Trent McConaghy: Ocean Protocol – The Platform Making Waves in the Data Industry #366

Transcript

this is epicenter episode 366 with guest Trent [Music] MCC hi I'm Sebastiano and you're listening to epicenter the podcast where we interview crypto Founders Builders and thought leaders on this show we dive deep to learn how things work at a technical level and we fly high to understand visionary Concepts and long-term trends if you like epicenter the best way to support us is to leave a review on Apple podcasts and if you're on a Mac or iOS device the easiest way to do that is to go to epicenter.com listeners of the podcast

will recognize Trent as a repeat guest in fact this was his fourth time on the show and today he comes to us to tell us all about ocean protocol which he and his team have been working on for some time now in fact ocean protocol just released its speak 3 which builds and improves on previous versions of the platform and now lives uh natively on the ethereum main chain ocean protocol is a platform to create data marketplaces and if you haven't noticed data is a big business by some estimates uh it is over $500 billion in Europe alone and what is obvious to everyone who is observing this space is that

there's a fun fundamental misalignment between those creating the data and those consuming it it's a very one directional value flow in terms of those who are providing the value which is the data itself and those who are extracting that value and those are big Tech platforms who typically use that data to sell signals and advertising to Brands and Merchants as Trent describes it there is a shadow data economy just as there is Shadow Banking and we need to flip this model on its head and if you haven't watched the recent uh documentary by Tristan Harris the social

dilemma I would encourage you to check it out because it really kind of summarizes uh this problem in a very concise way in a way that's easy to wrap your head around anyway the ocean protocol provides an alternative to this model an alternative in which data providers users typically can sell their data on the platform to whomever is interested in it whomever wants to buy it and that data set is represented as a token and that token's value is a function of the usefulness of that data to whomever wants to buy it so it's a much more Equitable Market where the value flow is more cyclical than one directional this was such a fun and fascinating conversation I always enjoy

speaking with Trent because he's such a Visionary and just all around a nice guy and I hope to see this model develop and I hope to see it really take hold because there's so much at stake here and the current model has so many things that are broken with it we're only beginning to see the impacts that that has on our society so I think that Lots is at stake here and ocean protocol provides an alternative if not a solution to this problem so with that here's my conversation with Trent MCC I'm here with fellow Canadian uh Trent MCC who uh who is a repeat guest on the show in fact I was looking just before Trent uh is actually uh has actually been on

the show four times so he holds second place after Shawn Jones who of course was our regulatory affer correspondent early in the day and so welcome back uh for a fourth time on on epicenter Tren great to be here it's going to be fun as usual yeah so actually the last time you were on you surprised me with Fred uram you guys were at some conference and you were supposed to come on to talk about ipdb and and then lo and behold you're like oh I got Fred here um let's talk about data and uh you know and and machine learning and and like sort of data rights on the blockchain and that was really interesting conversation and I was listening to a little bit of that in preparation for this um but for those

who perhaps are new to the show or haven't heard your previous episodes remind our listeners of who you are and what you're doing and how you got here uh sure so grew up in Royal Canada um trained as an electrical engineer computer scientist and then I did a couple AI companies um uh towards computer chip design as well as a PhD um on that as well uh in 2013 in 2010 I actually bought some Bitcoin lost those private Keys long ago in 2013 I I discovered um you know really what blockchain meant hanging out of room 77 in Berlin uh the aonomus room 77 and um kind of you know that was the beginning of really truly diving down the rabbit hole and um started hacking away at ideas and stuff and it led to ascribe then big chainb and ipdb then ocean now

so ascribe was basically um a project about asking the question how do you collect digital art and how do um artists that create digital art um get paid and this was you know back in 2013 2014 one of my co-founders uh uh was a Prof professional curator had worked in the Louver all these things so uh we did this uh and you know we released uh beta in 2014 and worked with a lot of leading digital artist and went live in 2015 in full production um and uh you know it was really fun really enjoyed it uh great cause all that um but scale was an issue we had built on top of Bitcoin blockchain ethereum didn't even exist at first right um and uh you know it was clear that the scaling Solutions weren't going to be coming anytime soon so we said

okay we don't need full more contract platform Etc um anyway so let's instead take a an existing distributed database and and decentralize it so at first we wrapped uh rethink DB uh and then that pivoted to to and we basically um put a bft algorithm around it tender actually by the end so that was um big chainb and that was in the sort of 2015 2016 2017 era and uh that also you know uh was pretty useful tool uh it was very um appealing especially to Enterprises U looking to dip their toes in blockchain who kind of understood databases and so on we worked with a lot of Enterprises um in that era and um it it was pretty neat at the same time too we saw that we really want to have sort of this public um blockchain

database utility if you will so um uh because uh big chainb software was set up uh in a a Federated way now we call that a POA type approach um then we needed to do a lot of governance work um sort of uh lining up many people to um be nodes etc etc etc and around that we created a a nonprofit organization uh Germany based one uh called ipdb interplanetary database and um so that was basically the the nonprofit arm of big chin B this was all token list by the way as well uh we didn't see the need for a token there really wasn't so we didn't have one um and so basically that uh went along and uh it's still around to this day as well finally in

2017 uh we saw late well actually even 2016 but especially 2017 uh we were starting to do projects um and think about how do you reconcile AI with blockchain um and at first just kind of exploring but then um people were coming to us saying hey you know like uh Toyota said we're doing autonomous driving we really need to have way more data than Toyota itself has so um we think that uh a decentralized to data exchange could be really really useful and you know what you wrote about about decentralized exchanges Trent this is uh great let's uh you know build a prototype so we built that and shipped that in Spring of 2017 and just in the last show Sebastian that's probably when I I talked about that we had just announced it um that same week in fact right I think I think

when I came on with Fred um I had just come off the stage of of announcing it in consensus exactly yeah I remember that so so um basically from then though and also in that episode we had talked about data exchanges and within a month or two after that you know the word ocean uh we came up with the word ocean for this project that had been brewing inside uh inside the organization um and it was really uh addressing uh we we basically when we were thinking about Ai and blockchain and all the different problems that you could solve um all roads led to data exchange um you know there's problems related to social media um where uh if you are uh a Facebook or a Google you basically have all this data of all the people they've kind of signed it over giving you permission to

do whatever you want and it's it's really really harmful to society um in many ways you could go on and on or just watch the social dilemma whatever and but there's a lot of other issues too right if you're um an AI startup and you're trying to uh build an AI model you're going to be starved for data um you just don't know where to get the data from and the thing is AI loves data with modern machine learning based AI deep learning and all this sort of thing to get more accuracy you need more data and you know you want to go from you know 30% error to to 10% to 1% to 0.1% to 0 1% depending on the application and for that you need you know 10x more data 10x more data 10x more data 10x more data and AI people don't have the tools

for that um you know how do they get more data um and there sort of been the state economy but it's just like um there's been a traditional banking economy that's all Shadow right um you know leading to the 2008 financial crisis and many financial crisis before that we've got kind of the same thing in the world of data right there's a shadow data economy and and we have a data crisis now that has been sort of Brewing uh over the last 10 years 20 years um and we haven't really noticed it because it's sort of been like a a frog uh boiling in in in uh a pot of water right U at first it wasn't boiling but bit by bit now it's clearly boiling and people are asking what to do so uh and just as crypto said okay there's this Shadow banking economy let's use crypto to try

to create an open uh money economy um and we have that not just with Bitcoin as a store of value and ethereum as a foundation but also defi on top um and all the things there so what Ocean's goal is is to say hey there's also a shadow data economy and uh let's use crypto tools to create an open data economy where there's shades of gr permissioning uh privacy and so on yeah thanks for that recap and all these things you know that you that you mentioned that you worked on so first describe then Big Chain DB then then ipdb to me these things were all these projects were all so Visionary like first putting art on the blockchain I mean this was in like 2014 I think the first time you came on this was such an

