Hey everyone, thanks for tuning in. This is Tim, the host for today's Crew.5 side chat. We're just waiting on, I believe, two more guests to join. So just hang tight, give us a few minutes.
Cool, looks like we're all here and for those who just joined us again, my name's Tim, head of social operations here at Kucoin. And yeah, so today's our first part of a three part series about AI as well as VR.
And today we have guests from four projects with us here today. So we have Eric Choi from Matrix AI. We have Neil from Clintex. We have Louie from Layer AI as well as Elliott from Varacity. Welcome back.
I believe you did a Twitter space with us a few months ago. So super happy to have you guys on and very excited about this series because obviously Apple will announce its first major project in
in almost a decade I believe, and happy to talk about all things metaverse as well as VR. So, welcome guys. Eric, do you want to start off with a high level intro? Maybe Eric, you can start and then Neil, Louis, and Elliott, you can go less. Go ahead.
Alright, okay. So I say good morning or good afternoon or good evening to everyone and thanks team for holding this to the space and hello to the fellow speakers. Alright, this is Eric. I will try.
I'm physically in Hong Kong. And so it's a good evening to everyone from here. So I'm from Matrix AI Network. And just a very brief introduction about Matrix AI. So we're in Hong Kong for over five
years and have been working on AI and starting from December last year we are into the S-Metrics 3.0 to trying to bring neuroscience with the AI on blockchain. So that's what
or even introduction of myself and brief introduction of Matrix AI. So I have a hand over to the next speaker. Thank you. Thanks, Eric. Very excited to have you on and looking forward to talking more about your project. Next up, I think Neil, do you want to go ahead?
Hi there. Can you hear me okay? All good
Yeah, good, good. Hi, so I'm Neil working with Clintex since 2017 and we have developed a clinical trials intelligence platform that really tries to apply
powerful and insightful analytics to clinical trials, helping clinicians to predict the root causes and the occurrence of major issues with clinical trials. So I'm really excited to be here
to share with you today about what we've done in this space so far and how we're looking at AI to help improve our technology. Awesome. I'm very excited to hear about your Qlintex as well. Let's move on to Lewis. Go ahead.
Hey Tim, how's it going? Can you hear me warm? Oh good.
First of all, good afternoon everyone, my name is Liz and essentially I'm part of the marketing team here at Lay Your AI. I'll give you guys a brief introduction on what we do. So simply put, Lay Your AI helps you collect and monetize your data from your everyday
activities, whether it be in gaming, sports or just in general any other lifestyle apps that we have on body don't want to our protocol. Now the way we do this is by we collect the user's behavior data from the apps that as I said our on body not our protocol as
as well as the same apps, but through a different piece of tech now, which is the headsets. This gives them the chance to incorporate our tech to the record and reward users data. And this is done through the SDK that companies can sign up and incorporate into their code, enabling, of course, this record and reward function.
And essentially, yeah, that's pretty much, well, that's a brief introduction on the layer-eye concept. Yeah. Awesome. And last but not least, Elliot, go ahead.
Hey Tim, thanks for the intro. We have indeed done a couple of AMAs and Twitter spaces with CooCoin. It's always great to be back in the CooCoin community. So I'm Elliot Hill, Simo at Ferracity Tech. We make advertising technology projects.
products for the advertising space. So it's a multi billion dollar industry worldwide. We deploy AI quite simply to help us identify and analyze big data sets, big data techniques and prevent fraud in the advertising ecosystem.
which is essentially what drives the whole web keeps the internet free. I mean, it's a hundred billion dollar problem. So we make solutions and have the only painted solution on the blockchain that uses AI and open loads of technologies to prevent advertising fraud.
Awesome and yeah, welcome back Elliott very happy to have you here again So next up I think I have a few questions for each of your projects and I think this is a you know a great Line up of panelists because you guys all incorporate AI from different angles and incorporate into different you know base
industries from pharma to to avatars to neuroscience. So why don't we just go by the same order and start with Eric from Matrix AI Network. So neuroscience AI and crypto how do you guys tie tie tie tie these three together?
