Episode 187 Fetch: The worlds first adaptive, sel

Welcome to Crypto Knights. Will we help you finally make sense of the trending world of cryptocurrencies? Hey everyone, I'm super excited today to have on our Crypto Knights podcast, Toby Simpson of Fetch.ai. Toby, welcome to our podcast. Thanks very much. It's a pleasure to be here. Awesome. Very excited to have you. Why don't we kick it off Toby with a deep description of your own background

and then we'll get to what Fetch.ai does? Yeah, sure. So I come from a computer games background. Finally, enough, I was developing computer games back in the Commodore Amiga days in the early 90s. So that dates me sort of developing large programs in 68,000 assembly language and getting totally lost in software complexity. And finally enough, actually software complexity or rather the phrase that complexity is software,

silent killer is one that really stuck with me, the idea that there might be a different approach to managing creating of these these huge programs that might manage that more effectively, but might allow more of the complexity, the interesting stuff that the grades between blacks and white to actually emerge as a property of a larger population of simple things interacting together. I got to be the

producer and director of the creatures series in the mid to late 90s, which is a real pleasure. So I think we created a biologically inspired reinforcement learning agent out of models, chemical emitters and receptors and reactions and all sorts of creepy things. And this thing was able to learn how to exist in its own environment with no human intervention at all. I thought that was spectacularly

cool. And if that philosophy could be used to do that, maybe it could be used to build huge virtual worlds. And I had the pleasure of doing just that in the early 2000s, taking these massive worlds. And I think that there were hundreds of thousands of individual objects all interacting. And it meant that these worlds would adapt to the people that were in them, rather than

us specifying the whole stack of rules. And that's one of the things with modern computer games. A lot of the stuff that you see is all that beauty is really just scenery. It's not real. If you strip or a scenery, there's very little there. And have human beings are creative. Stick them in a space and they want to do interesting things. And I love that approach

that you could potentially knock a tree down and make a lot of noise. And log cabin out of it without any part of the program having to learn about log cabins. So that's a long winded way of saying that I love the idea that problems can solve themselves. And that was part of that thing that led us towards coming up with the ideas behind fetch. Awesome.

Well, why don't we begin to fetch. How did you get the idea of what is the backstory? It's always a backstory, probably. And that's not wrong. Humble not it is usually exciting. Yeah. You're absolutely right. There is always a backstory. And this one's quite a good one because it's safe to say that it's more than a decade in the making. When I first met the other

co-banners of fetch and we were talking about these big environments and all these individual objects. And we were kind of thinking, well, you know, a lot of the kind of stuff we were trying to do in these these worlds is similar to the problems we're trying to solve in the economy. That there's all these moving paths and they're really, really complicated and trying to manage them

all from the top. And then we thought that the problem that we could solve down is like pushing hot water up hill. It's really difficult. And when we were thinking, well, wouldn't it be great if the individual component parts that make up these problems could. One, the in charge of their own destinies could make decisions independently of human intervention. And that they could effectively solve the

problems themselves to sort of a machine to machine economy. But we couldn't figure out how to get the scale. My experience in virtual worlds was very much client server based, you know, there's the bit you trust and all the clients, well, you have to you have to treat them as a, you don't trust them. And that's how you ensure integrity in the world. And I could

make worlds with potentially hundreds of thousands of objects, but you know, the real world is busy. You start having autonomous agents that are digital entities that represent data and hardware. We're talking about billions of these things. How do you make a space like that? And then of course, the long comes decentralized ledger technology. And you look at this stuff and scratch your head and say, well,

now actually this is interesting because couldn't we now distribute the efforts of making an environment that we want and all of these objects across many, many, many computers without actually having to trust any individual machine. Wouldn't this mean that we could create something that had linear scalability that we could make it as big as we wanted and build in an incentive mechanism to ensure that this

network would work. And that was what really led us to. And eventually idea that we could create this space and put effectively an economic internet, a world from machine to machine economy, where all these individual moving paths could work together to solve problems on your behalf or indeed on their own behalf. That is very exciting. Can we ground this with an example? Can we? So I

want our listeners to kind of understand the crux, the heart of fetch.ai right in the get core. Can you give us an example, a use case, if you will, of something that could not be solved before, but with fetch it can be and can be solved elegantly. What would be one such use case? Are examples. I think all of the problems can be solved now, but

just not as effectively and not in combination and not by joining them all together in this way. And it requires too much management and too much effort from human beings. And that's the problem that we have to do all of the work. And with all this computing power, you really expect that work to be done for you. And an example of a problem where there's an