interesting concept an interesting idea I think it was really the one of the first times that you know people were confronted with the idea of a of a non-fungible good on the blockchain um and this was before ethereum this was before nfts and then and then Big Chain DB I mean to me like I I latched on to that idea and of course ipdb afterwards I thought that it was so powerful you know as a as a developer like as a web developer I love the idea of having a permissionless publicly available database available on the blockchain on a peer-to-peer infrastructure I guess is the better way to put it and you know same same for IPs Fest like I I have this sort of similar you know attachment to that to that idea was that concept too simplistic you know I I think about

some of the shortcuts that we sometimes take when trying to innovate with like new technologies and you know I wonder if the um if the the ipdb idea was perhaps simplistic like like let's saying let's put newspapers on the internet but we'll just do that in PDF format right like not considering what the technology affords and the types of innovations that the technology provides you think that that was perhaps the case and that ocean sort of builds like a new model that really leverages web3 Technologies to the fullest uh so I think overall um first of all simple as good in general um but um you know you want to make things um simple but no simpler right uh to to paraphrase Einstein and it's it can be hard to

arrive at simple um you know Mark Twain uh has this quote that I just love he said I I'm sorry I had to write you a long letter because I had no time to write a short one and I think this is really true so uh you know Simplicity is hard um simple as hard uh I think in the case of big chainb it was a very simple conceptual idea leveraging you know all this great infrastructure developed for uh the distributed systems world like how how does Facebook actually scale right so leveraging those sorts of technologies that part was sound I think the challenge that big chb and ipdb had was um the sheer underestimation of how hard it is to roll out something that is permissioned um the technology uh is easier but the politics and everything

else around it is much much harder and I've seen team after team after team um you know say hey let's let's go for something that's um permissioned thinking that you know they can use that as a stepping stone for for permission list and it's just so much effort we even did that um for the first parts of ocean and stuff right we actually had spent a lot of effort um doing the the the politics if you will talking to a lot of teams uh and organizations uh to get them to be nodes for ipb and so on I remember those conversations yeah that Str I mean stratum was was part of that that initial group of people we were we were speaking about exactly this you know how do we set this up and and like you know governance and that was the challenging part is like not the technology it's

it's it's human interaction in governance that's the most complicated exactly so you know um the governance as well as how does the relate to the law because once you have a POA or Federated Network then you have to um you it has typically much stronger ties to Identity and then these organizations that are running the nodes have to um they have higher degrees of liability and then if you start to put together um basically an agreement uh for sort of a node operator agreement um of you know what rights and responsibilities they have the uh responsibilities and the liabilities start to a away the rights quite a lot actually unless you're very careful right and if they're if they start to get too much reward on the other hand from from just running a node then it has the risk of becoming a cabal

as well so it's really um a a tough thread to to to solve and frankly it wasn't really like we always had the plan with big genb to be permissionless anyway it was just a stepping stone so we we saw that okay um we could develop this more or we could go towards uh where we saw there was more you know more opportunity in a sense with ocean and keep maintaining big chb it's not like we just shut down one and went for the other we actually um evolved from one to the other basically now you know ocean is on a permission the substrate and even this more contracts themselves are permissionless by virtue of not having any built-in upgradeability and it's it's just basically uh it's radically simpler from governance perspective there is still governance right but you know on the

substrate side you have to do a hard fork and one level above you have to convince your community to switch over from one thing to the next and I view that as a really good thing right it's a high friction for um for changing decisions that should take High friction there are other cases where you want to have low friction even at the substr level um and I'm sympathetic of all of those approaches as well for onchain upgrades great but for oceans needs you know fully permissionless at the subst street level and permissionless at the Smart contract level is what makes sense and that's where we're at now cool let's come back to this idea of the the shadow data economy can you describe in your view what that means and what that looks like and you know for for for people who perhaps are I'm sure listeners are all

very aware of you know the the issues that exist with regards to people's data and you know you talked about the social Dynam I watched that movie just this week describe what the problem is here and what lurks in the shadows if you will the big problem overall is that our personal sovereignty is at risk and by that I mean our ability to take action and make decisions without fear of uh basically oppression or uh you know negative things happening to us and that sounds very kind of Broad and vague and it kind of is but then you can kind of drill in to what this means there's a

quote from the World Bank at two or three years ago that says you know the digital economy is the data economy and that reflects this idea that um as you know with every passing year um the world is becoming more and more digital and what's powering um the digital world is you know data itself and so there's sort of this data flowing everywhere but we haven't really given it its due in terms of this super important thing that we have to keep tabs on and um because of that you know the average citizen doesn't want to think about it you know they just want to share photos and stuff and I get that that makes tons of sense but the thing is there's businesses that have emerged that real that take advantage of this it's an Arbitrage so they understand that citizens don't know

about this or citizens kind of have given up on even if they do know about it they can't do anything about it so these companies say okay well let's take you know group these people into a thousand or a million or a billion people and then mine that data and then use that to sell stuff back at them or basically change their decision-making Behavior somehow sometime right and it's at the level of the company it's also at the level of the nation right um and there's interplays as well you know there's companies out there and individuals and organizations that try to uh sway election results right um by by leveraging data in various ways so there you know there there have been flows of data for a long time going back to you know even before the early days of the PC you know from the birth of the

computer H but it hasn't mattered for a long time because we simply hadn't haven't had the scale and even on the internet the early days it was so small it didn't matter people hadn't figured this out yet but you know starting in the sort of um early 2000s that's when sort of AI people realized that data was really really important and then you know Google themselves published this paper in about 2007 called the unreasonable effectiveness of data realizing that okay if they can actually um get more data then they can um have more accurate AI models and which basically turns into money for them right and the problem is that um they're they are incentive misaligned between the people and Google there's an incentive misalignment between um the people and Facebook why because of ads right um in their case they're trying to

sell more ads which basically means you know learning as much as you what you can so you can be as so so that the ads can be as targeted as possible and um that of course uh so they're they're trying to gather as much data as they can this data of course is also flowing into prism Etc you know after the Snowden Revelations it's not like prison went away the government doubled down and there's a 10x or 100x there so um our decisions are getting shaped more and more and more by companies with a profit motive um that is against their interests and um you you it's very very subtle right like um Twitter does it uh Facebook does it Google does it all this Instagram all these it's unfortunate this way and it affects you know our decision-making ability but like I said

it doesn't stop there right it's not just you know okay you might see these things there and might change your thought but it actually affects uh the outcomes of Elections which then leads to you know um presidents being hired um who then lead to basically ignoring uh pandemics right and you have a quarter of a million you know you have more people killed in the pandemic in USA than the Vietnam War and this is um one of the big levers that affected this is because of this interplay uh between data and profit motives and this misalignment of incentives so so that's kind of like the sort of uh the problem we're trying to solve from the perspective of you know a Mis misalignment of incentives and so on around data and you can view it as sort

of a tear it down thing but I also like to view things in sort of a Build It Up way and I I really prefer that and this is where I see okay what's uh the powerful way for people to think about this and it really comes down to not your keys not your data your keys your data so riffing on Andreas antinopolis on the Bitcoin quote and this basically means sovereignty over your personal data right so you should be able to control your data you should be able to choose who sees what when you know this also has the side effect of controlling privacy privacy really is just about the shape of information flows right and that comes down to a question of access control so if you do that at an individual level then you can also group it into higher and higher level groups

