BNB -3.68%
BTC -3.19%
DOGE -2.78%
ETH -3.62%
PEPE -10.08%
XRP -2.11%
SHIB -5.99%
SOL -5.99%
Best Crypto Poker

How Blockchain Can Help Bring AI Into Mainstream – Podcast

Eimantas Žemaitis
Last updated: | 31 min read

Artificial intelligence (AI) is the next frontier in Big Business. As organizations everywhere look to cut costs, increase their earnings and optimize workflows, AI has imposed itself as the obvious solution.

cryptonews podcast human protocol

But building AI-powered software – and putting it out there – is a lot more challenging than it sounds.

In episode 47 of our podcast, we hosted Harjyot Singh, technology and crypto director at Human Protocol Foundation. A seasoned product and engineering leader, and a successful, London-based tech entrepreneur, Harjyot discusses the problems with today’s AI.

On the podcast, you’ll hear why the lack of granular data in AI is a problem, how automation can help with data labeling, and how blockchain can help bring AI into the mainstream, among other things. You will learn:

  • What is HUMAN Protocol?
  • Interoperability
  • Machine learning bias
  • ReCaptcha vs. hCaptcha
  • Balanced & granular data
  • Micropayments
  • The future of HUMAN protocol

We talked about this, and plenty of other things, on our podcast which you can find on this link, or you can listen below, and let us know what you think in the comments!

Episode transcript:

Matt Zahab: 0:08

Folks, if you’re a fan of AI, blockchain and web three, this episode is right up your alley way. Our guest today is a London based tech entrepreneur. He’s a seasoned product and engineering leader, and has worked in a variety of companies and industries over the past decade with a focus on finance and distributed computing. He has also founded two successful ventures which built infrastructure to tackle issues like misinformation and privacy. His current focus has been to explore how cutting edge technologies like AI and blockchain can improve the quality of the day to day experience that the majority of consumers have on the internet. In his free time, he loves to contribute to open source projects go grassroots traveling, build custom motorcycles, and record music. On a side note, check out his Insta, it’s pretty freakin cool and right on point. Present day, this gentleman is the technology and crypto director at human protocol foundation who has some incredible news that’s hot off the press. I’m very pleased to welcome to the crypto news podcast. Harriet Singh. Harry welcome to the show.

Harjyot Singh: 1:13
Thank you, Matt, for the very kind intro. How are you doing today?

Matt Zahab: 1:16
I am doing lovely, very happy to have you on board. You and the human protocol foundation launched some incredible news today. We’ll get to that in a second. However, I know you’re a London based entrepreneur. I’ve been to London once two weeks there fell in love with the place world class city, London for a reason. How’s London right now? Is it is it got its legs back after COVID?

Harjyot Singh: 1:39
You know what? Yeah, it’s getting there. It’s getting there. I mean, we live in such a metropolitan city, which is full of life, maybe whatever time of the day it is, it’s quite difficult to digest what after effects of COVID left. But the city is strong, it’s multicultural. People have that hustle. And yeah, I can see some semblance of the past shining through.

Matt Zahab: 2:04
I love that it’s one of those cities, when you’re just walking around, you can feel the energy, whether you’re close the bank station with all the suits are short, it sure you know, having a party wherever the case may be just the energy, it’s all over the place. I absolutely love that. Before we get into human protocol, I’d love if you could tell our guests a little bit about yourself and your past

Harjyot Singh: 2:23
Sure. I mean, it’s a pretty standard story, you know, run up the middle I originally held from India. After high school. Luckily, I decided to move to Edinburgh in Scotland, to the University of Edinburgh to study artificial intelligence and computer science. You know, since being a child I was always been very inquisitive about computer systems, so on and so forth. But it just was a next step. And you know, as a person from a developing nation moving to a first world nation, a developed nation like UK, my focus was always that you know what, I’m going to do this degree, I’m going to learn all I can that I’m probably going to work for a major corporation or an MNC, you know, as a software engineer, probably white collar job with my head down and do my job. But as fate has it, I just saw that I was more attracted to startups and you know, cutting edge technologies like AI and blockchain. And you know, what, from first year, I started working in very exciting startups, you know, exploring different dimensions of these technologies that I just mentioned. By the time I graduated, I was a technical lead. And I had this feeling that maybe, you know, I can do something with what I’ve learned as well maybe make a dent on the world. And, yeah, I launched my first startup for Providence labs, which, in a nutshell, is a misinformation detection platform, which just doesn’t look at, you know, which news is fake being used out of context, but also tries to go a step further and figure out what the bias behind it is. So that we, you know, involve using very cutting edge, semantic labeling, image detection in the terms of AI, textual analysis in terms of ML models, little bit of blockchain work here and there as well to provide provenance for a particular piece of content. Then after a few years, once I started started doing well, you know, it was kind of running on its own. I kind of clashed parts with the human protocol. And here I am,

