They make, on average, $116,000, a little bit more, $116,661, which is dope! What's up, you guys? It's Adana. Welcome back to my channel. If you haven't already done so, go ahead right now. Subscribe to my channel and follow me on Instagram and AdanaPA. So, yeah, you guys asked me about the specialties, right? I talk about how much lateral movement we have and how we can go from here to there, and that's what I really love about the profession, but you really don't know all of the different areas that you can go into. So, I found this website that had an article breaking down various different physician assistant specialties and their salaries associated with them. You can always go to NCCPA, which is the certification board for the PAs, and they will have their information, the same information as well, because that's where this article got that information from. The first one, I guess we can start from top to bottom, highest paying to least paying, right? So, the first one is pathology PAs. So, pathology meaning a corner, working in that sense, in that lab, figuring out pathology. Those PAs make, on average, $119,000 a year, and their starting salary or their midpoint is usually $110,000, which is really good. So, the next specialty that one can go into if you're trying to become a PA is dermatology. And so, dermatology PAs, you know, they're studying the skin. They make, on average, $118,000. So, this particular article says $118,145. That sounds really good, and if you're really into Derm, where you have a love for Derm, then that is the area for you. The next highest paying one is emergency medicine. They make, on average, $116,000, a little bit more, $116,661, which is dope. And obviously, depending on how you schedule yourself, you can moonlight at other emergency rooms and make more money if you're into that kind of thing. Right? Who's not into making more money, right? So, if you want to work harder, you can go ahead and do that. The next highest paying one is a critical care PA. So, critical care PAs are your PAs that work in the ICU, and they make about $114,000. That's kind of like your average salary a year. So, there are going to be people that make more than that, and there are going to be people that make a little bit less than that starting out. But on average, you're at $114,000.  So, you can go into all of these various different areas, and they make, on average, $113,000 a year. You can also just be like a general surgery PA, and they make, on average, $106,000 a year. The other subspecialty that you can go into is like adolescent medicine. I really don't, like, I hadn't heard of that before, but they make, on average, $81,000. Gynecology makes $87,000. I mean, $87,000 sounds pretty darn good to me. I don't know. If I'm making that straight out of like college, and I'm getting to learn and like just bolster myself as a PA, I think I'd be fine with that. Pediatrics, they tend to make $88,000. The OBGYNPAs, which is the area that I want to go into, makes $89,942 a year, on average. Those are the ones with like the salaries, but there are so many other areas that you can go into. You can go into pulmonology. You can go into cardiology. You can go into palliative medicine. You can go into pain management. You can go into hospice. You can be a hospitalist PA. You can go into urology. Literally think of an area in medicine that you're interested in and then be like, hmm, I wonder if PAs can work there. And more than likely they can. And if they don't have a PA in that particular area yet, maybe you can be like the forerunner in that area and you can like go pave the way for other PAs. Hopefully this was helpful. Gave you not only some specialties that you can go into, but also the salaries of those various different specialties. You can make your choices based on that or just based on your love for the profession. You can always go to NCCPA's website and find out more information on the various different specialties that the PA profession offers and their salaries. I hope this was helpful. If you have not done so, already go ahead and subscribe to my channel. Follow me on Instagram and leave me a comment. Also, if you have any questions about this video or other anything else, go ahead and leave that in the comment section below as well. Like this video and hit that thumbs up button and subscribe. Thank you guys so much for watching. I will talk to you guys next time. Bye.


Morning everyone, or good afternoon, depending on where you are. My name is Matthias Liffus, and I would like to start this webinar by acknowledging the traditional owners of the land on which we all are today. For me in Perth, that is the Wajuk people of the Nungar Nation. And I would like to pay my respects to the elders past and present. And I'd like to extend that respect to the traditional owners of the lands on which you are this morning, or this afternoon, sorry. So this is the third Q&A webinar out of four for our Fair Data 101 Express course. And today we'll be focusing specifically on interoperability. Now today we have two excellent speakers, very, very knowledgeable. We have Rowan Brownlee and Catherine Brady. And as in previous sessions, they'll be giving a bit of a story about some of the work they've been doing, and then we'll be able to get into the Q&A itself. Now as with previous sessions, that in your go-to webinar window, which is hopefully on the right of your screen, there is a little questions module where you can type your questions in. You can type your questions in at any time. And then when we get to that Q&A session, I will be pointing those questions at Catherine, Rowan, myself. Okay, I don't think there's much need to delay. I don't think there's anything else to cover, so we'll get right into it. So I'd like to introduce my first speaker, Rowan Brownlee. So he not only works at the Australian Research Data Commons, but he is also quite heavily involved in the Australian Vocabulary Special Interest Group. Over to you, Rowan. Thanks, thanks Matisse, and welcome everyone. While I've got a few slides that I'll go through, and while I'm going through these, I'll switch off my video and then I'll come back in after the presentations. So I understand that you've discussed the use of vocabularies to support data interoperability, but if in the one subject domain, you have choices between separate vocabularies, how do you decide which one to choose? Faced with semantically overlapping vocabularies, how do you make an informed choice? And if you choose a vocabulary, how do you know that it's fit for purpose, backed by the research community that you want to work with and that the vocabulary will be managed and maintained over time? Next slide, thanks Matisse. I'll talk about this issue in relation to one example research domain, that of earth and environmental sciences. These are some organizations involved in earth and environmental sciences, a mix of Australian and overseas organizations. At each of these organizations, publishes vocabularies in the ARDC Vocabulary Service. Next slide, thanks Matisse. As more vocabularies are contributed to the service, users have reported uncertainty in making selections when faced with semantically similar or overlapping vocabularies. They express concern about making the wrong choice and want guidance to make informed choices. They want the vocabulary publishing portal to provide a community lens, the domain view of their community's vocabularies, explaining which vocabularies to use for particular purposes. In this example, over on the right hand side, an extract of results for searching on a concept titled Bohol. In this example, four vocabularies, four separate vocabularies are returned, each containing a concept for Bohol. So how is the user to know which vocabulary to use for their particular purpose? Next slide, thanks Matisse. Vocabulary users want guidance, but how does ARDC get the information needed to make recommendations about particular vocabularies? How does ARDC know which vocabulary to recommend for use for a particular purpose? One approach is to work with research communities themselves. In particular, working with those who have an interest or expertise in informatics. And one such attempt involves working with the National Earth and Environmental Sciences Facilities Forum, otherwise known as NISF. NISF provides a means for Earth and Environmental Science Research Facilities to periodically meet up to discuss issues of common interest. NISF member organisations have links to related organisations within Australia and across the globe. And they have an interest in encouraging uptake of community standards. So some good starting points, interest in informatics, understanding of the importance of using shared standards and relationships to like organisations here and overseas. And so we're aiming to work with NISF to benefit from their domain expertise, to gather information, to improve the documentation and presentation of information about vocabularies, to help users make informed choices, to answer questions like, which vocabularies address the common need or purpose? If I choose this vocabulary, how can I tell if it's well-governed, trustworthy, authoritative? And so you might consider NISF as an important element of research data infrastructure that offers a level of social interoperability, communication, common interest, social interoperability in support of technical and semantic interoperability. And if this approach is successful, ARDC will seek to explore its applicability to other domains. Thanks, Matthias, that's it. Great, thank you very much for that, Rowan, and for that insight as to how we get domain-specific expertise contributing to our vocabulary service. So next up, I would like to introduce Catherine Brady. Catherine Brady also works for the ARDC in our data and services division. Over to you, Catherine. Thanks, Matthias. As Matthias said, I work in the data and services area. I'm the program manager for the Australian data partnerships program that sits under what we're calling our national data initiative. Now, I just wanted to talk you through a story from one of the projects that we ran with last year. We, the ARDC, co-invested in something