Hey team, okay, thanks again. So this is a big question. And how many minutes can you give me to explain to the floor? Take all the time you need. Go ahead. Okay, thanks team. All right, so, um,
I will go back to 2017 when we set up the Matrix Eric Tech Web. Actually, we were inspired by the film Matrix. I'm sure the majority of the audience here have at least watched one of the episodes of
of the series. Our chief AI scientist, Professor Deng, in that summer, when some awards in the AI competitions and is quite renowned professor in this aspect, so we decided when will you say I to
with blockchain technology and then come up with something. And that's why we started the Matrix Network. And as I said, we were inspired by the movie Matrix. And that's why we have been always thinking about how we can so-called teleport
a human being into loud and then we call it a metaverse. So we have been working on that concept since day one. So right now we have been into we call matrix 3.0 and in matrix 1.0 we try to use AI to improve the
performance of our train, which is our main network. And to give you a solid idea, using the AI and come up with a hybrid consensus mechanism, we have a TPS, the highest record is 50,000.
TPS and we have reached on average, it is about 12,000 transactions per second. So that is what we have achieved in 1.0. But as long as the demand requires, we can scale up quickly.
to 50,000 or even more. So this is our achievement in the 1.0. And then in tip 2.0 we try to build a so-called the central AI economy based on this public chain. And of course, we are trying to upload the human brain into
So the midwest is still the same. So we have the mentor. We call matrix error network training assistant as one or product. And right now we are into 3.0 trying to mix the neural signs with this AI technology and also
on these public chain to do something exciting for the Matevers or Web 3. And this is a market about according to some research, it's about 528 billion. And just recently we have formed
partnership with a new world link equivalent in China. The name is Neurobatics. Both companies were inspired by the same movie and that's why we were together to build something together. This is an exciting project.
And I think some of you may hear about the Apple have said they are footprint in the newer science. And I think they will release more in tomorrow's conference. And just another recent news is
the Newerling has secured the approval from FDA to have the tips in plan to human beings as an experiment. So we see the neuroscience branding with our AI technology is a concept
exciting stuff of course and then we can use it as a DID solutions to train the avatar intelligence, the vision of our 3.0 group plane. We try to use the neuroscience and then also the use the AI to
20 avatars in chess and this avatars is unlike the avatars that we used to play in the game. It is very personalized of yourself, so-called "Tistro-Treen" in metaphors to do things for you to make decisions for you. But it is still a long way to go.
At least we started it and we have both renown to our professor then on the AI site and also neural matrix on the neural science site and we also have the blockchain. So we try to mix all three elements together and
This is certainly a very exciting journey and a very rewarding journey. So let's what we are doing and let's see about neuroscience and AI and those approaching. Awesome. Thank you so much for sharing Eric. I'd like to move. Why don't we just do one question each first and then if we do have time, we can
circle back just to make sure that everyone has enough time to share their insights. So Neil, tell us more about the future of AI specifically in the pharmaceutical industry and how fluid text can contribute to this future with your CTI platform.
Okay, sure, yeah. So I've worked in a pharmaceutical industry for nearly 30 years now, and specifically on clinical trials. And I really do think in a general sense, AI has a real capability to revolutionize the way that we develop our met and
medicine. So I'm quite excited about the next 10 years and how AI can be applied in the pharmaceutical industry. Kind of more specifically and across the pharmaceutical industry. I mean, I've seen AI being used to actually
design new medications, using algorithms to trial through vast amounts of data, looking at the structures of chemical compounds, looking at previous clinical trials, looking at real-world information from patients, and having
to identify things like what biological processes a future drug needs to target in the human body. And that's real key because it allows the drug developer to hone in on specific areas of human biology, whereas before
it was kind of hit and miss. So right now what we're seeing is you know the traditional fail rate for a new drug and clinical trials is about 90% of them fail and we're hoping that AI can change that ratio to much less than
90%. So they're actually using also AI to design molecules around these new disease areas. So there's a number of companies out there in a general sense that we're aware of and that we've been speaking to around clinical draws that
that are looking at new compounds that have been AI developed, if you like. So these are companies like Scrodinger, Silica, and they all have new compounds in clinical trials that come from AI design medicines. So that's quite exciting.
Specifically for clean text and for those who are kind of not aware I mean our Product CTI it stands for clinical trials intelligence and our platform goes just that it kind of consists of seven applications whereby we derive
kind of intelligent analytics from all types of clinical trial data. And these analytics can then be used to drive efficiency in clinical trials. And our analytics kind of expose and can predict the occurrence of key pain points during the clinical trial process.
