 Welcome everyone to our, let's see here, our April 2024 hyper ledger financial markets mortgage subgroup meeting. It's always a mouthful before we get started. I'd like to express our appreciation to the financial market special interest group and the hyper ledger foundation for their ongoing support and making this group possible. We do have, I'm really excited about having Karen Kilroy and I believe, or some weems, who's going to be talking about their book. Blockchain, Heather, excuse me. So, let's just go ahead and dive right in as always. Please note that this meeting is being recorded and under the umbrella of the hyper ledger foundation. So, we ask that everyone abide by the antitrust policy and code of conduct. The antitrust policy states that we avoid discussion of company specific products, pricing and projects. We don't make negative remarks about other companies or other products and the code of conduct states that we treat each other with respect. We don't discriminate and we communicate constructively. We fully support hyper ledger's policy of openness, equity and inclusion. So, everyone's welcome to our meetings and this is intended to be an open forum for sharing ideas and having constructive discussions. But if you want to learn and please learn. We'd also like to express our appreciation to our hyper ledger members and this slide shows the premier and general members as well. You can see that it's a growing list. If you're new welcome, please feel free to introduce yourself in the comments. And if there's anything specifically that you want, you're interested in, just go ahead and share that in the comments. But again, lurkers are welcome. Here's our agenda for today. We've gone through the introduction of antitrust code of conduct that's always required with our hyper ledger meetings. We'll go through some hyper ledger community slides. James will go through the status of blockchain in the mortgage industry and then Karen, I'll hand it off to you to walk through blockchain, Tethered, give us a background on you and Orson overview of the book and then discussion of any applicability for financial services or you're in charge of the agenda at that point. So, if you want to wax poetic, feel free. Okay, we always cover the slide in each of our meetings and this is to reinforce we're all on the same blockchain journey. We just may be a different path, different points along that path this group is meant to help everyone on their blockchain journey, demonstrate the feasibility of blockchain technology through the mortgage industry use cases and define potential implementation paths 2023 was a rough year for blockchain with the crypto winner and that's what we're going to do. That impacted us and now I think we're coming back. So, I'm really excited. The next several slides always mentioned and I'll go through those pretty quickly. This slide provides a different resources if you're interested in learning more about the Linux foundation hyper ledger. The second from the bottom is the link to our group wiki. Please feel free to take a look at that because it contains our meeting notes from previous. Meetings are recordings and curated articles about blockchain in the mortgage industry and we're up to over several hundred agenda talk about that as well. If you want access to these resources, you will need an L F ID and this will walk you through it. I'm not going to go over it, but click on the link and you can see the video. Hyper ledger certification highly encourage this as well and then blockchain training. I always mentioned this because this is how I learned about blockchain at least from the Linux foundation. Excellent training very worthwhile and one of my favorite words free. I was mentioning this at the beginning. I invite everyone that's in Southern California that's available on Friday afternoon to attend this embracing AI summit. It's free at UCLA one to 430 and then a reception afterwards. There's a link in the chat to go to this so definitely feel free and join. And if you go to that and you see me come introduce yourself with that and hand it over to James. You're on mute. I just realized. Thank you Marvin and welcome everybody to the April presentation. I've got a few articles and information that I want to share with you guys before our main presentation today so Marvin let's jump right into it on the next slide. So one of the first articles I wanted to bring you comes out a tech funnel. So this article starts with a traditional overview and current state of blockchain in our industry. You know, heavy reliance on paper documentation long term times and how blockchain can benefit those. It really delves into three fintech systems driving mortgage transformation and in 2024 so the role of data analytics in fintech lending and how fintech platforms leverage sophisticated data algorithms to analyze extensive data sets and this allows lenders to offer borrowers. Customize offers based on their needs. They talk about you know blockchain and smart contracts the traditional conversations that we've had. And then it really goes into the impact of AI and machine learning how applying AI and ML to structured and unstructured data sets and through pattern recognition techniques. It can create actionable insights and predictable outcomes. For instance research research has shown that AI can predict loan acceptance possibilities with 85% accuracy. And in the servicing environment can predict loan default possibilities with a 75% accuracy. Ultimately the article finishes up with noting the mortgage industries yet to achieve end to end technology driven operations at par with native fintech platforms. And mortgage lenders really need to focus on investing this year in superior data quality. API frameworks because they serve as the backbone for interoperability and integration between mortgage systems and fintech solutions. Compliance automation implementing automated solutions such as rule engines. Reg reporting AI platforms continuous monitoring adherence. And then you know cybersecurity it's always top of mind so you know great article worth checking out to see what they're kind of predicting for this year in the industry. Moving on to the next slide article. The next slide Marvin. So looking at