Amir Mabhout: DATALATTE – NFTs for Data

Amir is the founder of DATALATTE, a project using NFTs to help you take back control of your personal data. We discuss their first NFT drop focussing on Netflix data and explore how DATALATTE could begin opening up new opportunities for Data Scientists and Entrepreneurs.



The following is a rough transcript which has not been revised by Ocean Missions. Please check with us before using any quotations from this transcript. Thank you.

[00:00:00] Scott: Yeah, today we’re joined here with Amir from, data latte. and he’s gonna talk to us a bit about the work that he’s been doing. Data latte is a project inside of the ocean Dao, and it’s doing some really interesting stuff with NFTs and personal data. So welcome to the show, Amir.

[00:00:19] Amir: Thanks a lot, Scott. It is a pleasure for me to be here is actually my first podcast. And I’m happy that you’re doing good man.

[00:00:28] Scott: Awesome. Well, yeah. Glad to glad to have you on board here for your first podcast episode, and I’m sure it would be the first of many more. So I was wondering if we could start off and just tell us a bit about yourself and what led you to begin working on data latte.

[00:00:44] Amir: Yeah sure, so basically, I’m an engineer. I, I finished my PhD in microelectronics chip design about a year ago. And through my PhD program, I kind of got to the conclusion that I don’t have interest in, in this industry since I didn’t feel like what I’m working on is actually solving any real world problem.. So it was around the time that the pandemic hit..

So I left the university and started traveling in my van around Europe. Then there was initially writing my thesis on the road and afterward I adopted my dog and Pedro in south Spain, who is also my business partner now. And. So on the road, I started exploring all types of business ideas. My first concept was actually a cafe catering to dogs and humans.

And so I started to read about dogs, diet, and it started cooking for Petro. And after a week I realized that he’s losing weight. So I figured out maybe that’s the wrong idea. And at the same time I was parked outside of a resort in, in south Italy. I was doing work away in giving advice to this resort under solar power management.

So from that, I got really into urban sustainability for a while, and I was towing the idea of founding a fully sustainable cafe.. To showcase urban sustainable technologies and promote a greener way of living. And originally I was going to do that in Berlin. And so I started doing a lot of research and the more I researched, the more I realized it wasn’t feasible.

And I was more also interested in technology than food and after spending so much time coming up with all these different types of technologies, I want to put in the cafe, I realized that you didn’t have any idea or come up with a decent menu for the cafe. So at this point I gave up on the idea of actually going to food industry and I thought I better stay with technology.

And, so basically I was doing a little bit of research on variable sensors. And from there to the actual data you can collect from the bodies. I came kind of into the data protocols. So my research came to data protocols and at the same time, I was concerned and frustrated with a big tech that theu’re actually creating.

More problems for the people to maximize their data-driven, profit rather than solving problems. And also the economy gap they created, it was getting wider. And basically I tell it makes a lot of sense if we can give the power back to the people with data monetization, and also it’s time for the people to earn what’s rightfully theirs.

So after it got to this conclusion, I was crying, fired up. I, I tell them I’m going to talk to my sister because she was a data scientist, a professor. So I see what is the pain points that is a data scientist. she struggles with, and also students. She explained me that the independent data scientists really struggled to find affordable and also, access.

private data since all this data is in the hand of the data police. So I started all over again with this back of my mind, I did a lot of research into data protocols since they were in the realm of software. For me, it was more new because my background was hardware by, I was really sure of the direction that we are going with data and.

[00:05:00] Amir: So I started studying all type of modules to learn to program a little bit, to use it from a smart contracts to encryption protocol, you name it, anything that was needed. So. Yeah. That’s how data latte was born.

[00:05:17] Scott: Very interesting. So you went from trying to feed humans and dogs and ended up with a, a cafe that had a lot of technology and, and, and not so much food, and then slowly but surely, it led you to, to ocean protocol, and, and personal data.

[00:05:37] Amir: Yeah. And on top of that, it’s still, if you think about and say, you know, this time around the data baristas, their robots are making the caffeine data.

[00:05:47] Scott: Amazing. I love it. cool. So, I mean, you, you sort of touched on the, the problem that data later lattes is sort of looking to, to address there and specifically around, you know, these, these larger tech platforms, and maybe some sort of unintended consequences as a, as a, as a result of their data.