So, critics are currently trying to build on that platform now and expanded out to really capitalize on where AI is today. And we're working on a very valuable area of AI in clinical draws and that is an AI approach to
data management. So that's almost drug discovery. That's ongoing at an industry level right now, but this is about taking the data from actual clinical trials and applying AI technologies to that. So what can that do? In our opinion,
and it can really do two things. One is our first use cases around self-service analytics. So every day during a clinical trial clinicians need to look at their data. They need to ensure a clinical trial is compliant
to the regulations, they need to ensure that the data is accurate, they need to ensure that any safety signals coming from the data are detected, so is a drug safe. And also they need to ensure that everything's on track, they need to ensure, for example, that we're not missing key pieces of data.
that the patients are still participating in the trial. So CTI provides findable, accessible, interactive data right now to be able to drive that decision making. But what we have found in the early deployments of our platform is that clinicians
like to explore their data beyond these key areas. So an issue that might be detected using our platform might lead to another question that they want to ask the data. And then this needs to come back into our platform and we apply some technical results.
to deliver that data for the clinician. But this is where AI can help us using AI to understand our data, convert any question that a clinician might have of that data into plain English, from plain English into scripts that can interact directly
with our CTI platform and therefore by asking a question in English, our CTI platform can deliver back ad hoc tables ad hoc visualizations and kind of bypass the need for any intermediate programming resource and that's what we mean by
self-service analytics, allowing non-programmers who are clinicians to actually interact with their data and understand it more. Our second main use case then is, you know, around prediction. We're building AI algorithms
to be able to allow the prediction of certain events within a clinical trial. So for example, if a patient takes a drug A or a drug B or a drug C, what is the likelihood of them having an adverse reaction to that drug? What is the likelihood of them withdrawing
drawing from the trial, even going so far as what is the likely hood of them having a positive response to a new drug. So, you know, AI in terms of predictive algorithms can be a very valuable tool to know how your clinical trial is doing at any particular
So there's huge amounts of things, huge amounts of potential not just across the industry, but also with the data management use cases that clinics have to kind of embed AI within the pharmaceutical industry and within clinical trials. So I probably went on a bit too long ago.
No worries, no worries. Yeah, that's extremely exciting. I'd love to circle back and know a little bit more about what's coming next for you guys, but let me let's give the mic to Louis layer AI. So how does layer AI incorporate AR and VR?
Yeah, I know a great question. So first of all, let's start with a bit of context. So something quite known in general is a big tech is built on selling your data without the users really even noticing. So what they do is they
they sell your data to advertisers and you are the product without even knowing it. And here at Nairi, well, we aim to give all users full access, control, and ownership, essentially.
of their data without, with their data which they can then monetize from two. So essentially the way it works is, well one uses on the protocol that uses on our protocol, use apps across lifestyle
or even gaming. And then we collect the data, package it, and anonymize it with ZK technology, which is zero knowledge. And then lastly, we also monetize that data in what we call the global data marketplace. Supplying data
to build the next generation of AI modules across various industries, which could be like manufacturing, biotech, medicine and others, like if they even have its construction. And in short, we call this module the AI2N, which we've spoken about a lot.
and it's the merge between the blockchain and AI. Where blockchain ensures fast security and anonymous data travel and AI artificial intelligence ensures commercial applications and the monetization of this data.
Now of course going back to your question is how does this tie into the AI and VR world? Well as we know 2023 is is pretty much the first time in history where both AI and VR technology mature and meet mass adoption. This means that
millions of users, finally adopting AI and VR through these newly launched products like the Apple VR and the MetaQuest VR. Now, what Lager AI does is it connects users with the ability to take control
and monetize that data that's collected from the apps onboard it onto a protocol. And now, instead of just the apps, now with the Apple VR and the Metacrest VR, you will soon be able to do the same thing, both through the usage of these devices. And the way that works is
Say you're using your headset, right, for whether it's gaming or educational purposes or even some sort of online training that there is nowadays. Well, normally what happens is the big tech companies would sell off your day
to other third parties, right, as part of the business models to say. But now, with the help of decentralized technologies that we have access to now, we can take full ownership and control of that data.
Does that make sense? Yeah, for sure. Would you like to share more or is that your? Well, yeah, so essentially so what we do is the same as we do from the apps that are on what you don't have to be cool. We do the same, but we can also track.
The behavior data that's collected from the headsets. Got it, got it. And yeah, that's pretty much it. Just in the interest of time, Elliott, why don't you go ahead and share with our audience how your views is using AI to fight fraud and advertising?