uh families small companies larger companies uh Enterprises uh cities uh and even nation states right and they're all grappling with this so um if you can give them the tools to control and shape the flow of information them and about the things around them then um it can lead us towards uh where there's not incentive misalignment and in fact there's incentive alignment where you know if they share more in in a healthy way and so on then they can actually get rewarded and that's really the sort of Build It Up vision of ocean is about um you know uh tools for control of your data at a personal level all the way up to a national level um in a way that um helps to serve data sovereignty I think that incentive

misalignment is so key and I mean I think a good way to sum it up right if you kind of go up you go up the stack of this problem and is kind of fresh in my memory but like I think the social Dilma uh documentary that I watched earlier this week kind of sums it up pretty well or at least it makes a good attempt at explaining it in in layman's terms social networks platforms that that control large amounts of data uh are incentivized to use well the model that was created around that data is to sell advertising the advertising is sold to companies that want access to people's information in order to Target those customers more effectively and at the same time the companies that hold the data are incentivized to keep their users on the longest as possible because

that's how they maximize profit on the advertising side of that Marketplace the way that they achieve uh that goal of keeping the people on uh the platforms the longest well that goal was somewhat discovered by Machine learning algorithms that figured out that the best way to keep people on the longest is to show them outrageous that sends them into you know that essentially divides people that has an effect on you know we talk about sovereignty right you talk about people's sovereignty well I mean that that exists at a conceptual level the risk there at a conceptual level is sovereignty also in a general sense as in you know the sovereignty of societies and uh you know countries Etc because

people who are divided obviously um are are more more vulnerable and and at risk and I think it's a huge problem that if you get really into the weeds of it it's like okay well incentive alignments are broken here well you know is it platforms or is it simply the model is it capitalism that's that's broken in this particular model it's kind of like a it's sort of a chicken under the egg problem here but I I wonder if as long as there is sort of unfeathered capitalism and unregulated capitalism if this will ever change and if there will be better models that emerge and of course like ocean protocol is one antidote to that yeah I have a couple answers to that so um I mean one thing that capitalism recognizes that is

super unhealthy uh for any Market is monopolies right so that's why the Sherman Antitrust law was brought out and then after a couple decades they finally gave it teeth and that's what broke up the all the different pieces of of rockefeller's empire for example as well as led to the breakup of AT&T and so on we have companies that are now far larger and more dominant than basically you know the US steals of the world back in the day yet the The Regulators have forgotten that they can actually apply this tool to address this and that's that's an issue so this is basically not that's not a problem with capitalism per se it's a it's a problem with the enforcement of um antitrust so that's one one piece of the tool I want to mention the other one which is to me um

the happier um answer and it's co-ops so I grew up in rural Canada where um the local grocery store store was a co-op it's literally called the co-op we had those too they're all closed now though oh wow yeah yeah well and the local bank was called the credit union and that was the main bank where I grew up and um and basically there was kind of co-ops for everything and um these co-ops allowed um you know a thousand 10,000 people uh in the area to um each collectively own that grocery store for example and then uh get the dividends from the grocery store and it was acting in the best interest of the people and making a bit of profit on the side that's a very healthy thing there was another thing in Saskatchewan in fact at the time I think it was the large one of the largest

co-ops in the world if not the largest called the Saskatchewan meat pool it had I believe on the order of 100,000 Farmers as members and what it was was collective bargaining for Farmers so you sell your wheat and your barley to the saskat we pool then it goes uh as a as a large entity um it ships things by train to the ports it ships things by ship to to Asia and everywhere else um through the ports it does the marketing etc etc etc so it was a win-win right um the farmers BAS got some dividends from the ckat weat bll and um they had a market for for the grain they had distribution all of this and um it served everyone so this is actually a capitalist notion but it's capitalist saying cooperation is a good thing right and what I really love about the blockchain space is that um it

makes things like this much easier to implement as well as experiment with right to have um you know Collective organization of people towards um the betterment of that group of people right um in the form of dows and otherwise right that that's my kind of two answers I don't think we need to rethink capitalism there's been a lot of calls for that and even if we did need to rethink it I think it'd be very very hard the way it is but instead we can say okay on one one side make sure that um you know antitrust is respected and you know the privacy laws of Europe Etc and on the other hand double down and co-ops right and I think they could actually become U much more um common in this new age given how much easier it is to form them um in in the world of

blockchain you know like we're seeing for example the first Venture Capital firms that are Dows that are actually truly working right um I'm a member of metac cartel Ventures and it's it's an an amazing um organism to to observe so let's talk about uh ocean protocol it's switch gears a bit and uh so describe what what is ocean protocol and what does it try to achieve yeah so um I guess the goals are like mentioned address some of the issues around data in society misalignment of incentives as well as uh have tools for empowerment of people at the level of individuals families uh all the way up to levels of cities and Nations right okay and perhaps in the in the context of what we

were talking about earlier in the model how does ocean sort of flip the the model that we were describing earlier at the heart of it uh it's you know your keys is your data right um and then you can choose uh how to share that where but also you can um turn this data into an asset if you like right because you know the way we view it data is IP just like you know if you write a song and record it then uh that is a piece of Ip that then you can monetize uh via music Publishers Etc or via Spotify whatever you want right same thing with books or podcasts or whatever so uh data uh falls into that same category and of course data is useful in the sense of um you know people uh who build AI models need

data in order to uh make those models accurate they need more data and once those models are accurate enough then they can monetize it um in various ways you know more uh you know safer self-driving cars um more efficient traffic lights uh a lot of kind of almost mundane things but but this stuff matters right so ocean basically at the heart then is a set of tools to to make this easier to do at the heart it's access control so uh basically it makes it easy for people to uh establish a data set or a data service as an asset and then to to share share that asset or sell it transfer it whatever where there's maching around it and the way that we do that um as of the most recent release of ocean V3 the way we do it is

every single data service is its own erc20 data token and um by using that we leverage uh the full infrastructure of ethereum there's a lot of really cool implications and it also serves as you know at the heart it's Access Control right so it's sort of like unisox you know with unisx you can buy 0.1 unisx you can buy 1503 unisx but if you have 1.0 unisx in send that those to the Unis swap team then they will mail you back in the physical mail your uh pair of physical socks and so you are you can redeem those unisx with that pair same thing with data tokens um you can send 1.0 data tokens to the publisher of that data asset and in return they will give

you access to that data asset you know you can still speculate you can buy 0.1 data tokens you can buy 100 of them whatever you want but um in terms of redeeming getting Access Control it's that magic number of 1.0 so that's maybe a good summary ocean is a set of tools to um enable the web 3 data economy which is all about open um uh while reconciling privacy you talked about that every data set is an e an erc20 token what is a data set help us to understand what what that means specifically uh so there's it's every data service so data services can be data sets or yeah so I'll start with a data set though it could be simply a PDF it could be a spreadsheet or you know the machine learning version which is a