Business models and so on and so forth that we sort of hear a lot about. so, you know, would you mind maybe just doing a bit of a,a deep dive into, or shallow dive or however deep you want to go, uh, into the problem that, data later data latte that excuse my accent is looking to address here.

[00:06:31] Amir: Yeah, sure. So basically since we are a two-sided platform, Both for the people, internet users. And on the other side for data scientists, we focus on two main problems. And that the first issue is for the people is that they do not receive any benefit from their data while big tick earns all the money from it.

And also they don’t have any true ownership or control. Or they don’t have any, even have the control to say who have access to their data. What is their data being used for? And they’re not even aware of how creative these companies are in collecting their data and linking it together. There is minimal transparency on that regard with this complicated terms and agreements to force people, to just accept things like accepting a cookie.

When we go to a website. So basically the first major step, in my opinion, that was took, it was in 2018. When the EU passed the GDPR, laws that forced them to a low access, to allow access to people, to have their data and also request to delete that data. So these regulations are the rightest. But they didn’t solve the problem completely.

And here we at data latte, we try to put this law into full force for the people. And the second problem that we are addressing is for the data scientist. If you’re a data scientist who likes to work independently, you don’t have access to good quality data. You can Google a little bit, go on Cagle and find some limited databases.

But if. I want to have access to big tech data. You’ve got to work for the big tech, and if you work for them, you need to do your data science, project, or you need to do your work so that it maximize the profit of the company. You don’t get to choose and you don’t get to be creative, other possibilities.

What you can do with that data, you only get two. What they want you to do, and that’s not necessarily in favor of the people or the users of that platform. And then in a lot of cases actually is manipulating people’s behavior and exploiting their digital light. So this way we’re gonna deliver such a high quality data to data scientists, to develop applications with their creativity that ultimately.

Hops these people and try to solve actually wards problem. Yes.

[00:09:33] Scott: And it’s, it’s, it’s interesting. I mean, these a couple of points, sorry for just jumping in. I just want to kind of wrap up a couple of, of the sort of points that you touched on. I mean, one of them is this, you know, the, the idea of the data exhaust, or basically, you know, the stream of, of information, which is falling out the back of your either everyday interactions or, you know, your Netflix viewing history.

Google maps and all the rest of it, everything is basically just spewing out tons and tons of data. and the GDPR, sort of regulation came about and said, actually you own that. So you, as the person that is basically, you know, creating that, that data exhausts you. a fundamental riot or some form of legally recognized ownership over that, that data stream or those data streams.

And then you kind of, so that that’s sort of the, the kind of product, I suppose, you know, the source of the data and then the, the kind of the, the, the product, which is just, you know, all of this data coming together in some way, shape or form, and people figuring out, you know, ways to either use it or, or leverage it for.

And going to what you’re saying is that by, pulling all of that data together in a, you know, somewhere where data scientists can come along and, and use the product that, you know, let’s be honest. Most people don’t do. Aren’t even aware that they’re there creating really, and, and begin to sort of build things on top of that.

Is that, would, would you say that sort of a fear kind of summary of, of, of the sort of situation?

[00:11:16] Amir: Yeah, yeah, exactly. And another problem that I see with the current data market that is really advertising driven and know is everything is about selling something. So if you, if you want to sell something and you, you find you you’re selling a product to solve a problem, but what if the problem is not really actually a real word problems?

You know, the advertising industry is just trying to manipulate people to buy things that are not necessarily solving problems.

[00:11:50] Scott: Yeah, very interesting. and, and if, if that data is being pulled and. You know, predicted server inside of a, Fang companies in your good luck getting access to that. yeah.

Very, very interesting. So, you know, this. a space, which seems to be getting more and more attention as time goes by. Even if you’re just to look at the last couple of years, you know, with, with things coming out, you know, whistleblowers, from Facebook and the like, you know, is there other ways that, that people have looked at or are looking to address this problem that, that you’ve come across?

yeah, there are a lot of, foundations and standardization groups among the industry, the government academies, et cetera, that they, they see the problem and they claim to be solving this problem by introducing and creating a framework. And so basically. What I see the problem is that if, if you want to put this frameworks into action, it’s not easy.

when they try to bring big tech to do something that limits their growth strategies and hinders their profit. So big tech, having all the money and power don’t really adopt it on the other hand. what now came to being with web three is enabling an open immutable and democratic framework that really enables this time around to try to get the power back from these tech monopolies and a lot of other projects as well, or, claiming to give data back to the people and.

