realize, it's not that, you know, proof of stake is virtual mining. It's actually everything is about trying to get towards this ideal of one identity, one vote. So IPDB has its own path. You know, Ethereum has its path. Bitcoin has sort of a pseudopath depending on its governance, right? So with IPDB, you know, it has very transparent governance, you know, everything is recorded, et cetera, et cetera, and they oversee the choices of the

protocol. And like I said, anyone can write to it, anyone can read from it. The only different, and therefore anyone can be a client to it. The only difference is to be one of the validating nodes right now. You have to actually be approved by one of the, you have to apply and then the caretakers vote you in, right? So it's democratic already. And as time goes on, it will be more broadly Democratic. But I guarantee it won't be based on how much money you have. You'll never get to vote based on how much money you have. All right. Well, if you want a publicly open system as you describe it, that is a public good, I mean, that's a good starting point, you know, not to have interests of those who have the resources put forth before the interests of those who

don't have the resources. So there are a lot of things that I'd like to come back to. First, coming back to the foundation, you mentioned a few things that you learned from those who created the initial DNS and ICANN. One of the things that was interesting, that I find interesting about the IPDB Foundation and its governance model is these rules that you've put in place, right? No 30, you can't have more than 30% of validators in a single country or more than 50% of the validators. have to be non-profits. Do you think that if measures such as these had been implemented as founding governance, rules of organizations like ICANN, we would have a very different system today? How do you think we, what would the Internet look like today had those rules been implemented

with ICAN? Yeah. You know, for all I complained about ICANN, I think, actually, you know, it is powering the internet, right? It's this database that's powering the internet in a very particular way. It has its flaws, but, you know, we have these, you know, the main TLDs that everyone uses like dot com are, you know, I've been around a long time. So these things would have helped a bit. Would the internet look dramatically different?

Probably not because actually all in all, VNS is not that bad, you know, unless you ask some like deep crypto hacker, it's all in all not too bad. I mean, we had a conversation with the guys from the Ethereum naming system recently. Yeah. One of the things that I find, and we discussed this, and one of the things I find particularly unfortunate about DNS is the system by which new top-level domain names can be registered. Agreed. Not to have a whole debate about that, but what are the things in ICAN that you really think should be avoided in IPDB? And what can we learn from the experience, you know, 20, 30 years of ICAN?

however long it's been that we wouldn't want to have in IPDB. Yeah, there's a few lessons. So one of them actually was, in terms of dollar capture, what happened is that the registrarers captured ICANN, right? And what this means is the registrarers, you know, if they could actually start registering a whole bunch more TLDs, and they make much more money, right? So they made actually a very low barrier to entry for people to create a lot more TLDs. And now we've had this TLD explosion.

And so companies, like the big enterprises that want to protect the corporate brands, etc. I have to buy up all these other TLEs. And then also there's a sort of mad rush among everyone else too. Whatever there been a better way? Almost certainly, right? And so I think that's a challenge. You know, basically, ideally you don't have money interests making decisions that are for governance of sort of fundamental human infrastructure like the internet or the DNS, right? And so, you know, ENS is exciting, but I think actually, I don't know how much they've talked to the DNS guys from what I gather not very much. because there's a lot of other learnings too.

One one was David Holtzman, he's sort of an unsung hero of the internet for doing this, but he went and actually kept all the domain names of anything related to hate speech and hate words and, you know, racial slurs, that sort of thing. He actually kept them all to himself. And then as the internet was taking off, he actually gave it to advocacy groups,

such as like blacks rights groups and so on. And I think this was really wonderful. He just didn't tell anyone about it. But, you know, maybe I'll say right now, like full shout out to you, David, for doing that. Like, good job, man. So this is why, you know, this is, and there's a lot of sort of decisions that he made that were, he was just trying to be thoughtful, right?

And, you know, maybe there's better ways to do it. I think the fact he was making those decisions while he was still CTO at Network Solutions, which is a public, sorry, a publicly traded company. It was a for-profit, though. And ideally, these can be made much more in the open with a much more, you know, broad vetting process to try to include all the learnings from the past, right? And this is actually what we are trying to do with IPDB. And to give you a feel, right?

