Okay, I hit Recording Progress. You should see it pop it up in your screens and say yes, that you agree to be recorded. Welcome everybody to the 7th of March, 2024 supply chain and trade finance hyper ledger special interest group. Looks like having a number of people online live here today. So that's great. Thanks for joining. And also, we're glad that you're if you're watching this on YouTube. After the fact, and hopefully have some good stuff here for you. We're not in the interest of keeping the technology smooth. We are. I'm not putting up the all our welcome kind of hurt. I put in the chat here. You can click on the link here. The link for this actual session and go to the general meetings from our. Wiki page. So just get started as always are welcome. We're glad everyone's opinions, thoughts, ideas here. That's great. This is open and because of that open is also from an anti trust concern. Please do not share anything that is confidential or that nobody should else should know about here since this is an open session. So with that, let's see here. We have a number of, let's see, that if you haven't had a chance to listen to Lee in camp from ever ledger from back couple weeks ago. That's up on YouTube. You can go ahead and listen to that. And I can't remember who or who do we have in two weeks talking. I can't remember. Let's go look through finance. Through finance. Okay. So kind of a trade finance kind of story that'll be odd talking in a couple of weeks. So with that, let's see here. Jeff, I'm going to turn it over to you. Just going to Jeff and, and I guess I should, I should, before I turn it over to Jeff here. Sorry, Jeff, I jumped the gun. We've been thinking that we wanted to have a little bit more technology component to. What does what the special interest group brings to the table here and the good news is is that Jeff here has more of a technology background and either myself or Alicia. He can actually still code or our coding days are beyond us. So in this case, Jeff has put together a nice little demo of supply chain trade finance with digital twins. So we thought it'd be very interesting for people to see and And maybe this can be a basis or maybe even better a springboard for future work for not just the folks that are listening today, but also others as we go forward here in 2024, 2035, etc. So with that, Jeff, thanks for doing the work to build this this little demo here and some of the ideas of actually a Using blockchain in a in a digital twin environment and seeing how some code and some things actually work underneath the covers. So with that, I'll turn it over to you. Okay, thanks. I just a quick, just a quick check. Does somebody ask someone I just heard somebody Oh, nevermind. Okay. You can hear me. Okay. Yes, I have something I have trouble with this brand new microphone. So some alluded to yet. Today's presentation is going to be on supply chain digital twin. And there is a mock up of a blockchain upon a mock up blockchain that I wrote in Python. I actually wrote it for some Other folks to demonstrate NFTs and an artist that I know is interested in NFTs, but this is also a blockchain. So It's a Python program and I will get a little bit into the technical aspects of it from an overview. I won't go down to the line code. I think I can't see who was all on this call, but You'll get a two flavor flavors, but the crux. This is going to be about supply chain digital twin and I think people are familiar with digital twins and they're often talked about in the frame of mechanical equipment or a process Like an oil refinery where they have taken a A modeling software. Let's use a jet engine as an example. This is where you often hear about supply chain or sorry, digital twins is they will put the put the jet engine together. They do studies on it. They look at where and tear their expectations are it has so many life so many hours of before needs to be Maintained and so they will put that together and they'll not and they'll put that in some form. It could be software, maybe not software. And on the actual engines themselves on the planes that we all fly on. They'll have devices on there that are out that will then give out information to that Piece of software that says, here's the actual wear and tear on this engine engine such and such or it could be another piece of mechanical equipment and What they're getting then is what's the real time effect and use is it mimicking what we expected. If not, maybe the maintenance on that engine needs to be moved up on a schedule. So a lot of mechanical stuff, a lot of process units so forth and refineries food manufacturing plants use digital twins, even some Farmers use them because they again, they optimize what they think they should see and they get real time data that comes in and it tells them whether or not they're accurate or they have to move around schedules. Supply chains also though can be thought of as a digital twin and that's now coming out more in the literature. Where you can mock up the entire supply chain, make the digital twin optimize the the time frame, optimize the capacities that you see in the supply chain. And then get real readings that come in from devices and so forth or manual entries and they can see how the supply chain is performing. I feel like at the screen. This is what our presentation today is going to be. I'm going to give information about how the digital twin is put together. Some of the technologies that are used. We're going to use a company. We're going to call it a fictitious company, although this actually happened. So there's, I took a situation with supply chain and I changed it a little bit. But if you look at the screen, I won't go through all the bullet items, but it's going to focus on what a supply chain digital twin looks like. And in this case, well, I'll talk about it in a minute, but this is a supply chain that needs to be produced by a company who has an opportunity to purchase something and sell it. So there are supply chains that are a circle where there's