how blockchain technology is having an impact in real estate. So this is by debt soft and it opens up talking about how the real estate industry has a compounded annual growth rate of around 66.27%. The trend is expected to grow at the same at the same compounded annual growth rate till at least 2027. It's estimated that almost 50% of all transactions could be happening via blockchain as early as the end of next year. So the article provides examples of how can blockchain be used in real estate. It covers topics from real estate tokenization loan and mortgage security, urban planning, pre calculated property valuations, as well as government background checks and land and property registry and sales, which that's actually a topic that we've talked about last year as well. It continues with discussing the traditional benefits of blockchain transparency efficiency accessibility, and ultimately has an FAQ on asset tokenization blockchain in commercial lending and crypto in the real estate industry which is actually the next article I want to want to touch on if you can go to the next slide or Marvin. So you know in the past we have talked about crypto backed mortgage loans in particular and, you know, 2022 and early 23 we've talked about them quite a bit. I just wanted to bring you guys an update on what we're kind of seeing in that market. So crypto backed mortgage for those that you don't know it it's really an agreement where it requires the borrower deposit cryptocurrency as collateral to guarantee repayment of a mortgage. It starts with finding a defy lender that accepts cryptocurrency as collateral borrowers determine how much can be borrowed or excuse me borrowers must prove ownership of the digital assets to be used as security. And then the lenders determine how much can be borrowed based on available collateral loan value may also consider factors such as volatility of the crypto price markets, or the target property itself. The borrower pays back. When the borrower pays the loan back the collateral is returned to them at the end of the loan term. And if the loan goes into default per the loan agreement lenders will be able to claim part or all the collateral to cover the value of that default, and the assets in turn maybe liquidated. So that's kind of the overview that we've talked about before this article covers all those things but then it really talks about the types of crypto back mortgages that we're seeing today. And you know it used to be we were just seeing them for an initial home purchase, but now we're seeing them for home purchases. We're seeing them for refinances or what they're calling remortgaging where the existing homeowners providing now cryptocurrencies as collateral against the loan on a property that they already own. And then we're also starting to see crypto loans now in bridging loans these are used for interim financing when a borrower needs to finalize the purchase of a new property for a period of time until the proceeds from the sales of an existing property are credited. So we're actually starting to see new creative solutions being implemented with crypto mortgages. And finally it discusses the benefits and risk related to these types of funding instruments. The next article we have is from tech times is talking about how tech is shaping up the mortgage industry. It opens with Minzy or McKinsey and company reports that approximately 60% of borrowers are open to completing their mortgage applications online nowadays, and this is for both new homes as well as refinancing. The borrowers are increasingly seeking an efficient, convenient and streamline mortgage process. And the article discusses the use of API's blockchain, artificial intelligence, machine learning applications in the mortgage or the mortgage industry. API adoption, you know again as we talked really increases efficiency ensures data accuracy automates all that workflow and facilitates compliance with us mortgage rate regulations, while AI can train systems to perform cognitive cognitive tax tasks as recommending approval or denial decisions, classifying information institutions can use these in every step of the lending process to produce reduce cost as well as the turn time. And then it also talks about blockchain house, how the secure digital ledger works, how each blockchain contains a list of transactions that can't be altered, you know yada yada yada the immutable record. These are the traditional things that we hear out of blockchain benefits. Ultimately, this article does circle back to what we started within our articles today and the discussion of the benefits on fintech collaboration. And then the next slide Marvin. This is the last one I wanted to share while I was researching for various articles and what's going on in the industry. I'm always excited when we see the government institutions the GSE is getting involved with blockchain or AI, and I actually did stumble across this article. So, FHFA is housing an event this summer called Generate Generative Artificial Intelligence and Housing Finance Tech Sprint. There's a mouthful for you to Marvin, taking place at FHA FHAs Constitution Center headquarters in Washington DC, the events going to be going on from July 22 to July 25 this year. The applications to participate though are due by May 24. And you can find information we've actually got this on our wiki page you'll be able to click to the link from there. FHFA describes the event as inviting all interested individuals to submit an application to participate in the tech sprint teams will be assembled into functional groups with diverse expertise and experience, including participants from fields such as housing finance, consumer financial services, technology risks and compliance. The focus you'll see it there at the bottom. How might the responsible use of generative AI promote a transparent, fair, equitable and inclusive housing finance system, while fonts fostering sustainable ownership and rental opportunities. Tech Sprint participants will be demonstrating a key use for generative AI in one of the four areas of focus. Those four areas include consumer experience, assessing credit worthiness, operations and risk management and compliance. And in their process, they'll, they'll need to