Matt Zahab: 4:32
And then you went head over heels and here you are.

Harjyot Singh: 4:35
Oh, yeah, love at first sight.

Matt Zahab: 4:38
Looking at your background and again, whenever I have a guest coming on, I do the big lurk, I do the Twitter, the Insta, the medium, all socials, I listened to all their interviews and I’ve heard you speak before and you know, you got a hard on for human protocol as you should. That’s that’s the way it goes. Right. And I gotta ask why did you choose human protocol? I’ve heard this answer before on different pods. And I love this answer. So you got to give it to me. Why did you join them when you had such a bright future at your previous startup?

Harjyot Singh: 5:08
I think you know what, in terms of the industries, when we look at either AI or blockchain, we’re just at such an interesting junction. where, you know, the old school technologies are kind of transitioning out, but the infrastructural setups, the application setups, you know, all the tooling that made the previous generation of software possible just doesn’t exist. And being a part of a project, like human protocol allows you to really be pioneers in building the future, in a way, it allows you to marry the two technologies and build everything from the ground level, you know, the infrastructure level, to the protocol level, to the application level, and really contribute to the bigger technology ecosystem. And I think that’s what attracted me to human protocol a lot. And I mean, we can look at it in two different ways as well, right? Like being particularly about blockchain. I don’t know how much, you know, this is my way of categorizing it in my head, at least. Back when Bitcoin was launched, it was, you know, revolution, private money became a thing for decentralization, no more middlemen, and it turns people heads, then you started saying, okay, we can take the concept of private money and really generalize it. And hence came, the what I would like to call the wave 1.5, pre 2.0, with Ethereum kicking in, which is about, you know, allowing business logic to be run on chain in a decentralized manner. Right. Yeah. And that was cool. You know, it was cool. But then as slowly that industry progressed as well we saw you know, Ethereum really have its setbacks, be and bandwidth related throughput related. And then came a new generation, which is according to me the wave 2.0 with the multiple L1s and L2s coming to optimize build on top of the principles that Ethereum and Bitcoin already launched, you know, hyper optimize it. And that went great, some projects, stayed some projects will then we saw some really awesome technologies being built in that way. And I think that led leads us to wave 3.0, as I would like to call it. Now we have so many L1s, L2s, so many protocols running on different chains and stuff. And here comes the age as you might see you in the industry as well about interoperability. So a lot of protocols and applications coming out, try to be multi chain, you know, at human, our fundamental focus right from the beginning, was to be this multi chain protocol, to kind of again, as I was I might reuse the word pioneer a lot. But pioneer that third wave of blockchain pioneer that interoperability and build infrastructure that can help the big research ecosystem. Let’s take it a flip side as well. And I’m sorry, if the answer is going too long.

Matt Zahab: 8:07
No, great, keep going.

Harjyot Singh: 8:10
Let’s look at artificial intelligence as well, right. Like what I said earlier, that it’s a young industry, even though a lot of research has been done up to now. challenge we encounter almost constantly building more tailored ML solutions, you know, that really respond to people devices, etc, etc, is a lack of good granular specialized data. You know, your ML models, your recommendation engines, your personalization engines are only as good as the data you’re feeding it. And at the moment, there is really no good way for individuals, startups, researchers, even big companies, to get that highly specialized data. With human protocol, like, you know, with our initial focus on the ML market space, this is what we’re trying to fix. We have highly specialized workers, and very big experience in this domain, right. And what we can really do is democratize this data, we can make sure that these individuals, these companies, the startups, etc, who want the data the way they wanted, they don’t have to go out and search and do it manually. They can come onto the human protocol, leverage our existing expertise, get connected to skilled data labelers and actually get the data they want to build new generation of really highly specialized AI products. So you know, blockchain AI sync that was me head over heels.

