Epicenter - Learn about Crypto, Blockchain, Ethereum, Bitcoin and Distributed Technologies - Micah Winkelspecht: Gem – The Enterprise Platform That Powers Data-Driven Applications

Episode Date: November 1, 2017

We are joined by Micah Winkelspecht, CEO and Founder of Gem. What started as a Bitcoin API in 2014 has evolved into a leading provider of blockchain solutions for enterprise. Gem addresses the problem of digital data silos and the complexities they introduce when companies and individuals collaborate and share information. Their product, GemOS, provides a full-stack blockchain middleware platform which allows companies to build applications on top of blockchains protocols like Ethereum or Hyperledger Fabric. Topics covered in this episode: Micah’s background and how he got involved in the Bitcoin space How the company and product have evolved to support his original vision How blockchain technologies are transforming process digitization The siloed identity problem and what complexities it introduces for people and companies How GemOS is addressing fundamental issues in health care and insurance How blockchain technologies can support regulated industries Micah’s insights on creating awareness among enterprise clients The importance of building ecosystems and network economies which enterprise can leverage Episode links: Gem.co This episode is hosted by Brian Fabian Crain and Sébastien Couture. Show notes and listening options: epicenter.tv/207

This is Epicenter. Episode 207 with guest Micah Winklespect. This episode of Epicenter is brought you by Shapeshift.io, the easiest, fastest, and most secure way to swap your digital assets. Don't run a risk of leaving your funds on a centralized exchange. Visit Shapeshift.io to get started. Hi, welcome to Epicenter, the show which talks about the technologies, projects, and startups driving decentralization and the global blockchain revolution. My name is Sebastian Kutu. I'm my hair, Roy. Today we'll talk to Mika Winklespec, who is the founder and CEO of Gem.

Jem is an enterprise blockchain company that uses blockchain technology such as HyperLedgeer, Ethereum, and J.P. Morgan's KORM, in order to create a new type of flow for the exchange of data between enterprises and their customers. Micah, welcome to the show. Thanks for having me. So before we start, tell us a bit about your background and how you got to be involved in the blockchain technology space. Sure. You know, so I'm a developer by trade. I've been building software for a good 14 years. And I got into Bitcoin originally. I've been in the industry for a little over four years. I originally got into it largely because I was pretty pissed off at the financial collapse in 2009. And, you know, I sort of became a student of the history of money.

I started reading a lot of books about the Federal Reserve, and this thing called Bitcoin popped up on my radar, and it just sort of fit what I was looking at, both as a hacker and as somebody who cared about, you know, the financial system. And so I just got really involved here in L.A. and there was a small meetup group at the time. It was about 15 people in a park in downtown L.A., you know, two Silk Road drug dealers just exchanging Bitcoin in the park. Very sketchy. But it was sort of eye-opening for me. And I thought that this was much bigger than 15 people in a park. And so I ended up taking over the group and running events. And we grew the group from about 15 people to 1,000 people in a year. And so I sort of became the Bitcoin guy in L.A., along with guys like Brock Pierce and others. And at the same time, I started building open source libraries for Bitcoin.

So I wrote a wallet implementation, one of the first hierarchical deterministic wallets. And yeah, that was how I got started. But since then, you know, we got started by building Bitcoin APIs, developer tools for the Bitcoin ecosystem. And, you know, now we're building enterprise blockchain software. Tell us why you switched from building Bitcoin APIs to enterprise blockchain? You know, I think this is, again, this is four years ago when we started. So the market was very different. You know, there was not a lot of Bitcoin developers in the world at that time.

So I think it was a great idea that was maybe just a little bit ahead of its time. You know, I think today it would be, you know, there's a robust community of developers that are really gravitating towards digital currencies and digital assets and tokens. at that time, it was a much smaller crowd. So, you know, just as an entrepreneur, you, you, sometimes you have really great ideas and your market timing is not great. But what did happen was, you know, we had built up an expertise around digital asset security. And, you know, like we built the first wallet that was backed by hardware security modules, for example,

which really attracted the attention of the banks when they started taking a look at this technology. more broadly. And so what we recognized was that there was this really large growing opportunity around enterprise adoption of blockchain. And so we just decided to make a strategic shift and really focus on that opportunity. So broadly over the last three years, I think the idea around enterprise adoption of blockchain still gathered force in, or like late 2015 and so on. what's your impression of how the broad uptake of enterprise blockchain technology has been well i think enterprises are known to be pretty slow in general right so the adoption cycle

for any technology in the enterprise is two to three years at least and you know we've really only been in the you know i think we've really only gone through two full years of of blockchains as an enterprise technology and we're starting to see a lot more adoption and you know like the relationships with our customers has changed a lot in the last year or so I think a year ago every engagement was essentially an educational seminar for the enterprise you know explaining how this block blockchain technology is going to be you know transformative to their business and then you get to the point where they're willing to actually invest in doing a proof of concept. And the proof of concept, even six months ago, I think the point of it for the enterprise was to test the technology to see if it works.