issue is take energy for example. The way we do things at the moment is highly centralized. And one of the things that's changing in society as we're getting all of these electric cars around now and they're batteries. Why shouldn't I boil my kettle off my neighbor's car? Why shouldn't all the individual component parts, the things that generate power? And the things that use it negotiate with

each other autonomously in the background to get the best deal. This would be a network that would be more robust. Work better with the more environmentally friendly methods of generating and storing power that we're working on at the moment. And that'll be really interesting. And then there's transportation. I mean, if there's ever an exercise in pushing square pegs in round holes is transportation. If you're going

anywhere or doing anything, you have to use all sorts of different apps. I mean, great. We've got them all that you're the one that has to go poking around finding all the information that you need. And quite honestly, representatives of you, digital representatives, should be going out onto that network. They should be solving all of those problems and they should be bringing solutions to you without

you having to worry about it. And these are the kind of problems we consider perspective that are potentially solved by having technology like this. I see. And so now can we get into how does fetch do it? How are you building fetch so that you can solve? And around it, I have a smartphone. Can I use fetch or do I need a computer? How do I?

Has a layperson interact with fetch? You know, those kinds of things. Actually, most people will generally interact with fetch probably off their smartphone. Because one of the things that one of the great promises of blockchain is it's a shift of power and control from the centers of the network. And the network to the outside is about giving you the control over your stuff and ownership over

your stuff as well. So that the value that's generated from it comes to you. So of course, a mobile device is a great example of something that I would see as a roaming population of different agents that all the different sensors you've got in that device. They're potentially very, very useful. One of the examples I give quite often is that if a whole pile of people

on one street suddenly put their phones in their pockets, maybe it's just a start of raining. And this is the kind of information that if you join together all of this stuff when a state changes purpose, then that's valuable. Now, would I pay a couple of cents to get that information so that I either bought an umbrella or got in on a train rather than walking

to the station or something like that. But yeah, do you know what I probably would? Because those tiny little value exchanges, there are no real impact to you as an individual, but what they give you is so much more than just that. So I think a lot of people are interacting through mobile devices because it allows them to utilize and get better utilization out of the

information and the sensors they already carry. But also it's a great place for your stuff, your representative agents, the ones that know about you to live. And the idea that that data, all that information, the personal stuff is yours encrypted on your device. And the only thing that's out there on the network are representatives of that. And the fetch network is taking care. It's acting as

this vast dating agency. And taking care of ensuring that the agents that want something are placed right next to the agents that have it or might have it. And I really like that might part of fetch the idea that new kinds of interactions are investigated by the network just because of how it works and what it does. This is crazy to be and my brain is

buzzing with ideas. Also, for example, if I said, you know, right now Amazon might have all the information about the book. So I love to read and but I have specific interest. So so it's sort of Amazon having that information. Somehow over time, I'm able to provide fetch.ai that kind of information. It's possible that once in a while I'll get a recommendation for buying a book

or. But I might say, remember where I popped my car or. Let me know if Bitcoin hits $10,000 because I don't want to track it every day. Are all am I in the right direction? Can I ask all of these kinds of questions? Yeah, and you can, but it's even cooler than that. The fact that you're interested in certain kinds of books means that there might

be a representative agent that knows because you've told it that's out there positioning itself on the network to find out. What kind of books you might be interested in, but all the details of you, the stuff that connects that to you as an individual, they remain private all the time. There's just this digital entity that's running around there, allowing the network to connect it to things

that it thinks might be interesting. As a result of those preferences. And I think that's really cool. So it's not just a reminder service is much better than that because you don't just have to have one of these representatives that's out there. You could have hundreds of them. It's like having this huge. A fleet of individuals out there that are representing what you want, how they're

trying to solve all the individual problems that you might have and presenting them back to you. And I think that's really, really cool. And what we're doing with the network itself is using that huge distributed computer, which is effectively all of the individual nodes that make up this network using that to crunch all of the numbers to build this intelligence information to build this trust information.

