Built on Hedera - Neuron - DePin at Scale

[00:00:00]When you look at the scale of this, well, every sensor, there are millions of sensors out there today. There are millions of autonomous systems out there today. There's probably tens, if not billions of actuators and valves and signals. They want to be network connected. I'll let other people do the maths, but you know, you're talking about millions, if not potentially billions of systems around the world.

[00:00:22]>> So, a couple weeks ago, I got a comment to one of my posts and it was talking about Neuron. There was a question that came up if they could actually put out the sensors for Neuron's DPIN network and the answer was yes. We got that directly from James, but that reminded me I needed to get an update from Neuron. So, we have the CEO and founder, James, here today. James, thanks for hopping on buddy.

[00:00:45]>> Hey, Brandon. Great to see you again.

[00:00:46]And uh yeah, really excited to give you some updates on on where we've been heading.

[00:00:51]>> Well, your vision has never changed from day one. We've known each other for probably 5 years, maybe even more at this point. But of course, there's always tweaks and evolving to allow that vision to come to fruition. As far as features and products, where does Neuron stand today?

[00:01:10]>> Yeah. So, well, basically, we've already got the 4D sky network set up and that runs on the neuron protocol, the neuron infrastructure layer. And sort of just zooming out a bit, just to sort of remind some of your viewers, what is Neuron trying to do here? What we're building is really the infrastructure layer on how AI systems can talk to the physical world. So whether that's sensors, whether it's uh robotics or drones, how does AI interact with all of these physical objects? Because currently AI is very good. It's very it works online in the digital world. Uh AI agents can can buy and sell from each other. You can instruct them to do things um on in in that sort of digital digital realm. But the next layer is well, how do they now do things in the physical world? How do they ingest sensor data, understand what's happening, and then take action based on that? And so what we've done is we built the first network which was the 4D sky network which is now growing quite nicely. I think we've now sold 700 sensors roughly. So that's gone really well and uh we've partnered with Helium deploy um on helping to distribute those and we're bringing on other distributors in in other regions as well now. So, so that's sort of the next conversation, but that's sort of now growing to a point where we've got like a really good coverage across sort of most of the western world now. Um, we've also got some in like the Middle East and some in uh Asia starting to build up that global footprint. But then how do we also integrate other types of sensors and so our current next iteration of the project is really focusing on how do we make it easy for everyone to bring their sensors and their physical systems on board on onto the neural network. So James, the the first part of it is getting that infrastructure out there, getting the sensors in place, but for those sensors to have value, there has to be value created for the customers downstream. How are things looking on that side of it?

[00:02:54]>> Yeah, so we we're basically been going out and we've been bidding on a lot of projects. So um we've got some data customers who we've we've got in that pip pipeline at the moment. We're actually meeting one of them in a couple of weeks time who's coming to London.

[00:03:05]Very very large uh data analytics company. Um in fact, the largest in the world. Uh so you may be able to get infer from that who that might be. But yeah, we're meeting up with them in London uh from their data in team. I'm going to be talking to them about acquiring some of that data from from the network. Um and obviously it provides a lot of advantages over traditional flight tracking networks which sort of a very vertically integrated networks. So it's sort of kind of that centralized let's plug all of our sensors into a data center and distribute it via an API. What we're seeing now is that actually precision and understanding where the gaps in the data is really important and being able to provide a lower latency, higher availability data stream into these customers is actually really exciting for them. So, so yeah, we've got some really good good conversations going there. We've we've then submitted around about nine bids over the last eight weeks, which is great. So, um we're hoping to win some of those and that will help us to progress the the product and also go and start bringing in some some sales revenue from that. So, you know, we're hoping to be able to start rewarding uh people within the network shortly uh for for installing sensors and and contributing data. So, yeah, it's it's a really exciting period for us. It's been very much focusing on sale sell at the moment. Uh so, you know, we've been building for a long time. We built sort of that infrastructure layer out. Um and we've got our new uh the the actual new product which is going to be coming out sort of in the next few months. um which is basically going to glue all of this together and make it really easy for people to on board.

[00:04:33]>> So that's bringing value to agencies and airports and businesses out there. How about individuals? Is are there ways that an individual can get value out of what Neurons providing?

[00:04:46]>> 100%. Yeah. Well, so what we're seeing is a lot of individuals just buying the sensors and contributing data into the network. So, you know, this is an opportunity if you live in a good location, especially near an airport or where maybe there might be drone deliveries happening and things like this. Um, like these are really hot spots. So, being able to claim your hex and being able to go and get, you know, almost kind of earmark your your location. Um, so you can be the data provider in that in that area is is a great is a great place to be, you know, if you believe that we're we're doing right things. And hopefully, you know, given our backgrounds in aviation and within uh sort of drone technology, we do understand this area incredibly well.

[00:05:22]And so what we're trying to do is to really help the community to install these things, contribute that data, and get paid for doing so. Um, and this is this sort of creates an opportunity where actually, you know, it's not just that the big guys make all of the money, but actually us smaller guys can can contribute and and earn a share of that as well. So I think this is a really exciting time for deep in networks. You know, I think you've seen I think you saw over the last sort of year that some of those deepin networks were just focusing on selling the sensors to people, which is is fine. You need to grow the supply side of the market. But but there's also a demand side problem as well. There's no point in just putting lots of hardware out there and not actually doing anything with it. And so really our focus over the last sort of three to six months has been focusing on the clients, understanding what it is that they want, how we tailor and uh and deliver that product to them. um and really taking them through that sales funnel.