And I think where we've gotten now is that it's no longer about testing whether the technology works or whether it's going to be disruptive to their business. Now they're saying, okay, we want to get to production. So let's start building down a production path. and they're at the first phase of that. And so the engagements are very different. You know, we're starting to see, you know, where we really had to push the message to enterprises, we're starting to get RFPs that are being sent to us

by large companies that are, you know, 10, 12 pages of well-documented requirements for their project and they're just shopping for vendors. That's a very different relationship. So I think you are really starting to see a lot of adoption there. Oh, those early days, right? most of your engagements were just unpaid, you know, what is, what is Bitcoin? I mean, even before I even trying to explain how it was going to be transformative

to their industry, I mean, I've got so many pitch decks. It's like, what is Bitcoin? And I mean, I feel like a guest lecturer, you know, or at least I did two years ago. Yeah, absolutely. And so I wanted to ask you, so, I mean, we've been in the space for about the same time and we're in sort of similar, similar positions. in terms of the companies we were in. And so I'd like to get your thoughts on

where do you think the industry is right now in terms of maturity? We went from this education phase to the proof of concept phase to want to test things out and test whether or not the technology is mature and we're now moving into sort of pilot and production phase.

Where are we in that spectrum right now? Where are you seeing your clients? I think that there's still a large group of companies that are just getting their feet wet. But I think we're starting to see the first batch of companies that, you know, like many of the companies we work with already have hired dedicated blockchain staff, blockchain engineers. You know, they might be still in the innovation department, you know, rather than the critical infrastructure groups.

But you can see that these guys are, you know, They're investing pretty heavily in this. They know, I think, at this point, that this is too big to ignore. And so you're starting to see real money actually getting pushed behind it. I think that in terms of their actual execution, it's still very early. So I think we're starting to see just the first pilots that are, you know, going to market. But they're very limited. I think it's going to take a while.

One of the challenges with blockchains in general is that it's like a nice. networking technology. It's, you know, very low-level technology. And it really does sort of transform the way they think about their infrastructure. And so for them to basically rip out their old infrastructure and put something new in place, that's a very long process that needs a lot of betting, you know, when you're talking about systems that are managing billions, if not trillions of dollars, right? So it's going to take a while. But I do think that we're, the market is much more mature and its understanding of the technology, which I think is really important.

They're very educated now, at least in some of the organizations we work with. They really actually understand exactly how the technology works, and they have experts on staff. And now they're just kicking off these big projects. I think you're right about the technology and being comfortable with the technology, understanding the technology.

But I think that for the most part, a lot of these companies that that we work with understand the technology, but that's only 20% of whatever paradigm shift we're in. The other 80% is change management, is understanding how, and acknowledging and fully embracing the fact that we're no longer in a world where we will have siloed infrastructure, but the idea is to build networks and that through collaboration, and through sharing of data and through building these network economies, there is a tremendous amount of value that comes out of that. How do you respond to that?

And what are your thoughts on this? Well, I think that that's why you start to see a huge increase in participation and marketing and sponsorship from guys like Ernst & Young and, you know, Accenture and KPMG and all of these guys. I mean, these guys are actively getting into this because what they recognize is that this technology shift is going to happen, but it's going to take a lot of that change management, and that's where they really shine. And so that this is a whole new business line for most of these organizations, I think. And so, yeah, I totally agree with you. I think in the industry,

we often focus a lot on the technological differences between one blockchain versus another. and in the long run they're pretty minor compared to the amount of change that needs to happen in the enterprise to make this actually work and it's really about building an ecosystem around that technology and the ecosystem is the hard part so gem works in different industries we'll get into but I think you focus on sort of health care insurance and supply chains or trade. Are you seeing that certain industries are more mature than others or you think we'll adopt the technology faster or will have this sort of change management shift quicker than

others? You know, so we got an early start in healthcare. I think we were one of the first companies really to even talk about blockchains and healthcare and help to build that market. We've seen a pretty rapid change in that industry. I mean, we've had two conferences. in Nashville distributed health, you know, two years in a row. I think the first year there was maybe 300 people. The second year, there's about 700 people. And these are all, you know,

executives of the major healthcare organizations that are showing up to these things. So there's definitely a lot of attention in health care. But health care in general is known to be a pretty slow adopter of technology. So that's going to be a longer cycle. I think there are other industries that we're seeing where there's already a lot of technological change that's going on in those industries. And so they don't have a lot of legacy infrastructure that can handle it. And those are the areas that I think the technology can be adopted much faster. So, like for instance, in healthcare, going after the medical record itself is a pretty daunting task because all of these large healthcare organizations have already invested literally, like,

millions and millions of dollars in digitizing their health records and putting them into existing EHR or electronic health records solutions. But there's other areas within healthcare where there's not an existing solution like genomics data, for instance. I think we're starting to see in auto. This is an area that's rapidly transforming. The cars are going from dumb cars to smart cars, and those cars are generating, you know, treasure troves of data, and there's not a really great existing infrastructure for moving and sharing that data. And so that's an area where I think we can adopt much faster. That's interesting.

One of our very, very first pox at Stratham was, I think even the first one, was a health care, was in health care. And for some reason, and even like we had contacts in health care, like very close ties to health care. And we totally. pushed that industry aside because we thought it was much, much too complicated. And at the same time, I was seeing you guys just sort of shine in that space and going like, what are they doing?

