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and I'll definitely know that they're here.
So, hi everyone and welcome to the new Twitter space
and I am Joanna and I will be your host for today.
I think you guys haven't heard my voice for the past two weeks,
but I'm here and today we're having a very interesting topic
about from skills to settlement
and the main topic is who decide what AI is
intelligent is worth.
So I'm not sure if you guys are right now
in Hong Kong visiting the Bitcoin Asia,
but this is also something that they've been talking about.
And we've seen AI agents involved from general purpose
assistance into increasingly specialized system.
So instead of asking one agent to do everything
and watching it confidently attempt things
a definition should not be doing,
we're moving towards an ecosystem where agents
can call specialized skills, service, tools and other agents.
So that is what we're going to explore today.
So before we begin, I want to give a huge big thank you
to all of our guests today.
We have a lot of guests today, like around nine guests
for taking the time to join us.
So thank you all for being here
and we will have a fantastic mix of perspectives
and I'm really looking forward to the discussion.
So just a quick reminder that since we have a lot of guests
and we only have, let's say we will keep our space
in an hour or an hour and a half.
So I believe after question one for introducing yourselves
from question two, I will be randomly asking our speakers
or here with us today.
So, okay, then let's begin.
Let's aim for everyone to introduce yourselves.
So let me begin with Jackson,
the community consultant for Cypher Network.
Hi Jackson.
Hello, hello, is getting here me?
Yes.
Yeah, okay.
Hello everyone, I'm Jackson over here.
It's a pleasure to join this discussion
and my focus today is on emerging AI agent economy
and particularly how specialized AI capabilities
can be actually reusable and independently
capable services that agent can discover, combine
and maybe pay for.
So I'm especially interested in infrastructure
that around the economy and how skills are actually packaged
and most importantly, how performance actually verified
and measured as well.
Okay, so what it's like to me today
is the shift from AI from a single application
to whether ecosystem where AI agents can actually coordinate
with other agents and specialized skills
to complete a real economic task.
Back to you, hosts.
Thank you Jackson.
And can I have victory, the ambassador from Kotzenia.
Hi, victory, would you like to give an intro
about you and the project?
Yes, thank you so much.
Hi, I'm victory, community manager
actually at Kotzenia AI.
Kotzenia is viewed in AI need to distribute a car
with the structure, the computer layer
that AI agents and AI applications need to actually run.
So when you think of tenure, I think,
very viable and upskill and without
depending on any single provider.
So Kotzenia is viewed in, I mean,
the three things that defines what we viewed.
And those are the intelligence heavily
that allocates compute based on workload type,
a distributed compute network with no single point
of failure and zero knowledge that means
between every computation produces
cryptographic proof that it happened correctly.
So when I just doing just trust that the work
happened, what we're bringing proofs.
And I think this is the reason that today's topic really
matters to me because we are the infrastructure
layer of the exact problem being discussed today.
So when people ask who decides what AI intelligence is worth,
the answer depends entirely on whether
the intelligence can be verified because without
verified execution, you cannot really price a skill fairly.
So you can't viewed a repetition without system
that means anything.
So you can also create a market for AI
capabilities that functions on the C.
So yeah, that's all for me.
Kotzenia is viewed in the verification layer
that makes all that possible.
And that's what I'm here to talk about today.
Thank you so much.
Thank you, Victoria.
That is very interesting for a topic
and looking forward for further discussion.
And maybe I'll have a value real is uni base here.
Uni base.
I don't see uni base here.
Maybe they'll come back later.
Do I have the reference sensitive from data VLT?
I think you're on.
Would you like to give me a few?
Yeah, sure.
So hello, everyone.
I'm Azidi.
I'm the community manager at data VLT.
And it's really great to be here today.
So I'm actually looking forward to talk about
where AI data identity and Web 3 are heading.
And more importantly, how these pieces can work together
in a very, very practical way.
So yeah, from our side, data VLT is basically focused
on building infrastructure around verifiable real world data,
decentralized identity devices, AI and Web 3.
So the idea is to make data more trustworthy
by giving greater importance to where it comes from,
how it can be verified and how it can be used
across intelligent systems.
So what we have in building is a broader,
is actually broader than simple,
or simply collecting data.
We are working towards a more complete data infrastructure
while continuing the evolution of GVLT1.
And data VLT, DID, experience.
So yeah, that's a little about me
and what data VLT is building.
So over to you, post.
Thank you, Azidi.
And do I have a Mars Cat, Lisa from Mars Cat here?
Yeah, I see Mars Cat.
Hello.
Hello.
Hi, would you like to give an intro about you and the project?
Yes, thank you.
Hi, everyone.
I'm Lisa, Operations Manager at Mars Cat.
It's great to be here today.
Mars Cat is a primal safe course with three super app
built on a decentralized P2B network.
Inside the ecosystem, we combine private social,
a machine, one of AI assistants, AI agent services,
and so on.