[00:06:14]>> You're focused on that demand side, but I am very interested in the sensors.

[00:06:18]It's critical to have, you know, use sensors when it comes to AI and so many other things right now because it's direct observation of what's happening in the real world as opposed to, you know, things we're seeing with AI where they're making guesses and hallucinations half the time. Those sensors going into that adds an entire new layer of trust. So the first sensors you had out, I think they're called air squitter and you've had almost 700 that have been bought right now. I think half of those have already been deployed. Are you going to stick with that type of sensor or are you looking at adding other kinds of sensors that could supply other kind of deepin products?

[00:06:56]>> Yeah, exactly. So, so it's a really great question because ultimately like the 4D sky air squitter sensor is is a fantastic sensor, probably one of the best in the market. Um and so you know that gives us a picture of most things in the airspace and certainly what I would call friendly aircraft. So um anything that wants to be detected can be detected by these sensors. But there's a lot of aircraft that maybe don't want to be detected. And we we're seeing a lot of this in polit you know recent political events. I think in Ukraine for example 80 80% of the casualties in Ukraine have been from drones. So, you know, you're talking about like the the the war warfare at the moment is not being done on the ground with troops with guns. It's it's being done in the air with drones at the moment. So, there's a real risk for militaries and stuff to be able to handle and understand what's what's happening in the airspace. And and for the escitter sensor doesn't necessarily do that for you, but what it does do is it tells you who where the friendly aircraft are. Um, and you need to know both. You need to know the friendly and the unfriendly aircraft to be able to really pick up a full airspace picture.

[00:07:56]So we've been working with a a series of other manufacturers um some one of which is just recently out of Y combinator who make these sort of millimeter wave radar systems um sort of lowcost millimeter radar um others such as remote ID uh sensors we did some uh structured uh testing and evaluation of these sensors through the NATO Diana program we're part of um and this basically is m meant that these sensors are now integrated into the sort of defense stack and so what we're trying to do is to bring all of these both public and private private sensor layers together into a unformed uh sort of infrastructure where customers can access sensors of all varieties. Um and so we're, you know, some sensors sort of benefit from that wider scale distribution. Others are more targeted. So not necessarily the deepin model works for every single type of sensor. you know, if you only need one sensor, for example, uh at an airport to be able to see um a remote ID drone essentially, then then you you might not need a community of people deploying these things everywhere. But for the 4D sky sensors, the air squitters that we we've been selling, these need sort of a very wide coverage and they use multilateration to pin to triangulate the position of aircraft.

[00:09:08]You need a network of community of people deploying these. So, it's going to be a very varied and mixed bag. You can build deepends on top of the network or you can uh just integrate them yourself as a customer where you want them. Um so we've kind of left that to be as flexible as possible.

[00:09:24]Good stuff. So the next thing I kind of want to ask about is the people that are showing interest. You know, we've talked about uh the businesses initially. I know that there was a fair amount of people. I'm going to give a shout out to Milan because I know he was one of the very first people that was running one of those air squitters. has it remained people that are passionate about Hideera or has it expanded into to new people as well?

[00:09:47]>> Yeah, so we're seeing a wide range of people wanting to integrate these things um and not not just even like people in the web 3 community um but people outside of that as well. So you know initially I think our first batch of sort of 100 150 sensors uh were were like 90% of them were were Hideerira sort of community members. Um and that's been brilliant you know that allowed us to test the systems get them up and running get the product built properly and and uh and working um but then we sort of opened things up through Helium deploy. We partnered with Helium deploy for distribution and that that's given us a much wider network of people across the whole deepin space. So you've got people who are sort of natively on Salana and Bass and Polygon and all of these other other networks now sort of understanding how how Hideira works and and sort of getting a taste for for the community and obviously that brings people into other other businesses and applications within the Hideira ecosystem. So things like Hashpack for example um being able to track your points. We're using the HCS20 standard for points. Um so when people deploy a sensor they earn earn these points which basically are tracking how much data they're they're providing into the network. Um and they can do use uh track that on hashpack for example. So it's actually helping to sort of spread uh spread sort of people from different communities together using using the 4D sky platform as as that sort of uh vehicle for doing so. But then when you come outside of web 3, you're like then looking at like airports and drone operators and people like that now integrating them as well and starting to get a feel for okay, what's this new type of technology? How does this work?

[00:11:20]And you know, we've tried to abstract that as much as possible for them. Um, and the next pro product iteration is going to feel very weird because it's going to feel like a normal product that people it will have all of the benefits and uh the the qualities of a decentralized network, but it will present it to people in a way that they're familiar with, you know, whether it's Google, Amazon, whatever. It will feel very comfortable, feel very very natural for them. Um, and this will be able to cater for for, you know, both public uh applications and also private and defense and security applications as well. Unfortunately, James and I had some technical issues. We're going to have to continue that interview next week, but it does give us an opportunity. Now, based off of some of the things that James and I talked about, we'd love to get some of your questions. James is available next week.