So that as well as been able to look for objects in this world to be able to look at the environment. And if you're able to have geographically, they can also look at it from a content perspective. And I love that aspect of it. The fact that you could look from one content area, say politics towards another one, say history and see all of the different

things that might intersect it and then position yourself. So that the other agents, the other representatives that are out there, your next to the ones that are important to you. And that's why I do keep referring to it as the ultimate dating agency for value providers. That's what fetch is doing behind the scenes, making sure that they're the smallest distance and the least friction between an

agent that has something and an agent that wants it. And quite a lot of that stuff, incidentally, is going to be agent to agent. It may well be that one agent is trying to build predictions about a particular airport. I went the cues are going to be particularly bad. And it's doing it by buying up these tiny little bits of information from all the people who

are standing in those cues of their phones. So they're making a little bit here and a little bit there. And then it's trying to form that with some AI and building predictions about what might happen under certain conditions and then reselling that information. So it means that you'll be able to then potentially buy up for a center to and decide when to leave your house to

get to the airport. And that's really interesting. Because there's a it might well be that when you've brought a piece of information, it may well have been through four or five layers of digital entities before it gets to you. Maybe in thousands of individual transactions, transforming that data into something we're used to. Very interesting. So now switch from the use cases. How does this whole thing

work economically? Do I, if I have a piece of data, let's say, like you said, I'm putting my phone in my pocket because it's raining. And I tell you, okay, I give you permission to take that information and monetize it. And at a aggregate level, if you monetize it, give me a micropayment. Is that how it works? Yeah, but one thing to remember is there's not

actually the data itself that's on the network. It's a representative of that data. So of course, when the value exchange takes place, all of this stuff is encrypted. And there's a method by them that's logged on the ledger that the value of stage took place and and so on. And it works like that. But you're the way in which you create those representatives, quite interesting. One

of the things that we're working on and building right now is this network participation. The idea that you could effectively roll your own agents, then you could go to a page in this mobile app and then drag all the different bits and pieces into the agent that you like, press a button, create it and then where it goes. And then you've got monitor those things. You

could create different ones with different combinations of the sensors and perhaps and transform data and see which ones work and which ones don't. And look at them all together and monitor. And work with all of the different agents that you might create. So that's kind of cool. And in the end, you have complete and utter control over what it is that you're doing with all of

these things. And I suspect actually only one of the things that is common to a lot of the crypto space or just technology generally. I mean, the best examples of technology, of course, are the ones that you don't even notice. They're the ones that seamlessly integrate with your lives in a way that means that you don't have to do it in an office. And that's how

it works. This is something that's very important to us with fetch the idea that in the end, these problems are meant to be solving themselves and the solutions, the ones that meant to be coming to you. And that by doing this, by bringing life or putting these digital entities creating these autonomous economic agents, that all the individual moving parts are able to deliver their value and

have better utilization because they're able to work on their own behalf rather than everything having to work under a command of them. And that's the kind of control system from human beings. It's about reducing that complexity, by having a very large population of simpler things working together. And that includes knowledge as well, building a collective intelligence about the network, such as these trust is trust information

predictions, knowledge about which markets intersect with which markets, who should be connected to who, building that as part of the network itself for the benefit of all the users by just using the computing power of the network. Great. How do I, you know, me as an individual, can I make money with fetch or is it supposed to be large here, utility area and making money? No,

you need to make value in many ways. One, of course, is just because you might have a huge population of agents. For example, the ones that live on your mobile device, I have a habit now, much more than the annoyance of everyone around me looking at pretty much anything and thinking, oh, that's a population of agents. So, oh, that's a population of agents. And of course,

you can look at vehicles and think, oh, that's most definitely population of agents. All sorts of wonderful sensors and bits and pieces in there that can provide traffic information, climate information, and all sorts of other stuff that is useful potentially to someone. And the idea that you bring all of this data into play is really interesting. And I was once told by somebody around the data

warehouse that his problem was that data didn't get up on its own two feet and sell itself. And he said, because of that, when I want to sell data, I have to get on an airplane fly somewhere, sitting in a room with a whole pile of people. And then several months later, we're in the same room with different people and a lot of lawyers and a

contract that's two meters high. And then eventually we sell the data. And he said, so you can rest assured that a nest that data is worth an absolute shed load of money. I'm not even going to get off the chair, let alone do anything about it. But what about all that other data, all the other stuff? The cost to deliver it exceeds its value. Well, fetched

all that problem because now you can stick a little autonomous economic agent on all these data rights. And you can do that at virtually no cost at all because it's the same kind of agent duplicated many times. And now the network is taking care of introducing that information to people who might want it. So it brings all this stuff into play. It's not the data we