PV file it could be a piece of music it it could be 10 gab worth of worth of files um behind a directory so in Ocean uh we actually have uh it's quite General so you basically are simply selling uh a u well we have a a few different ways of defining a data service and it's flexible and it's going to expand over time to start with there are two one of them is a static URL where it could be basically say um a CSV file that you have sitting on Google Drive and um you then um sell access to that CSV file as defined by that URL sitting on Google Drive and of course it can be a decentralized network as well so so that's one example the the second example of the data service that we support is this is in the Privacy

preserving angle is compute to data so um rather than someone getting a URL and then downloading that CSV or whatever instead it's saying I'm going I'm a publisher uh maybe I'm a big Enterprise I'm going to sell my my data but people aren't going to download it rather they can go and run an algorithm R right next to my data and maybe just do compute a simple average uh from a particular column or a median or maybe something fancy you're building a linear model or maybe a fancy deep learning model whatever right so those are the two um Services right now types of data services that ocean supports and with time we will um support more and more and more um you know streaming data is is um coming down the pipe uh as one of the the most important ones but we see that this thing can get there can be

dozens or even hundreds of these things um so that's that's what we mean um and ocean itself um is sufficiently General these data tokens they're erc20 with one extra field uh called blob where it's just a string basically a bunch of information inside and that basically helps to support the various types of service Provisions so you you mentioned something that I'd like to to touch on you you said that the data can be stored on Google Drive when one thinks of you know the decentralized data Marketplace that you know we we we'd wish to have I don't think that storing data on like traditional Cloud platforms is the the first thing that comes to mind I mean in terms of availability censorship resistance privacy Etc you know help us understand the the the choice there of

storing data on on these platforms and what kinds of things do ocean do to you prevent some of the excesses that you know we've been talking about since a while ago well I mean at the end of the day you have to be pragmatic about uh understanding um you know what tools people are using right now and then providing a bridge to them to to sort of you know walk them um bit by bit over this bridge um it's not like you know you snap your fingers and suddenly you're in a full prist decentralized world um with the whole planet behind you right I should mention yes you mentioned Ocean Market so overall ocean is these tools which is smart contracts as well as libraries Python and JavaScript libraries and then react hooks on top and then on top of that we've shipped something that's a

consumer facing um web app called Ocean Market um and it is a place where people can go market. oprol tocom it's a place where people can go to uh publish data assets and to consume like once you buy them and of course you know swap back and forth trade on them um and you can even stake on them um and I can get into that a bit later so then towards your question if you think okay how do we make Ocean Market easy to use right for people it's it's web3 native you know you you you sign in basically by connecting your wallet that that's all all that but um for people that um aren't running their own um you know hosted service with with data sets how how can they actually um share their data you know maybe they don't know about filecoin or ethereum swarm or

anything just yet or or don't know how to use it but they do do know that they have a bunch of data on Google Drive or Dropbox or something right so uh you make it easy for them to to publish their data and you might say well that's not decentralized the thing is this is at the very Leaf node right so it's that one single person that has that data so the the the connecting platform is decentralized on the you know permissionless ethereum substrate as well as the smart contracts on top but that one final person at at the edge node um is is centralized by nature of it being supplied by that one person right so even if you say okay we're going to oriz this and stuff it doesn't really help because it's still one person supplying the data or one entity right and that's okay right um if they

are supplying the data and people don't want it they won't buy it if if they're supplying the data and they do a bad job where they have bad availability people will stop buying it right so they incentivised to do a good job there and I do see though that of course right like right now um people could um store something on Google Drive and Dropbox and a few other you know decentralized Services wrap it all up um make those all pins with PFS and then just give the ipfs URL right so um and that's a nice Bridge ipfs serves as a great bridge because you can have storage on centralized and decentralized storage mediums while at the same time providing that single URL so it's all about a bridge to get people across towards eventually this sort of public utility uh Network infrastructure where everything is permissionless um

including you know the cloud storage Etc for sort of all of humanity but we have to get there one step at a time great yeah I mean I think that's a good approach to allowing people on board uh with more Simplicity is to open it up to all the different types of storage providers that that exist and if within that we also have decentralized storage providers like ipfs or SC or some of these other ones and you know that at least provides alternative so that we can have that censorship resistance option if uh we wish to to choose it exactly and and just to add there too like ocean doesn't care because it's just about the URL right so people can provide a URL that can point to a service on CIA or an ipfs which is wrapping some other storage service or a Google drive or a Dropbox or whatever so

ocean doesn't care so let's talk about the different stakeholders in Ocean so obviously there's like the owners of the data you know those who provide that data point that URL you mentioned then there's also those who who verify the data there are the curators can you describe all of these different participants these different stakeholders and how how do their incentives align you to create you know this this platform absolutely so um at the heart of it you know the heart of the value creation is um a publisher publishes a data set and someone else comes along and buys a data consumer so you want to connect those data Publishers with the data consumers that that's the heart and the data consumer when they consume it they're

adding value to their business or otherwise right so you want to make sure that that Loop is is a solid connection so um Ocean Market and the other markets that can be created and then ideally that business is providing also value to the publisher right it's sort of this closed loop exactly well this is the thing right if the data consumer um doesn't you know finds that the data that they buy from the publisher is garbage then they'll just stop buying from the publisher so the publisher themselves is incentivized to create quality data right the heart of capitalism frankly right um in that way and that's actually a good thing um you know it aligns towards value creation that way in between uh is at the lower level of course um the main actor is simply the the the connectivity of ocean uh at the you know substrate level

ethereum main net right now now the smart contract level and then um the marketplace is on top and you know we've shipped a first Marketplace ourselves as ocean protocol Foundation which is um it's called locean Market I mentioned it and that's basically you know this uh you can view it as a multi-sided platform where the the two most critical um participants are the Publishers and the consumers however um you you want a market to form you want price Discovery all of this right and so for for Price Discovery you need the data services themselves to be sort of assets you know first class assets um and within with an ethereum of course um you have kind of two choices you can make them nonf funable or fungible but if you think about um data right when if I'm a

publisher publishing a um a data set it's it's not just like one person is cons going to consume you're going to have 10 100 a thousand right so it's it's clearly a more fungible thing so so basically we have these data tokens that are then um there as assets and it's those that flow from the publisher to the consumer now uh you can say okay well how does the let's say that the consumer data consumer is looking at data sets but they they want to have a good feel for like what's a good data set versus not right this is where curation comes in so so how do you go about um uh you know leveraging uh crypto infrastructure for good curation also how do you go about leveraging crypto infrastructure for Price Discovery right and this is a question we would get again and again and again

um in in Ocean from you know from the very earliest days 2016 2017 to um until basically shipping V3 like how do you set the price and there's lots of lots of theories about how to do this right um you know you can have auctions you can have royalties uh you can have uh order books you can have automated market makers etc etc right so so what do you do and we decided U with all this that um sort of taking a page from the the defi Playbook uh let's put in um an automated Market maker uh so when someone goes to publish their data set um it becomes a data asset its own token and then uh in the same right after that they have the option to publish a pool

and so we've got balancer technology under the hood so they publish a pool that is the data token and ocean token and um they put an initial liquidity of the ocean token and now you actually have an authentic price signal U between um basically as a ratio of the number of data tokens to the number of ocean tokens in there other people can come in there and stake and also people can go in and swap back and forth ocean tokens for data tokens people can stake and unstake to the pool and you know the cool thing about um uh amm's automated market makers uh adding liquidity being a liquidity provider is the same thing as staking right and this is very different than sort of the previous idea normally staking sort of locks up and slows down the velocity of tokens but in amm uh this sort of magical beautiful

thing happens where um by by providing liquidity um it's taking that actually increases the velocity and and the usefulness so this is actually what um Ocean Market has under the hood it's these balancer pools um and that's providing this um it's basically helping to form this market around this specific data token right in addition if you think about it you know you go to um balancer uh website or the unisoft website and by default if you want to look at all the pools it will sort by um which uh pools have the highest liquidity that's a really good um proxy for the quality of a given token it's not perfect um but for sure you know all the the garbage spam stuff is at the very very bottom with like $2 liquidity