called our data and services discovery projects in 2019, the last half of 2019. And they were small, short exploratory projects that were conducted in a limited time frame. And one of these that I'm going to talk to you about today, just to give you a bit of like a real life example, was the Australian Brain Data Comments. So the A, B, D, C, nice acronym, which was led by the Australian Brain Alliance. And that was under the auspices of the Australian Academy of Science. So some big players there. Now, their aim was to use a consultative approach to determine requirements for what they called the coordinated and internationally compatible national brain science data framework. And they also wanted to educate their neuroscience community on how to reuse their data for maximum benefit and to promote data sharing standards across that sector in Australia. So they assembled a working group of stakeholders that represented a range of disciplines in the neurosciences and across the private sector. So who thinks this is sounding a bit like it might be a bit of an interoperability challenge already, right? So what problems did they have in this sector? I mean, it's actually, this is quite a good example. So Brain Data Comments, that sounds like quite, you know, a homogenous sort of discipline, but it's actually quite a broad spectrum of methods and data across a range of sub-disciplines in the neurosciences. So when you're thinking about neurosciences, maybe it's the, it could be psychology data or data coming out of the cognitive neurosciences. There's animal behavior data. There's data that comes from MRIs and PET scans and molecular imaging. And there's macroscopies data, as well as molecular neuroscience data. There's electrophysiology and calcium imaging. They also collect neurogenomics and clinical data and computational neuroscience, AI and machine learning data. There's patient observational data and all sorts of other imaging data that they collect. So that's quite a diverse sort of data types in a particular discipline that seems narrow, but it actually crosses quite a range of data types. And what they had was no clear standards within or across those sub-disciplines. And that's not surprising, really, because partly that those disciplines, you know, from psychology to the calcium imaging in a cell, is, you know, that's quite different things. And it can depend on the type of equipment and software you use to acquire that data as well.  Now, what they found as well, that there were real and perceived barriers to data sharing in their community. There was a lack of appropriate sharing solutions. There was a lack of appropriate technical and other resources. There were legal and ethical concerns around the data. And obviously, a lot of it's sensitive clinical data. And there were concerns about the data ownership. And they found that software platforms did exist, but they weren't always user-friendly enough. And they weren't always adapted to cope with the different types of data in neuroscience. So what they did was convened some workshops around the country to discuss and build consensus around identifying the infrastructure, the technical and human resources, and the culture required to develop a neuroscience data sharing standard that met the fair principles. Now, it's really interesting, I think, that they included culture here and very insightful of them, because when you think about interoperability, you're probably thinking about technical challenges and solutions to the problem that are technical. And perhaps you're thinking around technical infrastructure and metadata and data standards and exchange standards for that data. But these guys identified culture as one of the important things they had to work on in their community if they were ever gonna achieve fair. And they started this process by bringing their community together, talking, asking them what would they need to do, what would they need to make happen to make their data more fair. And not just that, what were the perceived barriers? Where was the incentive? What was the return on investment? What were the social or discipline norms in the sector? And how can we make it easier to participate? So in this case, interoperability started out with getting the right people around the table, just a conversation, acknowledging those shared problems and getting agreement on a way forward. A shared vision of what interoperability might look like for the Australian Brain Data Commons, if you like. So acknowledging what is common, what's different. What standards and infrastructure exist already and what can be built on and what needs to be started from scratch. And working out what would be fit for their purpose if the goal was a national brain science data framework. So I don't really have an ending for this story. The project ended at the point where they did achieve some consensus around a way forward for the Australian Brain Data Commons, that it was a feasible idea and more exploratory work had to be done. And we'll be following up with them again in time to see how they've gone with that. But I think they made a really good start at the ground floor on getting the culture right and getting the people on board in order that interoperability might be achieved and might flow from the work that they've put in place by sort of starting, I think, from the right, putting a framework in place and putting that groundwork down and not just approaching it from a technical solution or point of view that sort of goes over the top of everything else. So on the basis of the success of the discovery projects of which the Australian Brain Data Commons was one of those, we've launched a larger program in the same vein. It's called the National Data Assets Initiative. Underpinning this initiative, we've got the principle that collections of research data can be national infrastructure when they support leading edge research and national end scale. So that's what that initiative is about. That's what a national data asset is from where we're looking. And what we've done is building on the back of those discovery projects. We've made sure that the fair principles, including interoperability, are an important component of the projects we intend to co-invest with under the auspices of this program. And all of our projects are being asked to sign up to the fair data principles and explore what it would be like to make these collections more fair. And they'll be learning from those early experiences of the projects and the groups that did that early work last year in the discovery projects with how they went about getting their community to look at the various data and how they might achieve fair and how they might work towards interoperability. So I think we had some really good lessons there and some things that people can pick up with going forward in our National Data Assets Initiative and the Australian Data Partnerships Program, which I'm program managing. So that's it from me as a little story. Great, thank you very much for that, Catherine. And I'm just gonna stop sharing my screen for this Q&A session. Now, we haven't got any questions just yet. So please, if you do have a question for Catherine or Rowan or you have some questions about the webinars for me, please pop them into the question box and we will get those answered. Now, Catherine and Rowan, what I noticed there is that both of you talked about the need for communities to work together or for consultation to help underpin interoperability work. Now, perhaps a bit of a left field question, but have either of you observed a situation where an attempt at interoperability has failed because there was no community consultation or no real community involvement? It's a good question. Go, Rowan. Just thinking of how that would... How would it happen? Who would be the groups that would be seeking some level of interoperability independent of the community or the people in their particular group? That's... I don't think I haven't had that. If that's what you're asking about, Matthias, I haven't... I suppose it could be more seen as maybe somebody thinks that something will help interoperability so they propose a standard or develop something, but because there was no community involvement, it was never really adopted. Nobody really went along with it. I'm sure there probably are plenty of examples of exactly that, but nothing concrete that comes to mind immediately, Matthias, but I think from the stories we've just sort of related there, that would be sort of a likely outcome, and I'm sure that has certainly happened across... I mean, perhaps we don't hear about them because no one likes to really talk about the things that go wrong and fail. So those stories probably aren't out there so much, but... Yeah, I think that would be... Sometimes they can be really useful stories to hear. I can remember one or two years back at the Air Research Australasia Conference, and there was some sort of panel or forum where a bunch of people got up and described projects or situations, things that just hadn't worked out at all, and that was very useful and informative. And in areas like health and medicine at hospitals and things, they have morbidity conferences or analysis. Something terrible happens, and everyone gets around and discusses it in order to learn what happened and why it happened. Maybe more of that approach could be brought into our area. Yeah, I mean, it's really easy to imagine interoperability not working out. I mean, the times when I've gone to a meeting, gone to a meeting and a group of us have prepared something that we think, oh, this is going to work, this is going to be of interest, this is going to provide a way forward. It reflects all of our assumptions, and then we provide that to the other members of the meeting and we find that, no, something else entirely that's needed. Yes. OK, so in the meantime, we have received some questions from our audience. So the first question is, and this is for both of you, whether either of you have advice on best practices for capturing decisions, agreement or consensus in this way? What's the best way to document and share standards? I haven't seen an example of any one