[00:12:08]We'll be able to record the second part of this interview. So go ahead and if you have any questions around Neuron or anything that James brought up, go ahead and drop those down below. But I did want to dive into a few more things with Neuron that should really get us excited, not just for Neuron, but the impact that it could have on Hideera as well. I looked at their website and saw that they highlight 160 million transactions. So I asked if all these transactions were on the Hideera network. James told me that they were, but they were still on test net. That said, they've actually generated over 225 million transactions. Again, this explorer is representing things that are taking place on testnet, but they are in beta at this point, and they have to be pretty close to swapping over to mainet considering how quickly things are progressing. The whole point of tracking neuron data on Hideera is to add trust and traceability, and mainet is really the only place you can do that effectively. With the expectation that this is going to impact mainet pretty soon, let's think this through. When it comes to scale, they've only had sensors out for a year or two. Late last year, it was only about 100 sensors. Now, there's about 400 deployed and a similar number that have been sold and should be connected soon. So, just 6 to 8 months ago, there was 100 deployed and now there's 400 and that's increasing rapidly. They have multiple customer integrations and as James said, they're bidding on many more. These are customers that are willing to pay for the data that the sensor operators are providing all around the world. If, as I expect, this becomes a sensor network with thousands of paying customers and tens or hundreds of thousands of sensors, heck, it could get well into the millions, the utility that this could provide for both Neuron and Hideera could go off the chart. Now, they're starting with drones and aviation because they knew there was a market for that kind of data. But they're expanding sensor data set will be useful for countless other applications from autonomous vehicles and deliveries to smart cities and homes. Plus data is AI fuel and Neuron's data set only seems to be going exponential. So we're starting to see in this beta phase on test net the potential scale that's going to hit the Hyera network. Then we're going to move to mainet but that's still on the Hideera consensus service. It's all data tracking, data providence, all that kind of stuff. But the next phase gets even more exciting especially for the sensor operators. That's when they start to get compensated. So, they should be launching their native token that's going to be under the 40 Sky brand pretty soon. And that's going to kind of be the the base layer of compensation for these different uh sensor operators.

[00:14:35]They're going to get payments in that.

[00:14:37]They're also going to get payments in USDC in the US dollar. So the customers that we're talking about there, they make their payments in US dollars and Neuron is going to distribute those to all the sensor operators depending on how much their their data is being used in the US dollar in USDC. So we're going to see transfers not just in HCS data, but we're also going to see value transfer done through the Hideera token service. And I'm not exactly sure how it all fits together, but James was saying they also leverage the Hideera smart contract service. So, we have to see how that's all going to come together. Right now, they're processing about five transactions per second on the Hideera test net. That's going to move to mainet, but then it's just going to increase not just in the size of the sensor network, the number of heartbeats, the the data that's being tracked on Hideera, but then we're going to start to see payments going out as well. So, really exciting stuff when it comes to Neuron. So, I want to get into something else when it comes to Neuron.

[00:15:35]Actually, there's a couple things.

[00:15:36]Number one, I contacted James because I like you probably want to know when they're shifting from testn net to mainet. He said probably within the next six months or that's what they're shooting for. It seems pretty pretty imminent to me that they're going to be making that shift. And if they came on to mainet today, they would increase the throughput on the Hideera network by 2x.

[00:15:57]But it's not just that. They're adding new sensors all the time. They're adding new services all the time. So we could see a three, a four, a five, an order of magnitude increase on the Hideera network overnight just from this one use case. And of course it has the same impact as far as revenue. Now most of them are Hideera consensus service transactions, but there's going to be payments going out pretty soon here as well because we mentioned that they're going to start to incentivize those nodes going forward, both with their own native token and with USDC. So we could have those transactions hitting the network as well. And this goes back to it takes longer than you might think, but when things do flip that switch, things can get exciting really quickly.

[00:16:44]Now, Neuron started building on Hideera, give or take about 2020. So, it's been 6 years and there's a lot of teams and applications that have been working behind the scenes that it takes that long before they actually reach mainet.

[00:16:59]I think over the next few years, and we could start to see this with Neuron within the next few months, we'll see not only additional teams hitting the networks and applications hitting the networks that have an impact, but a lot of these applications and teams will be going through their growth phase. In some cases, like I believe with Neuron, it's going to be going through an exponential growth phase. So, the impact again we could have on the Hideera network could be really impressive here in the months and years to come.

[00:17:28]So, we have James from Neuron back again. We did have some technical issues last week, but I think it ended up being for the best because I've gotten some great feedback, some great questions from the community and after, you know, wrapping my head around what Neuron is doing. We were just talking about it off camera, how grandiose the vision is, but also the fact that they're actually making it to come come to fruition and they're having success. we just had to have this second conversation. So, James, welcome back.

[00:17:58]>> It's pleasure to be here again and uh yeah, excited to answer some of these questions from the community. So, I saw a few um on the on the airwaves earlier, so hopefully uh hopefully I can do them justice.

[00:18:10]>> Yeah, I have no question that you absolutely will. We're going to start off with the first one from Gaston who said, "Hey, Brandon, I've been running a sensor since the spring here in Canada.