With IPDB, we've got these 20 caretakers. But then the board of directors, actually, it does include David, right? And it includes Greg McMullen. You know, that's the fellow who's running IPDB, the main guy. And he actually, before doing Big TeamDB and IPDB, he was actually doing stuff helping with privacy. You know, he actually did a class action lawsuit against Facebook on behalf of Canadians for screwing with Canadians' privacy, right? We also have Constance Chois who runs Kuala, which is a blockchain legal initiative, but she's ex-EFF, right? So all about, you know, privacy as well.

And then Nina Louis Sadler, who's a German lawyer and blockchain expert. So these people together, they're actually thinking about a lot about these issues, engaging with the government, basically really trying to build bridges to the law and what's going on, rather than trying to run away and say, you know, this stuff is different than the law than the law. So we're actually really, the IPDB folks are really trying to work with the EU and the German governments, etc. To try to actually set up the laws in a way that works. And I think, you know, that's really nice learnings. Going back, you know, like the learning that David had, he instills these every day in us and he asks questions as we're rolling this out. And not just David, right, Jim Rutt, who had been CEO of Network Solutions Inc through the 90s.

I've known Jim for almost 20 years and we iterate a lot as well about this, right? So we're really fortunate to have, you know, people who were rolling out these initial internet infrastructure blocks coming in and working with us. And it's not just those guys, right? Like things like, you know, last year there was the Decentralized Web Summit at Internet Archive. And you had Tim Bernersley there and Vinsurf and these guys continue to be involved. And I think that's wonderful, right? You know, they care about the future of the internet too. And, you know, for the first time in probably more than 10 years, like major things are happening, right?

Like all of this blockchain movement, it's not about blockchains. it's actually about next level infrastructure for humanity. It's the layers above TCP and next to it and above HTTP and next to it. And it's cool because we now have a business model for it too, right, in tokens, right? Rather than advertising, that is so healthy on its own. So I'll stop there, but overall, like we have to keep looking to history and reading about it and talking to people and learning as much as we can and trying to avoid repeating those mistakes. No, definitely.

I agree that having people like David Holstman part of this new era of decent. centralize infrastructure is great because we can pool from the lessons that they've learned and the things that they've done to try to avoid the same problems that we've perhaps seen in other endeavors. Coming back to the foundation, one of the things that strikes me is kind of unusual, I guess, given the type of organization or the type of technology that your IPDB is built on, is the fact that this is sort of looks like a typical foundation with, you know, governance rules and a board. And I'm curious, why didn't you, or why didn't you think that it would be a good idea to run the governance using a smart contract, for instance?

Just because a piece of technology is there, a shiny new piece of technology doesn't mean it's the best technology, right? You know, if there's a piece of statistics from a paper from 1925 or earlier, like by Fisher or Gouts or something, and it works better than a fancy new paper from last year out of, Stanford or something, then I'll use the 1925 paper, right? So same thing here. So there is governance technology that has been developed over hundreds of years. You know what they're called? Corporations, nonprofits, et cetera. And they actually, they have evolved to solve a whole bunch of issues around governance, right? Over hundreds and hundreds of years. And so what we're doing is we're actually leveraging governance technologies that have actually been adapted and used and applied over generations and generations. So to me, it's kind of a no-brainer. Like what I

use some governance technology that can only cover 10% of all possible cases and ignores the rest just because it's living in a blockchain versus some tried and tested technology that actually covers all the bases, all the messy human stuff, right? And actually has ways to address that. So to me, it's a no-brainer. Now, that's not to say that we don't want to use some of the smart contract-y stuff over time, right? But it's a walk before you run the thing, right? this stuff has to mature first. So we saw that why take the risk in governance on this, you know, a whole new set of technologies yet when it's not there yet?