that I would promote that you would necessarily follow. Again, it would probably depend on the context and the discipline. There might be some I know in medical and health. There's there are some I think there may be some I might be wrong with something called the Delphi principles or guide. And I know some of our projects were using that to structure how in our discovery projects, how they went about seeking some of that consensus. That might not be all of the way you document, but they looked to their sector and their discipline for or internationally for a kind of robust process, I guess, and of bringing stakeholders together. And perhaps maybe part of that would be documentation. But I'm not aware of particular others or something that's generic. Yes, and certainly I've I feel like this is can be a very community specific thing as well. So I mean, one of my favorite things to say to people asking any kind of data question is just check what is the standard or the norm in your discipline, which isn't very helpful. And I suppose that's where people don't have to go. Well, how does my community determine this? But I have attended workshops and seminars where people have been brought together to try and work on agreeing on standards or agreeing to move on a way forward. OK, in here's another question. Possibly this is a vocabulary question. Are there any examples of parallel coexisting vocabularies in a particular field that have a crosswalk built between them? Sometimes that does happen. I'm aware of examples in agriculture. I'm pretty sure that AgriVoc has mappings from concepts within that vocabulary to like or similar concepts in other vocabularies. And this can be a way of helping to bring different well data that's associated with different vocabularies can be a way of helping to take a step toward bringing that data together by expressing relationships at the level of the concept. These might be direct relationships from the concept in one vocabulary to a like concept in another vocabulary. Or another approach is to express relationships between a number of vocabularies up to a what might be described as a backbone or a pivot vocabulary or an upper level vocabulary. And in that case, it can be less maintenance over time because rather than creating a mesh of relationships directly from one concept to another, you have connections made up to common upper level concepts. And essentially you're hooking up trees from a vocabulary into that upper level vocabulary. So, yes, that does that does happen. And there are some approaches to expressing relationships between concepts in different vocabularies. Great. Thanks, Rowan. OK, now here is it's actually a question for me because it is about the prerecorded videos that our attendees have watched. So in a video presented by Liz, she made a reference to Principal I3 and that is metadata should have qualified references to other metadata. And the question is what exactly is a qualified reference? So Principal I3 without being incredibly explicit about it, unfortunately, it is implicitly talking about linked data and the idea that a piece of data or a piece of metadata can be linked to another piece of data or another piece of metadata with an explanation as to the nature of that link, which is that qualified reference. So, for example, you could have metadata about an author or a data creator and there is a link from that person's metadata record to a metadata record of one of their data sets, saying that this person is the creator of that data set. And there might be a reverse link as well from the data set to the creator, saying this data set was created by that person. So the idea is that these qualified references create semantic links that not only let you understand the existence of relationships between objects, but also understand the nature of that relationship. OK, here is another vocabularies related question. So how does the ARDC fit in with some other organizations that might manage data vocabularies or dictionaries? Now, for example, the Australian Institute of Health and Welfare has a range of data dictionaries related to health and community services and disease. There are quite a number of domain based registries of vocabularies. And one of the differences with the ARDC service is that it is cross domain. We're interested in publishing and enabling access to authoritative vocabularies from any number of domains. And that and we would also be interested in being either a primary point of publication or a secondary point of publication. So, for example, some of the vocabularies that ARDC publishes in the Australian service are available elsewhere in North America or in Europe. And certainly some of the resources available in AIIHW, I'm thinking in particular of their code lists, could be of a type which might be able to be represented in a format that could be made use of within the ARDC. And as we see, sorry, within the ARDC service, and as we see more registries of vocabularies becoming available internationally, we see increasing discussion in the vocabulary community about the scope of efforts around vocabulary, registry, interoperability, which would enable different registries to draw in and enable access to vocabularies that are accessible from other registries. So why would you want to do this? One reason may be to have multiple points of access, in case one access point falls over. Another reason can be that maybe one registry provides a type of service, a type of access, which is not available from another registry, or it could simply be a case of having a registry geographically closer. You might get a faster response than one in another country. So other, I suppose, areas of interoperability and ARDC is really interested in working with other registries in that way. Great, thanks, Rowan. Now, we've actually had some, while we were answering those questions, some people have been contributing to the discussion because with a few clarifying comments. So one comment here that, for example, in health and medical areas, so this is around consensus building. So in health and medical areas, consensus statements are often published by the relevant lead professional organisations such as the Royal College of whomever, whichever discipline of health and medical or sub-discipline, rather. And somebody has been brave enough to talk, to mention an example of a schemer and system that was not terribly interoperable. So an attempt at Western Sydney University's Adela project. And it was originally supposed to be interoperable with the European cell project. But unfortunately, it was not quite set up correctly with the right fields and the right systems to actually be able to contribute to that cell project, unfortunately. And then an example of a meta vocabulary that in the dark combines all the other vocabularies. Sorry, nerdy reference there. So the unified medical language system from the United States National Institutes of Health National Library of Medicine is a meta vocabulary that helps combine or link together the other vocabularies. And then a question about the fairness of vocabularies. So this particular person has been working on a project that ferrifies vocabularies. And apparently in that case, they're called semantic artefacts. Do we think the panel that is necessary that the vocabularies, not just the data, but also the vocabularies used to describe the data or used in the data are fair? Well, Rowan's nodding and look, I... Yes, yes, it would be helpful for these resources. And I'm aware of some of the efforts around this looking at what sort of properties should we reasonably expect to be associated with any vocabulary to make it more explanatory and give provenance and give information about authority. And so I think if you're working on one of those initiatives, that's a great endeavour to be involved in. Yes, absolutely. And I think to myself, you know, if a vocabulary is not fair, so an unfair vocabulary, I ask myself how useful it actually is and especially in the context of interoperability, where we do want people to or anybody, when they're describing their data or using vocabularies in their data, we would like that vocabulary to be a vocabulary that other people use as well. And so there are certainly some fair elements then involved in that. OK, now here's an interesting question, possibly a little philosophical. Could a common key language assist in targeting links between disciplines? Now, that's an interesting one. So I've been debating over the the meaning of certain words with some colleagues recently, and I think that certainly directly lead to me. Highlights or indicates the issues of of language, of any kind of human language, especially where words can have ambiguous meanings and mean different things to different people and especially have different meanings between different disciplines. So I mean, from from my point of view, I think one of the biggest misunderstood words is the word theory, which when you use in science, theory, a theory is considered essentially to be fact. Whereas in common vernacular usage, when somebody says, I have a theory, what they're referring to as the scientific principle of a hypothesis, which is the case of, I think this is the case, but, you know, I need to collect evidence to make that the case. So you have lots of people saying, oh, the theory of evolution is just a theory. Well, scientifically speaking, it's considered essentially fact. And then, but even then between disciplines, there are different meanings for the same words. So if you ask a librarian what a database is, you're likely to get a completely different answer to if you ask a computer scientist what a database is. I mean, there is some commonality between the two, but they are I think there's enough difference between the meanings to possibly cause confusion if you throw the word database into a document without a little bit of clarification as to exactly what kind of database you're talking about. Although, Roland, you're the vocabularies guy. You probably have a few more thoughts about this than I do. I was going to ask you about what I'm not familiar with the terminology of a common key language. What's that about? Well, I'm