But I think it maybe it also has to do with, you know, the different geographic, you know, we're here in France and you guys in the U.S. maybe it's different that way. But yeah, we totally pushed that aside in the very beginning. Well, I can tell you, it's daunting. I mean, look, the United States health care system is a crazy patchwork of disconnected services, you know, which the need is really great, you know, and that's, I think, one of the, the good parts about health care is that because they are slow adopters to technology, like this is not

an incremental change for them. There is massive amounts of value that can be unlocked. Yeah, I think that that's probably one of the reasons why there's such a need for it there, right? Like you said, it's a patchwork ecosystem. Let's move on to the next topic then. And we've sort of touched on it so far. And you're mentioning it when talking about the audio insurance space. is this idea of silos, right? And so you have these treasure troves of data that exist in silos. And the way that you guys address this issue at Gem,

and I thought that was really, really fascinating, is to talk about the problem of identity silos, so identities living in silos. Can you expand on that? Yeah, sure. You know, I think, I don't know the exact number, but essentially every single human on the face of the earth is now generating like an entire library of Congress worth of data about them. You know, we call this digital exhaust.

You know, and this is through the increase of devices that are spitting off data. You know, you're increasingly working with a lot more digital services. And you're essentially in your life going from service to service to service. And each one of those services, whether it's your, whether it's your physician or it's your insurance company or, or, you know, you're booking travel. Every single one of these companies has one sort of slice of you that they can see. And you're depositing data in each of these different silos. And each one of them is managing an identity that is you, that is me, Michael Winklespect.

So I have an identity, Michael Winklespect in, you know, Provider A, Provider B, Provider C. And none of them have a complete picture of me across all three. So this is a real challenge because, like in healthcare, for example, this is the really big problem, the big driver of cost in healthcare, is that there's no such thing as a longitudinal health record in healthcare. You know, I deposit data when I go to my primary care physician. They send me out to a specialist. I'm giving them more data. They're doing a bunch of manual copying and pasting of data from my previous record. and there's no unified record about me that they can tap into.

And this is what drives the cost of administration of health care. And so if we can create a system that unifies identity, not around the provider, but rather around the individual themselves, you know, if I can walk around with my life history of data, and that belongs to me, and I can provision access to that data at different service providers as I move along in my life, then we can start to unlock a lot of that value of that data across my entire life. And that's the real big vision. You know, we want to liberate your data,

and we really want to build tools that allow for developers to put individuals back in control of their data and put them at the center of their data relationship. That's an amazing grand vision. Yeah. And it's I think a vision that is shared by many people across the blockchain space and many other projects across the blockchain spaces is somehow to have all my data in like one central place and then provision access to that data as in when I need to. So perhaps like perhaps we could also take an example of like some industry. that you're targeting and how this fracturing of data impacts that particular use case. So maybe you mentioned genomics.

So tell us about how this problem translates into the genomics field. Yeah, so we're working with, and this is a new project, we're working with a large technology company in northern Europe. So they build a lot of the health systems, education systems, welfare systems for the governments of Scandinavia, mostly. But for example, they have about 60% market share for all of the EHR systems for Finland. So they're a really large provider there. In Northern Europe, in some of those Scandinavian countries, when a citizen is born, they have a blood sample that's taken. And that blood sample is essentially stored in what they call a biobank.

And they sequence that, they sequence the DNA and use that DNA for medical research across populations. But the citizen has like very little control or knowledge of how that data is being used. They have very, they don't have access to it themselves. And it's actually their data. It's about them, right? And so this data exists. It's already there. But it's not really being utilized.

And if we can actually put the citizen at the center of control over how that data is used and managed and shared, then we believe that we can actually unlock a myriad of new use cases for that data. Everything from providing that citizen with better diagnostics when they go to the doctor. You can eliminate a lot of diseases if you know the genomic profile of the patient. you know, it can be used to selectively share your genomic data for specific medical research that you care about. I mean, if you have a, if you have some rare disease or something like that, then more than likely these citizens would be willing to share their genomic data and their health

data with researchers that are studying that disease. But right now, that's not even an option because that data is locked away in these silos. So it's those kinds of ideas. And it's not just in health care. So, like, we're doing a project in automotive as well where we're building a data exchange between automakers and auto insurance companies. And so we're starting with two companies in Japan, Toyota and Iowe Niseidoa, which is a Japanese insurance company.

And we're building an auto data exchange that creates a unified driver profile, essentially, and it leverages the data that's streaming off of all the new vehicles that Toyota's putting out to the market. So, you know, cars are going from dumb cars to smart cars, and they're now generating a lot, a lot of data about your mobility, about how, you know, where you go, how fast you start, how fast you stop, how often you turn on your car, and a lot of other data, right? And that data can actually be used to create new types of products and services. So we're working with this Japanese insurance company to be able to create a new type of insurance policy that's based on scoring your risk as a driver based on how you're using the vehicle. And it's called usage-based insurance. And the really key component of all this is that we want to make sure that the individual, the citizen,

is at the center of control over that data flow. So they're authorizing the exchange of data for a very specific purpose to a very specific company under certain circumstances. And if they can give that consent, then the insurance company can use that to give them a discounted insurance policy. So that's their incentive to share that data. Do you see a risk there? I mean, so we were talking about this before the show.