[00:13:46] Amir: In general, the more, the better if users get to upload their data, 200 platforms and Arab from it.

[00:13:58] Scott: Yeah. Yeah. I mean, that’s, it’s, it’s a good point, right? I feel the consumer or the creator of this data and you have the ability to monetize through many different ways and it’s not necessarily a bad thing. And arguably, if you have more choice than you can kind of choose which ones you send your data towards and which ones, maybe you don’t.

so you, you, I think you touched on sort of this concept. Of WIP three, maybe changing the dynamic a bit. you know, w w what is it about, that a latte that, that you see, as being a addressed, you know, why does that a lot, I address this problem, and what makes it better than the others, do you think?

[00:14:37] Amir: Yeah, so basically, I, I see our platform is going after. Three three problems. And so basically two problems for the people and one problem for data scientists to solve. And the main problem for the user would be the data ownership and also the possibility of benefiting from it. So for that, we are providing a full ownership of the data and then people enabling to anonymously errand.

When that data is sold in our data marketplace. So that’s the first thing in the most basic thing that any data platform should offer to the people that finally with this technology, people can be the real owner of the data and not anymore through a third party. The second problem that I see is the economy imbalance and how big tech is widening the.

So to go about that in data latte, what we introduced are these data barista NFTs that makes our users, the owners of data Latin. So this NFTs are not just like a piece of artwork that are unique. They’re also the digital identity of the user in our plan. And what we do is that we provide, a set of data quests that the data baristas or the users can accomplish.

And by doing so they increase the value of their data. For example, we asked, for the first data upload to be the Netflix viewing history. So we, from that, we can see the tastes of the movies that people. And then we had the data quest and ask people if you would prefer to have a catch-up or minus with your fries.

That’s a very basic question to ask. And one might ask, how can you link them together? But if we know. What tastes of movie a person has, for example, a person likes to watch more action movies, and we realized that they prefer the majority of the action movie fans. They prefer catch-up. So that’s a sort of, insightful,results for data scientists to see these patterns.

And. Give it to the businesses around the movie theaters that if there is a action movie theater screening, then it’s better to put some ketchup options more in the front for the, for the people to catch. So that’s what we created this data quest and kind of the game effication of the process with this data baristas to bring them into a leaderboard and a ranking.

So they can do this data quest and increase their XP. And while they do so, the more expedient earn, the more intelligent their data barista gets and by doing so they will have higher watering power. Th some of the most,some of the most influential, decision-making who bring it to the doubt to decide and as well, they also receive a bigger share of the pie.

And the pie is actually the market feeds that were collecting it and sharing it with the data baristas and, coming to the problem for the data science. lacking good quality data is that we give them access to a high quality data that it wasn’t accessible before, for an affordable price in the data marketplace.

And this time around they’re free with their creativity to create actual products that solves real world problems and not necessarily stick to the agenda of a company that hires them to do it.

[00:18:39] Scott: Cool. So, I mean, there’s. Interesting, you know, kind of layers to how you’re building on top of this, you know, with three and the NFT stack.

I mean, one of them is that you’re using that in NFT as the kind of identifier of a data source. In this case, you know, someone who’s giving their Netflix history and whether or not they like a tomato sauce or Mayo. but obviously, you know, that. That data source could be many, many different things.

And, if that’s all sort of linked back to that, that, that NFT then, then you have that, that individual identifier, growing in value over time is obviously that is, is linked to, to the, the input source. Um, and then I think the other, the other I speak is, the, the governance aspects. So there’s also a, you know, early adopter community type, kind of angle to the inequity and that, that NFT ownership. so that’s yeah, it’s, it’s definitely, it’s a very, You know, unique way of pulling these things together.

What’s you know, what’s the response been like so far from, the users, that you’ve, you’ve interacted with, with data latte.

[00:19:50] Amir: Yeah. We have like around, more than 450 users, I think on our. And it has been pretty gradual, how we are growing. It’s been six months and our growth is very modest and I’m happy that is growing slowly so that we have a chance to actually connect with the community, to talk with them.

And they have been really supportive and appreciate Steve of what you’re doing. And they show that they have the belief in the future of this project and they just. asking us to release more and more. And now, now being in the other side, I realized when I was in other three communities in the discord and like users keep demanding like, yo release this, this product, we need to get this going.