And lots of, you know, wonderfully smart people are working on this, bit by bit by bit, and that's great because we'll leverage it as it comes along. But there's no need to add extra risk to this project, this new fundamental internet infrastructure, this database for the planet, by introducing risky technology at this point. So we're picking and choosing our battles. And to give you an illustration, You know, when I first announced IPDB, it was at the Blue Yard Summit last June, decentralized and encrypted, right after me.

So this was actually early June. This was actually the height of the Dow. The Dow had surpassed, I think, $150 million in funding, but none of the hacks had happened yet. I think Vlad was just started to write about his worries and some others, right? And so right after me, Christoph Jens was speaking. And so when I spoke, people had been asking me, why aren't you got, you know, are you going to ask? is going to make a Dow of this and all that. And I said, you know, I said directly, you know, we love the idea of doing a Dow, but not yet in time, right? And IPDB itself as an organization

is designed to melt away 10 years, 20 years from now, whatever it takes, once everything gets automated enough. Because, you know, we don't think, like, we think that over time, things can get automated enough, but we have to actually, you know, walk before we run. And so after my talk, you know, Christoph came up and he talked actually all about the Dow. And it was an interesting contrast, right? And what's really, really cool, you know, that obviously the Dell imploded in all this and, you know, the Ethereum community and the broader blockchain community asked a lot of great questions and has continued to learn from that experience since, right? You know, we haven't gone, you know, live running $150 million yet on with IPDB, but it will come too and this technology

will get tested. But I think it's really cool that the conversation flows. You know, we have a meetup actually with LeachineDB and IPDB. It's every month. And a couple months ago, we actually had Greg come on to talk about IPDB governance and Christoph talking about the learnings from the Dow. And then there was a panel afterwards with those two in Sherman Bushmacher, who is also a lawyer and she was one of the curators of the Dow, etc. And it was actually remarkable how similar the thinking was. These worlds are not so different as you think. Everyone is trying to solve the same problems. You know, how do you govern the protocol? What do you do when things go wrong, etc.? And we have various technologies to deploy, not just the smart contract technologies of the last several years, but also these old school governance technologies that go back decades. Let's use them.

Interesting. Okay. So now I'd like to talk about the network itself. And so at this time, so the network is sort of running as a test net, I believe. Yeah. Yeah. So the overall plan, yeah. So the overall plan is there's a test net and a production that will come. And with the test net, yeah, we've actually had the test net running quietly with some lead users since last October, but very, very quietly just to sort of vet it out. And more recently, we've been developing actually a developer portal for it, such that it's really easy to basically sign up and start using it and talking to it via an HTTP API. And it has a whole bunch of things like DDRs production and all this. You know, it's running in Gen X, Kubernetes, Docker, all this sort of thing. so that it feels like a full-on software as a service that's fully professional that you might expect. So we take a lot more cues from sort of the mainstream software world than from the blockchain world and how we do things, right?

Like, you know, the sort of shift to containers in the last two years is phenomenally useful, and we are embracing it wholeheartedly, right? As well as, you know, other technologies. So under the hood, basically, yeah, we've got these pieces in terms of it getting rolled out. So we've got this developer portal that now we've been opening up to more and more folks. We've actually had a wait list of 250-plus organizations. These have been tremendously patient folks. So those of you on the wait list, thank you for your patience. We're starting to now open it up to everyone out there.

So my hope is within the next month, all of those folks and beyond will be using the test net. And easily, you know, we really held back. We couldn't scale before because we really needed the developer portal to be there. there to be easy to use. So right now it's a test net. The caretakers are running the network altruistically, I guess, and also to test it out and make sure that this is something that you can move into production.

When the system goes to production, when it goes live, and when all those organizations start using it as a production system to build or decentralized consortium blockchain applications, you know, that's fancy stuff. How much does it cost to use the network? Does it cost anything? What's the economic model there? and will there be a token? Are you guys going to do a crowd sale?

Yeah, so overall, I'll talk about the now for starters. So we actually, once again, you know, there are no native tokens inside IPDB. We actually went the traditional web services way, which was asking yourselves, how much will it cost to store data for forever? And of course, forever is infinity, and then the price is potentially infinity. So then we said, okay, what about 50 years? So we said, okay, how much would it cost to store data for 50 years? And there's baselines, right? So if you put a gigabyte of data into AWS or it's $3 per gigabyte per month.