Because you've got more stuff to work with. How much are now I'm switching gears again, Toby. So have because you said you've been added for many years. I know that probably switched over or brought in the blockchain element recently. Where are you? Is this technology that solves this? Already been rolled out on the blockchain? Is it being utilized by the masses? Where are you with respect

to the productizing this idea? Well, we've had to build our own ledger. This is a piece of technology. Or generally that we didn't start out looking at blockchain thinking, well, let's build something out of this. We started out with a different problem that we didn't have a solution to. The blockchain type technologies led us to then able to make it work. There are a bunch of

things that we needed because this is a unique kind of problem when not just building a peer-to-peer network. For value exchange, we're building a peer-to-peer network that allows a vast population of digital autonomous economic agents to exchange value and find each other and work together to solve problems. So not only have you got these individual computers on the network, but you've got all the agents that

are connected. So that required a different kind of system. We needed a certain kind of performance. We needed to be able to do much more complicated stuff in smart contracts relating to AI and machine learning algorithms. We couldn't do with any existing solution. So we had to roll our own. We're very, very pleased with the results. We've actually released the code. Over 50,000 lines of lovingly

crafted C++ is how they're on GitHub for our scalable ledger. A lot of coffee went into the world. And that's how people can download, compile and run. We have a private test network and a lot less private and a lot more public over the coming months so that more people can play with it. They can get hold of the code and try it. Our unique virtual

machine that powers our smart contracts and machine learning and AI and stuff relating to this concept we call useful proof of work. That's also been released and we're going to be doing a community website and a whole bunch of documentation to get people involved in that. And there's lots of reasons why just coming back to your previous question about how people can potentially make money out

of that. This is part of the incentive model. In the end, you run one of these nodes because you collect value by delivering services to agents and been part of building this collective intelligence and that's trusted information. And the more agents there are, the more need there is. For these nodes to exist. So that's quite an effective incentivization scheme to ensure further decentralization on the network,

which of course is hugely valuable in a space like this because you do get more computing power, but also the network itself becomes bigger and more robust and can be reorganized in interesting ways, which is one of the things that we do. So the codes up and running, the systems up and running, it works. It's, we're looking at a main. So the network release in the

second half of next year. And but in the meanwhile, there's lots to do and lots to try as the test net becomes available and more stuff can be downloaded and built. Do you already have people using your test net? If so, how many and how fast are you growing? And we do. When you've, when you've gone to network, that can can can do so much. One

of the problems is that he went up doing a little bit of a lot and not a lot of very much. And we're aware of certain marketplaces such as hospitality, which turned out to be an interesting one. But we could use fetch to customize user interfaces to to short cut the process between what somebody might want and actually seeing the button to press to get it.

Transportation supply chains, CEO and co-founders are very, very familiar with with with with with this. And the fact that the individual parts of supply chains, you know, containers, nowhere, they're empty. But they can't do anything about it. The idea that you can eventually bring all these things to life is really interesting. And also there's aspects of the healthcare and energy, as I mentioned earlier, all areas

where we're building agents right now. I'm working with commercial partners to see how fetch performance in these spaces and delivering delivering that value. But we're also, clearly aware that as we we make all of this, this code in these systems public for people to try and attach agents the things to see what what fetch does with it. But that'll be very interesting as well. So that's

a lot of the effort that's going on right now, gradually building the size of the network in these different areas that we know work and letting fetch itself as a piece of technology. Explore intersections between those marketplaces that we haven't imagined. Which in itself is really interesting because you know, you never know, right? Humans know they they look at something and say, yeah, a really good

customer for this data is this. But what about the other one over there that you didn't imagine when you've got a network that's constantly exploring that. Then that in itself is a really interesting thing. So the current users sound more like developers rather than real users. How did I get the wrong? Oh no, they're real users. We're working with a number of companies working on strategy

company for what you. Working with healthcare equipment company calls a customer as well. We're members of the mobile alliance looking at transportation related applications to this technology. So we are actually building real agents that do real things and putting them on our test network and actually building these these examples of this technology working. And that's usually important for us as well. You know, as as you

start loading up this network with more and more stuff. You get to know what things work and what things don't. And you get to. And give the whole thing a shake down and let's take that hospitality example. How are they using it? Well, one of the the key parts of that was that when a lot of these particularly hotels trying to encourage people to use mobile

apps to order things in bars and the restaurants and other facilities and other services. And for one of the things that's problematic with that is context. And when you've got this app with a huge number of buttons and a lot of menus and a lot of options. You'll know, you know, every button you have to press, you lose a bunch of people. We know that from