Eh, I realized like how it is to be on the other side that you realize that. How, how much time and effort is to making things and what kind of problems can come on the way, you know, especially in web tree, everything is developing on the edge. You know, everything is getting updated and so on. So a lot of things can pop up, but the, the community for sure has made it fun as well.

And we, we see a lot of endless possibilities that we can engage with this community together, along the way. And making this ride really enjoyable for both of us.

[00:21:17] Scott: Awesome. And you managed to collect, I can’t remember the number, but I remember you collected quite a few, Netflix, view, view of histories as well.

[00:21:27] Amir: yeah, so w we had like the first batch of NFTs, the hundred and one data baristas, that was done like around the two or three months. I guess it in January and then we released the thousand and 10. And from that so far, I think 220 are minted. So in general we have like 300, 320 Netflix data at the moment.

[00:21:54] Scott: Cool. So the second, second drop, so to speak is, is essentially live at the moment and it will at the time of recording this and. If a user goes and drops their Netflix viewing history, they, they get to meet one of these NFTs is that correct?

[00:22:14] Amir: Yeah, it’s just basically three clicks. Like the user needs to download their Netflix data, logging to our dashboard and upload the data, which is basically three clicks.

We minty NFD on. Uh,to the wallet directly, eh, and we, we pay the gas. So the user basically doesn’t need to do anything after uploading the data. And we have sorted out all the pipelines that automatically cleans the data and pull it into the, into the pool. And we also published some nice insights about this Netflix data we published in the blog post with Rockwell index as well.

We, we saw some patterns. Let’s see. on Sundays, people are watching more Netflix. It makes sense. Also throughout the year, October actually is the highest usage of Netflix among our users. I would have maybe think more colder. And then season more colder moms, but actually October was the case. And we also saw like the, during the pandemic people started watching more drama than comedy before actually comedy was dominance, but this whole pandemic has been so dramatic that made people to watch more drama after heart, which we could see it in the day.

[00:23:37] Scott: Yeah, that’s really interesting drama outside and inside.

Co-ran so what’s, what’s maybe one of the biggest problems that you’re facing right now, in terms of, of, of pushing that a forward. I’m sure there’s, there’s many different things and, and you know, everything you’re pushing everything forward all in the same time, but is there anything that sort of stands out at the moment as being your, your number one hurdle?

If you could wave a magic wand and fix it, what

[00:24:06] Amir: would it be? Yeah, basically all it comes down to trust. Eh, in convincing people to give us their data. And basically it’s because people have grown increasingly aware of how big tech is using their data and what they’re doing with it. And people are feeling why later than disgusted, they lost the trust.

And when we’re asking for the data or provide some monetary benefit for it, people are skeptical. I think they have a hard time trusting us, unfortunately. And that’s the main problem now also blockchain crypto. And if these people are also a little bit skeptical about this, these new merging technologies and we believe like a little bit more adoption and education.

Okay. Bring people around. And we also do our part on educating people about this, this technology called T. Very cool.

if you were to fast forward and maybe, you know, go go a couple of years into the future, people have become more comfortable and familiar with, you know, with three technologies and it’s not that long ago.

[00:25:27] Scott: People were super skeptical of Bitcoin and I’m sure many people are still alive, but I mean, the ground has completely shifted on that. And, as a result of sort of 2020 in this last bull run, so it’s not too much of a stretch of the imagination, to think. You know, people will start to, become more familiar and comfortable with these tools.

it just a matter of adjusting your time horizons, I suppose. if the last day was, it was a huge success, you know, what would be different? How could you imagine this coming to life? It w if it were to kind of achieve all of your, you know, your, your wildest sort of dreams and hopes for, for the.

[00:26:11] Amir: Yeah. Awesome. It’s nice to think of the dreams. I hate to sound like I’m self-righteous, but I really believe that data can help, level out the economy imbalance and, provide opportunities for those that are from emerging economies. At the moment, the wars leading data centers and cloud infrastructure, I run by the superpowers, meaning most of the internet users data come from this countries and neglecting the insights from the global south.

Not only that, but also the services are an affordable and an accessible to those from emerging economies. And from what we already know, a I N business analytics Wolf require as much as data as possibly can get. So the global self doesn’t have equal access to data like the west and other capitalist nation.