I can't remember who it was, but I was speaking to somebody earlier this week who was telling me about this exact thing that insurance companies had tried to do in France many years ago but failed to do because of privacy regulations or reasons of privacy. Do you think that maybe one of the risks of going in this direction is that all of a sudden you can't get car insurance if you don't provide them with all types of data? I mean, we like, you know, the same thing exists in healthcare, right? Like if we could track everything that we eat, for instance, you know, maybe that way you could get a better health insurance rate. But the flip side of that is that all of a sudden,

if you don't provide all that data, maybe insurers will not insure you. Yeah, I think that's a great philosophical debate that we have to have, given the fact that we're generating so much data, that eventually that data can be used both for good and for bad, right? we can use it to increase opportunities and we can use it to discriminate. And there are regulations that are in place about the types of data that you can use to, say, offer an insurance policy. Certainly, that's even more stringent in health care.

And so I think that's a debate that we're actually having in the United States right now. You know, should the healthy patients be paying for the sicker patients? And it's a really tough, it's a tough question that is kind of at the heart of our societal belief systems. But the reality is that there is data that is available. And if you're a, if you're a business, a large part of your, a large part of the problem that you're trying to manage against is risk. You know, especially as an insurance company. Insurance company's entire business model is about pricing risk, right? And so from their perspective, the more access to data they can have, the better they can price risk.

And if they can price risk better, then they can create a lower rate for an insurance policy. And so that benefits the end consumer. You know, I mean, as a driver, if I haven't, first of all, we already use, you know, in auto insurance, we already use data to price risk, right? Like if I've had an accident in the last three years, then my rates go up, right? So we use data to price risk, but if we use more data, can we price risk better? And I think that ultimately that's the way the world is moving. And that actually allows us to start building things that can be completely automated. You know, we can start to build automated risk and automated adjudication,

and we can start to streamline a lot of these processes. So when I like scan across the blockchain space, because ultimately the problem of me having my data fractured across many places is well understood by many blockchain developers. There are multiple solutions proposed in this direction. So on the one side we have something like Orbit, which is building a personal server that I can put all my data in, to something like decentralized identity systems running on public blockchain networks where the idea would be the decedler that my name would be given to me on that, on a public blockchain like Ethereum, but then I could associate that name with all forms

of my own personal data on a system like IPFS. And I think there are many other solutions that are small and that are being tried. Could it give us an overview of what JEMOS is, like what JEM is trying? I would say all of the above. I think that what GEMOS is trying to do is it's trying to abstract away where the data lives on the network. And it should be able to link out to any data system so long as it's accessible. So GEM is really more of a middleware solution that allows organizations to register and link data that they have. available about a common identifier, like a patient or a driver, and to essentially allow for

other organizations, if given the rights, to be able to exchange and share that information. And those rights can be governed by many different policies. One of those policies could be getting the user's consent, for example, which is what we're doing in most of our projects. So I think that there's going to be data that lives on many of these networks, public, private, And we take an approach that that's all good. I mean, I love what Filecoin is doing and, you know, Juan Bonae and that project is really great. I think that the idea of a totally decentralized file store is probably a little bit more advanced

than most of our customers are ready to adopt, you know, in the enterprise. They want, they still want to build their castles around their data, you know, because there's a huge liability. around having a breach of that data. But our position is that that's okay. You should be able to keep your data in a silo, but what you want to be able to do is you want to build bridges to those silos. You want to build links to those silos so that you can free that data at the right time and right place to the right person. And so we want to build those bridges, essentially, that connects those silos.

Okay. I think I'm starting to get a better understanding of a, of what GemOS is and where it acts in the broader ecosystem. I had a question about implementation. And we can come back to GemOS and talk more about that. But one of the things that I find challenging is when we're talking earlier about, you know, this paradigm shift is finding the right people that can sort of instantiate what is a network. right. So if you look at something like banking, well, all of the banks are sort of in the same

position with regards to some overseeing authority or some regulator or their customers, right? And the burden of proof or any type of burden of having to share information sits equally on all of them. With something like a supply chain, it might be a little different, right? You might have a distributor, or say a chemicals company that is sourcing raw materials and their burden of proof is towards their customers, right, maybe like cosmetic brands or something or, you know, processed food companies and the end customer. So in your experience, how have you been able to instantiate these networks, right?

Does it start with one company or do you approach five direct companies or do you approach sort of a trade organization or like a federation or do you approach to regulator? What has been your experience like? So I think you're touching on a really big issue, which is, you know, how do you bootstrap these things? Exactly. You know, I think we're evolving, right, in our approach. Like when we first got into healthcare, we had this idea that we could just go to large health systems and each of them would run a node, you know, and then they would use that network to, share health data with each other.

What we realized very quickly was, like, you know, a health system is not in the business of running network infrastructure. And they buy software off the shelf from vendors. And, you know, that's how they acquire technology. So they're probably not the right people to run nodes for validating transactions on a network. That might be different in finance. I think in finance, you know, the financial institutions actually, might want to be nodes on the network.