And so with that as a baseline, then we said, okay, well, what about Moore's law? You know, storage is getting cheaper by cheaper, cheaper, cheaper every year. We found some very conservative numbers where it's getting 17% cheaper per year and then extrapolated this and we assume that a plateau is in 10 years. So basically it's getting a bit cheaper every year, plateaus in 10 years. But also we said, okay, if we're going to store this thing for 50 years,

knowing that it's getting cheaper, though, then how much is it going to cost overall, how much does someone have to pay up front? And as we ran the numbers with various models and so on, we also took into account inflation and the fact that you can invest the money. So they put X dollars in that gets invested with a... So we assumed actually 4% rate of return,

and that's actually typical value for government bond and tax hasn't changed much over the decades. 3% inflation, which means overall 1% rate of return. What this came down to for a number actually is the very aggressive estimates are about 25 euros for storing for forever. More conservative was about 75. So we said we're just going to start off with 100.

So basically when people are using the production net, it's $100 per gigabyte forever. And when we say forever, We define it as 50 years, but it's interesting. Once you put that money in, it gets invested, and it hits an escape velocity to go 20, 25 years in, such that it actually does pay for things forever, which is really cool. And it's very different, right? Because if you put something into, say, like, Bitcoin or Ethereum, you're kind of hoping that the network is going to stick around, right?

It's different here. It's actually a contract that you're making where you're paying money up front, but it's actually getting stored by this contract for forever. You're not just hoping that someone will keep maintaining the nodes. And that's really, really cool. And there's other long-term contracts out there. We looked around, right? There's things like this in trust funds, like the Rockefeller Trust Fund, et cetera. Graveyards.

You know, actually, I can buy a plot for myself when I die, you know, 50 or 100 years from now, whatever. And that's actually kind of interesting, too. And then I can actually buy plots for my family for the next 500 years. So you can actually have these long-term contracts that exist. And we've done that essentially here. So overall, we've ran the numbers. Like I said, it's $100 per gigabyte for forever. that's very conservative.

We actually hope that within a year or two of running this for the production net, that we can pull that down by 10x or more. To whom do you pay this money? How do you pay the money? Do you pay the foundation? Yeah, so right now, to start with, it's actually going to go through the foundation

and the foundation reimbursed the nodes. But very, very quickly, this is going to get basically more decentralized in the sense of they can pay one of many, they can pay one of the caretakers directly, get tokens for usage and then it's just like an ADBS token. It's not a fungible token that you can have an exchange, et cetera. And then by that, it doesn't have to flow through the foundation at all, right? And that's just healthier. So overall, that's kind of where we're headed.

Interestingly, it's super efficient. If you think about how much it costs to store data on Bitcoin, right? So one transaction, four years ago when we were going to describe three and a half, it was 10 cents for transaction. A year ago, it was $1 per transaction on Bitcoin because of the mining fees, right? Like the miners automatically to the fees. Actually, the Bitcoin network has been kind of going crazy this past week. So now it's been jumping up to like $3 and $9. It's kind of crazy. But I assume that we'll go down. But overall, even if you say it's $1 for transaction, then we run the numbers. And for us, it is if one of our transactions is one kilobite, which is actually conservative, then you means you can have one million transactions for that $100, right?

So that means we're many, many, many orders of magnitude cheaper than Bitcoin, right? Is it $10,000? Something like that. So that's quite exciting. So anyone who actually wants to store sort of data or even issue assets and tokens, here you have the system that's just using just straight up simple engineering. Like, you know, how would an engineer go about this? This is the numbers we came up with, right? It sounds kind of insane that you can be like, you know, so much cheaper. But not really if you kind of just go through the logic, this thought process that I just described, right?