[00:18:20]I noticed that there are around six to seven sensors in my city now. With that many, is it enough data to support a contract? If not, roughly how many sensors do you think are required to go after a contract? So, I certainly want to address his question here, but also I want to do a deeper dive on your sensors in general and the sensor network that you guys are establishing.

[00:18:43]>> Correct. Yeah. So, um, so yeah, it sounds like, you know, six or seven sensors in a city like will give you really good coverage around the area.

[00:18:50]So, that may not be like the the full extent, but but that will give you really really good coverage. And the reason we need multiple sensors isn't just because of coverage. It's it's also because of um a process we call multilateration, which is basically where you're triangulating positions from multiple sensors to actually find where the aircraft is. Like we're still dealing with a lot of legacy equipment that's on aircraft. Not every aircraft transmits its position digitally through the sky to to the ground so it can be picked up.

[00:19:18]Some of them just transmit their call sign, also known as like an IKO address, which basically um just is like a a way of identifying what aircraft it is. That was born from like um World War sort of systems where they were, you know, using radar systems and they could they could tell there was something there, but they didn't know what it was. And so what they started doing was was basically transmitting their call signs. So now the radar operator can see the aircraft but also know whether it's a a Boeing or whether it's a a military aircraft about to come into the airspace. So this is why a lot of these systems came about.

[00:19:52]But we we have to deal with those systems, you know, we can't just deal with some of the aircraft in the sky. We have to deal with all of them. And we actually there was a really good good thing that came out um recently. So it looks like the UKCIA um are going to be implementing a UKwide mandate for electronic con security for ADSB data.

[00:20:10]So every aircraft is soon going to be required to carry it. Um which basically gives us 100% complete airspace picture of everything that's flying. Now this is huge. Like this is a huge step and I've been saying it for a few years that this was needed. But what this does is it basically gives Neuron the ability to detect everything to track it and then to feed that onto all of the various systems that need to use that data to to be able to avoid each other or to uh navigate through the airspace and things like this. So yeah, coming back to the question, six or seven sensors like great a great starting point and we can certainly start selling contracts within that area. It would more sensors in that area be be needed probably almost certainly. So you know we when we're talking about very very lowlevel airspace so getting down to sort of maybe three or 4 hundred feet which is where a lot of drones are flying you're often sort of uh constrained by local buildings. So there might be buildings in the area that are blocking signals.

[00:21:05]So you actually need sensors in a lot of areas to cover the airspace appropriately. So yeah, six or seven sensors, great starting point. We can start selling contracts in that area. Um we may have some news in the next few weeks about about some of that, but there's more to come basically.

[00:21:21]>> So James, now these sensors, I know you went through a taking a lot of time to pick out the right sensors that would be able to get the right data that would actually be valuable out there. Now, I know that Helium, one of the first deep pin sensor networks out there, they kind of it seems like they rushed that process and the sensors that they put out weren't as useful as maybe what you have. Can you tell us specifically about these sensors and why you chose them and why they have the data that they can collect is so useful for not just the aircraft but other things you're looking at in the future.

[00:21:55]>> Yeah, exactly. So, we we actually analyzed multiple different types of sensor. So we I think we looked at about four or five different types of sensor before we selected that one. And the reason why is because we're trying to learn from some of the lessons that other projects had had uh unfortunately learned from the hardware which is if you deploy bad hardware you get bad data from them. So you need you need to choose the right sensors and the right technologies to be able to support your service. Ultimately someone is you're going to ask someone to buy that service at some point in the future. And so if it's producing rubbish data, it's it's not that useful to you and or your customers. So so getting that right was was important. And so we did loads of demonstrations and trials and pilots with customers demonstrating different types of sensors. And ultimately the end user wanted that type of sensor. That's the type of data they're looking for.

[00:22:42]That's the type of quality that they're looking for. It provides data on the right frequencies which is what they're looking for and it's the lowest cost which delivers everything that they needed. So we try to find the best value for money. Now, obviously there are cheaper ones out there, but but ultimately sometimes if you buy cheap, you buy twice. So, um this is really the cheapest you can get for the capability it provides. And they're actually time synchronized with satellites. So, these sensors are are using the GPS signal. So every second they're sending a pulse uh from GPS satellites which basically means that the sensor is synchronized with those atomic clocks on board the satellites and means that it can actually determine the timing when every signal is received within about 30 nonds which is like that's that's basically the the time it takes light to travel 30 ft. So we're talking about very very very small time windows that these these instruments are timing the signals by.

[00:23:34]But what that allows you to do is to get accuracy on the triangulation piece.

[00:23:39]Without that, you're not really you're not able to actually get any kind of accuracy. So if you get 30 feet of of accuracy on every on every timing signal, you can get kind of at those or orders of magnitude in terms of accuracy on the actual position. So let's talk about like the the coverage we we mentioned there. They're actually broken up into hex's. The first sensor in a hex, and you can let us know how big each one of those is. um the first one is going to have the best economics and then so on as we add additional coverage into those areas. Can you just kind of break that down how we split up essentially the globe to to get proper coverage?

[00:24:15]>> Yeah, so every every single I think it's about 2 kilometers roughly every every hex is in terms of its diameter from one side to the other. The first person in there will get 100% maximum rewards for that component and then anyone else who comes in afterwards will share the remaining. So there's basically two units. Let's think of it like that. Two units um of reward points per hexagon.