Yeah, sure. So I'm just going to start with a quick caveat that I think we talk a lot about AI and obviously AI is a very hot topic right now. But AI in itself is it's not a new technology. So we talk a lot about big data techniques and a lot about the deployment of AI to actually collect and
for patterns in data. That's been going on for a long, long time. What's actually generating the current hype cycle of AI and projects is generative AI to AI that can generate its own conclusions and also use data from big datasets to build
models for itself and also to help train itself. So that's part of what we do at Varacity and specifically through Bear Views. The Bear Views is essentially a platform that prevents fraud. We do this using 13 modules of which to AI and machine learning.
And another one is a blockchain-based module. And quite simply, it reads data that is associated with fraud, so this could be things like known bad IP addresses, or if it identifies a number of markers that is associated with a bot.
And this sort of thing and it'll read that data on a massive scale. We're talking about millions of impressions here and it'll identify that that is fraud. But where I think the real and that sort of thing in AI and the deployment of AI has been going on for a long time, where the real
innovation is happening and what is actually in my opinion driving this hype cycle now is the use of generative AI. So Google have recently shared that they have plans to introduce generative AI into their appetizing business. So as I said before in the intro, most of the internet is
It's driven by advertising. It's interesting what layer AI said there about user data and most of the internet is powered by user data. It's what keeps the internet free. If we didn't have access as advertisers and publishers to that day, people would have to pay on pay world sites to use
the internet, but there's a lot fraud in this industry. Now what we do at Ver reviews is we take all of this data that is collected by our fraud identification modules and our AI and we feed it into a machine learning algorithm and we use that to actually train new AI
models that can essentially be used for the next generation about fraud prevention. And so these do things like they will have inferences from data that the human couldn't because of the reading big data sets. And also we're looking into the new
frontier of generative AI technologies. So now that many advertisers are getting into AI in a big way and they're exploring generative AI, that's going to open up a whole new avenue of fraud. So we are at the forefront of that and that's why we train AI models in order to stay on
top of that problem. We were at a conference just last week where Google and Microsoft are actually talking about how they were going to roll out their generative AI products. And this is, it's been adopted at an alarming rate, but I think it's important to just
And the you know frame that in the AI has been around for a long time, but what's driving this current hype cycle is is generative AI, I think is the most important thing at moment. Very interesting. And I think I think you know, this is one of the first times in a while that we kind of so many guests on on one.
That would be great because I want to give some time for the audience to also ask some questions. Talk to us a little bit about the future trends and opportunities you guys see in crypto, AI VR as well as what you guys have any exciting news or updates coming up in the roadmap. Eric, you want to start first?
Okay, sure. So before I start, could you allow one minute that I can... No, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no,#
Okay, sure. So both clean text and measures are delivered. So clean text mentioned about the vast amount of Monday that require AI to process. And that's something that we concur. Because for neural science, a lot of data that we got could be lost. And that's why we have to use
AI to extract the useful data to process and use AI to do the deep learning. So that one can learn. The AvAta can learn the real emotion that attached to the human being. There's something that we're working on. And get back to the AI.
You talk about the ownership of data. Yes, right? So there's something that we are working on there as well because we see Web 3, one of the key attributes of the Web 3 is the ownership of data. So we want to train the avatar. That is attached to you. Sorry, you can decide. That the avatar can decide.
things for you can work things for you inside a web3 and can travel freely among different applications or websites etc. And then Varasati mentioned about the fourth thing and your science a good technology and because it's something like the
We are going to use the neuroscience or the ET as a pattern to log in to an account. That is something that we are working on with Rural Matrix. There is something I want to share based on the sharing from the fellow speakers.
want to talk about our exciting stuff or our roadmap. So just last month in May we have launched our in-house chat GPT equivalent we call it Mophias. So any matrix movie Mophias is the captain so we lame this
model morphers. So basically the purpose of this morph is trying to collect the feedback of the users and also the behavior patterns of the user so we can blend it together with the newer signs.
So this is something we already trained and we used this technology from the professor and then to deploy on our mental that I just mentioned in my first part of sharing. So this is one of the things that I like to share with you. We have the Inhouse Chat GPT equipment.
we call it Mophie's. And then second thing is, as I mentioned earlier, and I also share the Contelegraph report that we have formed a strategic alliance with Neural Media, which is the Neural Media Equipment in China. So the layers are very strong in the so-called bottom level technology.
neuroscience and we are trying to develop a variable non-invasive technology trying to log in to the blockchain and we will have something coming up in late June tonight which is the state one of our phase one, the variables and we will have videos we have
products that you can use to test. And the third thing is a mentor. We have a video trying to showcase how as an individual scientist or a normal user can use our platform to train their algorithm or data aloe butter.