And with Ethereum, you know, it's a little bit cheaper than Bitcoin, but we're still orders of making new different. But this is actually why IPDB is designed as it is. It's actually a database that's meant to store data, you know, not the hash, just the data itself. That's what a database does. And it's meant to be complementary to Ethereum and Bitcoin, right? And there are people building systems that have Ethereum and IPDB and actually IPFS too, right, all three for the files, for the structure data and for the business logic. Okay. So we're really running along on this episode.

I recognize, but I do want to talk about one last thing, and that is use cases for IPDB. I have some use cases in mind. You know, obviously, you know, talk to a lot of organizations and a lot of enterprise about how blockchain can be used to facilitate data transfer. Basically, I mean, I'm starting to see blockchain really as a messaging system in the enterprise context, as a governed messaging system between enterprise. And the potential for that is massive. So tell us some of the things that people are building on IP. PDB today or things that perhaps you see as use cases in the future? Sure.

So I'll push this from two angles, one from sort of verticals and one from sort of general purpose technologies. So verticals, maybe you and I talked to this in the last episode, I've seen sort of six major verticals that BigGDB itself is really most useful for, right? Identity, which includes authentication as well as storing personal data, towards the vision of sovereign personal data, financial, intellectual property, energy. supply chain and government. So of those, financial, mostly, you know, there's a desire for banks to be private.

And government, you know, it's sort of a bit private, a bit public, it's a bit strange. But the other ones are actually really great fits for public for their own various reasons. So for identity, you know, anything related to personal data, you don't want that to be held by some sort of consortium. You actually prefer that it's really much more public, right? And this is like, you know, towards the vision of sovereign personal data, all of this, it fits really well. So, you know, there's companies like Authentic that are building on top of us that are right now starting off with sort of KYC-ish stuff but are moving towards sovereign personal data. Other people doing consent-based stuff like consent tokens to solve GDPR, etc. So that's a really big use case, all the sort of stuff in personal data.

And we are engaged very deeply in that community around identity too. And I believe there's announcements coming in this too in the next few days at consensus. So the second one that is a really big use case is intellectual property, right? And so this is where we started once again with a scribe. And so if you think about when I create a piece of digital art, my claim to that piece of digital art should really be visible for the whole world, the public, right? And it's not just digital art, it's all the music, right?

Who composed the pieces, perform the pieces? Right now, this is actually all locked up by the big labels and otherwise. And it's actually really sad. So the music ecosystem is actually partly like largely, broken in many really sad ways. And what it means is that musicians, it might be three years before they're paid now because there's just so much data out there

and the collecting societies where it's their mandate to actually figure out who played what, when. It takes them three years to actually pay the artists. And I can keep going, right? All the other just sort of subfields of IP, everything from software licensing to novels. And we have people doing lots of the stuff on us.

Going to the next field, supply chain is a big one. And you might think this is very enterprising, but the challenge is actually how do you, the supply chains are massive, right? They span the globe and there's many, many subnets within. So it's actually really hard to set up a supply chain consortium that actually really covers all the bases. So it's very straightforward, actually, then simply just to use IPDB, right? Because then you're just putting the data on there, it's fine. Or maybe you start with IPDB, and if you realize you really want to actually have your own thing,

you can do it afterwards. But it bypasses having to do governance where you're actually figuring out how to govern who's running the service, right? So I think that's a big one. And then kind of overall, too, with government, there's sort of stuff that helps governments, and then there's stuff that does government-like actions. So stuff that helps governments is things like more transparency, et cetera, right? So it's really ideal if that stuff is put onto a public net. And I think that we will see things like this happening over time.

My favorite example here is actually Estonia. It's not running on a transparent blockchain per se right now, but it's been electronic since the wall fell in the early 90s. And these days, it would be natural if a government wanted to be more transparent to just sort of make that leap directly to blockchain to something like IPDB. It's just much more straightforward. But then government-like registries are actually really powerful. And my favorite example here is Benben.

They are a land registry in Ghana. Basically, that means if I'm someone in Ghana who doesn't have money, maybe I've been living in the same house for my generation, my family for 50 generations or five generations, we never had to headled to it before, even though, and that's simply because the governments have gone through too much instability, right? So no one really trusts the government to maintain the land registry. But if you actually have this land registry that is independent of the government, that, you know, no one can kind of pull down, then you can start to take mortgages on this.