[00:24:37]The first unit goes to whoever established a good center within that area first and then the second unit then is spread amongst anyone else who's within that hexagon. So if you're the first in the hexagon, there's a great opportunity to almost like reserve your spot and reserve that hexagon and be the infrastructure provider for that area.

[00:24:55]As we evolve the the model, you know, we're going to be introducing other types of variables which are going to help improve things. So things like say if you're near an airport you'll get a bonus um because obviously airports are a very critical piece of infrastructure that we want to monitor flights around also in other areas. So where there's say a city that's doing drone deliveries we may want to incentivize uh deployments within those areas. So so really we've got sort of like a malleable system for providing bonuses in certain areas where we want to direct uh supply side because we've got a clear client and demand side.

[00:25:29]So he was talking about the contracts there. What exactly is he talking about when he mentions a contract?

[00:25:35]>> So the kind of customers that need this.

[00:25:36]So airports are are a big one. So they have these thing called flight information displays that sit in the airport. They're basically a display of all of the air traffic around them. A lot of airports still use visual flight rules. So they literally have a guy with binoculars looking out the air traffic control tower trying to spot planes which seems a bit antiquated. Now we live in the world that we live in in a very digital age. You have other types of system out there as well that use these big World War II radar systems. Uh some of them are a bit more modern nowadays, but they still work off the same principles where they've blast out lots of RF noise basically around the environment and then wait for reflections and pick up the reflections from aircraft. Again, these are tens of millions of dollars to go and deploy these things. They can't really classify what type of object it is. So, you know, small drones and things like this, these things is too small for these to pick them up. you know, they try and eliminate bird noise and things like this. So, we need to move to a more digital way of working, not using analog systems, not using visual flight. We need everything to be trackable in the sky and that all needs to be interoperable with other systems. And so, airports is a is one that we're we're already targeted. We've got our first deployment in the UK and we're going to be expanding out to other airports. So, if you've got an airport near you that you'd like to try and sell your data into, get in touch with us or feel free to reach out to them and say, you know, here's here's the system that we've got, we can provide you with additional information as well, some maybe some brochers and stuff. So, if you want to help us to go and get your sensor being used by your local airport, then we we'd love for you guys to reach out and help us in that process. You know, we've only got a certain number of hands and a certain number of phone lines where we can call people up. So, you know, a community- based approach to this would be fantastic. The other kind of customers are like what I call global customers. So, we've got a meeting actually next week with one of them, probably the world's largest aviation data analytics companies. Um, and they buy data globally. So, they're looking for a global data set of every second where aircraft were using things like ADSB, multilateration, UAT, and all of the other data types that the the Jet Vision Air Squitter provides. And so these guys bite on mass because they're using it to answer people's questions.

[00:27:43]You know, maybe they've got a government comes to them and says, "Where are the biggest risks in the airspace?" Or it may be an airline comes to them and say, "Where where are my best routes for next year?" You know, which which route should I drop and which route should should I continue with? Um and these kind of decisions can be worth tens of millions of dollars for making the decision. So ultimately the data that informs those decisions needs to be accurate. It needs to be precise. Um, and it needs to be validated. It needs to be trustworthy as well. And that's what we can provide them with. So, we've got a meeting next week. We've given across some sample data. Um, and yeah, we're we're feeling quite optimistic about this one.

[00:28:19]>> So, James, I've learned so much just over the past weekend around these sensors from the fact that they're completely uh self-contained. So, all you have to have is a Wi-Fi connection or a LAN connection to the actual unit.

[00:28:31]Then, a wire goes up or a cable goes up to the the antenna. And you don't have to have a separate computer. It does everything by itself once you have that internet connection. But I do have another question. You've been talking about of course aircraft. The next thing we're going to talk about is drones. Is the air squitter is the data useful for other things like autonomous vehicles and smart cities, smart homes, things like that as well?

[00:28:53]>> Yeah. So the the air squitter also has um GNSS inside of it. Um and so we know um with some of the networks that that are already out there that GNSS data is quite valuable um and quite a lot of people need to use that. So for example, GNSS data is about 5 m 5 to 10 meters in accuracy generally for a typical GPS device, which is fine for some applications. You know, if you're navigating from Florida up down to California in your vehicle and you want to follow the road, then it's good enough for that. But where you've got drones and autonomous vehicles, they they need to know what lane they're on or they need to know precisely where they need to drop off the package. Um because you don't want to drop off the package in your nextdoor neighbor's garden by accident. Um, basically to be able to do that, you need to have what they call GNSS correction data. And GNSS correction data is is purely just um it's it's basically uh removing the error from the signal by having a fixed >> differential corrections.

[00:29:49]>> Exactly. It's you've got a fixed station that's collecting GPS data. It knows its position really accurately because it's been collecting that data over a long period of time. So it averages that data and it knows now within a few millimeters where its position is. And then whenever it receives a GPS signal, it can work out what the error is and send that to a nearby system. And so these jet vision sensors provide that have that capability. They provide that they have that correction data available. Um so we can also extend out to that as well. So this is this is this is a key point. Um we're also seeing a lot of defense applications, you know, where you've got, for example, a drone that coming into the airspace, you want to be able to differentiate between a friendly and a hostile drone. So, is it is this something I should be worried about or is this something that I definitely don't want to shoot down because, you know, we don't want to be shooting people out the sky. We want to be shooting, you know, enemies out of the sky. So, you need to understand where all of the compliant aircraft are to then work out whether something may be hostile or not. Um, and so this kind of data is you can be used for for defense environments as well, just to provide that this is a friendly, don't touch them, they're they're okay. um and have that sort of trustworthy source of of what's good versus not what's not good.