And then, probably about as not so clear, the first thing is about to train their models without too much pain. And then, Manta also allowed the miners to contribute their spare computing power. As we know, AR require three
the mental thing which is data computing power and also the algorithm so a mentor self-properties so and and also we have the Morpheus already deployed on mental already and yep so this the three things that we are working on and we have been delivering in late June and early July
and you will see this exciting stuff. And for more of us, you already, if you are part of the testers who joined the initial test, you already experienced that in mid-May and we got, in general, positive feedback, of course, we know there are some, there are some,
improvement area that we should working on then. There is something that we are not sure about. We will be working on that. So we see the U.S. science as a new technology to working with AI. Because AI can process a large amount of data that is difficult for human
and also for neuroscience, which is impossible to process before. So it can be more accurate or can be more precise to predict and to serve as the login or biometric information. And before I go, we have another biometric product we call the Bob wallet, which we
try to use the finger-wine as the technology to sign important transactions using your finger-wine. So you don't need to worry about before or even you can use your sign pattern when you're trying to login
can visualize an apple or you can do a symbol of a plant according to your pattern to look in and then to sign pens of a legal brand contract etc. So yeah a lot of application can be done to the entertainment, to the advertising. For example when you look at an advertisement on the
website, maybe you use your finger to move the cursor and then to click and click and then but the real emotion that when you see an advertisement is you are is from the tip of your your brain. So this part we can capture and
as part of big data that we are just mentioning. And actually EEG data is part of the big data which is shared in one of the by one of the speakers in the World Economic Forum just held earlier this year. So yeah there is something we are working on very excitedly.
and I hope to deliver a ledger and a lead line for you guys to appreciate. And that's something that I want to share with the floor. Thank you, team. Yeah, thanks for sharing Eric. Let's move on to Neil. Go ahead. What's coming next for Quinterts?
Hi guys, yeah, as mentioned earlier, I guess one of our folks is going ahead is really to push ahead with the build out of the AI components of our CTI platform, where well along the way there, we're developing a partnership with it, a really exciting
So that's one thing that's as in my role as head of clinical data analytics to make sure that that happens.
on time and we're hoping to do something in that space by Q3 of this year. But more importantly for me and a real kind of source of satisfaction for me is that we're delighted to have signed an agreement with LVL Health and Saladon Pharmaceutical
to support their clinical trial on cannabis-based medicinal products to support chronic pain or to treat chronic pain. Now this is a pivotal clinical trial within the UK and it's the first of its kind within the UK.
And it's not only a satisfaction for me in that, "Clinetex get a chance to support such a key clinical trial, but also for me at last, regularly, later have approved a study that help researchers conduct future trials into the use of whole plant can of
for chronic pain conditions. It's a real unmet need and something that really drives me on. Conditions such as outrightism, back problems, fibromyalgia and all that sort of stuff cause chronic pain that is that is under-treated today and really opioids are the only
real effective drug there and that causes lots of addiction problem so so this has this could be a real game changer here in the UK but also in terms of getting this as a licensed product to treat pain across the world.
world. And so the critics philosophy of having faster, safer, cheaper medicines, this is a chance to contribute to that. I mean, you know, it's a real kind of vision for us that we can contribute to meeting on met need and
patients and really up to 28 million people in the UK are taught to be living with some form of pain that goes under treated. So that's a real source of excitement where CTI will deploy the platform to support the oversight
operational efficiency, data quality of that big clinical trial and giving real-time visibility to LVL and to Seladon, Famous Sudacles on their clinical trial via dashboards and visuals and alerts and all of that good stuff.