websites, right? And ordering. This is why we have things like one click ordering because every page you have to go through the percentage of the people just drop out of the process. Because it's just too inconvenient. It's made worse when you've got a huge number of options. You're desperately trying to find the fear that you want and you're going through pages of this stuff. You know,

you I saw this actually in an airport recently, a comment which one it was. It was. Anyway, it doesn't matter, but there's some airport in North America. And you sat down. There was an iPad there. And you could order your drink and some food. And I was very thirsty and very hungry. And I gave up. I was pages of this stuff. There was too much to

do. Two complicated. So how we were using this was that by understanding the context. Like, for example, you're turning up in a bar. And you've got a book in your hand. And then I wanted to try and piece all of this together from your preferences. And your representative agents. And where you are in the hotel. And the kind of things that are surrounding you. allows you

to shrink those options right down and provide something that's far more tailored to the individual. But also more effective. Absolutely. Because sometimes actually you would fancy a bag of peanuts with your beer. But what you don't want is for that to be offered to you if you're allergic to peanuts or if you don't want them or if you've already got to be bag of peanuts. And

it's that kind of context stuff that kind of ability to offer people things that they want or might want and get that increasing the more accurate that is actually really valuable. And that ability to customize and tailor user interfaces to meet the individual. He's is one of the aspects of fetch that we we didn't imagine a year ago, for example. In currently because you're in the

test phase, I'm imagining this hospitality company is utilizing your platform for free. Or do they pay for it? Well bear in mind that fetch itself. As a matter of fact, network is public non-commissioned network. It's all the code is open source. As as more of this stuff comes out, anybody and everybody is free to download this stuff and build things on the fetch. This is a

tokenized business. But the token is the primary form of value exchange between agents in that space. And it needs to be that way because of course in order to ensure integrity on one of these decentralized networks. You need to have control over the incentive mechanisms. So the economics simply don't work unless you have such a mechanism. And as as token holders ourselves. As the amount of

value that one can get from from from these tokens on the network as a result of the connections. The ability to do the value, you know, that benefits us. And then there's a commercial arm that we have this expertise in building all of this and there are cases where particularly some aspects of healthcare, for example, we're actually private. Networks are more appropriate because even though all

of the communications transactions might be entirely encrypted, sometimes even the near knowledge that they took place is an invasion of privacy. And that's I guess the difference between the internet and the internet. So there's many different ways in which this stuff works. But the main fetch network itself is is a public network and is free for anybody to use. And once that main network is released

in the second half of next year, that's that's what we expect. Okay. And how will the tokens be generated and how many of them will be there eventually? I guess well eventually there will be and for those that are interested in all of this, we do actually have a token on its paper. It's on our website that talks about it's about 1.1 billion tokens, but they

are infinitely subdividable. So in the end you can work with much smaller proportions of these tokens, much in the same way people throw around point not not not one of an e for example. So it is not like that that limits your ability to be able to do things with the tokens. So yes, eventually there will be over a billion of these agents in so it's

open in circulation. And how are they generated? There of course, I think that's a good example. Yes, is a token sale, which is a great way of getting tokens into people's hands, where is a nonprofit foundation, which is tasked with the purpose of ensuring that tokens end up in the hands of people that are using them for the utility purpose, which they were intended. There are

mining rewards in the early days of the network to further incentivize the setting up of nodes as the value of the intelligence information on the network grows. But that's very much a short thing. Because at some point the value that some node generate or nodes operators get is from, as we mentioned earlier, delivering those services to the agents that are connected to the network. So there

are a great number of ways in which the tokens will end up in people's hands. And as has a people who are originally creating all of this is in our best interest, where as many tokens as possible to be in as many people's hands as possible. Because that enables those tokens to be in the hands of the network. So that's what it's like to have tokens

to end up in digital entities in all these agents. And let's then start doing all of this work, this machine to machine economy. That's that we're building. And they can go to www.fetch.ai and they can get your white paper, your tokenomics. Of that then your top. Absolutely. So fetch.ai is the place to go. We've got economics papers there. We've got the token economics paper. The original

technical introduction paper back from earlier this year. There's also paper detailing all of the technical details about how our scalable ledger works. And of course, it'll point you at things like our telegram, social networking. But also at GitHub. So for those that want to actually start hoping their way through the code and having a look. They are able to do so. And we're releasing more code

all the time. So that's what we're doing. It's very much the tip of the iceberg from that perspective. As we start winding down, it will be the other question that I had was who should be interested in fetch.ai. Can you give me your target segments segment or segments. Who should be interested. And then the next question obviously that I will ask is how do these people

find you. Right. But let's start with the first question. Are these businesses. Are these developers. Are these non technical, not non techy type of users. Who are you hoping to address. And then how will they find you. I'm pretty sure everybody is a very bad answer to that question. So I'll try and narrow it down. But we're also. Yeah. Now let's start with everybody. And then