so it's already gone and it's a pretty good first cut right so um that's actually also what ocean has itself uh if you think about it by default you go to Ocean Market and it actually shows you a sorted list based on the amount of liquidity in there so that's a signal for the quality of a data set it's really hard to arrive at a perfect signal for quality of data set what you need to do is uh provide a bunch of Statistics authentic signals um that people can use to assess whether a data set is useful or not useful to consume but also useful to invest in right and this is a key thing um you know so I'm going to mention there's sort of there's in terms of the the stakeholders in the system I've talked about the the the foundational ones which is the the

publisher and the the consumer data consumer there's the liquidity providers which are the stakers which are the curators it's the same thing in Ocean and uh implicitly they're also doing some soft speculation um because right now there's a 703 weight so anytime someone stakes in one of these pools it's 70% ocean 30% data token and that's simply because uh you know to avoid price fluctuations and to align incentives a bit better but besides that you know people can just purely speculate if they want right they can invest in a data token and hold if they think that the person who has published this data token is a high quality person if they know them if they think that you know maybe they they try out the data set they see it as high quality great they can buy it and they can hold it so

so basically this is also a key person in the overall ecosystem and so at the end you have the Publishers the consumers the the LPS SL curators stakers and this speculators and this is sort of the heart of it and then you're you've got this across many many many different data tokens SL pools and this is basically the uh how the markets are forming and what's happened you know we released to Ocean Market about 3 weeks ago and it looks like a microcosm of crypto itself right you've got you know you've got people that are doing the equivalent of an Ico which is an Ido initial date offering they're promoting on Twitter they're actually announcing the launch of it you know 24 hours before or a week before or whatever now and then people Pile in when the thing

happens s to to to invest and speculate and so on and at the same time and then you have data schillers and you have rug pulse and you have fraud and all of these things that you have in the broader crypto ecosystem but you also then um you know in this all this messiness you have a market forming this is how markets are born and so you know 2017 yes there was an Ico bubble but this is actually how the Bro crypto Market was born before that it's pretty quiet right there was um Bitcoin there's ethereum there was maybe 10 other coins but 2017 after that happened you know now we have these indices on coin market cap and coin gecko that point to something quite healthy you know 100 plus um coins that are really healthy so this is what we're seeing in um in in the world of data now

with these initial data offerings idos and speculation and all this you know data is truly becoming an asset for the first time ever and it's fully open just like defi right that's really interesting the data tokens represent specific data sets so there's there's a data token for each data set correct uh for a data service which is typically one data set but it could be a thousand right but it's whatever granularity the publisher decides yeah okay I see and so that's how you arrive so there's a liquidity pool essentially like an amm for for each of these data services that that's how you arrive at Price Discovery for that specific uh data service and the data set or data sets that exist within it exactly exactly and then yeah and I mean it's um that's the primary

market right so when the publisher publishes they deploy this pool that's the primary Market but then people if they want they can set up secondary markets too so we've seen people creating um uniso pools side by side and selling you know OTC data tokens and stuff right which is great so uh and as time goes on you know there's going to be some like large cap data data tokens right right now you know it's all relatively small yeah maybe traded on exchanges yeah exactly right so we're we're in early days but already you know in the last um 3 weeks uh we're at about 2 million ocean stick which according to the prices right now it's about um1 million EUR worth of worth of data asset stick so um you know it's early days but that that's quite exciting and we're um Ocean Market usage keeps growing growing

growing so I think the most recent numbers are about um 10,000 uh weekly active users um so I think that's that's the number yeah things are just growing growing growing and right now our challenge is to to address simply the scale issues as well as make sure that um the environment is as safe as possible to mitigate the effects of rug bulls and and fraud and so on yeah well we'll get back to the scale in one second so this ocean uh Market that that you mentioned is the the first and I presume the only market for the moment do you anticipate other markets forming and what kinds of specificities could those have um what are the types of things that would cause that to happen yeah absolutely so um we want to see a lot of them right you

can't have an economy a data economy with just one marketplace right you you need to have tens hundreds thousands of these things right and so Ocean Market code itself is fully open right um Apache 2 license so basically very um uh unrestrictive uh very open to use and um so we do encourage that and we even have um we we point to people of how they can do the you know Forks of Ocean Market or create their own thing and under the hood of course everything is on ethereum Main net including the metadata all of that right so it's very easy anyone spinning up another Marketplace can um basically get have all the data assets that are on Ocean Market on their Marketplace so how's this happening we view it as sort of a top down and a bottom up thing so top down we're

working with um a few different organizations that are interested in building own things so um for uh the better part of a year we've been working with Daimler um and around their own uh Automotive data exchange Marketplace still have your old Enterprise clients I see yeah I mean you know these are long-term relationships and whatnot um and it's it's kind of exciting right things have changed a lot in the last few years where Enterprises are much more open and comfortable about this so so we're pretty happy about that and there's some other basically government organizations in one out that we're working with too um that uh we have hav't publicly announced yet but um it's some of the information is already out there I guess in addition to that there's uh sort of startups that uh have publicly announced that they wanted to

have ocean power data markets such as molecule bzen protocol dexr and otherwise and each of these has their own sort of specific vertical right so um dexr for example is in the logistics um area where it's about um data that uh for example their customers they have about 10,000 trucking companies working with them and each trucking company has one or a few trucks and you know what is the specific location of each of these trucks over time what are the goods inside each of these trucks and right now all that data is private but it's that information is super super useful to uh in two ways one of them is to Wall Street right so rather than having to look at satellite images you can get much more fine grain information but secondly to um optimizing the scheduling of the trucking themselves right so you

can do basically better uh more optimized Logistics over time and right now the average truck uh according to stats I think it's either 1/3 or 2/3 empty because just the optimization is so poor so um once there starts to be a market formed around the data on this then you can actually optimize against it better better better so those are a few there but um over time we see that there's going to be marketplaces that specialize along a few Dimensions one is verticals like I've mentioned Right Automotive uh like diimler or um Logistics like Dex rate uh other dimensions are maybe you'll have a Marketplace that's totally tuned to AI right um training AI models and um and there can be variants of that like human protocol who we're working with as well you know they do uh sort of the H capture which is sort of a variant of

recapture that is um basically uh much more incentive align with the users basically so there's opportunities with the H captures of the world the human Protocols of the world um and other AI plays too out there where um it's just sort of a win-win and other things too like privacy first marketplaces or specific geographic regions and remember like you with a Marketplace you have to have a terms of service uh it's sort of a Last Mile facing thing so um certain countries might have very specific regulations that you want to serve so maybe you focus on just that country and maybe even geoblock everyone else um as you as that Marketplace and that's okay right you know we can't control things at the level of the substrate you know permissionless ethereum all that uh or the smart contract but that last mile um

of course things can be controlled by the the marketplace operator and that will actually help to serve specific niches so there's quite a lot of variety there oh yeah I guess one more important one is uh besides you know the publishing and of the data assets um how do you price right so by default we have these um balancer pools um but you can also uh you know make it maybe some people want to have Unis swap pools or or uh bankor or otherwise maybe people want to have uh orderbook based markets or Dutch auctions maybe you want to have a Marketplace that does a better job of initial data offerings idos right um just like if you think about icos it's all these variants that people had you know and in that case even too right Dutch auctions uh etc etc etc uh we can

see the same thing for data sets so there a huge variety and we encourage people to play uh with all of this you know the the capture thing to is is uh I think is one of the things that people don't realize to what to which point uh their incentives are are are misaligned there where there is incentive misalignment there and actually so you mentioned H Capia and I've I've seen H Capa uh before and I'm just on the website and I had no idea that you know that sort of Brandon Ike was behind this and that they're you know buil on on ethereum apparently or like they leverage ethereum this is interesting I'll have to look more into this yeah they're they're they're probably like the most used dap that no one's heard of right and um you know the

people behind it yeah it's an amazing team I believe Brendan Ike isn't directly involved he's just an investor or something like that but also helping to support it but he's definit yeah he's involved in some way I guess yeah yeah I I I was I was confronted with this recently where at least here in France to in order to use certain public Services you're obligated to to fill in a a Google recapture and you know in in French culture and probably also in Germany would probably be like similar sentiment to this if people knew that in order to access Public Services they were obligated to to enrich a gaffa like what we call in French like Gea you know the Google Amazon uh Facebook and apple Etc I think there was there would be you know some some outrage at least at that

idea and maybe we can unpack this because it's a nice example um so you know when you fill in recapture um there's usually two in a row that you do the first one is to basically verify whether or not you're human and the second one is basically Google hasn't yet classified whether which picture uh has a truck in it or not which picture has a car in it or not right and you're basically providing labels for it basically to help train the algorithms because the algorithm needs to make this mapping of right of image um to yes or no there's a truck in it right and so you're supplying data for training and that's you know hugely useful to Google for its other applications so you know you think that you know you just need to get into the site but Google itself I think 99% of people don't know this yeah