We're really proud to be helping to collect and review the data to support evidence generation for this type of treatment. And another kind of thing to bear in mind to just very quickly is that it's quite difficult to break into
the pharmaceutical industry. There's lots of inertia and resistance to change there. So that makes us immensely proud that we've taken the first steps there. And our strategy from the outset has been to support small biotech companies, niche companies,
academic clinical trials to prove the value of our tool and I think through our partnership with LVL and set Cenedon we can do that and use that as a platform to try and infiltrate big pharma which is a bigger ask but something that we're confident that we can do. I think the
Interest of time we give the others a chance I'll stop there, but I mean obviously I've lost a saison. Awesome. Really appreciate it. Neil, let's move on to Lewis. Go ahead. Yeah, no, sounds great. So without taking too much time besides of course having the about some great new punishment.
and development updates lined up for this month that will help us expand their AI to the masses. We also have something unique that's coming up which is our in-person Hong Kong event. Without giving away too much, we will be showcasing our native VPN and we
They're in person to show everyone how you'll be able to monetize with your data straight on your mobile devices. So to those who are interested, of course, stay tuned to our Twitter page as we will be sharing a lot more details on the event very soon. And these two next weeks will be quite critical for that. So yeah.
Awesome, Elliot, go ahead.
Yes, I mean in terms of our upcoming roadmap, I mean we're in quite a good position now we launched in 2017 and we've been building out a tech stack ever since our upcoming roadmap. We have a number of improvements coming to our product, but actually our ultimate vision and
We've already had a revenue stage, so we are already in a live environment with a number of publishers who actually already use our solution for preventing ad fraud and running campaigns advertising campaigns.
One of those we recently announced is the Times of Israel and they have 10 million monthly impressions and they run their ad campaigns, video programmatic ads through various views. So realistically the next step for us and the biggest roadmap part of them is scaling up and we have a clear roadmap for scalability.
the revenue that we generate from our advertising stack, we use after operating expenses to buy back and burn VRA from a circulating supply. That is really our most important roadmap goal now is carry on building our
business development team and carry on onboarding new publishers. We're doing more for that goal than ever before, we're attending a lot of industry events and we've got one coming up on Friday and London. We're at Can Lion this year again with now almost 70 people and I guess
So I think we're in a really strong position and you know it's quite interesting for a project that launched through an ICO in 2017 to now be live and actually in use and generating revenue clients.
That to me in our work to crypto for going on seven years now and having a product that is actually used in the real world is unfortunately pretty rare in crypto. But I'm very proud that this year through Vrassity we have reached that major milestone and now I'm talking about scaling up
up again as many users into our network and on to our platform as possible. All right. We have a bit of time left. So I've got our first audience member up here, Jason, I believe. Do you have a question directly at one of the panelists?
Hello, can you hear me? Yep. Okay, spin a grace face to far. So my question is just in terms of considering the OAI diagram, well like what are some of the challenges you've seen that may
rights and upcoming years in relation to maybe entertainment or maybe medical field of using AI and also how do you think maybe this could make it case. Which project which guess are you asking?
It's actually first linked there. CTI. So yeah, I didn't quite catch the question. Could you maybe repeat the question? I think the last
It's just he sees asking what are what are some of the challenges you see in AI? Maybe you can talk specifically in the in the pharmaceutical industry and how to mitigate those challenges
Yeah, so I mean when it comes to the pharmaceutical industry, that's a great question because as I mentioned earlier, there's inertia there and resistance to change and for AI to work across organizational boundaries of pharmaceutical companies, they need to be better at sharing
sharing their data with each other. Data is the oil that powers the AI engine. There's no way around the more data that we have and the more data sharing that we have, the better insights we'll derive from our AI.
analysis of data and be able to drive better predictive decision, have better models and all of that stuff. So from a pharmaceutical perspective, the challenge is encouraging pharmaceutical companies to share their data. And we can do that because
In terms of we're not asking them to share their raw clinical data in which they would have kind of intellectual property invested. We're asking them to share measures of their data or KPIs of their data to allow other people or other
companies to make performance based decisions based on their KPIs. So, so these KPIs sharing of information doesn't compromise their intellectual property. So, there's a number of discussions going on actually at an industry level about how big farming
intent to share data across their own organizational boundaries. And once those decisions have been made, which I'm sure they will be, it will open up a floodgate of AI potential opportunities for companies like Clintex to take advantage of because they have a data sharing agreement in place. It would be
be impossible for clean text to shape how they're going to share their data because it's an industry level discussion. But what we can do is we can capitalize on whatever decisions they make on methodologies that they choose to share their data. So I'm looking forward to that. And that is one of the things I think will happen
in the next two to three years, a better way to share data across organizational boundaries. Awesome. And next we have Domingo, I believe is how you pronounce it. Do you want to unmute yourself? And do you have any questions for maybe one of the other guests? Yeah, exactly. Hi. Can you hear me?