But in other industries, I don't think that's really the case. And so, you know, my feeling on this is that we should probably look to companies who run network infrastructure to run these nodes, you know, at least in the enterprise. And, you know, and we're exploring that path with a lot of these projects. There's a lot of interest from a lot of the, you know, telcos and telecoms to be able to be infrastructure providers as a service for industry. And that seems to be a decent fit. You know, the end customer just wants to be a user.

They want to use a blockchain for the purpose of moving data. They're not saying I want to own a network node. This episode is brought to you by ShapeShift. The world's leading trustless digital asset exchange quickly swap between dozens of leading cryptocurrencies, including Bitcoin, Ether, Zcash, Gnosis, Monero, Golem, auger and so many more. When you go to Shapeshift.io, you simple select your currency pair, give them your receiving address, send the coins, and boom.

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Whenever you see that good-looking fox, you know that's where ShapeShift is. So to get started, visit Shapeshift.io and start trading. And we'd like to thank Shapeshift for their support of Epicenter. So like James approach is that the data itself might be spread across different systems. But in some way, whenever I'm going to a provider and providing some of my data there, I can use that same data across another provider quite easily. Right. So tell us how you would architect, for example, a genomics data system.

So I'm assuming like for a genomics data system, the main parties might be me who's like sending my blood sample somewhere and getting my data. It might be my The company that's doing the sequencing and has a repository of my data And researchers that want access to that data and my doctors So what kind of technical architecture does gem build that would allow this data to be easily shared between all of these parties? So we like to understand your technical architecture and like how it would make map to what use case?

So Gemmaos is a piece of middleware that sits within each of the enterprises that wants to connect to this data exchange network. So, you know, essentially what they're trying to do is they're trying to create links to data that are linked to one common, say, citizen or patient identifier. and they're essentially registering the data that they have available about that patient. And if you, the patient, goes to one of these service providers, you can essentially provide a digital consent, which we are actually modeling on as a document that gets registered on the blockchain.

You're registering a consent document that says, I, you know, Michael Inglespect authorized the transfer of this data from this provider to the, to, to, you know, that's a consent document that says, I, you know, Michael, this provider to another provider or a research or whatever. Once that consent document's been recorded on the blockchain, any other nodes that are watching the network can see that it's been registered. And if they have a notification set up for that individual, they can get an instant notification that there's a change in consent, there's a change in permission,

and now they can authorize the flow of data from them to another party. So the first step of all of this that we're building is a consent management network on blockchain, which is like the first layer of facilitating data flows between organizations. And that consent document itself is a document that's registered on the blockchain. The next step is to actually register individual bits of data about that individual and actually do peer-to-peer transfer of data. And so we're sort of stepping our way through that in healthcare. So every party is a node on that network, including the individual.

The individual is not connecting. They're not running like a full node. They're connecting through a service provider that's managing their identities, which is running a full node. And those full nodes could be like a hyperledger node or like a tendermint node. Sure. Yes. I mean, at least from GemOS's perspective, it's totally agnostic to the underlying blockchain technology.

most of the projects that we're working on right now, we're starting to use Quorum. You know, it's similar enough to Ethereum, but is more configured for building federated networks, which is what most of our customers are asking for right now. And are you seeing any use cases where the federated network approach is not necessarily the best approach and therefore using a public network like Ethereum? Well, I think the beauty of all of the best. of this is when we have it all linked together. I mean, I think you're going to have, you're going to have value networks that are created as a federated network with a tight set of participants,

and then you're going to have public networks where I can register my public identity, and I can link that identity to an identity on a private network. I think that it should be able to be transportable, your identity should be able to be transportable across blockchain networks. And if we can do that, then really it's just a matter of building. links, you know, you can essentially link out to the different blockchains that you're a part of and into the data that's registered on those networks. But they can all be tied to your global identity. So I think that, you know, it's really hard for me to imagine that there's going to be one

world where there's one blockchain that rules them all and everybody is happily participating on it. There's going to be many, many value networks. And we're already starting to see lots of projects that are trying to find ways to unify those blockchains like Pocod and Cosmos and others, right? So I think the industry is moving in that direction, you know, away from one blockchain to rule it all, Bitcoin, you know, to we're going to live in a world where there's literally thousands and thousands of different networks that you can connect to. Why is a blockchain relevant as a technological tool to the problem of data sharing or making sort of data liquid? Yeah.

So I think you have to look at the alternatives. So the way data has moved and shared between enterprises today is. one of two ways. One is that you have some central aggregation service that basically acts as a essentially a broker of data between parties, right? They're like a central hub of all the data for an industry. Like health records are, you know, centered around EHR hubs. But then there's many different EHR hubs. And so you have this challenge of uniting health data from one EHR system to another. So they've created these ideas of health information exchanges, which operate like at a state level, and those become a central hub for interoperability of health

records from different systems. But then the challenge with that is that there's many of those hubs because they're only statewide. So if you travel from California, Arizona, now you're dealing with a different network. So this idea of trying to centralize data is always a problem. You just end up creating more and more hubs, and those become more and more silos. The other approach is to try to connect directly peer-to-peer between institutions. And the challenge with that is it works fine if you have like one or two connections. You know, you're making, you can use API technology to build a data connection from, you know, from an automaker to an insurance company.