planning, production, distribution, sales, forecasting, and then it goes back again to production and it's circular. This is not a circular. This is a little bit more tougher for a company to do. And again, this is where digital twin can come in and help a company understand a small supply chain for a particular instance, how well it's performing. Again, I got a screen here and I have, I took some that you can see the reference on the bottom about what a digital twin really looks like. And I talked about some of this already, but again, a digital twin will replicate the assets. So in the case of a supply chain versus a compressor or an airplane with different parts, supply chain has got components that has trucking firms, it's got warehouses, production facilities, it has sourcing. These are all components of a supply chain that is similar to components of a physical device such as, I go back to the engine. So they do correlate to two degrees supply chains that have the planning aspect to them, and you'll see that in a minute. So discussing here is one of the advantages of using blockchain technologies, you know, and when I say blockchain technologies, I'm talking about crypto payments, smart contracts, different different components that we're familiar with with blockchain and I'm listing them here. So the technology of your fabric is the blockchain technology, of course that does provide the capabilities that you see in these bullet items that does have interfaces to AI. As a matter of fact, the software, my desktop software, I'll show you in a minute, also has interface to AI, but the smart contracts and also something that we're going to touch on is about trade finance. For example, what trade finance does in a supply chain, which is key, especially for mid to smaller companies. But you can look down the list there and see, these are always advantages of a supply chain that can utilize a blockchain. There are many supply chains out there that do not use blockchain technology, they are ledger based, they are their in-house legacy systems. They do not have the advantages of, first of all, smart contracts, which can do partial payments, can do cross-porter payments. That intelligence in a supply chain is lacking when you don't use a blockchain technology. So we're going to demonstrate this. Again, we're going to use a fictitious company called AJ Coffee, which sources, and again, you can apply this to a lot of commodities, especially, but this is a company that has opportunities that come up once in a while to purchase rare commodities. In this case, it's a unique coffee grade that's come available on the market. This is, again, not part of the supply chain. It isn't a way we're not going to model that, but they've got an opportunity to buy a very rare coffee that's in high demand and luxury hotels, businesses in the U.S. They've got customers that are craving for it, and so they have their hands on it, but the coffee has to be collected from the producer. It has to be in the United States, ready to go in a warehouse at a certain time frame. We'll see that time frame. This is where, when this occurs, a company such as this AJ Coffee, there is not a supply chain in place right now to do this. So they have to construct that supply chain quickly through contracts, through technology. It's almost a one off to meet this one high margin coffee that they're going to sell to their customers. So reliable supply chain is critical, the ability to track what's occurring because there's so many moving parts, anything from farmers ability to load pallets to trucking in Ethiopia, trucking in the United States, ocean vessels, warehousing, all those pieces are needed on the contracts have to be signed so that that coffee arrives under certain conditions, warm-up conditions, not spoil it. It's the U.S. for sale. So the blockchain technology that's going to be using here in this digital twin is going to employ the blockchain itself, IOT devices to enable that to happen. Absent that there's no real time tracking of all the issues that can occur, whether it's weather, whether it's traffic conditions, problems going across the ocean. And so I'll show in here how the digital supply chain twin can assist with that greatly. Again, why, so we can talk about supply chain digital. But why showcase what a blockchain looks like. I think a lot of people are familiar with the blockchain. I don't know how many people on the call have seen a blockchain, whether or not you've been out to Ethereum I.O., or you've been out to Bitcoin's blockchain. We'll see in the demonstration, we have the slide deck. We also have a running program that will show you a blockchain in action. It's a desktop blockchain, but it is getting feeds. And you'll see the fields that are involved and gives you a good idea of how smart contracts actually operate in the blockchain. Again, what the fields of like fields and blockchains are very similar, whether it's Ethereum, Solana, Bitcoin, the fields that are used to store transactions are very similar. And those are key in this demonstration because you'll see how IOT readings come in and so forth. But that's a real key here is to be able to give a visual of what occurs on a visual twin supply chain. Again, it doesn't have to be a blockchain, but you'll see a huge advantage to having this blockchain. It can be permissioned, it can be permissionless. That would be up to the vendor. What are you at this point? Does anybody have any questions on digital twin supply chain I haven't covered? If not, I'll move on a little bit to keeping in mind the time a little bit into technically what you're going to see on the screen. Hey, Jeff. This is a couple of questions I just want to make sure. So in the in the scenario you're setting up, I think the key thing I heard is that AJ coffee just they got lucky and they found this source of coffee beans and now they got to figure out how do they get it from here to there kind of thing. Right. And so this firm scours the planet, coffee growing and cocoa regions to find rare coffees. And