Actually, I do have a question about regarding this project. Actually, what do you think is the best strategy that you can bring more user into your project? And what makes it feel
confident about the survival and sustainable success in the near future in Web 3 crypto ecosystem. How about this?
Uh, sorry, which guess are you asking this question, too?
Can I repeat my question once again? Yeah, but do you have a question for specifically for for because we have four for panelists up here? Who are you asking? Who's a question for?
I have only one question that is like what makes you feel confident about the survival and sustainable success in the near future in this project.
Why don't we do this in line with the future trends and opportunities and sustainability?
time. I'll give each of you guys a chance to speak your final thoughts. Anything you'd like to share with the KuKoin community and audience before we wrap things up. And I think maybe just because
We had to go through everything so quickly talk to us a little bit about the future opportunities in the intersection of AI and XR Eric let's just go down the same path the same order
Okay, Tim. So before chat GPD born, so I think the majority of people here don't really use the concept, FADE, HENSEOM, AI tools until chat GPD comes out. So we are working on neuroscience in the same sense, which is
quite groundbreaking and that's what we vision that can help to address the issues in the metaphors and to enrich the metaphors or web-free setting. There's something that we believe the UI and the UI and also blockchain technology can help
with the WebPree particularly talking about the about time in general and trying to create an early U inside a WebPree that can help you to make simple decisions and can work for you inside the metaverse. And you can enjoy more freedom in the fiscal world because in the fiscal world you have a country that by inside the
bitvizor, wapery, you don't have any web. Someone that attached to you, close to you, to do things for you. And there's something that we are quite excited about. Awesome. Very, very happy to have you on Eric and very insightful thoughts on your industry as well as AI. Neil, one of
You go ahead and do you have any final thoughts to share with the audience? For those who have been following us for the last six, seven years, we've come along way, we've built this too over time in collaboration with the industry. Our CTI platform
It's not something that has been developed in isolation, hoping it will find applicability for in the industry. It's been designed with industry. And so we're very excited that we've come almost to the end of a journey in terms of having CTI fit for purpose.
building on the AI components to it. We've signed a deal for it to support a new clinical trial, quite a high profile one here in the UK. And I think with all of that, that forms a very important sales pitch to try and break into big firms. So I'm really excited about
about the future and the sustainability of our product in that we have it ready to go. We're going to start with small firma, niche firma, academic clinical trials, prove the concept and use that to break into big firma. So I'm really looking forward to the next two, three, 10,
years. Lewis? Yeah, no, I agree with what he just said. So I'm very excited for all of the possibilities that are opening up with the AI and the XR, all of the immersive experiences, the personalized experiences, everything would just be in the next couple of years more efficient and
work with Justin General, be more productive. I think this is also a very monumental point for ecosystem where our community members will also start to supply data to AI models for the first time, so that's pretty cool. And yeah, for the people who are listening, you make sure to join the community. Also, then last but not least, Elliot, go ahead.
Yeah, so I actually just have a note, you know, a lot of people listening in obviously were on a cue call in spaces here. So a lot of you have been interested in trade and opportunities in the space and projects to look out for. I think we've got a really good collection of projects here and showcase and what they're doing.
today, especially interested in what you guys are doing at ClinTeX, it sounds really useful. I would say there's a lot of projects right now trying to piggyback and use AI to get exposure, but just make sure that you're looking at projects in the space that have real world utility.
they're actually solving a problem and they're actually going to deploy AI in a real world environment to improve things in parallel with blockchain technology that couldn't be solved with any other technology. And I think those projects are going to be
here in the, you know, in the next 10 years still building. So yeah, just pick projects that have an actual core use case and a building for real world problems. Yeah, I think that's a very important point, Elliot, in an awesome way.
way to end this. Obviously AI has had a lot of hype. I definitely agree with you that at the end of the day tech is here only to solve problems, right? Tech by itself is not useful unless it solves any problems. But yeah, again, for everyone, I mean, you know, I see a lot of hands up.
And sorry guys, we run out of time, but we do have another part 2 and part 3 of this AIS and VR series. Tomorrow as well at tomorrow June 6th and Wednesday June 7th at the same time 9pm,
time. And yeah, I just would like to thank our guests for coming on. I really appreciate it. And I hope to see you guys next time. See if there's any opportunity to have a one-on-one fireside chat with each of you. And yeah, appreciate it. And see you guys next time. Bye.
Bye. Thanks all. Thank you. Bye.