That's easy. But what happens when you want to scale that network out to all of the auto-examination? automakers and all of the insurance companies. Now you have to build a direct connection between every single party. And so that becomes unmaintainable. And then you have really big challenges around data syncing because everybody has a different story and different timeline of events. So that doesn't really scale. I think blockchains can provide a third alternative, which is sort of the best of both worlds.

You have sort of virtual centralization. you have one single point that you can connect to. You know, everybody sort of agrees to connect to the same point by connecting to the blockchain network. But the information and the data transfers are peer-to-peer. It's one organization trading directly with another organization through this network with no center intermediary. So it's a bit of the best of both worlds.

And I think that's the only way to really scale these kinds of exchange networks. So in this example you gave about health records living in different systems in different states, it occurs to me that there may be one issue that remains, even if you do have this sort of, you know, this one thing that people connect to, which is a blockchain, which is data formats. So for one state will have one type of data format. Maybe it's like XML in some structure and then maybe other states using Excel or some, you know, crazy thing like that.

How do you... How do you manage this sort of incompatibility between IT systems? Yeah, so that's the big challenge. And that's why you need a sort of a middleware solution because you need to be able to somehow communicate in one common language on this network. And every industry has their own efforts to standardize data formats. And a lot of that work is going on right now. So like in healthcare, there's a new format called Fire, FHIR.

that a lot of the industry is starting to try to standardize around. It's going to take a while for the old systems to really adopt it. So one of the first things that we did was we built in, well, I should take a step back. So GemOS has a schema manager that allows for organizations to be able to create or import data standard schemas in a JSON-LD format. And so the first one that we actually brought in was the fire standard. So just out of the gate, you know, GemOS allows for developers to be able to use fire documents so that we can communicate those across systems. But it is a huge challenge, and it's not one that blockchains alone will solve.

You know, companies need to agree to speak the same language. That's going to be a universal problem across all these things. I think what, you know, at least around identity, there's been a pretty great effort industry-wide in the blockchain industry to help define those standards. You know, we're part of the decentralized identity foundation, which is trying to standardize the document types for an identity, for verifiable claim, for like lots of things that relate to identities in general. So I think we can get some standardization around the identities first. We're working on building, you know, consent document standards. And then, you know, each industry will have its own specific proprietary data formats.

So in this sort of data exchange, so we said like the first model is a model where you have these data intermediaries, right, that mediate the exchange of data across multiple enterprises, but then the problem is there's lots of intermediaries. You could have like peer-to-peer exchange of data. The third model is something like a blockchain where presumably, so I have my iron. on a particular blockchain and then whenever I generate health data that health data is put on some other system but a hash of that health data is maybe associated with my identity on the blockchain right and then in any scenario where there needs to be an exchange of data like two organizations can agree to trade my data and be sure that the integrate like the block

The auction ensures that the integrity of the data and the exchange can be like an economic exchange between two entities. Sure. Yeah. There's many reasons why somebody would exchange. Some could be economic. You might be purchasing access to something. That's one type of exchange.

It might be that I've presented my consent for sharing my health information and the provider has to share it with another provider. But in terms of the technology, yeah, there's some reason for. an exchange. And what we're registering on the blockchain is a few things. So you captured a lot of that. So one is that we're registering the hash of the data that's associated or linked to an identity. We're also registering the permissions of that data as well. So we're using the blockchain to be a global permissioning system for data so that it can prove that, you know, the right individual had the rights to modify or change the permissions on that document.

And then we're, you know, essentially the hash is being encoded into a URI, a content addressable URI, so that we're providing a way to basically use standard HTTP to be able to like link out to that data. And so the blockchain's acting like a like a giant index of all the available data about you. But everything, even the index itself is only visible if I have the rights and permissions to see it. So, you know, we're like the standards that we're using here are pretty stringent around privacy. And, you know, one of the things that we want to do is be the first GDPR compliant data exchange, you know, powered by a blockchain. So GDPR is general data protection regulation, which is going into effect in May of 2018

in Europe. So we're, you know, we're trying to build all these privacy features in as a well. So tell us what the gem, like in terms of technology, what you have built until now and like what is JMOS and what it allows. So GEMOS is an application development platform for building data-driven applications. And it has many different layers. So we have a network layer that basically creates an abstraction layer for connecting to different

blockchain networks. We can use this paradigm for data sharing on pretty much any blockchain that has basic smart contracting capabilities. So, you know, right now we have adapters for Ethereum and Quorum. We're adding support for HyperLedger Fabric. And so we can interact with any of these blockchains. In fact, an application could actually interact with multiple blockchains at the same time if there was the need for that. You know, I think in the future there'll be more need for that. We have an identity management layer, so we're managing the identities that each organization knows about.