so these are legitimate copies. There is a topic called geisha from Ethiopia, which I think is $50 a pound. There's copies in Panama that are $10,000 a pound. So these are very limited. It has to do with almost like wine growing conditions. This company contacts organizations, farmers one on one. And when they do get an opportunity to get a certain lot of it, then they look at their customer base. And they're interested. Yes. And they now have to put a supply chain up depending on where in the world this is going to occur. There's coffee growing regions across the planet. So this could be again doesn't even have to be a commodity but there are situations where you have running supply chains and you're producing a commodity or something and you're planning it, you're selling it. And then you're doing more planning. These are one offs. And so there's 12,000 pounds of coffee available. It's in a particular farm in a particular place in the world and they have to get it to a certain place over time frame and they have to now construct a supply chain. Yeah. And I guess the next flavor for that are kind of taking that is the key point, I think what you're trying to say with the digital twin is that this creates a model of what that supply chain could be. Yeah, I'll get into that in a second about. Yes. Yeah, there you go model. Okay, cool. Yeah, and you'll see this is this is the model that'll be produced and then it results into this and then we'll see that in action up to the blockchain. Beautiful. Beautiful. So this next screen here is the actual blockchain. It's just a power point but we'll see this running. Again, this is a blockchain. It's a little bit different than some of the commercial ones because I'm showing more information on this blockchain that you normally see for example over on the right the blockchain itself when a new block is added you don't really see that occur, whether it's on Ethereum or fabric, but I'm giving some information what's going on behind the scenes with some of the data, some of the data fields that occur, and you'll see how important this is when we start running it when you start seeing things like smart contracts. Jeff, when you say when you say on the right, do you mean the pink block? The pink block. Yeah. Okay. Thank you. Just a little bit trouble seeing it because all the stuff that's scrambling on my screen for the presentation. So it's the pink block. I'll get into that in a second. But this is what was created in Python. And so this is this is the screen in the front. Again, I don't know how I'm going to show the components that were used. Those are menu items. And again, this was there are wallets on here. There are NFTs you can tokenize. Our assets things like that with this blockchain I demonstrated to somebody that that's interested in doing that. So this is actually been used more than the supply chain, but it's been altered for this demonstration. Because it's a desktop, I'm just going over some stuff real quick. The blockchain is actually kept in a file, which are some smaller blockchains out there in the world that do use files for their history, rather than database. I'm a certain why but in this case this is a small blockchain so there's JSON files that are used and you're seeing a picture of the blockchain up on top wallets and the different currencies that are in the wallet. So if you're interested in Python out there, what components of Python were key to build this one's for dictionaries. It's very well into blockchain instruction, and then lists of dictionaries without those data structures and be able to be 10 times as much effort to try and create a blockchain. And one of the things you can see over on the top right is fields that go into a transaction of blockchain that is very common if you always wonder what the theorem is storing or the Bitcoin is storing if you see up and there was this transact essay, that's a dictionary. That's actually a list of dictionaries but you're seeing all the addresses, the values, things called if you don't know what the gas is, it's a cost to run it on here, the coin that was used and then some of those other fields you're seeing down there are some of the data you're going to see. So you haven't seen where what kind of data goes into a transaction of blockchain. It's very similar there are some that have a little bit difference but not a lot. And then we talked about JSON. You're programming in the 21st century, you have to know a lot about threading. And so threading is running on my desktop right now, but it stopped. And so, when that thread runs again I'm on a desktop is closed my whole computer down but I have to read a lot of things in to run that blockchain so that's kind of little technical. When you're on the bottom that indicates the fact that when you're on a laptop and not a server. The threading doesn't exactly work this one would tend so, but again I've got threading in there someone was curious about some of the data that comes in as all, you know, than threads. The graph interface again is a is a commercial product that's distributed for free. It runs the software once the graph interface starts up. You're actually under control the PYQT five. You know I just got some information about how it's imported and then it's a class so it's good. There's a constructor that starts that up. And then, of course, Python has classes and objects so the blockchain is a class. You can see some of the functions in that object listed there which again are very common to blockchains. And then the wallet which I'm not going to show in this demonstration but the wallet is also a class. There is a way of sending currencies to people within this program. So that's just my little bit of the technical aspects that we want to pour the code out on top of somebody but just some of the constructors and some of the ways this was built. Any questions out there at all. I heard a question that's okay. So we're going to do is on. This slide is going forward is a demonstration of how this supply chain digital to work