I think 90% people are totally unaware and actually I was unaware of this until recently in fact I I was unaware that you know the previous capses that we had before which were just like fill in these letters or write this word was also operated by well most of them were operated by Google and was to train their um book scanning uh algorithms so yeah so to summarize then right so basically in doing that second step um you are um giving value to Google by your human efforts right but what if instead of that value going to Google that value was going to the person running the website and to the holders of a token um and even maybe back to you directly right and that's what um human protocol is about right um the website now can monetize actually from this they don't even need to serve ads anymore they just

monetize based on people filling out the the um you know proving they're not a bot right which is pretty cool um and then also though you know they're going towards having their token and stuff and so there can be nice alignment there for the people who believe in this and finally you know maybe at some point also back to the person that is um proving they're not a bot in the first place right so to me it's a great use case I don't know why but uh this kind of a tangent but like I have been just bombarded with with Recaps recently and I don't know if it's my IP address is flagged or something but I'll have to do 10 or 12 attempts before I can actually access a website and it's it's so painstaking I caps this there's part of a reason for it and that is basically

the AI models have gotten better over the years right so they're running out of easy stuff so they're basically um getting you to do the hard stuff because the easy stuff has already been modeled right I think it might have to do with the fact that I'm filling in so many Capas that maybe they think I'm some kind of a Capa filling bot or like you know someone in some Far Far Away country filling in caps for for pennies that could be it too yeah uh so let's talk about um you know privacy which is so Central to this entire topic well I guess my first question is what types of compatibility or compliance does ocean have with uh regulations like gdpr or the the CCPA in California ocean uh serves these

regulations very well so uh in gdpr uh for example um there's this idea that certain sensitive data can never leave European soil if it's generated on European soil right like Medical Data yet if I'm a a medical researcher and say USA um the ideal is that I have data across you know 10,000 hospitals across um Germany and France and all of Europe as well as China and Australia and so on right so uh how do I get access to this data with gdpr um it would have be basically well the traditional way was where you basically try to make deals with hospital by hospital at a time and store it all in one big Central database and then um build a model from that and

actually Google had something called project nighting Gale doing this and they had a huge huge push back and rightly so right cuz like medical data is super sensitive and actually there's other ones too like um other big organizations that were trying similar approaches and that's really like a big no no fortunately um there are uh better ways to approach this and so when I think about privacy the best way is it's not about like either it's not a black and white of I see my data and no one else can because that's not very useful it's it's more like structuring the flow of data you know who can see what when right and that comes down to permission right giving permissions to people revoking permissions to people to see certain data uh data services so so that that's the heart of privacy now going back to this example um from Health what

you can do is if you're trying to build an AI model why not do something like Federated learning where in Federated learning you create an initial random AI model neural network whatever and then uh it's just random at first it's super stupid but then U it goes and it sort of as this bot it kind of walks to the first hospital let's say a hospital here in Berlin gery and it updates itself based on the data in in that hospital in Germany so now instead of you know 50% error like you know basically random uh it's got 40% error right and then it goes to another hospital let's say in Paris um and it updates itself and now it's got um 30% error and by the way the whole model doesn't have to go to the hospital it's just um an update of the model so um you don't have an attack

Vector there and then you go to another um Hospital in say Leon France um you keep going going going going from hospital to hospital to hospital and the error keeps going down down down down down so once You' went across um 10,000 different hospitals you've got a very accurate model but what's cool is the data inside each Hospital never ever left that hospital right you know people have been uh developing these techniques for Federated learning um going back to 2015 2016 and Google started making it really popular and famous in sort of 2017 era the thing is Google's version of it is yes the data itself can stay um at the leaf nodes at the edges but guess who gets to play the middleman Google right so a problem once again and you've got leakage there so what if you can

actually have a middleman that is you know not incentive misalign that can still help to coordinate um all of the this learning of this model and that's really where ocean can really help so basically what you're doing is you can learn your basically do the training weight updates Etc at the last mile at the edge as well as the orchestration in between can be done um using decentralized uh substrates like and and ocean basically can play a key role in this because um it's you know these data tokens are providing the access control of you know who can see what um data sets when right and so that's kind of the dream right now no one has built this particular application of ocean with Federated learning but you know

there's some really great um efforts around this in an a fully open Way open mind is a project out of the UK led by Andrew tras an amazing person and you know this is kind of where they're headed in and um we hope to see an integration of open-minded ocean at some point and there's talks around that and stuff too so I think you know that's a good example and you can do this in a simpler way too you don't even need to get fancy with um building an AI model it could be Simply Computing an average across uh 10 different or 10,000 different hospitals right so uh and that's very very useful you know if you're a multinational Enterprise and the data can't leave any one of your um offices then you can compute an average across each or in Canada right Canada actually has this problem too they're

trying to get Health Data um from the different provinces but if you each province has own rules and so if you sort of take the intersection of the rules um from all the different provinces of Canada you end up with an empty set it's zero the rules don't the rules Collide so a very nice solution to this is something like this you know Federated analytics for just averages or Federated learning to get a bit fancier and that plays well with gdpr basically right because then the data never ever leaves the soil so how does ocean address permissioning of data as it's utilized and transformed and I I don't know if this is the right way to think about this but I imagine you know data being used to train a model and and then you know then I kind of Lo lose track of

like how that data exists like it when form it exists and in the context of gdpr or other regulations like it if the you know the owners of that data still have rights to the results of the computations that were performed on that data you know essentially can can one retrieve the data once it's baked in does that even matter and is this something we should be concerned about at scale perhaps more than just an individual level yeah so I think there's two pieces here um to unpack this one of them is um you know what about where there's sort of this pipeline of you know data being transformed being transformed being transformed and the other is you know um what are the rights that would attach to that so um you know

in an AI compute pipeline um you might have you know some initial raw training data and then it might get cleaned so then now you have clean raw training data and then it might you might train your AI model and then you'll have your trained AI model and that's a piece of data as well and then you might have some new data coming in to that you want to get it to predict on and it makes predictions and those predictions themselves are also data so we've got um data at various steps along this flow each one of those um is its own data asset right it can be its own data token if you choose uh you don't have to it depends on you know what workflow you want but with ocean ocean doesn't care right if it's the super raw training at the very beginning or whether it's um

some predictions at the very tail end or something in between right um it really doesn't care if you do want to have it at every step along the at every step along the way um that actually probably helps towards Providence of the data right so um with gdpr and all that you um actually one of the requirements is you need to know where the data came from right so that it wasn't so this actually um ocean really helps that way because then you can um have data that is trained in a way where you know where the raw data came from um and you can kind of vot for and stuff right and that's a big problem even preg gdpr days and stuff right um but this will actually help to address that but now you actually have the Providence of of each step along the way um to the tail