sorry, I understood there to be a comma in there. So could a common comma key language assistant targeting links as opposed to a common key language? Now, sorry, if the if the person who asked that question could let us know if a common key language is a thing, that would be great. And here is our last question that's come up so far. What is the difference between a vocabulary and a terminology? It sounds like one for Catherine. Just a vocabularie. There are probably some there are probably some definitions around it. I suppose the terminology about what these things are is itself overloaded. And one person's terminology can be another person's vocabulary. This came up recently, again, in discussion around health and medical services. There's a national vocabulary service, the National Clinical Terminology Service, and they provide access to a major health medicine vocabulary called SNOMED. And they refer to SNOMED as a terminology, and it's provided through a terminology service. And yet I would understand it to be a vocabulary that perhaps a more complex vocabulary than we might typically see represented through SCOS, through the simple knowledge organisation system. SNOMED is quite complex. It has a large number of specifically typed relationships between things that are more specific than just generic concepts. But yeah, I've heard these terms used interchangeably, taxonomy, terminology, vocabulary. I don't think I'm able to offer anything more specific. Do you have some thoughts on this, Catherine? No, I like your answer, Rowan, about well, yes, it's really the semantics around it, but some people's vocabularies and other person's terminology, I do like that. I mean, really, you're looking whatever it's called, you're looking at how authoritative it is and how it's well structured and all those other things that you might look around a vocabulary. And I suppose what it's known by may, though distinction between those things at the meaning may have been lost over time and in some senses have come to mean the same thing rather than something different. It sounds like an examination of said vocab or terminology would only be the only thing that would reveal whether suited your purpose anyway. And I just went and had a check of the dictionary. And then look, I mean, a standard dictionary doesn't necessarily reveal very disciplined specific uses of terms. But interestingly, the first definition I found for terminology was the vocabulary of technical terms used in a particular field, subject, science or art. So I think that does sort of lend itself to Rowan's interpretation of terminology, vocabulary being used interchangeably. And again, I think that's a classical example of where confusion can arise when people use different words to mean the same thing or use the same word to mean different things. So perhaps what we need is a meta vocabulary that defines the difference between a vocabulary and a terminology. Those definitions become recursive, though. Don't know about yours, but I think that one you read out is both vocabulary and terminology in order to define it. Yes. And here, somebody else has introduced another term. So an overarching term for a vocabulary used by a branch of knowledge is a lexicon. So look, we and somebody has now commented that their head is exploding. So perhaps we need to pull back from this from this part of the discussion. Although that being said, we are coming up to time and we haven't had we have got some discussion happening here. And in fact, here's a reference to NKOS, Networking Knowledge Organization Systems. And I believe that's being raised as an example of something that does help define knowledge systems and or rather knowledge organization systems, which, yes, we could talk about all day, but we won't. So in our final moments, so unless any more questions come up, well, I'll start the wrap up of this session. So in fact, I think I need to go back to sharing my screen. So if anyone doing the course has any particular technical issues with accessing the quiz, with doing the activities, please either contact Nicola Burton directly or bring them up in the Slack. Maybe you'd like to discuss one of the activities. And we do have a discussion channel in the Slack workspace. We're also welcoming any kind of silly discussion that you might have if you have a GIF or a meme or any terrible fair puns. Now, when this webinar finishes, you will be asked some questions for feedback as with previous webinars, and we do use this feedback to improve future webinars. So thank you very much for all the feedback you might have given to a previous webinar. Now, we have not had any more questions, but we are getting all the thank yous rolling in. Actually, there is a comment from somebody saying we do not need more terms. So I'll leave that with you, and otherwise, I'd like to thank you, Catherine, and Rowan, very much for your time and for sharing your stories with us and being on a somewhat philosophical panel. And to everyone else, thank you for coming and have a fantastic day. Thanks for this. Thanks, Catherine. Cheerio, everyone. Thank you all. Bye.


Hey there friends, thanks for checking in at the range. Now we've got the new Steyr L9A2MF. Let's see how it goes. Nice. The L9 has a 4.5 inch barrel and the A2 are the new models that Steyr is coming out with. It has a redesigned grip that offers interchangeable back straps, and grip panels. It has front serrations, a 1913 rail, same trapezoidal sights, a flared out magwell, a very nice shooting and comfortable gun. Now we're used to that with the A1 models but this is phenomenal. I mean this is my second or third time at the range. I really like what Steyr did. They also extended the beaver tail for more control. It does have a loaded chamber indicator right there on the back plate of the slide, a button pops out. That way you don't have to unholster the gun. You can rub your thumb across here to make sure you have a round chamber and also a sight hole indicator where the barrel meets the slide. Let's try it again with these trapezoidal sights. It's got a triangle front sight, angled rear. You just fill in the triangle with the angles in the back and it's pretty dead nuts. It's kind of like you're cheating. I jumped on that one. The A2MF has a modular frame. That's what the MF stands for. The serial number is right there. It is imprinted on the internal chassis which makes this modular. Steyr will have exchange kits for different grips, different colors, different sizes, and everything a shooter could want in a modular platform. Here we have steel case 9mm made by Barno. Steyr L9A2MF. Let's see how it does. Ate it all up no problem. So there it is guys. Steyr L9A2MF. Many people were wondering when Steyr is going to have this in the country. They are expecting them to be in mid to late summer. Really not sure at this time. It could show up sooner. I'm sure they'll let you know. But there it is. Very nice handgun. Great improvements made. I'm so impressed with it and happy to have this at the range and showing it off to all of you guys. If you like videos like this, please subscribe and share. I always appreciate the thumbs up button. Thanks for watching and you guys be safe.


after several years. And for the last seven, eight years, people have worked on tokenization, with an asset tokenization, deposit tokenization, bond tokenization, etc. But the cool part about 2023 was rather that this was the year when instead of things moved out of pilot stages. So while pilots had been going on for so long, we started seeing real transaction volume taking place. So today, Onyx does around a couple of billions of dollars of transaction every day. In the month of November, JPMorgan said that they will be creating their own L1 platform. And also we have seen that number of them have been moving towards L2. So this is the year in 2023 where we saw that actually tokenization came out of the shadows and finally started moving into the production stage on both traditional finance and T5 space. And it became the buzzword, even the likes of Swift. So Swift, of course, everybody has been predicting this, but in 2023 market Citibank started its own prediction, etc. And even the traditional finance giants like Swift, you all know about that they started working with T5. So that has been the thesis we started working a couple of years back as well. Of course, our asset class was very much specific. Like typically we have seen that when we talk about asset tokenization, equity, bonds, T-bills, they have been and of course real estate have been at the forefront. World and blue had children, at the other hand, to work with commodities and mind you, not gold but agriculture commodities. So essentially that is what we have been doing. And we have been developing layers of, we have been building the entire stack and we have been building layers of that stack. So the first effort started with, of course, commodity tokenization, wherein we adopted a policy of asset tokenization when the assets are stored with third party custodians. Then on top of that tokenized asset back lending, which we have, I mean, maybe very surprising to many, but we have been doing tokenized asset back lending with TRIAD-5 banks in India for last more than two years, almost three years now. We just launched a couple of months back, a tokenized commodity exchange. And when I'm saying commodity, these are all agri-commodities. Then we also launched DeFi in last, in 2023, April, which is blue finance. And that is the stack which we have built today. Now we are, of course, expanding it further. We are working on taking the solution to an import or export using tokenization. And of course, which has been something, supply chain tokenization has been paying under work for a lot of time. But our approach has been a bit different. Our approach has been to start with asset tokenization and build slowly the stack on top of that. So that is something global commodity finance is what our core focus will be. And of course, in that a lot of infrastructure building is also required, which we have been doing or we will be doing over a period of time. For example, when we started working and we needed Oracle data, we