recommend control measures and incorporating careful consideration of the associated risks. So as I mentioned, there is a link to this. One of the nice things though, if you follow the link, you can participate virtually as an observer, not as part of one of the teams. But if you go into the link, you'll see an apply today when you go to apply today. There's two options there's a participant option and an observer option which is a virtual option I've actually enrolled myself for that. You don't get to attend the entire three days, but you do get to attend the opening and you do get attend the team presentations at the end as well. And Marvin over to our, my last slide. So this is our hyper ledger wiki for the mortgage entity subgroup. We always bring this up each month. In the upper right, you'll see the LF ID information that Marvin referred to earlier. There's a great little couple minute video there that shows you exactly how to do it. All of the articles that we've talked about today are on the right hand side, including that link to the FHFA. Tech sprint over on the left hand side, you've got the navigation pages. You've also got links into all of our previous presentation since 2021. We've also got all of our previous articles and industry research that we've presented over there so there's probably roughly about 120, 150 articles that are directly available on the site, but in the background we've curated well over 300 articles over the last three years now. So if you're looking for additional information, feel free to reach out and Alma dropped into the chat the length there that you see for the wiki so highly encourage you guys come check out the wiki. Sign up for an LF ID as you do you'll get notifications when we make updates to the wiki. You'll also get notifications for these future presentations as well. Marvin that wraps me up. I'll pass it back over to you for introduction of our guest speakers. Thanks James. That's always exciting information. Next, I'd like to introduce Karen Kilroy our speaker today. Karen is a moderator of the blockchain AI roundtable, which was established under the hyper ledger media entertainment sick and shared by Brett Russell. Karen is also the founder of file baby and also a contributor to see to PA coalition for content provenance and authenticity and Adobe lead initiative under the Linux foundation. We're really honored to have you join us Karen so I'll hand it over to you. Thank you will I be able to share my screen. Yes. Okay, fantastic. Boy thank you so much Marvin I really appreciate the invitation here and it says I need to wait until you stop sharing. There we go. And I'd also like to present my colleague introduced my colleague here Orson weems, who is president of file baby. Orson is my current focus and he is going to co present with me. And we got this fortunate occurrence because my internet is having trouble today so as the fickle finger of fate would have it. We have the privilege of having Orson with us. Welcome Orson. Yeah, thank you. Can you hear us Orson. Yes. Okay, can you see my screen. Yes. Okay, so the first thing I want to talk about is the state of work in the AI economy and it's not good news. We were promised jobs that aren't coming. You know, the whole the will be new jobs will be new jobs will be new jobs. Well, there's going to be like maybe one job for every 50 jobs, you know, so those are going to be the new jobs, and a good example of this would be in the the US Homeland Security has just put out a directive they're hiring 50 chief artificial intelligence officers. And while they're not saying it you know the writing is on the wall for this type of a thing that what's going to happen is the, the functions of the people themselves. The state workflow. Well now we're also building the people that are the steps and the workflow. And that's just a fact of the matter. That is just the way it's being done, and it's across the board and it's everywhere. Right now we're kind of to the to the state where a lot of CEOs say well I don't know if we're bringing in AI it's like I laugh I wonder how long they're going to be there, because they look at the fattest salaries to cut first. And, and so what's happening though instead is it's coming in from the bottom up. And, and, and by that I mean that every single tool that anyone uses now has a co intelligence built into it that makes the person who leverages that, you know, five to 50 times more powerful than they were a few minutes ago. And all of this is, is it snowballing it's getting bigger and bigger and bigger and bigger and like to the point where I wait until the day before to do my presentation at all like this one I did this morning because you just can't. You just can't do it any sooner because it's changing that fast. And, and one of the things that occurred to me this morning is, well the way that people are going to survive which I've thought about this for for a long time since I, since I wrote my blockchain tethered AI and I met Orson at the law at the fit bill public library Center for innovation when I was presenting about this very topic. And it just seems like a million years ago now even though it was what just a year ago. And, and what we were talking about is okay you know, knowing this is what's happening all the all the jobs that were done by people are now going to be done by AI. And the knowledge of the people is just being absorbed and the people aren't getting paid you know what's going to happen you know. So what what we decided is we have to have a way to make sure people get paid for their training data. And that gap there I would say in the in the meat grinder funnel is you know what we have to watch it. Where is, where is this all going where where is AI, and back the other way when you get output from AI. Where is that coming from and one of the links that I put from one of my writings in the I put it in the chat. It's AI is opaque box is really a supply chain. And I recommend everybody read that, because that lets you know like the steps of AI because it seems like some big mystery that now all of a sudden you have a co intelligence that can make you far more powerful than you were a few minutes ago. It's not, it's not mysterious, because it's it's just hidden from