TLDR

In this episode of BidCast, Jason interviews Yu Hu, the founder of Kaito, discussing the company's impressive growth to a $33 million annual run rate. They delve into Kaito's business model, which includes information as a service and innovative marketing strategies like the Yapper leaderboard. The conversation also explores future revenue streams, the role of AI in capital formation, and the importance  of community engagement. Yu shares insights on tokenomics, NFTs, and Kaito's vision about InfoFi and how they plan to expand beyond the crypto space, setting ambitious revenue targets for the future.

Chapters / Timeline

01:00 Introduction to Kaido's Growth Journey

03:47 Revenue Breakdown: Information as a Service vs. Platform

06:56 Market Dynamics: Business vs. Investment Firms

10:07 Innovative Marketing Strategies in Crypto

12:58 The Future of Community Funding and Capital Formation

15:52 AI-Driven Solutions for Token Distribution

18:59 Kaito's New Product Launches and Market Positioning

22:03 Flexibility in Investment Structures and User Targeting

25:05 The Role of Stakeholders in Project Success

27:46 Speculation and Market Dynamics in Token Economics

35:55 Solving Distribution Challenges in Crypto

40:00 Innovative Referral and Incentive Models

43:19 Personalized User Experiences and Data Feeds

44:04 Information as an Asset: Trading Narratives

51:12 The Vision for a Unified Social Media Index

55:36 Revenue Models and Token Dynamics

Transcript

<Jason Kam (01:01)>:

All right, we are live. Welcome to another episode of BidCast. I'm your host, Jason Kam, aka Maple Leaf Cap. Today is April 23rd, 2025, 5 p.m. Hong Kong time. BidCast is being livestreamed to BitClub members. Questions are from my own and the members. Today I'm speaking with Yu Hu, the founder of Kaito. Yu Hu, welcome.

<Yu Hu (01:24)>:

Good to be here.

<Jason Kam (01:25)>:

Yeah. You publicly disclosed that you're now run rating at 33 million AR annualized. Can you just break that down for us, like where it's coming from? Because that was like a massive increase versus when I talked to you last year.

<Yu Hu (01:41)>:

Yeah, so obviously like the whole Kaito journey has been a bit of a massive growth, right? So at the very beginning of 2024, which is just over roughly five quarters ago, so 15 months ago, we were generating roughly 100K of revenue. And since then, there's been significant adoption on various different parts of the businesses. And so the number that we gave specifically was annualizing the Q1 revenue and the two kind of main components to it. One is

<Yu Hu (02:16)>:

what we call information as a service, which is the traditional business that we've been running over the past basically, started monetizing in early part of 2024. That's our API business and our subscription business. And then that's making a roughly, I'll say, somewhere between 30 to 50 % of the revenue that we disclosed. And then the other business is basically the new business that we launched in December and that's kind of the Yapper leaderboard slash what we called information as a platform business. Obviously Yapper leaderboard will be in the first product out there in the market but subsequently we're going to be launching a lot of the newer products and that's the other the basically the remaining part and yeah so that's that's kind of the whole makeup of the 33.

<Jason Kam (03:11)>:

Sorry, and the traditional Info as a Service business, what's the breakdown of API versus subscription?

<Yu Hu (03:17)>:

Yeah, so I mean, we're not breaking that down, it's both are basically, you know, both are growing still and both are very, resilient and, you know, cutting through actually. I think one of the underappreciated aspects of that business is it brings us all the...

<Yu Hu (03:45)>:

business relationships that we currently have. One of the things that people were kind of surprised about when we first launched the Yaps campaign is people were instantly thinking that this is another social fire farm, it doesn't have any fundamental, but actually all the stuff that led to the Yapper Leaderboard was because of the business relationship that we had over the years and clients are basically asking us to have new ways beyond just like doing analytics.

<Yu Hu (04:15)>:

asking us for new ways to actually...
crystallized growth and all that kind of stuff. So the kind of the pro side and the API side both are still growing very fast and on the API side we're powering a lot of the, historically a lot of the kind of AI agents, applications, but nowadays we're doing a ton of large scale enterprise integrations in terms of, for example, we, I think maybe
Maybe like a month ago, Falcon X announced that their new flagship product is integrating with all the kinds of data. So in terms of all the search capabilities, mind share, sentiment, a lot of the social graph stuff. And increasingly we're doing a lot more of these large scale enterprise integrations using all the data that we have.