They have kept their being kept as a slower pace. Econometrically. Compared to the global north. So I believe providing, affordable, reliable, and previously inaccessible user data to developers and data scientists around the world can remedy that. And we hope one day to be the Kickstarter for, and economy.

And, hopeful contributing to raise the standard of living and overall the quality of life.

[00:28:02] Scott: That’s awesome. So, I mean, in a way, really it’s democratizing data ownership. and I think if you were to kind of plot data ownership on a, on a map at the moment, I’m sure someone’s done it. it would be fairly top heavy with, just a handful of people kind of pulling all the strings in their regard.

So yeah, it’s definitely a very. Very interesting space to be, to be exploring. so you mentioned that, people can go and sort of mint their own, NFT at the moment. If, if I were to go and upload my, in my Netflix,viewing history and presumably there’s no, personably, identifiable information and, and, and that, and that.

yeah, basically your Netflix viewing history is just, the title of the movie or a serious rewashed. And next to it, the date that your wash that. So. I mean, like, basically if you even publish it online, like nobody can really identify unless you’re like, eh, worry big fan of, I don’t know, like a movie like diehard or didn’t know that you watched it like 15 times in a, in a weekend.

[00:29:12] Amir: And people like you boost about in your social media, that you are a fan. So that’s important way of identifying it, but they’re are not going to sell also this data in a, in a raw. Yeah, we’ll do it anonymously in a poll. And also when it would be the raw data, then we incorporate the, use of technology of computer data.

Meaning we don’t give the access to the raw data. We give access to the algorithm to have access to the data, train its model with it. And, like without actually getting any identifiable information.

[00:29:49] Scott: Yeah, cool. And if I was to do it, so is the governance NFT thing finished now? Is it, or is it still open or is there, you know, what, what is sort of the, if I was upload my, Netflix viewing data now, what, what would I get.

yeah, so you get the NFD, your data will go to the pool. So when we sell that pool to data scientists, you earn an income from it. And in the dashboard, there are two tabs of data quest and Dell. So in the data quest, you get to, for example, if every month you update your data, you will get, you will earn ESPYs if you, For example, answer to this question of ketchup or myo, or some certain data quest that ma makes your data more valuable.

[00:30:38] Amir: You earn ESPYs. And then in the Dell, we asked our users, would you like to earn our native token four days XPS and what kind of a name they suggest for it? So that was like two questions initially asking our dad. And we always kept bringing new things to the data quest and the doubt we are at the moment designing this, this quest and also we are working on, and new product that will come to the dashboard as well.

That, we’ll make this whole process of collecting data requests from the users, way more entertaining for the user. I wouldn’t spill too much beans about this product, but basically you play to earn. So what, like aside from selling data in the marketplace and earning for the people, we’re also creating our own, eh, native, eh, community.

What is token that they get rewarded to actually make their data more valuable and also participate in a Dell. Cool.

[00:31:45] Scott: Very cool. So, aside from, from, you know, contributing towards, the, the first data pool and, and receiving an NFT, if people listening want to get more involved with data latte, what’s the best way for them to do that.

And we can, yeah.

I mean, it’s to get to how our dashboard works and so on. if there is any question they can just pop up in our discord, if there is any problem, we have, we have a big team. We are around 15 people, including federal my talk and we’ll be online to answer any quick. And basically for anybody who liked to help in this movement, just spreading the word, creating more awareness, pre bringing people together for this.

[00:32:32] Amir: Cause of having a fair data economy that everybody get to profit from it. And not just the big man on.

[00:32:41] Scott: Well, awesome. Hey, thank you so much for your time. And, yeah, really looking forward to seeing how things progress, with, with dead latte. And, I am not a Netflix user myself, but, my wife has, so I might have to, give myself in the NFC.

[00:32:58] Amir: Yeah. Yeah. It’s for sure, dude, in also next month, you’re releasing the next pipeline for. So users also get to upload their Twitter data and get the NFTs. Very

[00:33:11] Scott: cool. I’m sure that one will be a great test case for the world of crypto Twitter. so very much looking forward to, to seeing that.

Hey, was it, is there anything else you wanted to add before we.

not really. I just want to tank you and voices like you, that debate is ideas and bringing more awareness to the people and, yeah. Thanks a lot of Scott. What was the

[00:33:38] Scott: man? Thank you so much. And thank you to you and Pedro and, and the rest of the team.

[00:33:44] Amir: Yeah. Thanks a lot, dude.