us. So please, please read that article, when you have a chance. Now, with this, as you can imagine, the sharks are starting to circle. The, you know, as traditional in our economy. It seems like, you know, people take a bite take a bite take a bite take a bite until there's nothing left for human beings to live on and, and, you know, they keep taking the bites there's, you know, the first layer takes the bites well they're smart they know that you got to leave somebody to live on, but then there's, you know, piranha, piranha after piranha after piranha nibbling away at people until there's less than nothing left and they end up on the street. They end up in a parking lot in a Walmart parking lot living out of their car. And we just got to say enough that we're not going to let this happen and we're not not going to let the new set of sharks. We're going to pray or piranhas prey on the new paradigm of work, which is going to be primarily gig gig economy for training in exchange for training data, because the reason that this data has to stay fresh with human knowledge is because if it doesn't if it's not freshened up all the time. It collapses upon itself. So you the models the AI collapses upon itself so it has to have fresh meat if you will. And so the group that I'm addressing today, and the Orson, you know, this is so important because you're in a position to make it public. If someone starts, if the piranha start nibbling away at this through a public finance blockchain where this type of event is recorded and a tamper evident at ledger. So we're going to kind of dig down in how that could happen, and why it's not a pipe dream at all this could happen quickly. And Orson, would you like to add anything to that. Thank you. Thank you so much. And what we're talking about is addressing what I think was just said in the previous presentation is how we can make this where it is tamper evident, so that there is a traceability if you will. I just wanted to just mention and talk about why we think that the authentic content is so important. And some of the, the, the substandard or the standards group that we sit on are the, the C2PA as well as the content authenticity initiative. And these things are so important, because we don't need people are as I like to say the bad actors coming in to address or to even take or manipulate anything that can be used lies for the consumers that can help the consumers and dealing with this mortgage industry and the fintech. I mean, what Aaron is saying is just vital for us to get on top of it right now and we're going to talk about some of the things that can help that with the way that blockchain and the other day I can address that. Thank you. Thank you, Orson. And there's ways now to tell whether content is authentic. And one of the links that I put in the chat was to C2PA. And what you can, that's a that's a coalition for content provenance and authenticity. And it's not anything that happened yesterday and it wasn't even created for AI. What C2PA was created for was to combat fake news. And so this group of leaders has been around for maybe five years now, crafting a set of guidelines to make sure that when you see a piece of content as a consumer that content, you can trace the provenance and see its authenticity and you can go so far as to see a hash or fingerprint of the original contents to make sure that nothing has been tampered with. It stops short of blockchain, stops short of blockchain, and they call it blockchain ready. So, so this is a tremendous opportunity for anybody who already is in the blockchain business to to learn about content credentials and be able to connect with that and even file baby our product, which is a platform for content credentials, we don't, we don't, we're not married to any particular blockchain implementation we prefer hyper ledger fabric, but we welcome other other blockchain implementation so we can connect your blockchain customers to this content provenance and authenticity platform with no problem. So, but what you can do with this, in addition to like a fingerprint that that makes the item tamper evident and this, it also has like a history, and a history of the file like a, the ingredients that created that file so if it was generated by AI like generated by Microsoft responsible AI, for instance, it says that in there, and it already says that these these credentials are embedded in the files, and most people do not know it. And so, and I'll say it again, they're already in there, and most people do not know it, and open AI is another member of C2PA, if you generate an image through Dali, these content credentials are already in there. If you save a file and Photoshop you have the opportunity to save the, the content credentials, and it's on and on and on and on BBC just a couple weeks ago released a video news verifier so when you're watching a video, you can dig in and find the content credentials. And, and so that is like the, the, almost like the consumer facing and of what I would call blockchain Tethered AI, which was my project that I worked on for so many years. And I'll get on to that in a minute but let me have Orson chime in on this topic, because I'm sure there's many things I didn't tell you can't hear you Orson. I'm sorry, forget that far you're talking. I just can't believe what we're talking about all the, what the content authenticity and and I'm getting this some message in my room sitting in my seminar room one moment. This. So one thing that Orson will probably talk about is how with C2PA, you can declare a file as do not use by AI. Right. And so if you have a piece of training data go ahead and take it out from here Orson if you have a piece of training data what we can do is I like to call it the, the DNA of that file we actually embed that with and that file can be designated and we know the provenance and the authenticity of when and where and who and how of that. So Karen, I think what you were saying about the content credentials is really embedded in that makes a lot a lot of way for the way that this can show that who owns it and when it was created. Yes. And so we tell if we can tell something not to be used by AI which is already established and and we then we then we should be able to tell