Ultimately, they're managing a registry of all the, say, customers that they're aware of that are on the network. And they're monitoring for changes, any notifications or changes that are being pushed to the blockchain about those customers. We have a data integration layer that allows for us to integrate with existing data infrastructure to register these data assets on the blockchain and pull them from the blockchain back to the data system. So sort of like an ETL layer. You know, we have a schema management layer that allows for users to be able to create custom schemas or use existing standard schemas.

We have schema.org and fire, and we'll be adding a lot more. And then ultimately what you do with the product is you're using it to generate a custom application-specific set of rest APIs. So our whole concept here is that we don't want a blockchain platform that requires blockchain engineers. We want to build a system that allows for any reasonably skilled full-stack engineer to be able to use the platform to build data applications on top of a blockchain without having to understand how to build smart contracts and things like that.

Like our smart contracts are all packaged in. And so they're thinking more at a business object layer. Like they want to create a patient record. They want to create a car record. They can think at the business object layer and just interact with a simple rest API. What I mean when you say that your smart contracts are packaged in? So like we've built contracts for, identity registries and document registries and other basic and like permissioning

registries, all the things that are the sort of core components for facilitating this kind of data exchange, we've been building those and those are, they can basically be ascribed to any sort of resource in our system. So you can take any resource and turn it into a document, for example. We have different behaviors that you can attach to resources. One of the behaviors is it can be documentable, which means you can record a version history on the blockchain of every change and modification to that resource over time.

So we built a smart contract for that that manages that versioning history. And we have a permissioning registry that allows you to register the permissions of that document or that resource over time. So those core functionalities we've sort of baked in. But ultimately they are smart contracts that are executing on top of a blockchain. So we've talked a lot about data. And data seems to be very much at the core of just a public discussion at the moment. Of course, if you look at it from the regulatory side, you know, GDPR in Europe.

And then in the U.S., there are some regulation coming into effect, I think next year about health records. And then there's sort of the higher level discussion about, you know, who should control our data. Of course, you know, big companies control massive amounts of our data and users and customers have very little access to it. There's sort of been this acknowledgement, right, of this problem. And more and more people, I think, are becoming aware and becoming sort of educated around this idea. And I'd like to get your thoughts on, you know, Where you think this is going? Are we going in, you know, I see it sort of, there's two directions, right?

One that is desirable, which is, you know, these types of technologies start to become more prevalent and users and consumers have access to their data, can control who has access to their data and perhaps even sell their data and monetize their data, right? And the other way is, well, we just keep going in this direction of more and more centralized. So where do you think? things are going and how do you think we can bootstrap this this this this right direction we want to go into yeah i think um i think that's a really big question that we need to be asking ourselves as a society right now because we are generating unprecedented amounts of data um and we you know i think

uh um that we've generated more data in the last two years than we have in the last 5,000 years of humanity. And we're really only leveraging about one half and one percent of all that data. So it's just being collected and stored. And it's largely being highly centralized to only a few organizations. I mean, Google, Apple, Facebook, and Amazon have the lion's share of data about us. And that's troubling, I think, to me. Do we really want to live in a world where only four companies have a total grip over our valuable data and know everything about us. We've seen what can happen when that data is highly centralized, you know, with like the Equifax breach, for example. They lost 145 million Americans highly sensitive records. So can we

really trust these guys to be the gatekeepers of our data? And, you know, the other side of that is that data is becoming extremely valuable, you know, in a totally digital economy that's powered by machine learning, and AI, that digital exhaust that we're creating is actually tremendously valuable. And it will become the primary source of the value that I think humans create, actually. You know, more than just money. I think money is one side of the equation, but data is the other big one. So we have to ask ourselves, who should benefit from that new value and that value creation? Should it be four companies or should it be the individual?

So I think that there's almost a social imperative to find ways to put that data back in the hands in control of the individual. Now luckily, there's legislation that's being passed globally that's actually shifting in this direction. And there's a bit of a movement around this in parts of the world about putting the data back, centered back around the individual. General data protection regulation is a piece of regulation that does assert the rights of the individual to have more access and visibility and control over how their data moves and is managed. It goes part of the way. But there are other movements. In Scandinavia, there's a grassroots movement called the My Data movement, which is a group of companies in Scandinavia that are all gathering around and saying, we're going to put the data back in the hands of the individual.

And so I think that that's the way the world is moving. And there's going to be a struggle between the two worlds. But ultimately, if you can actually center the data around the individual, then you can create a much richer data profile. And that data becomes way more valuable because it's not just a sliver or a tiny view of data about somebody. It's the entire story. And you can derive way better fidelity and information and clarity

about an individual when you can see the entire picture, whether you're talking about their health profile or their driver profile or their travel profile or any other industry. And so that's, you know, I think the world is moving in a user-centric, customer-centric model direction. Yeah, I totally agree. And I think that there's sort of this idea

that data and the average, aggregate is more valuable. Like so for instance of, well, I'll give an example. So we had Trent McConaughey on a few months ago, I guess. And I saw him recently in Berlin at the 9984 conference. And he gave a talk about, um, about self-driving vehicles. And so in, in self-driving vehicles, what's important is not necessarily the AI itself. It's, it's the data that is being fed into the AI that is, well, you know, improving the models and making sure that we don't, get into accidents. That's correct.