[00:31:02]>> Now, I want to dive into some of the stuff that we really can start getting into scale. Of course, the aviation is important and there's a lot of data that's needed for that, but the drones is where we could definitely see things blow up. And Michael has a question around that. He asks, "Are there chances of a partnership with Amazon and Walmart?" And maybe you can get into how retail drone delivery, that market is developing in general. Yeah. So, drone delivery has gone through what they call like a chasm of despair, I guess you you call it, because uh people started building these systems. We're like, "Wow, these are quite capable. They're they're already able to do deliveries."

[00:31:37]Like the delivery was was doable eight years ago. The technology's been there for a long time. What hasn't been there is the safety systems and regulatory pathway to be able to do it legally. So, you know, if you want if you're happy to fly illegally, then I wouldn't advise it, but drone deliveries is not a problem that needs to be solved. that's already been done. What hasn't been done is how do you ensure that when you're flying a drone on a long distance without a pilot or a person able to see the drone and visually observe it, how can you actually stop it from crashing into things? How do you make sure that the helicopter that's flying through this flight path isn't going to be on a collision course with your drone and then you take, you know, you cause this catastrophic event that shuts down the whole industry? This this problem hadn't been solved. So some of the regulation that you're seeing coming through like the mandates for electronic consecurity uh so every aircraft having to carry a transponder on board. This is again this is one of the building blocks uh to enable this kind of safe operation to take place. Secondly you need to be able to build the infrastructure to actually coordinate these systems. That's where we come in. And then thirdly as well you need to actually generate the the ground infrastructure to be able to provide the the data and also build the hubs the drone hubs that will enable the deliveries to take place from point A to point B. So there's been a lot of work going on from the regulatory side.

[00:32:55]There's been a lot of work going on the infrastructure side. And now what you're starting to see is it all coalesce and come together into what I think over the next three to five years you're going to see an explosive growth in the in the drone industry. more specifically with Amazon and Walmart. We're already speaking to Amazon, so there's already conversations going on there. Walmart, I don't think we've spoken to those guys yet, but I'm pretty sure we're probably one phone call away from them. So, we're trying to focus on a on a subset of customers at the moment and and work with them to be able to work out exactly what they want, how they want the data presented, what kind of fields they want in in those data streams that they're receiving, and then building up those projects on a case-by case basis. And what that will enable us to do is embed into those systems and scale from there.

[00:33:39]But we're still we're still early, I would say say on the drone deliveries.

[00:33:42]We're seeing pilot projects, you know, across the world in in specific cities.

[00:33:46]So they're starting to scale out now. Um but yeah, over the next two to three years, I I I'm going to I expect sort of quite significant growth in that area.

[00:33:54]>> Well, I think this is an example of kind of what we're seeing in crypto in general. I mean, finance has tremendous regulation that overhangs and it can cause things to move a lot slower than the crypto industry would like it to to move. And it's the same exact thing with the aviation industry and drones is of course coming into that space. You know, there is so much regulation that has to be considered before these things that we know will eventually come to fruition actually make it across the line and actually start to impact the market.

[00:34:23]>> Yeah, exactly. and you've seen you've seen a few companies come and go and we've managed to stick around because we've got like lots of different applications that we can apply this technology. So, you know, we're having to be quite clever about our go to market strategy. We can't just be all in on one application. Um, especially if it's not being fully proven out yet. So, we have to we have our fingers in multiple pies. The neuron network can can integrate any type of physical system, not just these uh aircraft tracking sensors as well. So, you know, we're we're applying the same technology across a broad stroke of different systems. Some of the big opportunities right now are in counter drone systems, uh, funnily enough. And I think what you're seeing is, uh, a lot of governments want to have the counter drone systems in place before they allow the drone systems in fully, if you know what I mean. So, they want to protect the public. You know, if you see a drone flying across a city, you want to know that it's a friendly drone and not a rogue drone that's going to do some damage or come and decide to fly into the wrong building that it's that it's not meant to. So, it's important. I think governments are are sort of prioritizing the defense systems first before enabling, you know, drones to be let free in the within our cities and and local environments. So, so I think for drone defense, you need to know, as I say, the friendlies and the foes. So you need to be able to spot both. Um so being able to combine this together allows us to accelerate the network, build up that complete airspace picture that people can trust and then that becomes the basis for then how drone deliveries and other different civilian applications actually get get realized.

[00:35:55]>> Well said and well covered. Now I have a couple questions here from not Jack.

[00:35:59]First he says, "I admire James' commitment to not issuing a token until Neuron is sustainable. What are the pros and cons of doing things and I quote the right way?