somebody something that if you use this for AI pay this person. And we're very close to that right now. We've already proven that you can. We've proven the claim that it can be that that that a claim do not use by AI works. A few months ago, we hired Scott Harris who's as an executive project manager. He sent and when I was in a hurry to get a press release done I said Scott, I need a I need your picture. And he sent me one that was postage stamp size and anybody who's ever done a press release knows you can't do anything with that so I thought, let me see what I can do maybe I can use Firefly to make it better right. So I dropped it in. It put his face on the statue, put his face on the Mona Lisa. I mean it put it was putting his face on everything that I was, I was freaking out because this guy is 38 years out IBM I oh my god what did I do. I clicked it and shut it. And then, but I noticed while it was pulling the picture in that it said it was checking for content credentials. And then one found came in. So then I thought well let me check Ethan keel who is a senior data scientist from Walmart, who works with us part time. And I said let's let's check Ethan, because his picture, we've claimed it in file baby. It says do not use as a AI training data. And so let's see what happens so I dropped in Ethan's picture in it. It said, this says do not use by AI and I'm rejecting it can't use it. And so as more people sign on to see to PA and and the, and the other organization that's a broader organization which is content authenticity org, which I don't think I have in the chat. But that's more of like a, like if you if you have a website and you want to say that you implement implement the C to PA credentials you'd sign up for content authenticity and you would get some banners and things like that. And then we declare your participation. That's a much broader group. The C to PA, we're the work, working groups that we narrow down the actual issues, and then we define how to fix them and or how to address them and then we make standards. And then tooling is created out of that so that's that's the C to PA level. But anyway, let's go on. What about blockchain. Well, well, well, you know I don't have to tell this group what blockchain is and I'm pretty sure I don't have to tell you what enterprise blockchain is. Blockchain is really, really important for AI. And this is a concept that I worked on since to the C 2016 2016 is when I started and and the way that I got started with blockchain tethered AI is in addition to being a full stack software engineer you know a dragon boat coach. And if anybody knows what a dragon boat code, what a dragon boat is. And if you don't, it's a, it's a 41 foot long boat with a dragon head and a dragon tail. And then there's 20 paddlers that sit facing, they sit facing the front side by side and rows of two. And then there's a drummer that faces them that that keeps the beat. And my job as the coach is, is, is to steer the boat I stand on the back and steer this 41 foot long boat with a with the 12 foot long steering or and we race, and it but that's dragon boat. And I had the opportunity when I lived in Austin, Texas to coach a team from the Texas school for blood for the blind visually impaired. And we spent a lot of time on the boat and by the way they won their race because nobody thought they would win and they, and they didn't take it seriously but the kids got medals it was fantastic. But they worked for months, months, months, months to get there. And, and they. And while they were working, I noticed that every time they, they stopped for a break right these are teenagers now older teenagers like 18 to 22. They get the phones out, and they get the headsets on, and they would just be like every other teenager you know flip flip, you know, whatever they're doing playing games and they taught me all about the stuff they're doing. And while I was doing working with them, I thought you know, it would be great. And this is when the visual recognition was just starting I thought it'd be great if you could take your phone and pointed at something and it would tell you oh well there's your caretaker over there you know you're not abandoned or there's a tree there's a you know you're in a beautiful whatever if they could see with the phone. And so I thought well maybe someday you know who knows and, and then IBM came out with their Watson build challenge. And when we, during that, we progressed through my company kill, excuse me kill right blockchain. So we progressed through the different steps of the Watson build challenge and proposing to make this, and during the process we were challenged by the IBM engineers. Okay kill right blockchain. What's this AI app got to do with blockchain. So we started really thinking about it. And we realized that the data, you know, if the data is what feeds AI, and you're, you're a blind to visually impaired person, you know you need to rely on this data with no critical data you know this is no light thing. You know we don't want anybody tampering with it so I thought, well that would be where you use blockchain. And so I brought that out to some engineers and they said you know what if you data you think that's important with data also think about the algorithms. Basically, we opened an entire can of worms, and realized that there was nothing that was securing AI. And you can even go so far as to reverse AI, as long as you have a tamper evident audit trail, which is what this group brings to the table. So, I also want to address identity for a second. Identity is something that that is brought to the table by blockchain as well and then also you can interface with certificate authorities that support C to PA. So then that can be an end to end solution where you've got the same. You've got the same certificates, and the, and the blockchain is all based on stuff from the certificate authority so you know there's ways to tie those things together. Distributing tamper evident verification is controlled to you know there's nothing that does that like blockchain right we all know that. And I'm preaching to the choir here control three governing instructing and inhibiting intelligent agents. This is after they become released into the wild. And in my book