with this size firm as a opportunity to buy something very expensive copies from around the world. And so one of the things that you look at supply chains and this covers all supply chains is. If you're going to develop a digital twin, there's things that you have to do up for one of them is you have to look at where all the components where the assets of that supply chain. If you look at an airplane it's got a lot of different parts. They call assets the landing beer, the tires engines will supply chain the components and assets are things like in this case, the farmer farmers warehouse their acreage, the loading operations truck lines. So ports and Ethiopia ports in the United States, the ocean lines, anything involved transporting that coffee. It's final delivery. This is considered a component. So you go through and look at all your components and then in those components are supply chain processes now. One of the things that I don't have on here I was the ending in the end was, we're going to show trade financing on this and how that works. That would also be the loan, a thin tech company would actually be considered an asset so underneath the supply chain processing to see about securing the thin, thin tech loan for that coffee and that again is a process also within all those assets. There are things that in the supply chain I think of as rates, how fast can the coffee be loaded may not be one day depends on the kind of crew they have depends on the weather. Of course transportation, how many hours a day can they drive what are the rates or the routes and so take all the components and assets that are in the supply chain. So when you add the processes around and you start producing what we see as a digital twin. And so from the work that on the slide you're seeing here what you end up with is something like this part in the colors. This was used for something else and so it's just, it was a change over some of us I'm using also as a demonstration but what you're looking at is actually all the assets involved in the supply chain. So the top is, that's a, that's a real farm in Ethiopia that produces that coffee, that rare coffee that and so you have your contracts across these firms that you see. The ocean shipper isn't really shown yet but there's a reason why then you see the capability so when you're doing a mock up of the supply chain and you're saying you've got a delivery date of end of March and you're in February. The mock up portion of the supply chain is can we actually get that coffee to that customer or customers in the timeframe that we need and so what you have to do in your contracts is you've got to go back to each one of these individual assets and what is their capability? How long does it take to load coffee? How long does it take a truck line to get from Ethiopia? And you go out and look at contracts, who's the best class at this and you look at the risk around it. And you end up constructing that supply chain. And what you end up with is something that looks like this that I think we've all seen. Here's the chain of transfer of that coffee from that farm into the warehouse. The avian warehouse is an actual warehouse I see in the spelling down there. It's an actual warehouse of the port of the war. And so that's where AJ Coffee stores his products. There's operations that occur when it's bagging, grinding, so on and so forth. And so what you're seeing here is the classic supply chain. Now if you have this all mocked up out on paper on a PowerPoint, you can see here all the way down to the bottom and go back up here for a second is we'll follow at the bottom. You'll see that based upon the capabilities that we agreed upon. For each one of those assets or suppliers, we can do this, maybe with some risk involved inside of this, but based on capability of each. It's a go and so you tell your customers, yes, we can do this now. Once you have this all in place. By the way, I'm going to backtrack this one does have some of the risks that's involved in some of this and we'll see some more risk come up the demonstration so AJ coffee what you can do is decide utilize a clock chain by OT to track this to see is there any of these risks that pop up or anything that happens that we mediate what risks we have behind it and so automation is the best course of action so what I'm going to do here. I'm going to flip over and this is the Python program so I'm going to start this up. What you're going to see now I have I have interjected myself into this where I've got the stopping to explain some of the course of action that occurs and some of the live data that comes in so what you're going to see on screen. And now, these are blockchain transactions of these don't apply to us the ones that do apply to us. We'll see in a minute are we'll see the hex addresses and I've got some dots and those are the ones that you'll see. So, imagine this is all been this contract have been signed. We're ready to go so AJ coffee and I was going to start using this blockchain technology so the first thing that's occurring up here is there's a request to the AI that agent AJ coffee uses to go out and find financing to and so there are fintech companies that will do this based upon in this case of coffee. firm that's got money in a warehouse and this is often called warehouse trade. So, warehouse received financing and in two weeks there'll be some more detail on what this actually means but essentially what's happened as a company called so by which is the real company has looked at AJ coffee and said their risk profile is good but an asset in a warehouse coffee that they're going to leave in place until this is done and so AI has gone through interest rates, capabilities of fintech and a selected so by is this is where we're going to get our money from we're not going to go and get our assets and so on the bottom you're seeing $200,000 so a transaction has gone into the blockchain so far has transferred to crypto $200,000 into AJ copies wallet. So that's where we are right now. We'll close this. You also