[00:36:10]>> Yeah. So, it's really hard because like everyone you know four or five years ago was like saying launch a token, launch your token. Um, but we had quite a few advisers like telling us like don't rush into this because it can be something that can destroy your project for you and and I think I would definitely recommend people to to do that. Now, obviously, you know, the downside to that is that people become nervous. they become a little bit jittery around you not having a token. People are wanting to deploy sensors. Um, but they're kind of expecting something in return uh for for doing so. And obviously then that sort of creates a a sort of a an overwhelming feeling of of trustworthiness in and belief in your project. But you know what we want to do is to bring people on board into the project who believe in what we're trying to achieve. And ultimately the the commercials will work out when the the business works out. So you know at the point where we we're bringing in revenue and we're bringing in revenue in in large at large scale then that kind of makes sense to then make that that next jump. If we do that beforehand then and we get the business model wrong then ultimately we end up killing the project. So it's really important we have the full end toend chain defined and clear before we start sort of pushing the token too hard. Um but we are hoping to do get that done soon. So, you know, we're starting to see the the business model being played out and uh proven in in real world. So, we we once we've got that kind of fully validated, then we can start sort of doing the rewards um and doing that properly. We we may actually even start off rewarding people um in other ways initially before we can go and actually implement the token. So, we're thinking about doing some uh USDC direct payments to to users just because if we win data contracts, then we want to be able to share some of that with the Cook community. And so, that would allow us to do that. I think that that is a good starting point. And then we roll across to the token when the timing is right.

[00:38:02]>> Well, let's get into some of the economics around running one of these sensors. I believe the sensors are about $900 a piece. That doesn't seem to be preventing anybody from getting involved, and I'm really impressed with that. So, it's kind of a kudos to your your vision of what you're creating. And I believe right now we're on test net.

[00:38:19]We're going to be moving to mainet hopefully within the next 6 months. I believe every 2 minutes you're sending a heartbeat with data. There might be additional data on top of that. That's give or take about 60 cents per day. Uh and then I I'm assuming that once you do have a token, you're going to be paying that out to uh incentivize people. And like you're mentioning here, there could be those USDC payments for anybody else out there who is paying for those uh data feeds as well. Is that correct?

[00:38:46]>> Yeah. Yeah, exactly. Like those numbers are roughly right, give or give or take a little bit, but but you're in the ballpark. Um but yeah, we're we're doing heartbeats through the network. Um we're sort of going to revise that probably when we come to mainet just to make sure that like the you know the pros and cons. We we you you want to have regular heartbeats, but obviously there's a cost to that as well. So there needs to be a balance between providing people with a regular update on whether a sensor is online or offline versus the cost of doing so. So there is a balance here to to make, but I think we're roughly in the right ballpark where it is at the moment. It's affordable on a per sensor basis. Um and it provides you with a very quick update. So if a sensor goes offline, you know within a minute or two that it's offline, which is which is plenty good enough. And ultimately when a sensor does go offline, you still get the error u messages that will come through. So you know any customer who's who's connected to a sensor as soon as they become disconnected they will report an error through uh through hideera to basically prove onchain that that that system has gone offline for whatever reason. So these updates can also happen quite quickly from that that process as well. So ultimately what we're trying to do is to prove the unit economics um for the things like drone delivery. Um but we've we've done it all on paper. It all works on on things like that. But now we need to prove it in reality.

[00:40:05]>> Understood. All right. So I have another one here from not Jack who said, "Project Diana seems to be connecting Neuron with valuable resources. Can you share how it's going? What are the costs and benefits of working with that program?"

[00:40:18]>> Well, it's been massive for us ultimately. Um, and we see it as like a huge acceleration of our goto market strategy. What we've seen is like you know a lot of groundbreaking technologies have in the past they've produced you know they've come from a defense background um you know things like DARPA for example invented the internet so you know some of these uh programs have have come from very uh defense related backgrounds or defense funding and really why do we use that?

[00:40:43]Well defense what what defense does is it basically tests technology that's right at the cutting edge of where things are right now. Once it's been proven in a military environment, then it generally comes back home into a civilian environment and used for for more friendly things. You know, a lot of the >> GPS is a great example.

[00:40:59]>> Yeah. Ex. Exactly. Exactly. And um you know, these technologies are generally quite groundbreaking. And we're basically solving that problem within defense at the moment, which is the clash between interoperability and sovereignty. Everyone wants to be interoperable with the with other systems, but they don't want to give up sovereignty of their own systems. So, how do you coordinate two systems that want to connect to each other? You need a third party to coordinate them. So, who owns that third party? Like, who who owns the server? Basically, that's that's the big question. Who owns the server? Um, and nobody everyone wants to own it themselves, but they don't want to concede it to someone else because otherwise my system can no longer coordinate with any other systems without your without your coordination uh layer. So, that becomes a bit of a problem. So what we what we said is well how about everyone runs a coordination node. How about everyone runs one of these coordination servers. Um so not not everyone like every single system but anyone who wants a sovereign capability can run a piece of the infrastructure themselves. These are synchronized through uh through consensus and we use the blockchain to be able to do that through Hadira. Um and we can also introduce if there are say for example military or very high security applications we can also introduce private chains as well into that layer. So they becomes the synchronization layer and we can see that with things like uh hashere which is out there which is a really exciting product from uh from hashgraph and so we can sort of see this public private sort of interface happening. Um, and what we're what we're essentially doing is basically federating that across lots and lots of people so they can own their own piece of infrastructure but be connected into other people's. Um, and this really is what solves the coordination problem of how do you interoperate without losing sovereignty as well. Be be part of the infrastructure yourself.