end of you know the you know your Providence of the initial raw unclean data Providence of the clean training data Providence of the trained model and Providence of the the final predictions and those predictions you'll probably have many sets of those over time so uh that's uh you know helpful for gdpr and just as an asset in general right it helps to drive the value of the asset just like like a scribe days right um in a scribe you know we were doing digital art and um the value of an artwork is only as good as its Providence right um if I had a painting that and I claimed it to be by Leonardo da Vinci well people will say well prove it right like show me the the lineage of ownership right and if I was able to show that um then you know I could have a fortune in

my hands but if I can't show that then um it's probably worth zero although there can be some Arts um you know experts that come along and try to verify it and it's often kind of fuzzy there's you know even a fraud market around just that right but the point is pro Providence really really matters and um you know what ascribe had done was establish Providence for for digital art and that helped to establish the value of the piece in a big way and for data it's also super helpful right because we'll have you know much better um sort of culture around Providence of data and models that are trained and so on and that will actually lead you know make it a lot easier to to comply with gdpr and so on so that's on the sort of uh the one part the second part I'll be quick

on this is uh the the rights so basically um we view uh data as IP and uh and specifically as copyright if you have sweat off the brow to generate this data then this is actually your copyrighted data as an individual or as an organization and so with that then you can do whatever you want with it but um the way that ocean sets it up is Ocean Market specifically because uh you know the lower levels don't care but Ocean Market it has the terms of service that we thought through and even Drew on from ourcrib days and so on of course which in turn draws on things from like second life and otherwise we uh in that terms of uh and conditions it basically says um you are claiming that you have copyright or or at least the rights to

this data initially and then um when the next person um buys it from you they are um getting rights to basically it's sort of like a a license right um in fact it is a license and then you have sub license sub license sub license going along but it could be where you know if you want you can have uh the the the ocean Market doesn't support this right now but what we envision is that you can have licenses that are more restrictive and uh towards reusing uh data in various ways and this kind of goes in the realm of remix rights right like um you know when when um an artist say a DJ uh does a remix of uh of a song created by say a rock musician then they have to get a license from their rock musician

to get uh to do the remix and probably the rock musician will get a cut of the royalties at the end as well right so it's a similar thing here where there needs to be some sort of legal agreement uh between the the original uh creator of that work or the exclusive owner of that that piece of Ip and the subl licenser for the remix rights and we'll we'll see how this forms we see that you know crypto is a funny thing there's sort of the the full follow of the law to the letter of the law etc etc etc approach and there's also the sort of more wild Westy approach that some people prefer to follow um given that you already have a lot more protection built in into the blockchain itself so how much do you need to to leverage existing IP laws and we don't have a

good answer to this we don't know how it's going to play out so we kind of support both yeah and I know I know you guys have spent a lot of time thinking about this I mean these conversations were happening you know even in the days of of ipdb and you know how ipdb could be uh compliant with gdpr and there's been a lot of thought and so I'm like I I trust that uh that you guys have you know found suitable solutions to these problems one of the things we haven't really talked about very much is uh the fact that so so the previous version uh we're now of course in V3 of of ocean the previous version was built as an ethereum side chain and you mentioned before the show that you're now on the ethereum uh main net can you describe how that works so we haven't really

talked about the smart contract and what it does exactly and then like what actually does exist on on the main chain explain for our listeners what that looks like sure happy to um and you know the reason we initially did the POA uh side chain was we saw that we would run into scale SC issues and um the V1 V2 versions of ocean were were pretty complicated so uh we actually had even run tests to deploy to ethereum Main and it was um super painful frankly um it took you know days for the first successful deployment um and this is just simply because of the she complexity of the contract with our V3 we said let's change the mental model where instead of having our sort of own custom access control um smart contracts let's put that into the context of uh

ec20 and and then we can leverage all the infrastructure of erc20 directly right um just like I mentioned before with analogy to unisx Etc so uh that's what uh uh the heart of the mental model for ocean is is you know uh you have access to a given data asset you have custody of this access if you have 1.0 data tokens and then you can redeem that if you send the data 1.0 data tokens to the publisher and so so that's uh the heart of it and that allowed us to simplify ocean a lot uh so it's um you know radically simpler than before and also simp conceptually to deal with much more interoperable and so on right metamask traditionally a crypto wallet is now a data wallet right Tresor is now a hardware data wallet right balancer and Unis swap are not only dexes they

are now data exchanges right Aragon and DOW stack are now D data Dows right so um this is all possible um and we can have you know stable coins Based on data assets this is all possible simply because of the erc20 routee so so that's kind of the heart of it the mental model of data tokens as Access Control and so what it looks like um in ethereum there's uh basically three main groups of contracts and they're quite simple one of them is a factory to publish erc20 data token and um so we have a template for an erc20 data token and I guess I mentioned before it's it's actually simply the open Zeppelin ec20 template plus this extra uh field called blob and that allows a lot of

flexibility in terms of new sorts of data services and to save gas costs uh rather than um like the reason we have the template rather than just doing it from a library and stuff is to make it simpler to deploy and also to save gas costs we're using uh uh EIP 1167 proxy contract um approach such that it's just much much cheaper to deploy so that's the first part the second part is the balancer pools and uh once again you know uh we're we're close with the balancer guys uh I've been an adviser to them for a couple years now and um we at the same time we did not use the balancer uh contracts that are deployed to M it directly and the reason is gas costs as well um it's okay for someone who you know wants to create a pool of

eth and say ocean with you know millions in liquidity or eth and die with tens of millions in liquidity whatever right but if you've just got a a data token where it's much more longtail asset of you know 100 bucks 1,000 bucks liquidity then U are you willing to spend the gas fees of $50 $75 whatever the the gas prices are um just to deploy that and it's it's much more of a stretch so we said you know what let's also do a friendly Fork of the balancer uh contracts so beool and so on and the factory so they've got a factory with plus a template uh and have it also follow this EIP 1167 proxy contract pattern so we have that as well so that's the second part so we've basically got a factory and template for data tokens a factory and template for

balance or pools and the third thing is simply just for metadata it's a very simple thing it's a simple contract DDO doall and um with it you have um basically if you are the publisher of a given data token then um you have a slot in that particular smart contract where you can uh write the metadata and and update it uh and the metadata is things like you know name of the publisher uh description which can be pretty long um and a few other fields so so that those are the basically the three main things and um they're all simple on purpose and from that right sort of in the stack we have a piece of software called provider which does the handshaking for the publisher to to receive the tokens and to give access and we also have another

piece of software called um Aquarius which is uh basically a metadata cache to make it easy for the ocean Market to serve the data without having to retrieve it directly from onchain all the time so so that's the the the components simple on purpose and even as time goes on hopefully even simpler obviously you've been working on on Ocean for some time and since you you began uh this this project like other blockchains have come along the way that perhaps uh offer more scalability than you know like the V1 ethereum have you considered building ocean like separate instance of ocean on other blockchains or perhaps at some point uh porting it to like something like salana for example where there's like very high

through what what that additional scalability provide uh ocean that it does perhaps doesn't have today yeah absolutely we've thought about it right I mean I gave a talk on bitcoin scalability issues in 2014 and um we had such scalability issues with a scribe that uh we you know we built our own blockchain just for scalability right um blockchain database Big Chain DB so we thought about it a long time even theories around it right that there's sort of this fundamental trade-off between decentralization consistency and scale right like you want ideally you're fully permissionless decentralized and you are consistent as in you solve double spend and you are um scalable as in um can handle sort of planetary needs right and when I wrote that post in 2016