From the AI side, what interests us most is what happens
when AI moves beyond simply answering questions
and the stars become becoming an active participant
in digital networks.
And agents may need to communicate with users, access
different services, execute tasks, interact
with applications, or inventory coordinate
with other agents at the other points, intelligence,
a lot of agents in life.
You also need identity, privacy, communication,
and a settlement infrastructure around it.
That's where Mars Cat fits into this conversation.
We were interested not only in making AI more capable,
but in creating an environment where AI services
can actually operate securely and create
a sustainable value.
Yeah, that's about me.
And Mars Cat, thank you.
Thank you, Lisa.
And next, let's have community manager from New Verify.
Are they here?
Let me give another try.
Is there a verify here?
Do, do, do, do, do.
No.
OK, maybe they'll come back later.
I see Vulcan community manager from PrimaCast.
Would you like to give an intro?
Although from my initials, you are loading,
but I'm not sure if you're still connecting or not.
Or would you like to try?
Can you guys hear me?
Do, do, do, do.
Hello guys.
Can you guys hear me?
OK.
Then let's move on first.
Maybe you can try a network and come back.
Next, can I have the core contributor
from SpoonOS?
Manchus, would you like to give an intro of yourself?
OK, sure.
We started as a skill marketplace as well.
So skills is what we will be talking about today.
And later we focused on a product, actually.
And because our bedroom is in Web3,
so we decided to focus on prediction markets, plus AI agents.
We did a successful run during the World Cup, AI
making predictions.
And some of the models were quite successful.
Of course, with predictions like with bad things,
you cannot always be 100% correct, but still this analysis
that AI provides is pretty useful for end users.
Yeah.
Thank you.
Thank you.
Thank you so much for your intro.
Oh, I see that a unit base is here.
Can I have a real head of ecosystem
from unit base to give an intro?
Hello.
I just saw you somewhere.
Yeah.
Hey guys, sorry for being late.
No, wait.
Yeah, could you hear me?
Yeah, so I can hear you.
Yeah, hi, everyone.
Great to be here.
So this is a flannel representing unit base.
We are doing a decentralized AI memory layer
for the autonomous agents.
For us, we aim to help AI agents remember,
collaborate and evolve across platforms through long-term memory
and in the upper ability.
Basically, our flagship products include
unit base, a Chrome extension for managing AI context
across different AI models and AI models and languages
and bit-aging on-chain service marketplace where AI agents
can be discovered.
So happy to be here to discuss a bit more about the how AI
agents like SKUs and the future look like.
Thank you, Vario.
And OK, I have two more guests that cannot connect at the moment.
But I think they will be back just in a bit.
Then let me move on to Alex, the developer ecosystem
leads from News Network.
Hi, Alex.
Hey, how are you doing?
Good, how are you?
Yeah, thanks.
Thanks.
Amazing.
Yes, so present myself.
I'm the ecosystem leader at News Network.
And to picture it simply, so right now
we can all agree that the market is just
loaded with AI agent and we do it like so many.
But one thing that we can notice is that they are all
trapped in that centralized silos.
Indeed, they can execute tasks.
But they don't really have that lot native economy that
would allow them to be fully autonomous.
Like they don't even own their own identity.
They cannot build the very fire reputation.
And they cannot transact independently within each other.
And this is exactly what we are building in News.
We are building the decentralized economic
layer for the AI agent era, which
means that we're going to be able to give, by the way,
the main net is coming very soon.
So we are going to be able to give to each agent an identity
and through that identity.
You can actually see all of the history of that AI agent.
You can see the task he was mission on.
And also, let's say that you want
to build a marketing campaign.
But in that marketing campaign, if you do it
with an AI agent normally, and if you use,
I don't know, like, Claude or Codex or Grocer or anything,
then most likely it won't have all of the skills necessary.
But if you do it through NewsNet, work with that AI agent,
you can find the other best agents, maybe,
to read that to script, another one to create a video,
another one to scrap the information
about the potential client that you want to contact.
And all of that will be made with just one script.
And the good thing is that as they're
going to have reputation, each AI agent
is going to have an identity, where that AI agent will know exactly
which agent to trust.
And it will be able to reward them and to pay them in a secure way.
So to make it simple, to make it very simple,
that's what we are building.
And news AI, the future of AI agent thing
so that the AI agent can be fully autonomous.
Thank you, thank you, Alex, for your intro.
I think Volcan is requesting again.
Let's give it a try to see if everything's OK.
I Volcan, can you hear me right now?
I can, thank you, yes, you may.
Yes, can.
Thank you so much for joining.
And right now, would you like to give an intro about yourself
and your project?
Yeah, sure.
Well, hello, everyone.
The community manager from PWTA.
It's good to be here.
I'm on you guys today.
Thank you very much for inviting us.
So at PWTA, we are an AI powered media network
that owns news podcasts audio.
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