[00:42:49]>> James, this next one comes from the HAR bull world. It's something that a lot of people in Hideair are going to be really interested in. It comes from Oak 1337.

[00:42:58]He said, "James, I'm a current beta tester with 4D Sky. Recently on the Discord, Nakolo said they were testing and opening the floodgates on the consumer side and shared a screenshot of over 61,000 messages per second. I'm wondering if things are full throttle like that 61K screenshot, what does that translate into for the Hideera mainet in terms of TPS?" So now James, let's get into the potential scale here for Neuron and Hideera. Now I've seen I think towards the end of last year you only had about a hundred uh different sensors deployed. That has increased to 400. You have several hundred more that are ready to be deployed that have already been sold and you're selling more every single month and obviously there's demand from the customer side as well.

[00:43:48]Let's just talk a little bit around what the scale potential is for both Neuron, for your network and for the Hideera network as well.

[00:43:55]>> Yeah. So, you know, we see a future where Neuron is connecting pretty much every physical system out there. Like this is this is the end goal. This is the this is the moonshot goal. Okay. So, you think big and you know if we can achieve half of that then we're in a very good space. basically any system, any sensing system, any autonomous system, um any aector or robot, um any even any kind of like actuator that's like triggering, I don't know, a valve or things like this. These can all be connected in to the internet. Um so imagine like you you how you browse a website today. Um you browse through your you know, you type in your URL and that basically guides you to that person's computer that has the website on it. And that's how it works. That's you've got like some kind of way of navigating through the internet to get to the computer that holds the website software on it. Um and that's what allows you to view it on your own computer. There's no no such system for physical systems at the moment. So if you want to access a sensor, you have to go through someone else's website um who's probably built a vertically integrated centralized network of sensors. That that's fine, but it adds a huge amount of vulnerability, adds latency, adds all of these qualities we don't want. Now everything's moving to the edge now. Um this is happening in defense and in particular everything is moving to the edge. So a drone is an edge system. It's not it's not centralized. It's it sits at the edge.

[00:45:20]An autonomous vehicle is an edge system.

[00:45:22]A robot is an edge system. You're seeing all of these physical devices. They're all edge systems. So we want to coordinate these edge systems with each other directly. We don't want to have to have all of these this middleware in the middle that's trying to limit speed limit uh or increase fragility and all of these other things. So when you look at the scale of this well every sensor there are millions of sensors out there today. There are millions of autonomous systems out there today. There's probably tens if not billions of actuators and valves and things that or signals that are on, you know, train signals and bus routes and like you just you can experiment >> switches or tolls and everything else.

[00:46:05]Yeah, >> exactly. All of these different systems basically we want to be able to connect internet connect them. They want to be network connected. Now, we can network connect everything through these central platforms, but we've already discussed the problems with doing that. Well, we're moving now to an agentic world where AI needs to be able to interact with these things when, you know, in a permission and safe way. We don't want to, you know, we don't want to unleash the Terminator quite yet, but but ultimately these systems need to be AI accessible and we we're essentially providing the layer for doing so. So, you know, when I'll let let other people do the maths, but you know, you're talking about millions, if not potentially billions of systems around the world.

[00:46:45]>> Well, that's exactly what we want to hear. James, I appreciate you giving us time, not just last week, but this week as well. Is there anything else you want to touch on before we let you go?

[00:46:54]>> I think um I think the only last thing I would talk about really is the coordination layer, which um is going to be released very soon. I've seen the the prototype of it already. It's ready to go. It does everything that we want it to do. We're we're just reviewing that and um adding some other bells and whistles to it. What it will allow you to do is to basically build an agent card for your system. So if you want to integrate a new system into the network, you can literally point your code, sorry, your code, your claude, our our code repo and you can build a node for your whatever system you want and using AI. So it has all of the skills, all of the capabilities to build a node. You build this node, you deploy it onto your onto your system or next to your system if you want to, you know, plug a Raspberry Pi into it and now that can be network connected into the neural network and people can buy that as a service from you. So say if you're building deepin networks, you can connect all of your deepin infrastructure into Neuron. We've actually signed an LOI with um another deepin who's going to be doing some integrations with us very very soon. Um but you can also um also integrate this now at the at the client side as well.

[00:48:01]So say if you want to have an AI agent and you say, "Hey, build me a flight tracking application using Neuron." It will then search for the connections to the sensors, build all the connections in, and then generate your software without having to actually do any of these manual integrations yourself. So, what it means is now we're living in like a vibe coding or AI assisted coding uh world is that you can just tell it what you want it to do and neuron use neuron as the infrastructure for enabling you to do it. So, if you're building a real world application, just speak to Neuron and it will tell you how to do it. Well, James, like we started off today, you know, I appreciate your grandiose vision, but even more so having the dedication to actually working so hard that it it comes to fruition and it seems like we're getting really close to that point. I want to thank you for giving us some more time today and I want to thank you for building on Hideera.

[00:48:52]>> Thanks very much, Brandon. Always good to speak to you and uh yeah, if you if you're interested in a sensor, check us out at 4Dsky.com and we've got plenty of information on that. So, thanks very much.