see some screens here and this is good a bit more data to each transaction that's you will see occurring. I was checking the time you're sorry. And it's 9% financing on with an expectation of 12,000 pounds of this coffee that's this company produced. And so this is the case where AJ coffee is right now they've got the money. Now they're talking to the farmer. And what we'll see in here is ledger and so in a blockchain transaction this is what they look like you can see the dress is also a little bit on the fields over here you're seeing these are the transaction hatches that end up being put together and then hatched again into a block. But here is a ledger agreed to purchase this copy from see if the open top for 13 dollars a pound that says this is Stanley grown and the farmer has an SD certificate which they will transfer over. So, again, if the blockchain is open. And of course this is sped up with me mentioned this may go over a couple of days but here's the contract that's been put in and there's a little bit demands sort of the case is required. There's a smart contract that's going to put into place and the smart contract that what's going to do is smart contracts come into blockchains as transactions whether it's fabric. Ethereum and so what you're seeing up right now is a smart contract just been just been thrown into the ledger into the blockchain for this cost 163,000 dollars roughly that farmer for 12,600 pounds of coffee and in that contract of course our dates and so it's going to three days to load it. It's going to be paid as it's loaded. IOT devices will determine how much has been loaded per day, and one third of the purchase prices will be held out until it's completed in three days and there's a certification that that is the copy that they say it is and one of these are going to see on here is a contract is going to be signed to a company to do a certification and block just got formed because of the transactions. Okay, so you just saw block it produced. And it's a small block. I've got it so it doesn't cash for. But the transaction across is the transfer the ESG certificate from the army farmers and so coffee is coffee is now starting to be loaded and AI has popped up and said well that we have a problem and so I'm going to flip back this for a minute. So this producer has a capability to produce 5500 pounds of coffee to load it into a container and so they have to average more what over 4200 pounds of data meet that three day contract. What's happened here. IOT devices is the first day they loaded only 3,154 pounds. So as come up and said, we have an issue. We're not going to meet the three days at this rate. It's almost happened is AI has transmitted requests to the farming co-op to say, we guarantees we need that we're going to meet the three days we have a truck coming in and we want to go to the merge charges. We have this massive supply chain. What do we need to do here. And so the coffee company farmer has agreed to put more manpower on there to meet the three day requirement. The thing AI has done again, this is part of training sets of AI has looked at the weather forecast and for the next day and it thinks there's a possibility of a rain. And so, whether then wait to the end to find out, we didn't meet the three days with IO and AI and blockchain in between. It's popped up immediately and said, we have an issue. What are you going to do about moving more popular next couple of days and so what we'll see down the bottom here and it closes as this is the partial payment for just 3000. The other problems that have not paid them. All the contract when we get paid as they get loaded. And so, the loading is occurring. We get IOT is tracking it and now they've loaded up over 1420 pounds so it's even the last. Another condition related and so we're not getting squeeze a little bit and so it's being monitored this loading and here we've got 5400 pounds loaded now so the additional status come in. So we've increased the loading and I can't see on the bottom, but it's not in yellow. We'll see more detail and I can't see about what's actually occurring on these transactions and here. 2500. 2600 pounds were loaded. And as a result of 1650 calls have been loaded in the container and it has met that 224 date, which was here. So through that interaction between AI, IOT devices and again the AI was a supplement of the devices way up front and showed that there was going to be a problem loading week at three days. And so quick action was taken. This entire transaction could have gotten with the vendors could have got killed right there. It didn't mean one thing they want to. But up front is line here's by with the final payout. So let's go on those ledgers, as you see this go. I haven't actually stopped so you can see some of the payment so that's that one. How about is ocean liners will come every couple of weeks. And so you have to meet that otherwise your sales are over. So you just saw come up with a contract for the port. I think it's pronounced to be the biggest port and there's a contract and not to hold the coffee. Transaction which is a digital bill of lighting for 12 hours to a public on metro lines and so metro lines is on site they're loading that said one big container on that coffee in a wrap container. The contract is going to put up with them again that's these are all ledger transactions in a blockchain. Again, a normal blockchain would run much faster than this but again I'm slowing it down for this demonstration. So we're at a point in this sense of supply chain where the truck is now got and so it's back here. We're going here. Here's the, there's our capability so there's a distance to the port, these 21 hours they're going to eight hours a day. And so this is what we're tracking through here on the next out devices so I have to device is actually on the container. The two reasons what is the distances travel also there are coffee, this is a commodity so they're humidity and temperature conditions that they must meet. So, they've got 96 kilometers and they've