blockchain tethered AI, you'll find detailed instructions and code that tells you how to, how to begin an AI project responsibly. You know the things to think about the way to keep the origin itself of the project from drifting. If you, if you create an AI to pick dead chickens out of a out of a pen, which is something that has actually been suggested to me. But then that drifts and all of a sudden now you're killing chickens that are almost dead. That needs to be declared somewhere so you can back it up. And, you know that that's an extreme example but there's, you know that applies to everything. But you also need to know how your government, how you're governing what your processes for governing your AI system and governance. Hello, blockchain trust networks you know it's like, it's like the old ad where some of you might be old enough to think about it but the you had the peanut butter in my chocolate where the guy was Reese's peanut butter cop and the guy would walk out with the with the chocolate another guy would have the peanut butter and they'd be bumping into each other and then all of a sudden they got peanut butter and chocolate. And they say that's how the Reese's Cup was invented. But this is, you know where the Reese's Cup of content credentials right we have all that back and all that tooling that that the people that have been working on things like news providence for years and years, they need us and they don't really know it yet. So it's good time for us to rise up to that challenge and caught inhibiting intelligent agents. For instance, like, let's say you have a rogue AI, you have to have a way to bring that back into your governance process and to into. It's into the workflow with the engineers. So everything is all trackable traceable what happened what was the complaint with the engineers do to address it what was the training data and algorithms and how do we trace those so every one of those is a is an opportunity for And in showing the authenticity through user view viewable Providence. This is where you would put a trust logo on a on a on a on a model that goes along with its data sheet, and you would tell it, you know, here's how you can prove that of the Providence of this model and paying for training data is a badge of honor. Adobe, I hear him say it often, you know, all our training data for Firefly is paid for, we've paid everyone. And, and that's a badge of honor and that's an up and coming badge of honor and Orson would you like to speak on any all of this for a minute. The what you just said the last point was that badge of honor with the with the content logo or the credentialed logo that is a valuable thing because that gives the household or good housekeeping seal of approval from years ago for those that are on here that understand what they that gives a seal of approval that gives the the the reason that we need to have this and what we're talking about today with the definitely the user viewable Providence that's going to be a big thing with the type of things that will go along with this, the finance and the mortgage industry in the fintech. Yes, and I'm going to also take that one step further and invite you to use your imagination for a minute. You might even want to close your eyes, because we're going to go into the future 100 years. And what we're going to think about is typing something into an AI and having an output. And now who's getting paid, who's getting paid for this stuff that it's been accumulating for the last 100 years. And the question is, probably, it's probably nobody probably that person is long dead even if they ever got paid in the first place. So that's where you can come in, where there's huge opportunities to create new products that provide futures for AI. And I don't know if anyone has ever heard of Bowie bonds. Bowie bonds were created by David Bowie's manager, Bill Zisplat, back when David Bowie his first manager just cleaned him out so he was really famous at the end of the 1970s and penniless. So he had to carry on this image and he was completely broke. And so he met a new new group of people that said, look, you know, these songs have future potential. They're strong. Let's let's let's sell futures so you can get back to live in your life. And we can get on with your music catalog. Imagine what would have happened. Imagine how music in general the whole thing would be different if his manager hadn't come up with that idea. So, so, so we're in the same boat here. When someone, let's say a veteran tells a war story or Orson tells me boy you sure have some great stories but you've got stories about everything you should sell your, your stories. But you know what am I going to sell on how much am I selling them for, and how long can this company use them. And then what happens after that. And, and it's not just my stories you know let's say that I'm a famous actress right, I might be a really marker marketable hot property. Well the thing that's going to be is they're going to want to make me stay young. Hello, you know, like they're not going to let me act other than when I'm at my prime. So how do I get paid. How do I get paid for my image. And how do my, how do my, how do I develop wealth for my family and generations to come, while my image continues to be used. And so Orson do you want to add to that. That's what we're looking at right now is, and we've seen so many things from legislation says put in place to protect main image likeness voice. We've seen George Carlin's image utilize and the lawsuit recently that was settled because of this but I think you're on the way that you're sharing and some of the things that I've seen in the chat. Some of the comments in the chat here. We have to deal with this now, and be responsible companies, or be responsible companies to utilize how we can add the protections and the provenance to give the consumers. The confidence that this is not something that is fake or deep fake, etc. And we have to do that. And we're able to do that right now as you're talking about in this presentation and working with some of the partners that we work with. Yes. And so, you know, I would conclude by I'd like to show you my shirt that I wore for this today. Slow your roll. And oddly enough, I've heard this phrase, bunches