started working with IOTs. And what we realized that the cost of IOT was quite high and we had to leave that path. But now once again, we are launching that under a deep in structure, means decentralized infrastructure on physical infrastructure on blockchain. So we will be adding that over a period of time as well. So this is the stack which we have been building for the commodity market. The first commodity stack was, of course, agriculture commodities, but in future, other commodities will also come over here. Excuse me, are you advancing the slides or is it still on the first slide? No, I'm advancing the slide. Oh, I don't see the slides advancing. Maybe there's something. Oh, I'm so sorry. Oops, that's that's a huge huge. Oh, I went on slide number four in this meanwhile. Wait a second. It's, am I changing? Are we changing? Yes, now. Okay. So let me just then I will take 30 seconds. So this was the first slide we talked about that tokenization is finally moving out of the pilots and POCs and has come actually in 2023, we saw that already happening. A lot of work happened on the mennet levels, also onto the private blockchains. One more shift we saw happening and which in my opinion will be a bit, it will be different from how we have seen that. So we saw enterprise blockchain, we saw public blockchain, but in my opinion, over a period of time, we will move towards a world where these two will be, and that is something even Basu is doing with Hyperledger, that perhaps we may have, may move towards a world where the transactions happen on specific chains, like Apollo is saying elements, or it may happen on L2 like Nomura is developing. And those will be supported by the security of a large element, for example, Ethereum or Solana instead of the previous model where we were building enterprise blockchain and then we are adding DeFi. In my opinion, slowly the things will change. So that is one thing we have been seeing. Secondly, I was talking about this slide, what is happening in the tokenization market. Third, this was the slide I was talking about, that we have built a stack on the commodity sector. So we started with tokenization as the base stack, added to add file lending on top of that, added decentralized finance on top of that. And just last to last month, we have also started a tokenized commodity trade platform or tokenized commodity exchange. Only for physical commodities, no derivatives over here, so no securities. And of course, our idea is to take it to a global. So this is where I was. And so the core idea when we started talking about tokenization of commodities was several, I mean, there were several factors which we saw that we can solve by if we bring the commodities on the chain. And I have been into the commodity sector for more than 10, 15 years, even before I started into blockchain at least 10 years. So that experience was why I chose commodities instead of equity or real estate. So the first thing is that commodity markets, especially the physical commodity markets are highly fragmented. And the reason being is that physical commodity markets, unlike pure financial assets, whether those are equities or crypto digital assets, require consumption and that plus they require logistics, they require movement of commodities from one part of the world to another part of the world. And that creates friction into the process, but also it creates very highly fragmented markets because there are a lot of intermediaries into the chain. So if we can remove few intermediaries, then of course we are in a position to remove some of the problems of fragmentation. And that was one aspect why we started working on commodities. And the second part is commodities markets have a product called commodity finance, which is essentially inventory financing. So commodity cycles are in such a way that everybody in the supply chain ends up holding a lot and a lot of commodities. It means your lot of money is locked into a lot of working capital is locked into that inventory. So commodity finance is a way to solve that inventory problem that liquidity is provided by giving loan against inventory. And that's a global product commodity finance is $250 billion product across emerging markets across European markets. Anywhere you see commodities, you will see commodity finance. But what we have seen and we have seen in many markets that this market is prone to high level of frauds, whether the frauds happen in India, China, South East Asia, Singapore, these are some of the examples. Latin America means almost at every point, every bank of the globe has suffered in commodity finance. And as a result, many banks actually have pulled out of this and hedge funds are currently the real players into this market. So that was the second thing that how do I create a commodity finance market, which is less fraud prone, because the fraud was largely double spend problem multiple lending at, I mean, all these, whether you see NSEL, Qingdao, all of these are about multiple lending against the same collateral. Only Access World fraud was different in the sense that Access World is a Glencore subsidiary Glencore is a well-known in the commodity markets. So in physical commodities and Access World was just a duplicate fraud, a duplication of deposit receipts. But other than that, most of it has been about multiple lending. So we thought that blockchain will be able to solve that. So we created a product that goods, I mean, the product was already there, goods are stored in bonded warehouses, inventory is stored in bonded warehouses. Loan is given against that. We brought that on chain. So we brought the commodity on chain and we brought the commodity finance on chain. So that was the core idea, how do you reduce fragmentation? And secondly, how do you reduce frauds? Today, we are one of the large blockchain platforms in asset tokenization space. Of course, in India, we are number one. We have already tokenized approximately, this number has gone to almost $700 million now. In terms of asset tokenization, we have a network of 1500 custodian warehouses. We have already served and I'm talking about retail customers here, approximately 20,000 participants starting from the level of farmers to the level of intermediary traders to also processing mills and commodity processing mills and so on. And we are working one of the few institutions across the globe to work with traditional finance institutions on tokenized asset lending. So we are working with few of the names in India. We are also working with the government sector and that has been going on over there. So this was our journey started on the private blockchain under the umbrella of and it is still going on under the umbrella of brand name of world. We added group finance on top of that. And when we added group finance on top of that, what it did that, it allows the liquidity to flow in either from traditional finance banks or from a decentralized finance protocol, depending upon where the liquidity is cheaper. So two years back, DeFi was cheaper and traditional finance was actually costly. Now traditional finance in India is cheaper, actually speaking, after the rate I can in the US market. So how the system works, very simple. These are commodity owners. They can be like very small farmers. We have given loans of less than $100 as well to farmers and they can be large traders as well. They can be institutional traders as well or they can be institutional mills as well. They have commodity as inventory. They bring this inventory to a bonded warehouse. Why bonded warehouse means this is a third party warehouse. This is not in control of the borrower. These are the warehouses on our blockchain network and the goods are deposited. They are verified, verified both using technology. So we have brought, as I said, we started building with IOT, but we have machine learning solutions deployed here. Plus there is a physical verification agency as well and the price of the commodity is determined using price of accounts. So based on all this data, we create commodity non-fungible tokens, which go into the platform and then that can be used as a collateral against which both of our traditional finance banks or the DeFi lenders, both of them can lend. DeFi allows us access to the global market, TradFi allows us access to the regulated Indian market. But of course this same model can be taken to any part of the world and the same model can be used for purpose of lending by people across the globe as well. This is take-out-to-ticture, essentially the same thing shown in a different language because the part is about TradFi and DeFi. So how we have done that. So the one which you see on the left-hand side, this side, this is our private blockchain, which we have created on Quorum. So Quorum was our choice at that point of time. So these are the same borrowers or depositors that bring their goods to the assets, custodians. There are banks, there are asset verification agencies, all of them write data on our private blockchain. That is where the permission blockchain, that is where the assets are essentially tokenized and created as an NFT. If these are banks as a lender, then the entire transaction gets closed over here. There is nothing which goes on to the public blockchain. But if DeFi is a lender, means someone is lending from a DeFi protocol. So we have created a bridge between the permission blockchain and we are here on Polygon. So between Polygon and the permission blockchain, we have created a bridge. The bridge sends NFTs or the collateral to the Polygon network and takes the liquidity from Polygon network to be given back to the borrowers on to the check. So for the interface level, we have interface over here, typically web applications, also a mobile application. And here it's a pure mobile based interface. But whatever the interface at the end of the day, the core idea is that the assets are minted on a permission blockchain. And later on, if there is need of DeFi intervention, then they move towards the DeFi protocol. This is the same thing which we did. Essentially, we have already talked about. So what I will do, sorry. And the core idea here was, so of course there are other DeFi products