got 202 kilometers over the next day, and they should be less was a traffic issue or break down which has some risk on, they should make it to that. If you open for there you see they have on 226 that's the date is intended so we're still on schedule. It hasn't met the temperature and humidity requirements. So they will now be paid. You'll see the transaction down the bottom. So that ledger entry and not only is this black chain new ability really showing through here in the fact that these transactions you cannot change but it's showing timeframes and this beautiful. I just, just a new, a new ability of a black chain really senior because this is all people contracts and so forth. So, the courts got the copy to take it off the truck. Again, there's a storage requirements or they're showing what that is. Now, it's waiting to be loaded on an open liner. So, the transactions come in. This is our war block chance with new blocks are created. So you can see the contract is overseas shipping from to Newark. It has popped up again. So, this is very topical so the original contract was that with a company called Mediterranean shipping company. They went up and said, for risk that's things that are occurring in the Red Sea right now with the loss and so forth. They don't trust this mentoring shipping company AI with all that information has says Merced is the least risk if we're going to continue to go through this Red Sea is, which is the only way it's going to meet that date requirement in New York can't go through around the heart of this switch it over to Merced. They seem to have a much better handle on when to go across where they go. We believe it's litigate center so AI has actually come up and said well let's do a different shipper based on data we have recent data. Some analysis AI has done and let's use Merced Merced shipping for this so what you're seeing down there you just saw the transaction went into Merced at the bottom here. It's about another $1,600 a shift to Merced, but the decision has been made to send it to them so Merced has got it the copy right now smart contract was put in now to Merced. You can see some of the detail where it's going to go the conditions across again a smart contract. This is smart contract entry. This is the storage contract. You're seeing here that in New York when it arrives. So before it gets there, the contract has been was already put up and the transactions were not put in yet. And so it's one thing you want to make clear is they're not doing this on the fly they have these contracts. What we're looking at is the ledger entries that go into track. What it is, they put a permanent ledger transactions as far as what's current for this entire supply chain. So, IOT is now indicated that our coffee is moving so the warehouse has got it they're moving that coffee. So here it is now it's on the dock so that's why it's gotta it's gotta get to that dock by certain dates so that the vessel can pick it up. Now Merced has got it you can see is this container has been loaded on the vessel. We're all good there. March 1st, we missed March 1st, then it's two weeks later and we have real issue. So, this is just a digital deal, the lane that comes in on the ledger. And this is stored on here and some of the gas costs and if you move gas costs when gas costs involve documents to get expensive on watching story documents and watching so you'll see IOT views are small. These gas fees are tiny, these are costs. Not much data with an IOT but when you talk about full ladies and so forth, they get expensive. So, we're getting we're getting now as IOT is coming in showing conditions in the container and some GPS coordinates of where is that ship so it's a 22 roughly 22 day transfer across the ocean. Obviously in this demonstration, I cut those out just to show that this is track humidity, temperature is tracked inside that that container that's holding all my coffee. And I just have a few more before it arrives.  So, um, There's one more. So here on the 23rd of March, so it's made the 22 days, made it to the Red Sea, and the containers being offloaded by MRS and it's now going into the warehouse freight yard, which is in Newark, New Jersey. I believe it's called the New York port, but it's in New York so we're still tracking it. Here's payment now to the trucking firm that's going to pick that container up out of that warehouse and move it across to this is the port warehouse over to AJ Coffee's warehouse for processing. So that's, you're seeing that contract go in. That's a full payment. And what you're seeing here is a coffee has now been loaded into the warehouse AI. AI component where they have this and related to trade finance is always looking for opportunities from a trade finance standpoint. Again, looking at marketing conditions, it's, it's mentioning that there's an advantage that maybe you want to borrow against the coffee. Again, it's a recommendation. There's no action. That's a career of AI is sending a sound again. Communications isn't just on a blockchain. It's for emails. This can be mobile phones. But I'm showing how AI is keeping high on everything that occurs. And given even recommendations out and good interest rates, maybe you want to continue to do more trade finance against some of the coffee gets sitting inside there rather than it just sitting there. So the trucker has pulled the container now from the warehouse and back in the US. It's a lot of a mile trip to go to this ABM warehouse, which is in this area called the Sunset Industrial Park. AI has come up again and stated, based on current traffic conditions in New York area. Let's reroute it. Let's take it. We know it's through now as long as it's going to route. Maybe road construction. Maybe there's some other problem. So it's come up and said, let's redo a route. So, so JB Hunt that we're going to follow this route. So that's been approved. The logistics. And the truck is moving. And again, we have you're saying it's kind of five miles. So far for 13 miles or if they were tracking this