of times this week. And, but I would say that to you, because AI, the companies you've seen them all talk about oh well let's stop let's stop it's like what a joke, you know anybody who's ever played tag on the playground knows that that's a lie. And so, so what you want to do instead is you want to be forward thinking you want to come up with, with financial products and instruments that can be used so let's say someone puts the story out for training data, or their voice or their likeness, there is a way where they can walk out with money, and, and go get themselves something to eat go get themselves a place to stay. And, and there's there, there's probably going to have to be financial instruments that support that. And they need to be trackable and traceable. It needs to be red flagged if anyone takes a cut. It needs to be red flagged if the shell game is played with the money, and it doesn't end up in the hands of the people. So, with that, I'd like to conclude Orson, did you have anything else to add to that. No, I just really want to thank Marvin and James, especially Brett hyperlage for allowing us to make this presentation and any questions I think you put our contact information below please feel free to reach out to us. We want to work with this responsibly and we want to make people feel good about the potentials of what AI and blockchain can do and how it can benefit us, as well as users and the consumers that we want that we're talking about that this can work for. Thank you. And just a suggestion. You can subscribe to our service at file dot baby. And what that would bring you is that's the C2PA platform that we've built. And it would just bring you, you know, we cut a lot of time off of your learning curve to to get on the C, C2PA bandwagon, and then you can figure out okay here's how I would interface this with blockchain. So, I'm going to open this up for questions. Thank you. Thanks Karen. Thank you, Orson. Excellent presentation. I read your book, it was an excellent read and as I was going through what I really appreciated in the book were the examples that you guys went through and it had a lot of diagrams. I'm a visual guy. So that that was awesome. You walk through the four blockchain controls. And as you were going through those examples. Is there any one of those blockchain controls that you think is more important or more effective or more effective than the others, especially for our industry for mortgages or financial services in general. That's a good question. You know, identity is critical. And, you know, having a good way to interface and identity is something that's that's pluggable. So there's all kinds of efforts for identity going around like for instance when LinkedIn verifies my identity they do it through the university where I'm a student so you know they go to somebody who's seen me I mean the university knows who I am. And so the the the my LinkedIn says I'm verified because of that so so there's, you know, many, many, there's probably hundreds of identity systems that are going on out there. So one of the things would be able to develop standards to plug these in. Another thing you could really do is participate in C2PA. And I recommend that to anybody who wants to and if somebody wants to come in and see what it's like, you can volunteer through friends of Justin, which is our nonprofit, and then we can take you to a meeting. And you can, you can participate and see what it's like and you can even keep volunteering through friends of Justin, if you want, but you know then also to you can join with your own organization. It's really an awesome group. They're there hustling on these standards. And, and so there we really don't have like a mortgage subgroup. And I think that it would be excellent to have a mortgage subgroup so I would say, you know, please, Marvin and everyone I'd like to see you, you know, in C2PA and reach out to Orson or me if you would like to volunteer and and come to a meeting and we can get to a schedule all week about all the sub topics. And my, my particular task force is a trustless task force, where we're developing standards for certificate products along with the certificate authorities that then can plug in so you know the timing is perfect if you have a group of of mortgage providers and lenders that are using blockchain network this is the perfect time to come in and say here's what we need. Right. And start getting in those conversations. Okay. Marvin I wanted to add to the follow up on what your question was I think that the controls, definitely the controls one and two of what can can you slide put that back there your controls on the four controls. And that's what Karen said that the identity, but you, I think, all of these very pertinent, but I gotta tell you wanted to would be really almost in that order, because that's some of the things that you want to give the background and the history and as well as the, you can speak very boldly that someone knows that you have those in place with blockchain I think that can go a long way in this industry. And I think there's something for us to build off of which is Karen just said we can create what we need to for this industry. We can do it work with you all to do that. Yeah, we're available to do that. The see you said something that triggered something for me. Oh the source of the data. Here's an example for the lending industry. Let's say that there's an accusation that a biased decision was made on on lending. And let's say for instance you've gone to great lengths to make sure that you're not using bias training data. And by biased I mean, you know, my women and minorities have been overlooked for the last 50 years and so you're going to base it on that and the AI I'll make those same decisions right because garbage and garbage out. So you want to be able to prove that you're not doing that. And so, so this is a way that you could actually prove the source of all of your training dating you know this is not based on bad loans and and officers that got fired. This is based on the high road. And what we want to see as an organization. And here, you don't even have to ask me twice here's the link. And you can track it back yourself. That's an excellent example because that there's