or protocols who are doing RWA financing. How we differentiated ourselves over here is that typically all the DeFi protocols require a fintech. They work with fintech, they work with third party. And thereby, the benefits of decentralization actually stops working. So for example, a DeFi protocol will give loan because when they are doing RWA, not when they are doing digital asset playing. But if they are doing RWA, they will give loan to a fintech. Say for example, in Indonesia, the fintech will acquire customers will give loan over there and take the money back from the borrowers as part of collection and pass it back to the DeFi protocol. On our platform, at the other hand, there is no third party in between. As you saw that everything is, I mean, of course there are players, but all of them are connected through smart contract. So the money doesn't goes to world or money doesn't goes to a third party fintech. Everything remains on chain. Each part of the transaction remains on chain. So the borrower directly dips into the pool and takes money from there by providing their assets. So there is no third party coming in between. So end-to-end integration has got that benefit. And that means that we have been able to also create some sort of social impact over here. So I will take a pause over here and if there are questions, I can answer that now. Or if there are specific areas on which you would like me to focus, I can bring that into the discussion away. Don't hesitate, guys. Please ask questions. Of course, it has to be Jim first. Right. Thanks, Bipin. So yeah, my big thing on the DeFi and the traditional banks is they usually have very, very different rules and regulations that they have to comply with. So my guess is, and this I need your help to understand it better, but I'm guessing your platform has to accommodate those differences in regulations in a sense. So if I'm borrowing money, if it's coming from one of the DeFi things, I have a different set of I assume rules and regulations, they're going to apply versus me borrowing from some commercial bank or the equivalent of that in India. Does that make sense? 100%. So actually speaking, DeFi regulations have yet to be framed in many parts of the world, right? Even the USA has not regulations and is rather saying that the existing regulations apply. And in some countries like Japan, Singapore, etc. have already created a framework. India is one of the countries which has decided that they will only go for regulating the assets, except for a few things, only after G20 adopts the regulations. So that way we have no regulation. We have a regulatory arbitrage over here, but you are pretty much right Jim, that when it is a bank lending, we have to comply with every regulation related to the banking sector. And that's how we build the solution. That is why the initial solution was built on permission blockchain. It used quorum, where private transactions was possible. I mean, that was before Hyperledger brought private transactions. And we built it through the solution from that perspective. So as of today, we are in a position to follow the regulations related to banking sector, even if we are into the DeFi, because the core was built using those regulations in mind. Alright, so then the other thing that in the US, if we're doing the same thing you're doing and had to comply with regulations, one of the challenges here, and I don't know if it matters in India or not, don't know, is here, if I were operating in this network as a participant and I wanted to borrow money for whatever I'm selling or buying in this ecosystem, if I'm doing that in the US, the banks that I would be borrowing, getting my loan from, would be required to support AML sanctions real time on me. So if I'm a legitimate borrower last year, and all of a sudden, the federal government now puts a sanction on me as of today, the bank has to say, oh, I can't give you any more money, among other things that they'd have to take as an action, because the sanctions are real time. Do you have to deal with sanctions at all? So India now applies AML regulations on any crypto participant, including exchanges, including DeFi protocols. So we have to follow that as well. Alright, so every participant in the DeFi side then is a known entity legally to you, exactly. We don't work without KYC. Excellent, thanks. Yeah, it's not pure DeFi that says that it's not anonymous, it's not sensitive to this trend. But the core idea of DeFi for us is that how do we pull global liquidity into a global South? So for example, if Jim wants to give loan to a farmer in India, he can use our protocol to do that using stable coins. Excellent. Money. Yeah, it's a great presentation. Can you, I missed the part about the cash movement. How does this cash work through the system, both on your private network as well as when you work with your DeFi side? So that's where the problem area is still is. So where that is where once part remains, it still remains on traditional financial side. So how we do that just allow me a second. So if the cash movement, if it is a banking transaction, okay. So as we saw that the banking transaction happens entirely on the permission blockchain. But one part which is not on the blockchain as of today is cash movement. Because we have to use react for this purpose. So what we have done that we have connected our platform to the banks core banking system. And as soon as there is a cash movement that gets registered onto the blockchain. But real cash movement in the trade file ending doesn't happen on to the blockchain. So we actually speaking India has launched a CBDC. We participated and we went to the finals. We did not win the finals, by the way, with the same proposition that Indian CBDC should be used on our protocol for lending to farmers, whereby we replace the fiat currency and we bring the CBDC so that this entire transaction happens on blockchain. So that is one part which still remains as of today, outside of the blockchain. But once the CBDC comes and once some of the banks we are working with are permitted to use CBDC for that purpose, we will be able to use that. Coming to the DeFi side. So on the DeFi side we use on-ramp offering solutions. How the cash movement happens on the DeFi side. So on DeFi you have two players. One is the borrower and one is this liquidity providers. So say for example, James sitting in the US and here a farmer in India. So how it happens that the liquidity provided provide stable coin liquidity into the group pool. And in the group pool when they provide liquidity, the stable coins come into group pool. We convert that stable coins into first of all, we convert them into dollar and then we convert that dollar into Indian rupee and give Indian rupee to the borrowers. Of course, we case that exposure as well. When the money is returned because we give only six months loan, we don't give high duration loans. So after six months when the money is returned, that figure currency we receive back from the borrowers, we convert that into stable coins and we send it back to the liquidity providers. I hope I was able to make it. That's great. Thanks. Sure. Thank you, Mani. By the way, if anybody goes back in history to the development of the federal reserve and the subsidiaries, you can say that it was due to the seasonal nature of agricultural commodities in America. Back in 19th century, America was a very powerful agricultural nation. Well, it still is. But the financing ebb and flow is what created the federal reserve. Financing of agricultural commodities is a basic feature of finance. In fact, it might even be the foundational feature of how money and finance started. In a sense, you are striking at the base of the system. I have one question for you, which is, I noticed that you are on a 2 to 4 percent fee. The fee structure is 2 to 4 percent, but others are 0.4 and 0.5 only because they are only dealing with the part of the system. Or how do you justify, because there is a lot of focus given to the fee structures, especially, for example, the Bitcoin ETF coming up, and could you comment on that? Sure. So, we've been there are two parts. When I said 2 to 4 percent, actually speaking, we are still cheaper than others because when you have a fintech in between that, fintech takes 10 percent. So, while the DeFi protocol only earns this 0.4, 0.5 percent, the fintech, which is working in between, which is taking money from here, keeps a spread of approximately 8 to 10 percent. Happens in India as well. In India, fintechs borrow at 15 and lend at around 24 to 30 percent. We are the other hand, the total cost starting from end to end is 2 to 4 percent. So, it means that we have been actually able to cut it down significantly and still keeping that on our books. So, in case of other DeFi protocol, it gets divided between the books of the DeFi versus books of the fintech. Here, it accrues on our platform. Second part, the on-ramp, off-ramp solution itself takes away approximately 1.5 to 2 percent out of this business. So, as a result, we are not actually, I would say that, enriching ourselves a lot by exploiting the borrowers. We have actually reduced the fee significantly into the ecosystem. Today, the rate of lending for me in India to the farmer segment is 9 percent per annum. That is just 1 percent above the mortgage rate in the USA. So, we have been actually able to, and that is actually speaking microfinance in India is in the range of approximately 24 to 26 percent. We are at 9 percent. So, we have been able to reduce the cost using this entire structure. Despite the fact that a lot of that money accrues on our platform. Significant portion also goes towards the cost, but it accrues on the platform. So, that's the benefit that our revenue goes up comparatively. Said that, we have cut down the cost of lending for the borrowers by 50 percent to 70 percent as compared to microfinance or even traditional lending ecosystems. The only reason I brought it up was because it gives this particular slide wrong impression. Actually, this slide was not meant to be here. This unfortunately, I opened a deck which is an investor deck and not a product deck. So, that's where this came