container. The truck is moving and we're cracking those conditions. So it's now gone seven miles. It's met those conditions. The IOT has come in and it's for some reason it's still at seven miles. So the truck has stopped on this new route. You're looking at this humidity. So AI is directed us into on this supply chain into another route, but yet this seems to be stuck at seven miles. It's still stuck at seven miles. But what's happened here, we notice is the container has gone off spec compared to what's written in the supply in the smart contract. The temperature has gone up to 20 degrees centigrade, 75% humidity while this thing is sitting there. Now this container has its own refrigeration and humidity control with an engine on it. So there's something strange occurring here within seven miles. So again, there's an alert that the truck has stopped. It has now made it to the warehouse. The humidity is high on it and the temperature is still high. So there's something that's gone wrong with this container. So it is getting better now. The humidity is high, but the temperatures come back down. And so you're now at the warehouse where it'll be offloaded. Oh, by the way, it's all occurred through the same day. So we have, so the warehouse is not collect that container. And so we are all still we have some flex in the time so you're still good. And so some things has helped us with the course was that at the beginning was the the request for manpower to load. And some of the things such as such as rerouting with Merck, that was a big advantage of AI. I think at this rate here, this is again, in the supply chain using these technologies is smart contracts and market smart contract has come up. Just actually put a transaction in the same we're not going to pay the trucking company JB hunt because the shipping conditions exceeded what we were told it in the outside of contract so the transaction and this is data that goes into transactions as it came into the world. They inspected it in the seals been broken in the container. We'll keep going here what actually happened here is the company is used companies use AI for a variety of reasons one of the things you always have to make sure you have been there is the proper training sets. Using AI what it did is has logistics in there. However, we routed that container into a very dubious area of New York. And so what actually happened is, this is information got back from the truck driver is that truck was stopped at gunpoint. There's a container on a truck going through a very nasty neighborhood nasty area. We broke open the container. So it was exposed to newer conditions, weather conditions, but also if that broken over. What actually happened when they broke that can open they saw what they saw there were coffee beans. We had no interest in the coffee beans. We just close the door on it and let the truck go. And I use this example because AI signing AI using a company lining up the AI vendor the cloud provider the AI provider. That's one function and that's the easy part of AI the hard part to see more and more so using AI is how do we use it. What data do we have to train that model. So AI was probably trained in different risk conditions and they have come up and said you know the traffic is a little bit more lengthy on the trip or still within one day. May use any more gas we can send it to some area that are higher premise to higher risk and so this is a case where a I won't say AI fail, but we need to really know how to use AI before we deploy because it could cause problems again it helped in most these cases. But there's an example of a problem with using AI and that's why we should such as a sort of almost at the end here so that this is just because he sees your IOT tag that container. They're going to put 2000 pounds of coffee bags again this is for their customers so I still running this coffee even though it's their own warehouse and 2000 sorry 2000 positive women for grinding the rest is going to go bags. And right now you're just watching you're watching now is as far as the supply chain pieces is this is done the blockchain is just running, but what you're seeing normally. We just keep popping up here is this is what they look like when you're only a blockchain you'll see data come in. These are high numbers on a purpose, but you see blocks in form. I don't think I have anything else here. But again just an example of how a. Digital tool works for supply chain that's quite complex because well moving parts and the fact that this is supply chain that is improving out. It's not running and running and running. It's something that they have to bring forward very profitable to get it over here. It's $14 with all the costs upon its retail sales 50 so it's high margin. It's worth the effort. You can see how effective the blockchain IOT work with an AI to make sure that this copy will be made in a very tight timeframe timeframe with. Conditions to keep the coffee beans. That's pretty much it. I don't think any questions anybody has, whether it's Python or. My chains. Yeah. Thanks, thanks Jeff. I'm going to turn this off. So you got, you got a little crime story in there also as you're going through a truck jacking in New York City or New Jersey, maybe I don't know. It is. It is something that happened. Okay. It wasn't actually coffee. It actually wasn't coffee or something else but. That is a real life example of the pitfalls of companies. Right now because there are two companies that have the data training sets available to take into all considerations when they get calls such as that so. But you did see the AI advantage to the I especially the IOT without IOT devices and blockchain ledger to view and accept these. Right off the bat, the coffee grower would not have met the port for three days. Now your risk is one day missing the ocean liner coming in and those ocean liners do come in only to the four weeks in that court. That's the biggest port. So even though this is a mock up of a such a transaction that it's a commodity.  