a whole series of regulations applied to the mortgage industry to counteracting that exact example. Thank you. You're welcome. Just a couple observations. So Karen Wars and I think you're right on the money actually last month we our presentation was about digital identities and some of the efforts that are being put into the financial industry. One observation it's interesting as you know listening you present especially control for when we talk about showing authenticity through user view will provenance. You know the first thing it makes me think of is the blue check mark on, you know, X formerly Twitter, they love to say. And you know when that initially came out, people saw a lot of value and evidence well. And as we've seen over the years, some things have changed and different owners have come into power and things have changed again and so now it kind of makes that okay is that blue check mark as trustworthy is what we used to think about it. What I like about this concept is you've got that user viewable provenance. So it's not just seeing that blue check mark it's being able to understand and be able to view okay what's the actual history of it so that now I've got the comfort level that it's approved. I'm not relying on somebody in a glass tower that's getting paid and saying okay I'll give you blue check mark, because I believe it is you so just a you know an observation along the way. Yes, James and it's also. If you think about it that different groups can trust different sources to right right. So, you know, it's just, this is really what happened that's this is our, you know, this is our audit trail. So, yeah. Any more questions or comments. I think I'll be pretty close. Yeah, I think we still have a couple minutes because I do have a couple other questions. So, as those four controls are being executed for blockchain tether AI, where should the output from those controls be stored, because I assume they're not going to be stored on the same blockchain and then kind of a related question at the very beginning that that all of this was based on hyper ledger fabric thing. My second kind of question is, why was hyper ledger fabric chosen and I assume that all of this is still applicable to other blockchains that your blockchain agnostic. Okay. Well, first of all, the read the you're probably gonna have to ask me the first question again as my brain is not that big. My buffer is shorter than that. My first question, where should the output from the four controls be stored. The output from the four controls is, we, we have it stored in a special blockchain tethered AI system that's built for that that handles the machine learning workflow. Okay, and, and so you have the AI engineer, you have the, you have the machine learning ops ml ops, right, and then you have stakeholders. And that's, you know, that's kind of the major workflow and then after, after the model is trained and deployed, then you have the public. So there needs to be some kind of a special system for that. Now it could be, you might be using something like Microsoft responsible AI that handles a lot of these workflow items, and then you want to API your blockchain. Because all this is caught on every bit of it is caught on as far as the workflow and steps and, and you can't just turn things loose and I believe in Microsoft responsible AI they've already got C2PA integrated. Oh, okay. So, so that is a big deal in the reactor series of the Microsoft training. There is a video, not this current one but the previous one I believe that talks about C2PA and I have not seen it, but that's what they told me. And so, but, you know, I would say think it, you know, platforms that are built for responsible AI. And so that's kind of how it is. Yeah. So like your financial stuff would probably stay on its own blockchain. This would be, you would say, and you might even set up integrated blockchains for training data provenance and stuff but, but yeah the basic I think the, to answer your question I think it's yeah it's just, it's its own system. Next question, I can't remember. Why was fiber hyper ledger fabric chosen in, because there, there are so many blockchains and we're always stressing interoperability. Because my company built this all at we built the examples for my book blockchain to the other day I would try to know where I laid it. Oh, here it is. Kilroy blockchain built all these examples and, and we're, we're hyper ledger fabric shop at the time. So that was, we've built things like a 1031 transfer blockchain tethered application and you know I have that still in the can if anybody's interested. And we also built a closing something for closings that does, does the blockchain audit trail. And so any of those could have AI integrated with them and you'd have an instant blockchain tethered AI. Industry application. 1031s are probably pretty big deal to that. That could. Yeah, and 1031 exchange for anybody that's not familiar with that that's when that's an IRS law that lets you. When you make a profit off of a property it lets you transfer that that amount to another transfer your profit to another property within certain guidelines and certain timeframes. And as long as you do it right then you don't pay taxes on that property money that you made, and it's like a tax deferral thing and it's really gets complex but what blockchain can bring to it is that audit trail then that you show you can show the IRS and say, just really happened. Yeah. Yeah, yeah, that built so yep. I showed that we're have only one minute left. If any of the participants has a question for Karen or Orson. I know I've kind of been monopolizing things as I tend to do so I want to open it up if anyone has one last question. Okay, we're at the top of the hour. I you shared your contact information Karen and Orson. Thank you very much. This has been very interesting. Yeah, definitely ordered the book. I read it. It was a great read, but then, you know, I tend to dive into these things. And it was very educational in terms of how to manage AI so highly recommended Karen Orson, I'd like to reach out to you later on and talk about some of those other blockchain applications. Thank you so much. You all have a great day. Have a great day. Bye bye. Thank you very much.