up. Yeah. Okay. There are those other questions which I had posed to you, which we will go into especially now. One of the things is the volatility. Meaning, when you're maintaining your treasury in multiple types of instruments, let us say Ethereum, let us say Indian rupee dollars, the volatility of each one of these moving independently of each other would also affect your treasury, so to say. So, the treasury management becomes a very important part of this exercise. I wonder whether you could comment on that at all. Sure, Vipin, I fully agree with you. So, as a result, what happens is that we only deal in two currencies. We deal in stable coins, dollar-back, so only USD. And secondly, right now, the native currency, which is India, if we go outside of India, there will be another native currency. So, we are very much, because when I jumped into commodity markets at the same time simultaneously, I came into currency markets and have been working into currency and I was in 2008 when currencies went like, especially emerging currencies went haywire. Some of you would be there during the 97 crisis as well. I was still in college then. But what I'm trying to say that we have been very much focused. We don't take the liquidity in terms of digital assets, means no Bitcoin, Ethereum, nothing like that. Only stable coins. That allows us to manage the volatility comparatively between only one currency pair, which is USD INR. When we go to other countries, it will be USD, maybe since if we go to Indonesia, it will be USD Rupiah and so on. So, that is where our focus will be. How do we manage the currency risk only for one pair of the currency instead of having so many pairs. And second part is that we hedge the entire exposure. So, that is because we are dealing with small borrowers who typically don't have any idea how the hedging happens. And secondly, many of them don't know that the liquidity is coming from a dollar pool. So, for them, it's the converted INR. So, they don't even know that they have to hedge that. So, we take the hedging position on their behalf. So, trading management is certainly very important for us and we are focusing upon it and that's why we have kept the exposure highly reduced at this moment. Thank you. Anybody else? Any questions? Hi, I had just a quick operational question. I think you can answer pretty fast on that screen that's up right now on the architecture. So, if I'm a liquidity provider, there's this web mobile app. Are wallets involved? Is there a hot or cold wallet involved to transfer from PI to the crypto? Yeah, so there is a wallet. So, if you are a crypto, so we have created it for both crypto natives and non-crypto natives. If you are a non-crypto native, but that is only for Indian people, they can give us INR directly. So, we accept INR here in India as well. Otherwise, if you are from outside of India, you will have to give us a stable coin through your wallet. So, the moment you open the mobile app or you open the web app, it will first thing it will ask you is to connect your wallet. Because what also happens, we also give because these are over collateralized loans, so we also give the collateral, we also bring the collateral charge creation in the name of the same wallet and also we transfer the interest in the same wallet. So, wallet connection is required for all that purpose. Because the part of yield also comes in blue tokens. So, for example, if we have to provide yield today, so it will be approximately say 8% on dollars, we add yield plus 10% blue token yield. That is where the DeFi benefits start coming in, that the yield is not coming from the lending activity, but the yield is also coming from being part of the ecosystem and in the form of a token as well. Where is blue traded? Blue is not yet listed, but we are working on listing it by a month of effort. So, right now private markets will do finance tokens, but not yet publicly listed. Maybe we will take it offline, a bit more technical question about the whole quarter of infrastructure. Maybe can I reach out to you later? Sure, money anytime. Yeah, maybe if you can share with me an email, I'll reach out to you. So, at this time, I have to also say that money is going to make another presentation here, where he is going to link the entire, you know, his thought process are system-oriented. And so, his product is going to link both the payment side into the picture. And also, when you are talking about other financial, like equities and other things, then you need some kind of, you know, clearing, exchanges, a lot of financial market infrastructure, which is actually being worked on today by people like LSEG and the Euroclear people, and mostly on, I mean, some of them are on Corda, some of them are on other blockchains. Yeah, we just want to clarify, I mean, the focus will be on more on privacy, privacy on the chains using zero-knowledge proofs, and how we are implementing enterprise alleges. This is just the first of its kind. Yes, because that's essential for all implementing all of these things, like order books or any kind of cap tables. Any payment, payment, payment, you need privacy, and that's fundamentally to be a solid problem. Yeah, so even if you're focusing on that, that is in pursuit of creating the trading of what we can call it, RWA, for lack of a better term. But they are all different kinds of RWA. There are dematerialized RWA like shares and stocks, and there are actual physical RWA like commodities in real estate. So when we have this veil of the market laid over the whole thing, then we have more interoperation between all of these commodity types and payment types. Anyway, go ahead, Ashish. Sorry to hold forth on certain things. No, that's a great idea. So I mean, that's the thought process as money mentioned, that privacy using zero-knowledge proof and all, because if we want traditional finance to come on to, or if we want a measure of traditional finance and defect finance, then certainly we will require these services, we will require and as we are seeing that the ETF is coming up and people are saying, hey, it is all against decentralization, that you require custodial and all, but without them we are not going to move anywhere. So those things will be certainly required and people are building that and I would love to discuss money, because I have my own thought process on should we build something on those lines. So would you refer to this also as a supply chain trade finance solution? Over a period of time, yes. Over a period of time, that's what we are actually taking a solution to that our focus market is commodities. So whatever happens in the commodity business, we would like to be part of that over a period of time. So right now what we are doing is inventory finance. We are providing the inventory, we are taking the inventory in the warehouses, bonded warehouses, giving loan against that, but that's a very pawn market sort of a structure and then we have just started the tokenized commodity exchange. So the third step which is coming up is of course the supply chain finance and over a period of time, of course, the idea is that how do we use tokenized tokens transfer as a tool of import, export and if we are doing that, how do we bring import, export, supply chain financing. So all that is part of evolving stack for us. So if you have more material, otherwise we can continue this discussion or you can go ahead and Okay, so I will then maybe I mean the other discussion was there, but maybe I will just take this slide small one and the core idea of why we use blockchain was this one that how do we how do we solve the multiple lending or other type of fraud problems or this. Also, one question always happens that what about the commodity physical controls because you are saying that, hey, I have these assets and these assets are in the control of the warehouse, how do we ensure that. So for that we have certainly built certain machine learning solutions, we have put data from many places. We are also working with one of the largest warehousing, we are in the process of working, it is on will take a lot of time, but the largest a lot of time in the terms of procurement process of the government, but largely, we will be working in a such a fashion that how do we use intelligent machines to have a to have a control on the movement and also notification of the movement of the goods. So we are working on that pilot is going on and hopefully in next few months it will convert into a full place last project. So that that's because physical thing remains a challenge, especially in commodity space. Also given that in India, especially or in other parts of the world also in some parts of the world, like in the US you have storage in large silos. So the value stored in a particular silo is very high and you can deploy a lot of costly technology solutions. But here in India, we do storage in a 50 kg bag, a 50 kg bag of weight is approximately $20. How do you put something in that $20 bag and how do you monitor that? So that remains a challenge, we will be working on solving that. And the second part was that we have been able to reduce the cost, we have been able to create a centralized lending process for the lenders and so on. So that is where we use technology to solve some of the problems and some of the problems are being tried to be solved over a period of time. We are seeing that a deep in infrastructure network of IoT solutions, intelligent cameras and so on to come over here. And we will also see that we are also planning as I discussed earlier that how do we merge all of that over a global trade platform. So that's all I believe for me to say but I would love to have further discussion if there are any questions on that or any specific part which the people would like me to talk about. One of the things that comes up is whether what to do about default, that's one. The second is what is to be done about deterioration of physical commodity. That is what happens if rain or any kind of insects or rodents attack the product. The third of course is that you are obviously not going to lend against commodities that are extremely fragile or extremely volatile. Those are the three things regarding that including liquidation in terms of default would be great to talk about those. Did he disappear? Looks like he did.  