GEODNET: The Rails for Physical AI

Transcript

My name is David Chen, co-founder of Jonet. Today I'm very very glad to uh give you some update of our project, the recent progress and also our recent development how Jonet could be the rails for physical AI. So let me give you some quick update of our uh status. So this is the latest our Jonet network the RTK network. We are officially the world's largest RTK network. It consists of 22,000 base stations all over the world especially cover Europe

uh United States and a lot of western countries while excluding China and Russia. So to reach this state is not easy. We have web two competitors already there. So the biggest one in the United States is called a company called Trimble. It's a public company worth uh tens of billion dollars. They have spent hundreds million of dollars try to deploy the similar network as we do but they spend the rest you know past 28 years and they have a network about 5,000 base stations and we approach we take a different approach and up to date

we are four times bigger than the public company. How do we do that? We are using blockchain. So we are doing a decentralized way. So every base station owners will deploy the station at home using existing network electricity and maintain the base station which tremendously save the cost. So that's why within four years we can deploy four times bigger than the second competitor and second our network can deliver two centimeter accuracy XYZ.

That's about 100 times better than regular GPS. So because we can provide such a accurate precision network, it could be really useful for a lot of applications like autonomy and automative and also precision agriculture. So a lot of the recent uh tractors running in farmer farm field they are already unmanned. So imagine you know those tractors running in the farm field 24 hours a day, seven days a week with a precision that can make it do automatically. But you need to have the accuracy up to at

least uh better than 10 cmters. The regular GPS won't work. But because our network can deliver 2 cm accuracy, they make it totally totally possible. And also think about the robots and drones. If you want to deliver from one place to another precisely, you need to use our network. So let me give some uh real um use case. This a quick introduction what's the difference between RTK and a regular GPS.

Another use case for our network for autonomic lawn mower to get this precise positioning you need RTK and also for VR if you're not the objects right in the place you need a better positioning service and also Jet can be used for HD mapping. >> Okay. Because Jonet

solves a real world problems, it generate a real world revenue. What make Jonet different from many crypto project is we are getting revenue from the real world not from hardware sales but actually real business paying us. It's totally you know different from other crypto projects. So up to date we have more than 165 paid enterprise customers including like automative uh precision act robotics and there are companies using Juna because they need a reliable high precision positioning infrastructure for

real products and operations. As a result, as a result, Junet has now reached more than 10 million USD revenue ARR from the real businesses. For us, this is important because that provet can be really useful not building the decentralized infrastructure, but it's useful for real businesses. So uh because we can getting real revenue from real visitors and our tokconomics is we are using 80% of those revenue to buy back tokens from

open market and burn them permanently. This is a a promise. The transaction and token bones are visible and verifiable on chain. So there are two charts which you can find in block works website. The left one shows the weekly burn uh tokens in USD. You can see you know in the past several years our revenue growth and also our burn growth as well. The right chart shows the burn rate. Burn rate meaning the token burned in USD value versus the token minted to the to the miners. We are reaching 100% which

meaning we are burning at the same level or even more than the token we minted. So that make a very unique feature like we are towards a deflationary tokconomics. So this is our summary of Jonet to economics and how the flying wheel works. So we have stations deployed all over the world. We have 22,000 base station right now and we generate a real useful data for real businesses and they pay us. We get revenue from the real world and we use 80% of the revenue to buy our tokens and burn them and that make a

very positive flywheel to make Jonet a very attractive crypto project. Okay. So that's the current status. The question we need to answer or the question we need to ask is what's next for Jonet in the AI era? So let's re review the two unique capabilities Jonet offer. So first we offer preise location up to 2 cm XYZ. So that's very useful for web 2 and that gets us a lot of revenue and second Jet network provide a trustable position service

unlike GPS. So GPS signal is very easy to be faked. You know imagine you know in the Middle East conflicts, Russia, Ukraine uh conflicts the GPS GPS there is can easily fake but for Jonet we provide a way that the positioning is reliable and trustable. So uh Jonet can prove you are where you are and that's that's basically is the native feature of Jonet. We called it proof of location.

So we are using 22,000 base stations all over the world with a precise location up to two centimeters and you can prove the device is actually in the place where you claim you are. And we can do the decentralized uh proof. This is very critical because GPS cannot provide that trust level but Jonet can. We essentially create the layer for crypto project and any other uh projects really relies on the trustable position.

So uh we are working on a application called tokuran. So to run is a application that we use for agentic AI. So for the agentic AI they they they already know the internet data. They pretty much consume 99% of internet data already but they do not have direct information for the real world real time data. So for them to get real time real world data it's not available before until now. So if they want to get data info real time data they can send a task to our tokun application through a MCP

through API which is publicly available and took will dispatch those tasks to real human agents. The human agent will go to the place location, take some photo, get their token, they get their position verified by Geonet network and then upload those data to the server and then be dispatched to the AI. So because Jonet can prove the location in a crypto way, those data are trustable. Well, of course, the the the human agents will be paid uh with crypto tokens and the AI agents will get the real-time data and

they can process and continue the valuable uh data analysis. Now the agentic AI can cross boundary into the physical AI. Uh let's give you some use cases AI agents can do with Jonai network. So they can check the store venue conditions like food traffic Q lens whether a store is open uh real time and second is onsite inspection uh you can go to the you know check the construction progress equipment conditions property status and also traffic and mobility like what's the

available of parking and road conditions transactions president and local market intelligence, competitive activity, pricing, promotion and events and crowd verification. So there are many use cases that can be done with the help of Jonet. So the Tokuran app is currently is already available in play store and also in secret phone. We're we're already the top one g top one game in Salona secret store. Now we are adding another feature we call the work for AI try you know adopting the the the the

feature we described before. So the AI agent will generate a lot of real time real world tasks and the tasks will become available to the users of tokon users. they can go to places get their information and location verified and take real-time data and upload to be consumed by AI. So in that way we can imagine the tokman workflow AI will become a very unique and useful feature which is not available before.

So let's look at this you know the agentic AI will evolve into physical AI and that's like a lot of uh like uh Nvidia and other you know big name companies that towards this way and we believe uh Junet provide a unique way with proof location protocol which is essential and also we provide a platform platform the work for AI platform to make it totally available. So that's our answer how a physical AI can be real into place and Junet is a rails uh for the physical

AI. So um please follow us uh in X uh our X account is at Jonet and we have uh uh stay tuned for our Jonet uh the token run application workflow AI feature will be coming up very soon.