Matt Zahab: 9:47
And the rest is history. Now you hear a lot of companies talking about their ceiling and being like, oh my ceiling is x high or my ceilings why Hi. This is a very high ceiling. You are tackling massive, massive industry. Which are undoubtedly part of the future like AI. Now, when I was doing research for this, and you said it a couple times in your opening spiel there, the word interoperability came up. That seems like it’s the hottest word out there. Right now every crypto startup in the world is using it, could you just give our listeners a quick sort of 30 second you know, elevator explanation on why that word is so important and how it intertwines with web 3.0?

Harjyot Singh: 10:28
As I was saying, the web 2.0 came and you know, different L1s , and l L2s sprung up, it turns out, each of them have their own individual strengths and weaknesses, you know, pros and cons. Now, as a business owner, as a person who wants to create particular business solutions, it might turn out that, you know, one chain here, one infrastructural change might have some pros that’s fit a small part of your business requirements, while the other might benefit the other, you know, and at the moment, there is no existing way. As a, you know, business developer or business creator, whatever application developer to really leverage the benefits of multiple chains simultaneously. It starts very fundamentally, right, there’s no communication, no token transfer between various students. And that’s what interoperability really means. It means you leverage the strength of multiple chains simultaneously, to solve real world use cases.

Matt Zahab: 11:30
sounds like you took that from Webster’s dictionary there. That’s straight money right to the bank. That’s exactly what I wanted to hear. Back over the human protocol here. Now, I’d love if you could also, again, I know I’m asking this question all the time. But I’m a huge fan of the 30 second elevator pitches, because it just gives the listeners and myself such an easy way. Because if I just tee you up, and go ahead, explain human protocol, you could go on for three hours. It’s that complex. And there’s that much to it. But if I’m asking for just a quick synopsis of how sort of the three main stakeholders are involved being, you know, the people who set tasks the people who get paid, and the people who develop Can you just sort of tie that in 360 to how and what human protocol is?

Harjyot Singh: 12:16
That’s a good question. So see, in a nutshell, the way I would describe human protocol is that we are essentially building infrastructure that allows anyone to create decentralized marketplaces, where humans and machines essentially collaborate together to solve any possible task. So now, that’s a very low attendance, you know, and what does it mean? You know, with the age of Uber, and, you know, the whole gig economy post, people really started understanding that they can work pretty much from anywhere however they want, as long as they have an internet connection, a car, or a scooter, whatever. And that gave birth to a whole new generation of gig economy products, you know, and gig economy products are nothing but just a two sided marketplace. Now, you already have platforms like Fiverr and Mechanical Turk, where these two sided marketplaces exist. But you know what, to build a product like that. It’s very complicated. Like, you know, it does require domain expertise. But it also requires overcoming a lot of very complicated technological challenges. And this infrastructure that we’re building at human protocol, will basically make it easy for new companies springing up in the gig economy space, to build that back end to build that technological infrastructure to facilitate this. So you know, everything from creation of a particular job, to managing and matching it to workers to verifying the job quality results, and to even, you know, micro payments and paying out the people who have worked and getting the relevant results of the job back to the job creators, we provide that end to end flow in a seamless manner. So actually, business creators can focus on the nitty gritties of the domain where this two sided marketplace operates. They can focus most of their efforts on marketing on PR, on really honing that user experience. And human protocol basically provides everything underneath.