I think it was um it was you know that was kind of a revelation and it was very useful as a model right and so uh ipfs for example is decentralized permissionless and um scalable but it doesn't solve the double spend problem right so it's not really a blockchain per se um but it actually has some really cool data management with crdts and stuff ethereum and Bitcoin um they are permissionless and decentralized uh as well as consistent you know they solve double spend but they haven't been scalable traditionally um and then big chainb went the other route where it said okay we need scale and we need um cons consistency self double spend so we're going to loosen off a little bit on the decentralized by starting out being Federated you know po po right and

that was the decision at the time and others have discovered that since right now you know about a year later Vall discovered it or so maybe half a year and now it's more commonly known as the scalability trilemma right i' called it the dcis triangle so it's quite quite a well-known thing and the cool thing is um from the time that I wrote it I was hopeful I said this is just an engineering problem it's going to get solved people are going to find ways and lo behold they have right which is great right and the usual trick um of of a lot of these is to leverage random numbers you know M Carlo algorithms are an amazing trick for scalability um across the board you know use them a lot of places and you know how efe2 does it help um polka do does it uh how alaran

does it in more is where you you know have this list of a thousand or 10,000 candidate validators and then you randomly select 100 of them or so right and then those become your validators for the next um you know hour or 24 hours or whatever and that's a very nice approach because um it kind of addresses issues and there's other approaches as well right uh salana for example yeah they focused on solving the band bandwidth issue drawing on their days as Qualcomm Engineers right and I have great respect for ccom engineers I worked with them a lot in the past so I think there's a lot of great approaches out there that you know essentially DCS triangle scalability tremma you know at first there was just theoretical Solutions and then people started building the real solutions and you know they're coming live which is great for

ocean uh we we've been you know tracking all of these um and we said you know to start with we're going to deploy an ethereum but after that you know we envisioned that ocean um to be truly ubiquitous and that is part of the goal of ocean you know to have a true data economy for the globe we need to be on all the substrates basically any substrate that has any usage at all we should be on it and so it's a journey right to get there bit by bit by bit so start with ethereum and then uh start to deploying to others um either ourselves as The Core Ocean team or encouraging other people out there in the ecosystem to deploy but it's not just deploying the ocean contracts you need to have Bridges um to connect to the ocean Community because we need long-term

sustainability um and we can get into that as well so that's actually sort of the constraint that holds us back from you know deploying a bunch of them right now and you know there's other examples of this out there already right like usdt is on many chains um more recently um chain link has sort of done sort of a blitz scale to lots and lots of chains as well and I think that's great right so we envision the same we think there's a lot of great teams with great technology out there and Cosmos and polka dot have done some extra cool stuff to to make this easier for a lot of things too so you know we have relationships with a lot of these teams um and we're hopeful and it's definitely a part of Ocean's future towards ubiquity cool it's good to hear so as we

wrap up I I I wanted to talk a little bit about the future and and the ways in which you envision ocean will evolve and one of the things that came to mind is this idea of data markets as a data stream uh you know currently in the ocean market like as as I understand it one you know uploads a data a data set uh and that's sort of like a a fixed asset and one can purchase it and you know that data set might have different versions or it might evolve over time but it's it's it's very much like a a sort of fixed uh type of um of asset but of course you know data Flows In in permanence and uh and one you know might have use for like a a constant stream of data and I think this would be useful

you know for building applications like social networks Etc H how do you see ocean evolving towards a more fluid marketplace where you know data flows can be supported yep so this is uh yet another type of uh data service so just like right now ocean has static URLs and comput to data as two types of services um definitely uh streaming data is a type of service that uh is a priority for us to support there's actually many variants of that right like graphql actually has built in streaming support and um there's other um you know sort of web 2ish techn IES that also help to uh support streaming data so so we look forward to to having support for that and then as time goes on you know we see

that these are going to get become more and more refined in terms of the support so more specialized so maybe there's going to be 10 different variants of streaming data you know there's some some great projects out there that do streaming data probably streamer comes to mind as one of them and you know we're collaborating them great team um and that will be a very nice feed of data into ocean um ecosystem and Ocean Market itself right um so so that's I think a good example example there's a nice stepping stone piece and that is because the um the URLs themselves are static um under the hood people can keep updating the data set so we see people um in Ocean Market where they they post a data set for sale but then they promise to update it every 4 hours or every 24 hours and that's happening

right so that's sort of a way to to kind of get there a good good example of that is is swash where um it's this data Union of thousands of members um where they're sell collectively bargaining collectively selling their uh browser uh um data their browser history data as this data Union and then they're selling that actually um on Ocean so and that's also related to the streamer project too so we're we're quite excited for many many data services over time and there's other you know decentralized data services that we think are going to be very very useful feeding into ocean as well you know the ones that are more pure data- is um such as numeri signals chain link uh feeds um and more and then uh also the storage Services themselves right um they're starting to accumulate

more and more data too um the file coins and and seas and ethereum swarms of the world and so on right so all these things I think are going to be you know uh better and better supported over time in more direct less frictioning ways as a note to end on I'd like to ask you what types of things do you hope people will build on Ocean what would be uh for you like sort of a a sign that ocean has achieved its gold overall I mean generally right this isn't really it's a vague gopost but ubiquity right like where it's um kind of just part of Internet infrastructure in a way that everyone kind of accepts it right just the way that um TCP I is like that and the web the web on top um and so on and

uh to me that would be great um to get to that point um but it's going to take you know probably decades right um that's okay right H what does that look like um in specific measurements um maybe just you know knowing that um ocean tools are used by these higher level uh by by different like all all the different organizations as just part of their overall toolbx uh but also critical to that uh you know because this is not just a one or two year Journey but you know decades long sort of thing and also it shouldn't be dependent on just myself and The Core Ocean team we need to actually have um a plan for long-term sustainability to help make sure this is well funded right and on that you know I won't go into too much detail but we did design System

Dynamics around ocean for exactly that where there can be funding over time 51% of the token Supply uh follows uh Bitcoin style emission curve and this goes into basically funding for the community to keep building and developing projects on top whether it's uh well a few things core infrastructure uh apps and Integrations on top um U Outreach and unlocking specific data assets and so on so those four things uh are things that can get funded over time by this U earmarked supply of ocean the majority of ocean suppli is earmark for this and and then how do you curate that and uh the answer to that is uh via Dow technology right um that's basically technology for collector decision- making over time so we are in the

process of rolling out ocean da which is sort of the final piece of the puzzle of the overall ocean system and um it's going to be a humble sort of thing we're going to start um slowly start with small budget but then over time Bit by Bit by Bit grow the amount that is funding and then at some point flip the switch and it'll be funding from this 51% Supply as well so so that's kind of uh you know critical towards uh Ocean's goal of ubiquity and from there you know there's going to be other posts and stuff that are be going to be interesting along the way but I guess another one is where you know when when you stop hearing about people um complaining about how bad Facebook is and so on right like when that's no longer part of the conversation that'll

be a pretty good goal post right or when people talk about how you know they're making half of their income from from data that they're selling from their personal data or from other things on the side that's a good goalpost so so things like that right towards this overall goal of ubiquity as sort of infrastructure for civilization that's a great note end on Trent thanks so much for coming on once again and uh hopefully we'll have you on a fifth time maybe uh in some in in sometime and hopefully we'll get to see each other in person very soon for sure thank you very much thank you for joining us on this week's episode we release new episodes every week you can find And subscribe to the show on iTunes Spotify YouTube SoundCloud or wherever you listen to podcasts and if you have a Google home

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