Maybe in Mexico or Panama, your next opportunity. So it's a flexible supply chain in that sense. Today than other supply chains. You know, they're not easy to use out your devices, but if you're making a robust cell copies use copies example. You've got production farms, it's been 30 years to get planning. That's a play chain is right. Not seeing those are that easy either, but this is a little bit more difficult when you have to frame the assets imports every time in the process of keep checking back with their capability. Yeah, good. I got one question and then we'll throw it out there and see what last questions we have. One question is what's, what's the most work or where's the biggest set of work to set up all the digital twin, because I like what you did and in terms of you know all the detail of how things are moving along there, and how it could play out going to, you know, either using the blockchain to then enable something to happen, whatever, you know, whether it's going to, yeah, it's going to be similar to AI use, just going to be that back end so the digital twin is based off of this right here. And this contract, going out and getting the contracts. Again, I'm talking non touch, but getting the contracts understand their capability and can we meet this timeframe or what can we do to meet this timeframe because I've got very big profitable transaction here which is all that coffee thing to different suppliers. Putting that together. As far as once this is put together, these become just a name of blockchain. Let's take fabric. This does becomes not entries into feather. And so contracts go in. Some are smart contracts. Some aren't in the capabilities are put in. Then you tie your AI inside. Again, these are things that fabric provide that blockchain is now available. And so you don't have to build the blockchain.  And then you may have a person, again, you know, some of those IoT devices, you're going to see maybe once or twice a day. So you get a person, whatever role that you want to have and they can monitor the blockchain. I think I took the program down. You guys shouldn't have, but there's a way to search then on those transactions come in. There's actually some of the chain ID. So you can go and query the blockchain and say, give me all the transactions or the chain ID, you know, just listen for chronological order all those different transactions that you saw. So you can get up to date information on blockchain. But it was really just the back end. It's like AI, you have to do a lot of work on the idea to make work properly. And then you have all these contracts with all these warehouse now, depending on how big the firm is, but AI was critical on the ocean shipper and it was critical on this famous farm. So that's the hard part. Okay, good. You can sign up for a blockchain. You can build your own if you want out of fabric. Or use Ethereum, but a lot of people are using fabric. So, Callito comes to mind.  Any last questions here, we've got two minutes left if there's a last question. Going once. A couple things. I have actually loads of questions. Very impressive. Jeff, very impressive. Thanks. I'm wondering among many stuff about data, you know, like for AI. Where does it feed on? Does it. Only data on the blockchain come from oracles, right? Does AI or can AI get data from oracles? Does it scrape the net? What does it do? Yeah, it gets from Oracle so that. Let's see here. So, yeah, it gets it from oracles. The IOT, the IOT has to have a target so the IOT will have a target. But oracles are anything that the blockchain can pick up, right? I can pick up, you know, giving example right here. This is a quick way of working on Oracle. This has gone out now and it's just, these are up to the second prices of all the cryptos that I plugged in here. So this is an example of an Oracle. There's no different than what I just showed you on the screen here. It just goes out through API and closes the stuff and this is the latest crypto prices that are out there right now. So, the data comes through oracles. The AI feed itself, whatever technology you're using, open AI, like an example, you can, you're creating data sets have to be in otherwise it's making decisions on nothing. On IOT, the readings will then come in to that data source for that AI and that will come through as an Oracle. Okay, you're reading it to an Oracle. Good. In Christos, I know you said you had lots of questions here. I'd ask you since we're at the top of the hour. Jeff, you're good with getting emails, right? Yeah. Okay, good. So, and put your presentation up with your email on it so that people can get a hold of you and also it's easy to get them on wiki too. So, thanks for the questions there. Yeah, thank you. I'm getting a lot of questions around the Python from Lincoln. So people are curious about using one of the Python uses. Okay. So, putting it together a blockchain just to know. Python is that a lot of interest. So, good. Okay. Great. Thank you. Thank you. So, Jeff, thank you very much for sharing here. Good. Very good scenario. Appreciate that. Like the detail in the steps so that everyone kind of gets what's actually happening there within trying to build this digital twin of components and process of there. And then it's great how you added in here's the places where we're using the blockchain for value or here's where we're using AI for value, et cetera, kind of along the lines what Christos you were just asking there. So with that, let's stop again. Jeff's open for questions here. Maybe we'll see where this goes. If you have some ideas, you know, what we call we can springboard off of this uses for the future. To further demonstrate some of the value within supply chain and trade finance. That is awesome. So, with that, enjoy the rest of your day, whether you're listening live right now or listening recording and look forward to seeing you in a couple weeks when brew finance is going to talk. So thanks a lot. Thanks everyone. See you later. Bye everybody. Thank you. Thank you for this on YouTube shortly. Bye.