Matt Zahab: 14:25
Right, that makes total sense there. Now, another word that I’ve heard you say many times is granulated data. Now human was born of the desire to bring more balanced and granular data to AI. That’s a very again, I feel bad I’m giving you huge questions here. Very, very, you know, this is a high pay grade question. If you asked me this, I just they style and I want you not to start, but can you explain that problem? And I’ll repeat that human was born out of the desire to bring more balanced data to AI and can you start to explain that problem and how Human protocol solves that

Harjyot Singh: 15:01
I think I’ve touched upon this in a previous question in my previous answer, but let’s look at it right. It really jump into, like ML’s products, for people who don’t really know how ML operates. ML algorithms are nothing but blackbox algorithms, you know. You tell them, this is the data that needs to go in. And this is kind of the result we were expecting on the other end. Okay, right. And the machine here basically self regulates, teaches itself on what kind of results it’s looking for. So a very simple primitive ml model would be something like, you know, is this picture of a dog or a cat? And we provide the machine certain examples of labeled data where, yes, dog, yes, cat, yes, dog, and cat, so on and so forth. And it teaches itself and develops that algorithm itself. But now, that’s a very simple problem. And for a machine to do even a simple binary classification, like this requires 1000s and 1000s of labelled images. Or exactly imagine when the use case gets more complicated. You know, be it in terms of food recommendation in terms of the Tesla you’re driving, in terms of mapping out the weather. These require very complex labelled data and complex in the sense that they need to be particularly labeled in a way so that the machine will understand and get the right information out of it. Right. And also, it also has to be balanced in the sense that, you know that there’s no bias in it. So now the bias question comes more when you’re building out technologies, like facial recognition, you know, when you’re building out technologies, like biometric identification, so on and so forth.

Matt Zahab: 16:55
Wouldn’t the bias come from the data scientist who’s implementing these like ML algos?

Harjyot Singh: 17:01
No, no, actually, it doesn’t. It comes from the data.

Matt Zahab: 17:03

Harjyot Singh: 17:04
Yeah, the ML algorithm is a blackbox algorithm almost right? The kind of data you’re feeding, it is going to be what the result is going to come out. So for example, and I don’t want to touch into this territory, because it’s quite tricky, but it just illustrates the purpose. You know, you have people from x, y, z races and the pictures being fed for a facial recognition algorithm, just because of the nature of technology and the exposure to technology, most of the datasets that you have of human faces are going to be from a particular dominant race. So might turn out an ml model built on that the third or the second, racially distinctive. Humans might not get recognized or picked up by a facial recognition algorithm, just because of the data set. I hope you understand what I’m trying to say. Yeah,

Matt Zahab: 17:55
I do. I get it. We get it.

Harjyot Singh: 18:00
So yeah. So that’s where the bias is. And I think just to finish off and wrap up that point, the third one was verification. So whatever data you’re getting, how do we assure its quality? That it’s actually labeled in the manner and there’s no automated systems for that at all? Right? So the need for data is there, data is missing. And that’s where human protocol kicks in. We have tools that allow really, you know, specialized labeling of data. For example, Intel we are partnered with intuition machines H capture whoever partnered with uniform image labeling tool called Inception for textual labeling. And these allow, you know, these companies to build out really specific needs and demands of what kind of data they are looking for, connect that with our partnerships with existing tools, and the already existing millions and millions of skilled data labels. And suddenly, we see that okay, we might actually start making a dent in this data problem.

Matt Zahab: 19:05
Wow. That’s quite the story, Harry, I’d love to talk about CAPTCHA for a second. I myself have used CAPTCHA probably 10s of 1000s of times. I’m sure most of our listeners, every single one who’s listening to this show, right now you’ve all used capture as well, you know, when you log on to your bank, or any one of those websites, and you have 91 2, I don’t know, 20 boxes, and it says, pick the docks and you got to choose every box that has a dog or one of the most classic ones is the crosswalk. Now, you always have to do that. Google used to have that they used all the data in an unfortunate way, Harry, I’m sure you know this a hell of a lot better than I do. And you can talk about hCAPTCHA as well. So with that being said, the floor is yours.