Then you can start, you know, use these mortgages as loans to get education, to start companies, etc. So I'm very, very excited about Ben Ben, because they're doing exactly this, and they're doing it for Ghana and elsewhere. They're engaged with the UN and others to really bring these sorts of services to help the poor. So overall, identity, intellectual property, supply chain, and government-like things. Energy, it's kind of to be determined. You know, there's been a lot of experiments in energy. There's some cool things like we're working with energy, you know,

Germany's largest energy provider on several blockchain projects. But many of them are actually sort of more supply chain related and so on. So for energy itself, I think we'll see, but I think it makes sense that it's public too. Overall, to give you some numbers, I'll just, I mentioned, yeah, like a waiting list of hundreds on IPDB. With Big CheneyB itself, there's about 30 organizations that we know of building on us. About half or two-thirds are startups. The other third is, you know, large enterprises, consortiums, et cetera. And for everyone that we know of, you know, there tends to be another, you know, five or ten as far as we can tell that aren't.

And we hear about another new one every day or two these days. It's pretty exciting. I heard about a couple more today because of consensus, right? So people are starting to realize that, you know, Big ChainDB and IPDB are a complementary piece with the stack, right? It's not just, you know, blockchain as a noun. It's actually you've got, you know, decentralized processing, decentralized process and decentralized database, right? And then with this, you know, plug in the pieces, right? And they discover that Big TeamDB is really easy to use.

Now we have this public net. People can get going, running against it in 20 minutes, right? you know, all you have to do is just start making HTTP requests, right? And then you're good to go. So I'm interested in a lot of these enterprise use cases for obviously. At Stratham, we're confronted with a lot of these same use cases. And in fact, we, a lot of the industries that you mentioned are specifically the industries we target. And one of the things that I think is really important and that sort of consortium closed networks provide is the, well, a couple of things. So one is the ability to have sort of privacy built in, this idea that only the consortium has access to the data and you can have very malleable permission rules

where I send data to one of the participant in the system that, you know, I encrypt the data so that they can read it or perhaps two or three participants and that eliminates the possibility for sort of business intelligence to be done in the network. and then you can revoke access to the data, this sort of thing. And then you can layer things on top of that. Like you can do sort of zero knowledge proofs, right,

built on a blockchain network where only two participants are seeing the data, but the others can still validate the data to be part of some validation rules. I think that these are really, really core to any blockchain implementation at a large scale for enterprise, especially in sort of regulated processes.

So, like, for instance, in insurance, we have regulated processes. where you're going to need these kind of features and you need the regulator to be involved even in setting up the system and the governance and everything. How do you think that, do you think that given these constraints and that are oftentimes regulatory

at the high level, do you think that public networks can really compete with consortium networks given those constraints and how tightly they're set by the regulator? Yes, and here's why the technology of today is radically different in capabilities than it was three or four years ago. So, you know, we all kind of are calibrated by Bitcoin, where everything's sort of out there and public and so on, right? But just because in networks, public, doesn't mean that you can

have shades of privacy inside, right? So Zcatch, for example, right? You've got privacy in terms of the value that's sent, right? But you don't have to just have that. I view privacy, you have privacy at three levels. You have privacy of identity, i.e. anonymity or pseudonymity. You have privacy of the value transferred like Zcatch is doing with your knowledge proofs. and you actually have privacy in the payload itself, right? And, you know, the payload itself, this is something very specific to Big ChainDB. It's a database, right? So, you know, acting as a database, it's about the payload.

Of course, it supports tokens, et cetera, too. But on the payload side, this is really our sweet spot, right? So right now, you know, if you're using IPDB and I want to give data to you, if I wanted, I could say, hey, Sebastian, what's your public key? And then I would just encrypt it with your public key. I put that on the network, and then you could decrypt it with your private key, right? So that would work. Of course, if I'm just sending to you, then there's a better way to send data

than via a blockchain where all of that encrypted stuff is written there forever. We should use some sort of more lightweight messaging system, right? But that's possible. But another more relevant example is, say, I have personal data that I want to share, maybe some medical records that I want to share with, you know, a thousand different scientific teams around the world to do, to include in their scientific research, right? The breakthrough here is that we can actually now have read permissions as assets.