You've got like Google controlling parts of that data. And then, you know, for instance, another company controlling other parts of that data, they're only getting their proportion of that data. And then the AIs are only learning in proportion to the amounts of data they have. But if we're in a situation or in a system where users could essentially, you know, control their data, but sell their data to all these cell joint car manufacturers or AI companies, we'd be in a situation where we'd be massively better off. Yes.

And where our AIs would be just learning so much more about us and preventing assets. And that's actually a real use case. So in addition to the goal of building usage-based insurance in the auto industry, one of the large reasons why they want to build this auto data exchange network is because, like, for instance, one of the participants is Toyota Research Institute. and one of their driving missions is to build autonomous driving. I think that's actually one of the guys who was giving a talk. Oh, okay. Chris Ballinger maybe.

One of the challenges with autonomous driving is in order to build safe models for autonomous driving, you need lots and lots of driving data. And there's not any one automaker right now that has enough data to be able to produce a safe model. So what they have all recognized is that the only way they're going to build safe models is if they can work together and pool their data. And so they have to find a way to be able to do that and to be able to do it securely and to do it in a way that respects their data rights. So that's a really interesting thing. It's like if I'm contributing a sliver of my data to some really valuable machine learning or AI model and it's generating a service and that's generating value because I've contributed my sliver of data, is there a value?

is there a world in which we can actually reward that individual for their contribution? Can they actually receive their portion of the economic benefits of that service? And I think that's where blockchains might be able to really help. We can potentially tokenize these things and actually have a working model for creating direct economic benefit to people who are willing to contribute their data for building a service powered by machine learning. And are you seeing similar initiatives in healthcare, for instance? Because it seems like healthcare, there's massive benefit there as well. There is. And on the research side, I mean, like drug makers, in order to do a clinical study,

they pay hospitals up to $100,000 for a qualified participant to join a study. So the hospitals are basically hoarding this data about their patients so that they can basically receive, you know, these giant payments so that they can help track. down and locate a patient that can join a clinical study, especially for like rare diseases and things like that. So I think that market can be totally disrupted. If I can, as an individual, have control over my health profile, my genetic profile, and other things, I can essentially opt in to join a study and hand over my data and potentially

get paid a fraction of that price, but at least I'm getting it directly. So, you know, maybe instead of paying a hospital $100,000 to find a patient, they're paying me $10,000, but I'm better off. And, you know, the company is better off and it's a win-win. Yeah. But although I wonder that many times, many times like the individual incentive, in the case of the hospital, the individual incentive is to hoard the data so that you can make money. so like sometimes like the incentives of capitalism act against the sharing of of data as well it like I guess what I'm trying to say is it just may not be an IT system problem it might it might be an economic incentives it's it's a total cultural problem too you know I think

most people aren't even really aware of the problem and and so I I think that it's a big step for telling an individual to say, you know, to tell an individual patient that they should now take over their medical records, you know? I mean, how many of us actually do that? How many of us have even a digital copy of our records from our doctors, right? We just, we show up at the doctor and they recorded in their system and then we walk away. But there are populations where people have actually really learned that firsthand. So when you talk about chronic illnesses, cancer patients, people who are very very, you know,

visiting doctors a lot. They end up actually, just as a requirement for being able to make sure they're getting the best care, they end up carrying around binders full of their own data and they bring it over to every provider that they show up to. There are people who are highly motivated to take control over their own records. And so I think that, you know, there are pockets where this can be really valuable, at least in health care. I think this is a movement that's going to take a while to develop, where the general population really has the awareness of what's going on with their data and the value that it's generating for other companies and not for them. But as they start to realize that, they may want to take control over it. That's why we're

really starting more on the B2B side, because there's clear incentive already for facilitating data sharing. But ultimately, we want to drive this towards the consumer too. What is like the near-term future for GEM? What projects can we expect to see and what might be some of the big achievements that your company makes near-term? Sure. So, you know, we're doing this project with the health system in Finland around genomics data exchange. We're definitely diving in and really focusing on building that out because we think it's a really strong use case for for our platform and for building out data sharing in general around digital consent.

And we're also using that as a use case to start complying with GDPR regulation because they're in Europe. So that one's going to be a big area of focus for us. The auto data exchange that we're building with Toyota and I.O.E. Niseidoa is a huge area focus for us and we want to be able to expand that network out, not just to Toyota and I.O.E., but to other automakers, other insurance companies, and to build a really large network around that. And, you know, we're, we have other customers who are launching data exchanges and want to use our platform.

Unfortunately, I can't announce all of them yet, but they're in other verticals like travel. And then, you know, I think in the long run, we are looking to figure out how we can extend this from just business to business data exchange to bringing the bringing individual citizens in as participants in the network, whether it's through partnerships or through our own software or our own apps. But ultimately, we want to build an ecosystem around this. Well, Mike, it's been a pleasure having you on a show.

I wanted to have you on for a long time, so I'm glad we can do it. Yeah, it's great. Great discussion. So thanks for coming on. And we look forward to having you back on again sometime. Absolutely. Thanks, guys. And thank you to our listeners for once again tuning in.

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