I'll sort of refine it. But if you this is one of the problems that that's when I work with this stuff every day. And I've got an idea and my mind. Who will find value fetch. But the reality is that who will eventually find that. It's just completely different. Something a conversation with someone recently. We were talking about when Apple originally launched the app store. It

was just an avalanche of surprises. The individuals out there had great ideas and suddenly had the power, the ability to be able to bring them to life just like that. And you think of all the innovation that we saw. In such a short space of time, whole new genres of entertainment and applications and things that the no one had ever considered. But somebody had thought of

it. And that's one of the wonderful things about stuff like this. But it gives the ability to do things to individuals. If the power to create individuals where they wouldn't have had that before. And I think that that's super exciting. But of course, you know, we're talking to people in the spaces that we're aware of. And anybody out there involved in fields of. And we're talking

about transportation and mobility and energy. And particularly those connected to smart cities and looking at how these things could be structured in the future. Of course, but very, very interesting in talking and working with people like that, because we believe that fetch is a really good way of optimizing solutions to those problems. And we would like to investigate how that can be done and build more

examples of it. And then, of course, there's developer's. And this is a space that thrives off enthusiasts and developers. Ever since that original Bitcoin paper came out, it's just attracted people who just want to tinker and play and investigate and think and try. And that's the exciting space that we're in. And we have something which is different. But it's designed to support this huge environment where

digital entities get things done. Our machine and machine economy are massive decentralized world for autonomous economic agents to solve problems on the upper half. And, and, and, quite honestly, what I imagine people will be able to do that space is nothing in comparison to what other people will be able to do with that space. Wow. That is pretty exciting. Great. So, and where would you like

all of these people to find you? I know we already have the website, vegetable, or AI. Are there user communities where the users can interact? Talk to each other? Help each other? Is it a, is that a Slack group? But telling them where do you want them to go? Telegram is the easiest and quickest way. I think that's a great way of interacting with us. There's

a lot of us there. We love talking to people and it's a great way of interacting with us, especially directly. But we're not hard to find. We have our offices in Cambridge, all the details of where we're going to be. We are where we work is all on our website. And there are many, many ways of contacting us. From a community and a developer support perspective,

we have a community website that's where putting the finishing touches to at the moment that we expect to be out in the very near future. We'll link through to that, of course, from our website. And that's where people can build fetch type smart contracts, build AI and machine learning applications on the ledger. We run the code, test the code, interact with other people, and get help

and access to documentation. So there's a lot of that stuff coming. But in the end, the root to all of those things is through our fetch.ai website, where we keep all of the ways of contacting us, either just to watch what's going on or to take part. We make sure all of that is right there. Toby, it's almost impossible. Given how big the vision is and

how it's more like a app store that was a great analogy where we cannot even predict how people will use this because you're suddenly putting power into the hands of curious, smart, innovative type of people. So I cannot do any justice. I feel in such a short session. We're certainly going to have you back multiple times. I can see that. But any closing thoughts, any, any

points that you want to mention, any questions I did not ask. I just think that we're all collectively in an extraordinary space. We all know that this space is going to change the way that we live our lives, change the shift of balance of control over the stuff that belongs to us to us and enable a whole new kind of way in which problems can be

solved and things can be presented. And that is incredibly exciting. And it's enormous privilege, I think, for all of us to be tinkling around. And I'm enormously excited by what we do. When you look at blockchain in isolation and you shouldn't, you know, blockchain and decentralized ledger technologies, they're a part of puzzle. And when you start integrating them with other technologies, all the incredibly exciting things

that are going on in multiple agent space, multi agent space and machine learning and AI and decentralized and distributed computing. And you start joining all of these things together. And the kind of stuff that you can do is just extraordinary. And I think that's, that's, well, it's a lot of fun. And at the same time, watching all these new things just come out of nowhere. Yeah,

it's a great space to be in. Well, and we reassure the very best. Thank you very much to people joining us and you have a fantastic evening. And it looked forward to having you back in the near future. I look forward to it. Thank you very much indeed. Thanks for listening to the crypto night. Never miss an episode. Subscribe now at www.cryptonites.io.