Think of it like tokenized read permissions. And this is something we've been working on actually with some lead clients over the last few months. and we will be releasing it actually with our next release. It's 1.0. It's in mid-June. And we view it as sort of this beautiful marriage between the ideas of blockchain and the ideas of database read permissions. So read permissions as assets.

I'll give you a feel. So imagine, now I gave this example before where I had encrypted your data with, or encrypted my data with your public key. But instead of that, what if I encrypted my data, a symmetric key, And then you want to read my data, maybe because you're a medical researcher, or maybe it's something related to metadata of music or something, right,

where there's going to be lots of thousands of shares. So then basically, I simply, I've got this data that's sitting out there. It's encrypted with a symmetric key. And then if you want it, I just simply encrypt the symmetric key with your public key. So I'm basically giving you, securely giving you the symmetric key to this, right? And I'm doing it in a way where that can even be revoked in five minutes, right? Because you can actually have arbitrary crypto conditions around this. We're using the interledger crypto conditions protocol around this.

So you can sort of have arbitrary combination logic that has, you know, multi-sig like one of two, which is like an or or two of two, which is like an and. You can have inverters on the data, you know, signatures. You know, the inputs are signatures or facts or time, right? And so you sort of arbitrarily compose with these multi-sig and or gates, etc. and inverters, and then in the end, you can do whatever you want with this data. And it can be things like, okay, I'm giving you permission, but you don't have permission to pass it on to anyone else, right?

Et cetera, et cetera. So overall, this concept is wildly powerful. And it actually resolves a bunch of the questions. I think consortiums are asking for privacy simply because there hasn't been an awareness that this technology is even possible. Now that it is, it just makes more sense because then you don't actually have to deal with the politics about who runs what nodes, etc. You can just use the public net, right?

and it's just so much simpler. Now, there's still going to be cases where, you know, people will want to have, you know, data in jurisdictions. You know, the laws are still a bit fuzzy there, et cetera. So you're going to need that, right? But if you, if that, once that gets resolved, the thing that makes sense overall is actually all of the stuff is, you know, encrypted on a public net. And by the way, too, you might ask, we asked, what about quantum, right? And here's the cool thing. Because IPDB is well governed, then we can literally migrate the data from the existing,

algorithms to a more quantum resistant algorithm in the future when that stuff starts to get more real. So that is even not a concern because IPDB has good governance. Fascinating stuff. I wish we could go on, but we're nearing, I think probably the longest show we've ever done. We're pushing on over 90 minutes here. So we're going to have to wrap it up. I mean, there's so many other things that I would love to cover. We'll have to have you back on at some point, perhaps even with some of the board members from from IPDB or custodians. We could definitely do that again.

So yeah, thank you so much for coming on, Trent, as a repeat guest. And by the way, you're getting up there and the guests that have been on the show most often.

I think you're at the fourth, probably your fourth time now. One thing you mentioned board members and I actually, I hate to miss people out and I think I forgot to mention Casper Corgis. Casper runs Estonia E-residency

and he's a board member as well. We're really honored to have him. So I just, wanted to mention because I always like to give attribution when it's deserved and do. But thank you for having me. I always enjoy being on here. And once again, thanks for being flexible with me and Fred having a crazy idea to do this together. No, it turned out reasonably well. I hope everything got, I hope all the recordings are fine and there's no screw ups on the technical side, but it should be fine. Awesome. Yeah, so thanks again

and enjoy the rest of your week in New York at Consensus. And we'll look at for speaking soon. Thank you. And to our listeners, thanks again for tuning in. We are part of the Let's Stock Bitcoin Network. You can find this show and lots of other great shows that like Stop Bitcoin.com. Of course, if you like the show,

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