Harjyot Singh: 19:45
So I think the reCAPTCHA I think, is a product by Google. I’m not too familiar with the story, like as in the nitty gritties of the story, but the general gist was, there was a company that built this bot stopping You know, CAPTCHA product. Google really saw the mass appeal in it and bought them out. Some people might be wondering, okay, so CAPTCHA’s help in preventing bots. So what was Google’s interest in it? Apart from the bot stopping? Actually, it turns out captures are an excellent tool for labeling data. So when you get nine images when you’re logging into something, and you see, which are the boats, why do you think they’re asking what the boats are, there for? It goes into creating better data for them. So that leads us to hCAPTCA. So hCAPTCHA was pretty much the first partner application that we had, that utilize the human protocol in its backend. Phenomenal product, power, something insane, like, you know, 15% of the internet traffic. And their philosophy was a little bit different in the sense that they wanted CAPTCHA solvers and the websites powering these captures to actually get rewarded for the work that people are putting on there to help train the data to improve the data quality. And that kind of, you know, lead to the generalization of human protocol. And, yeah, here we are. And they still tend to be you know, one of our biggest partners

Matt Zahab: 21:32
That’s great for humanity as well. Funny how that all ties in with the with a company or foundation rather called the human app. Now, speaking of the human app, I know you and the team are launching that very soon, very curious to know what exactly is the purpose? And why is it so important to the foundation?

Harjyot Singh: 21:48
So you know, as I was talking about, you know, the building that two sided marketplace and that initial marketplace that we will be falling into, which is the machine learning and the data labeling marketplace. Human app kind of born naturally out of it. You can almost imagine it as a one stop place for earners to you know, solve various data labeling challenges, and, earn some money for doing that. And I wish I could dive a little bit more into it. But as of this moment, while this being recorded, I cannot but you know what, just watch out on our social channels and you will learn more very quickly.

Matt Zahab: 22:31
And you will learn more very quickly. You heard the man, keep your eyes posted and your ears posted as well for more that speaking of incredible apps, if you are a sports Gambler, or a poker fan, you gotta go check out coin poker. Absolute treat of an app, they were developed coin poker rather was developed by an incredible team of poker players and sports gamblers. Using a revolutionary blockchain technology based platform. Coin poker uses tether as the main in game currency and $CHP as in game fuel. $CHP is coin pokers very on token that is almost acted as a stable coin great by an A great coin overall, with tons of utility. coin poker also features instant and secure transactions using usdt Ethereum Bitcoin and $CHP tokens. And the best part if you want to fly under the radar, there is no KYC involved so takes about two to three minutes you’re up and running dancin and romancing and you can take advantage of everything within coin poker. That is huge promotions as they give away 1000s in fiat value every single week. And one of my favorite parts like I said is the mobile app whenever I’m on the go I can whip out my phone play a couple hands the Texas Hold’em or bet on some sports. Again not the best time for sports right now it’s you know mid summer all you really got is baseball waiting for hockey, basketball, football soccer to come back on great sports book as well. Highly recommend check them out. That is coin that is coin Harry, you sports gambler or a poker fan at all.

Harjyot Singh: 24:02
Poker fan, here and there.

Matt Zahab: 24:03
If we’re playing texas, you can pick any two cards in the hole. What are you going with?

Harjyot Singh: 24:10
If I’m playing Texas, two and seven.

Matt Zahab: 24:13
Come on? Two seven offsuit grabs the straight flush? thank you. to rescue one, get

Harjyot Singh: 24:22
Pocket aces never get me anywhere, you know, I’ve noticed that

Matt Zahab: 24:26
I’m the same way as well. Every time I have pocket aces, I’ll usually get beat with two pair or three of a kind or something of a like. But anyways, I feel like you’d be a shark on the poker table. I would not be too excited if I saw you on the other end. But that is a story for another day. Going back into human protocol here. I’m very, very curious to understand how humans proposition is different to legacy ways of buying data. I know the permissionless aspect is huge. And I’d love if you could tell me a little bit more about that. Sure.

Harjyot Singh: 24:57
So the first thing as you said the permissionless aspect is quite massive, you know. Traditional industries, we always tend to tend to rely on a middleman. And you know, when you get more parties involved in any place, everything from the costs of acquiring the data to the biases that the multiple data might have, and the various verification and activities, you just have to trust someone else to do it on your behalf,

Matt Zahab: 25:30
Too much friction, there’s way too much friction when you have everyone involved.