Are you guys hearing what Ashish is saying or Jeff is saying? I don't see him either. It does look like he's gone as a participant. So now I'm going to VIP and you can pick it up from here. Well I mean you know these are the questions that I asked him to address. Well here he comes again. He's coming back in. Oh beautiful. I am so sorry I just got disconnected for a couple of minutes. Yes so the question arose I mean I asked three specific questions dealing with the physical commodity. One is default. Second is decay or destruction of the commodity due to improper storage or due to some extreme events. Third is of course how things are getting liquidated. Okay so I can take one by one. So in case of default and liquidation will be intellect right? So what happens in case of a default that if it is of course stratify bank we don't need to worry much about how do we work on the default because it's when the defi is there then we take care of the default process and the liquidation process on behalf of the liquidity providers. So that's one intervention we have to do. However the good part about this asset class is commodity is highly liquid asset class. So it's not real estate. So you have an asset class which is highly liquid which can be sold in almost any part of the work means of course you can sell online. We have our own trade platform where it can be sold but even if it is to be sold physically we can even sell it in a small village or maybe rural market, small urban centers as well. So we actually speaking in last two and a half years of giving loan we have zero default. We have zero case of for liquidation. Of course the track record will not be maintained forever but we are ready for that eventuality. Actually speaking that was the core idea of providing the exchange as well that one idea of exchange is by trading people are essentially selling goods and we are recovering our loan and the interest from that sale proceeds itself. So that helps us in collection and we can use any day to sell online that commodity. Secondly we can sell offline as well. So those parts are there we have physical infrastructure where houses are there which are manned by people and those people are actually in a position to sell it in the market as well. Coming to maintenance so in maintenance terms there are several aspects. One each and every penny of the commodity on our platform is insured. So actually speaking because we work with a lot of government sector total insurance at any given point of time on our platform because of the government's own insurance policies and all. I mean last few months back it was approximately it was approximately I would say that a billion dollars because they have a stock which is tokenized but they also have other government stock and they have to take insurance for that. So approximately less than a billion dollars but approximately 900 million dollars of insurance was there approximately six months back. So every penny is insured that's one against any sort of physical problems that may happen plus any sort of implied fiduciary fraud is also covered in those insurance policies. The third part is maintenance how do we ensure because insurance will not cover poor maintenance. So for that process what do we do that the maintenance records so there is a 15 days every 15 days there is a fumigation process and there are other processes in the warehouses which are to be carried out. So again those records of those processes have been carried out or not it's also available on the blockchain itself. So for every warehouse when they do those activities they put a record here on the blockchain and that is available for verification by the lander such man. Sounds great. Unfortunately we are running out of time so if anybody else has any last questions now is the time to ask or you can contact Ashish on his email and thank you Ashish for showing up and being so forthcoming about all your your platform and I think this is the place where RWA will start with the physical foundation. Yeah great great solution well thought out and you know want to see more of this as it evolves and you you are starting at the right place so I think in a sense the roadmap you have forward sort of makes a lot of sense logically at a point you'll integrate other standards and so on as you hit what I call different areas of what I call supply chain but for now you've really had a very very solid start well thought out so thank you for that. Thanks. Thanks a lot Jim. So Vipin thanks thanks a lot thanks everyone for listening so patiently and joining us especially quite early morning in some parts of the world and thanks the hyperlager foundation for giving us this stage. We would love to talk about RWA in future and hopefully whenever you are doing the physical event Vipin I will be there in New York to attend that. Yes we are going to have it probably in April sometime we don't know but it's going to be run by Jamil who has got one of the Jamil shake he's got one of the biggest networks of people. I think his hyperlager meetup has got 40 000 people so we are talking about numbers that you know there are beyond what we are capable of in hyperlager but it's going to be physical and he is planning a multi-day event or even a single day event and hopefully some of these products will feature in that. Thanks a lot and goodbye and good night. Thank you thanks everyone looking hopefully we will connect soon Vipin.


Okay, so John Friedrich with Meta Integration, John. Thank you. So I have precisely one slide, and it is only five minutes. They always say spend about five minutes per slide. There it is. Fairly simple picture, right? Now, we called it the big picture, and I say we because Christian Burma was going to be here, but unfortunately is going to be a little late. So it's just me, and but we called it the big picture, which of course could mean a lot of different things. I mean, if for example, you're in some kind of conference about, I don't know, string theory, I guess the big picture would look a little different than it does here. Actually, even within this community here, what is the big picture of course varies a lot. Now this is the big picture mostly from what we see as a company Meta Integration. If you know us at all, we deal with being able to exchange information, especially what people deal with in enterprise architecture, in master data management, et cetera. In other words, what we always refer to as metadata. And so what we talk about is being able to move it around. Now, why do we do it? Well, so all our partners can actually start to look at this big picture and start answering some things. One of the things to recognize here is because of the development, even going back, because of the development of relational databases and then all the stuff that came out of it from business intelligence, standardized ETL, all these wonderful technologies have allowed us now to get a good picture of the entire data flow architecture here, horizontally across at the bottom of this picture. A very good picture of it. In fact, we connect into just about every one of the technologies that is in the exhibit hall, one way or another, so that people can do that. They can take it and bring it together. And in fact, many of those partners have solutions to do that that we then feed. So it works out really well. The idea being that you can actually access all those different technologies, business, intelligence, data warehouse designs, of course data integration, ETL, ELT, that sort of thing. ODIs, any SAPBW, all that kind of stuff that would be in the enterprise, being able to capture metadata out of there and be able to therefore answer where do those business reports come from? And if I make a data entry over here, where does it appear? And if you can answer those questions, it's huge. You're answering things that the business user wants. And as we know, that's where the money is. Business users will define that. You can also answer a lot of wonderful information management questions. For example, if I'm going to make a change to a system, where will it impact, et cetera. Okay, we know all these things, but keep in mind, as I said, what has created that opportunity has been, in part, standardization and in part, the fact that very powerful tools exist out there that we can then take advantage of the fact that they have a standard way of doing it, at least within that environment of the tool. So what we've done, obviously, is put that all together into one nice picture. You have a nice end-to-end lineage picture. But the other thing that needs to be recognized that is equally maybe even more important, depending on which community you look at, this community probably even more important, is what we refer to as semantic lineage, but this vertical component. The idea is that there are, in fact, relationships that can be, and in fact, lineage impact, et cetera, type questions that can be asked vertically. And of course, actually, even from data flow issues, for example, change of something, what does it do to what is in your enterprise vocabulary? Okay, here's your terms. Then, what terms are those mapped down to in these reports that you wouldn't have seen data flow for? These are all huge, huge possibilities in terms of being able to answer, as I said, fundamental questions like, where's data coming from? Where does it go to? And therefore, how do I manage what is sitting out there? Again, five minutes, and I think I'm there? 30 seconds. 30 seconds, oh, I was looking at that one. So I'm pretty close to the end. Basically, what I'm trying to get across is a recognition that we're spending a lot of time, in a lot of ways, we have mastered, in a lot of ways, the data flow, lineage impact analysis problem. And we're just now beginning to really understand how to tie in the semantic lineage side to that. That's gonna be a big, huge push. I think you'll see a lot of the companies out there putting it together either through metadata management solutions, enterprise architecture, all that kind of stuff. Thank you. Thank you. Thank you.