Harjyot Singh: 25:33
Yeah, it’s just all just friction, you know, it’s very hard these days to Trust, especially various institutions, you know, because, yes, let’s be realistic, everyone’s in it to make money in one way or the other. But, you know, the onset of the blockchain industries, and the whole distributed ledger technology, this gave birth to this new movement, which I fucking love. It’s connecting people directly to other people. And I think that has been one core value that we, you know, try to nourish to human protocol. So that, you know, we cut out the middlemen, the data requesters, and the data labels can get connected directly, the micro payments, the verification, the assessments, the, you know, matching is all done by third parties and pools of third parties involved. So we actually, as human have no say in it, that’s awesome, I think, you know. And it also helps us, you know, not be responsible for things like the expenses, it’s just, you know, you plug in your two you can purchase, I think there’s one more thing that’s very cool about this, let’s say the new age, human protocol way of doing things, right, is, let’s look at where a lot of the data labels come from, right? They are from developing nations, where, you know, they have access to good internet, people are supremely educated, but the jobs might just be lacking. Through human protocol, they might be able to get work. But in these developing nations, big point of contention is the banking system, right? To execute payments across borders, it can take these to weeks, even months to get payments for a small piece of work that you’ve done on the internet. And plus, you know, yeah, it’s just a logistical nightmare. At human protocol that’s kind of been our sole focus, when you know, these earners from developing nations should be able to earn the money for the work that they’ve done almost instantaneously. And that’s what we do.

Matt Zahab: 27:51
Can you can you tell me more about the micro payments, this is something that I’m incredibly bullish on. And I definitely think it’s the future. I know, a lot of companies are doing this. Heck, there’s even what were you and I are doing right now sitting chatting on a podcast, there are no companies out there. And there is software where you can get micro payments from listeners who come in and stream SATs, as we’re both speaking, we can donate those to charity, that may have been a little teaser. But super cool things like that, I’d love if you can tell me about the future of micro payments and what exactly a micro payment is.

Harjyot Singh: 28:22
The traditional systems were if you know, you have to send money from party a to party B, you have to kind of batch things up, you know, so that there is enough volume involved, so that the fees involved from transporting money from A to B can be managed can be optimized. Now. I mean, micropayments is a pretty obvious word, we do not have to do that anymore. Because of the New Age L ones be Ethereum, Solana, polka dot scale, etc, etc. It’s very easy to send direct transactions for as little as two $3. I mean, it depends on the gas price, especially when it comes to aetherium. Right? Some, but you know what I mean, on principle, it functions. It functions that a party can just directly transfer funds, tokens, etc. to another party B which can be sitting across the world, you know, you don’t have to rely on traditional payment solutions, like swift or IBM, or all these things where, you know, one bank communicates to B to C to D to E to F to G now, it’s a direct point to point. And that’s why micropayments are so awesome and it allows it all to happen in a trustless manner. Like I do not have to, you know, really trust the other person’s bank who actually sent the money, why hasn’t it arrived, all these frictions just goes away, and that allows people to really, you know, chill the fuck out, do the work and really know that they will be rewarded in it. appropriate manner. And that’s awesome.

Matt Zahab: 30:02
That is, that’s the future of work and the future of work is remote. And the future of remote work is micropayments and taking out the middlemen taking out those intermediaries, and that’s exactly what human protocol is doing.

Harjyot Singh: 30:13
Almost sounds like a manifesto, we are writing here, Matt.

Matt Zahab: 30:17
It is. That’s why I’m bullish on human protocol. But tell me about the long term vision as someone who is going to be an investor, as soon as we get off this pod, again, done my research, whenever I do my research on a guest and their team, and everything checks out, I’d like to put a bit of do re me into a company. Again, it’s always a treat. But with that being said, Tell me about the long term vision of human protocol and what myself and our listeners and consumers can expect moving forward.

Harjyot Singh: 30:50
I think, first of all, the priority is to get this protocol like, you know, the main core protocol, infrastructure wise, out on Main net, and probably a few L ones and L twos as well, just because our optimism, let’s say, in terms of the volumes of jobs, that will be processing, I think one chain is just not going to be enough for us. So you know, and it’s building all those core functionalities, which is almost there you know, and releasing it out to the public, making sure that the interoperability is working fine, all those things. Then just taking the level up from the core protocol, it’s about expanding this machine learning data marketplace that I was talking about earlier. So we already have existing applications like Intel, h CAPTCHA, inception. But for more granular, more specialized other forms of data, the next steps will obviously be adding these new applications that really can be used to label these kind of data’s right. And I think that’s going to be a high priority. Then I think the next is, you know, we want to foray into tertiary applications as well, why not prediction markets, why not leverage the existing technology that we’re building to enter prediction markets, on chain verification for stuff, you know, the sky’s the limit, and hopefully, later down the line, I can’t offer you a date here, but really open up the project more toward to our community. The community starts having a biggest thing in the direction we’re moving in, in terms of governance in terms of the features that they want, in terms of getting the developers involved in terms of opening up a grants program, you know, where various business creators, you know, who really specialize in a particular domain, start leveraging the human protocol to build specialized marketplaces that are just not the machine learning data labeling marketplace.

Matt Zahab: 32:59
And there you have folks, that’s, you got a whole lot of stuff to look forward to there. Now, by the time this episode airs, it will be Thursday, August 12. And the official coin of human protocol, $HMT will be live on a couple exchanges. Can you please tell me what those are here?

Harjyot Singh: 33:19
Yep. So yeah, by the time it goes out live, if it’s not already live yet, the coin will be available for trading and buying at on FTX coinlistpro and And maybe a few other exchanges quite near in the future.

Matt Zahab: 33:37
Lovely. Good to know, Harry, this has been an absolute treat, learned a crazy amount. And truly, thank you so much for coming on here. Really big fan of your team and human protocol. But that being said, any questions for me before I let you go?

Harjyot Singh: 33:54
No, no, but thanks for the compliments. You make me blush. Matt, I need to speak to you more often.

Matt Zahab: 33:59
That my job. Give me a call whenever you want to, shit. But, Harry, absolute pleasure. Thank you so much for coming on. Last question for you. Where can our guests find you and human protocol on socials and on the web?

Harjyot Singh: 34:13
Sure. I think majority of our presence is on Twitter. So for Twitter handle, I think Matt you will share the link wherever you upload this as well. But the human protocols official handle its human underscore protocol, spell it like I pronounce it. To follow me it’s underscore Harjyot. Now that’s going to be a very complicated spelling for you guys. So follow Matt’s link there. Otherwise, we have quite a few telegram communities as well, our official news chat, announcements channel, discussion channel, and some regional communities as well. So yeah, just follow those links and feel free to reach out to us. We would love to hear from what you guys are thinking.

Matt Zahab: 34:54
Folks, whether you want to set tasks, get paid or help develop, definitely check out human protocol is there unlocking the world’s workforce by a new way for humans and machines to securely connect and collaborate. Harry, you’re the man appreciate you jumping on. I know it’s late for you as well. I can’t thank you enough. And I’ll definitely be having you on for round two in the future. Hope you had a blast. I certainly did. And thanks again.

Harjyot Singh: 35:19
Thank you, Matt. Thank you for having me.

Matt Zahab: 35:21
Folks. This was the crypto news podcast with Harry Singh from human protocol foundation. They got a lot of really cool stuff popping off in the near future I will include links to absolutely everything. As always in the summer we are dropping on Mondays and Thursdays when September rolls around. We’ll be back to Monday, Wednesday and Friday mornings. Hope you’re excited for that. I certainly am. love y’all appreciate you all. Hope you’re staying safe, healthy enjoying the last couple weeks of summer before we get into the September to December grind. But keep on doing what you’re doing and we will speak shortly. Bye for now. Love you all.

Contact details

HUMAN Protocol
Twitter: @human_protocol
Telegram: HUMAN Protocol

Harjyot Singh
Twitter: @_harjyot
LinkedIn: Harjyot Singh


Learn more:
Justin Sun Finally Snatches a Beeple, as Sophia the Robot Enters NFT
Bill Gates-backed, Blockchain, AI, and Big Data-powered Virus-fighting App Launched

New Crypto Market AI Prediction System Wants To Automate Crypto Trades
The Answer to Forecasting Bitcoin May Lie in Artificial Intelligence