<Jason Kam (04:51)>:

Yep.

<Jason Kam (05:12)>:

And the breakdown there, how much is investment funds using you versus businesses, generally?

<Yu Hu (05:21)>:

Yeah, at this point is more businesses than investment firms. think at the end of the day, that's the state of the market right now. you know, it's just a bigger portion of the crypto market is always going to be project teams. And project teams have...

<Jason Kam (05:25)>:

Yeah.

<Yu Hu (05:45)>:

uh... you know more dollars to spend uh... it's been frustrating

<Jason Kam (05:48)>:

Yeah, that's for sure. Or fucking poor.

<Yu Hu (05:52)>:

A lot of the funds actually, it's very interesting dynamics in a way that even some of the whales are able to deploy more money and dollar than a lot of the liquid funds in the space. This is a very different market structure and dynamics there. obviously at the same time, the benefit of working with all the projects is the business is very, very resilient. As long as the project's operating, as long as people are on the team, then basically people need the tools to be doing their jobs. And market going up or going down doesn't really have an impact. The same goes to API business as well. Once people are integrating with that, it's very, resilient. But also at the same time, a lot of the Yapper leaderboard clients that we have essentially materialized because they've been kind of using the information service platform that we built.

<Jason Kam (06:56)>:

I guess the churn there is low, but it kind of is cyclical only in a way that the market gives the funds and the companies more or less money.

<Yu Hu (07:04)>:

Yeah, and to be honest, like, for...
So just in terms of the churn part, the high churn part is always the individual traders market. And I think it will be the same for a lot of the sort of a subscription based services in the space. The individual traders are very volatile, but it's making up a very little proportion of our revenue, even just on the pro side. And in the 33 million number, because annualized run rate number so it already factored in all the market downturn in March already.

<Jason Kam (07:44)>:

Yeah, and off the other part, which is the info as a platform, how do you make your, I'm guessing like 20 million dollars plus annualized there?

<Yu Hu (07:53)>:

Yeah, it's so we obviously have different ways of making money there and we are also in the process of expanding new revenue streams but currently we launch Yapper leaderboards with various different projects and as part of the service, we essentially run all the data indexing, analytics, and core marketing with every single project. And then we charge a fee for that, for the service. So one of the very big focuses for us in Q2 is basically having two new revenue streams, actually three more revenue streams coming out of the information, actually two new revenue streams coming out of the information as a service.

<Jason Kam (08:22)>:

Hmm.

<Yu Hu (08:41)>:

sorry, information as a platform business and then one more revenue stream coming out of the what we call the third leg which is information as an asset. So maybe I'll just cover the kind of the two additional revenue streams. So one is going to be Kaito .

<Jason Kam (08:57)>:

Yeah. Sorry, before I go there, I'll dive deeply into them just in just a bit. So like Bera pre-TGE, they come to you, like, I want to pay my KOLs and have them show me. And please help me devise a campaign and pick out the best KOLs who can show me. And I'll pay you a million dollars for you to devise a campaign. Is that roughly the right way to think about it?

<Yu Hu (09:04)>:

yeah.

<Yu Hu (09:18)>:

Yep.

<Yu Hu (09:26)>:

No, so it doesn't currently work that way. So the way that we basically charge is we charge a flat fee for data indexing, analytics, and all that kind of stuff. And each of the project would essentially set aside their own reward pool. We don't take any dollar from the reward pool. And every single dollar of the reward pool basically goes straight to the users.

<Yu Hu (09:49)>:

But as a service provider, we essentially run the data indexing algorithm and obviously the distribution of all the rewards. And then we charge kind of a six figure for that kind of a data indexing for one year of service. And then...

<Jason Kam (10:07)>:

Hmm.

<Yu Hu (10:08)>:

And then so upon renewal, people can essentially decide whether they want to renew the service or not. basically two big camps of projects that are considered in this one is post TGE. If you are a very mature kind of a protocol, then you can, you know, projects such as Polkadot, you know, back in the day, spend huge amount of dollar in terms of incentivizing KOLs and now using, you know, Yapper leaderboards

<Yu Hu (10:38)>:

essentially organically incentivized content creators and influence in the space the ultimate proposition that is in the past because crypto doesn't there's no digital ads in the space because you can't run any ads on Twitter then every single campaign and the main distribution dollar basically goes a handful of KOLs in the space which is very ineffective

<Yu Hu (11:08)>:

And and the majority of the times you basically Set aside a huge, you know either carry around or reward for a very handful of people And hoping and also at the same time you pay people upfront hoping that they deliver It is actually one of the most

primitive and non-transparent opaque distribution methods in the world. So the kind of alternative solution that we came up with was that we essentially incentivize people to set up a public bounty so that it becomes freely accessible for everyone to essentially participate which generally generally speaking generate much better excitement across crypto

<Yu Hu (11:58)>:

but at the same time you only reward people based on their actual performance. So people need to put up the work and actually generate kind of a high value, high impact outcome to be able to qualify for being paid. And so essentially everything is essentially being rewarded after the impact is done. So that's kind of a kind alternative structure. And if think about

<Jason Kam (12:03)>:

Yeah, that's cool.

<Yu Hu (12:28)>:

I'll confer pre-TGE and post-TGE. Post-TG, you essentially always have some sort of marketing dollar that you need to spend for every single healthy company in the space and outside of the space as well. And people, for example, the Jupiter will be running their own content creator campaign, stuff like this. Every single community, every single big product will essentially run something similar. Historically, it's all manual. You basically go through thousands of different tweets. Some of the products use

<Jason Kam (12:36)>:

Mm-hmm. Mm-hmm. Yeah.

<Jason Kam (12:51)>:

Yeah.

<Yu Hu (12:58)>:

Twitter API which is costing them close to a million dollar a year in terms of just the data indexing and then you basically manually go through all of this and then you know pay your community member with you know

<Yu Hu (13:14)>:

with some sort of activities. Yeah, it's very manual, but at same time, it's all alternatives, for example, be like Polkadot back in the day, you pay actually 37 million that was disclosed in six months working with influencers and KOLs without very explicit metrics to essentially evaluate performance and effectiveness. So we're kind of changing this structure.

<Jason Kam (13:15)>:

extremely manual.

<Yu Hu (13:44)>:

a fraction of the money, you can now basically have alternative way of incentivizing the entire community and crypto Twitter to be, you know, talk about something that's either educational or insightful or talk about stuff that's relevant and very important for your narrative and some of the specific campaigns that you're doing and you can always measure kind of...

combine this together with whatever campaigns that you're doing. For example, the way the Manta is doing this is Manta are launching a ton of new products. And every single product that essentially incentivize people to be educating the whole market about this new product. Either they're kind of the new index fund, the banking side of things, and stuff like that. And it's using a fraction of the money to essentially mobilize the entire.

<Jason Kam (14:18)>:

Yep.

<Jason Kam (14:22)>:

that's cool

<Jason Kam (14:36)>:

And the flexibility there is they can pay through tokens as well as US dollars. That's cool. how many logos are there with this $20 million kind of run rate? I'm guessing it's actually growing because it doesn't just go away after TGE. They might want to pay you less after TGE, but it's a SaaS annualized service.

<Yu Hu (14:43)>:

Yeah, and then go ahead. Yeah, sorry.

<Yu Hu (15:00)>:

Yeah, it's an analytics service and the so the way I think about it is two kinds of different markets. One is the pre-TGE market and the other one is the post-TGE market. The post-TGE market is effectively you're working with more mature protocols that have sustained for years of development, right? So they're not gonna, you know, go away.

<Yu Hu (15:26)>:

And then they have also substantial treasury, think about sustainable development, all that kind of stuff. And then they are most likely to be renewal, long-term sustainable, multi-year kind of contract that we think about. And then the pre-TGE market is a bit of both. So you have a lot of the...

The primary focus for most of the pre-TGE market and the nature of the market is people would essentially spend significant marketing dollar going through the pre-TGE process because that's when you build up awareness and build up the brand throughout the process. And post-TGE, some of the projects will be able to continue to thrive, but some of the projects will not be able to make it over the long term.

<Yu Hu (16:22)>:

But essentially that part of the market, we convert some of the projects to be long-term customers. And some of the other projects will eventually maybe discontinue. But as long as the asset issuance side will always continue, then we'll always have a stream of more projects essentially launching through the mechanism as well.

<Jason Kam (16:43)>:

And how many logos do you have that contribute to that 20 million annualists?

<Yu Hu (16:46)>:

I think it's roughly somewhere between 40 to 50.

<Jason Kam (16:51)>:

40 to 50. wow. OK, so they pay you a lot of money. OK, got it. Makes a lot of sense. So that's 20 million annualized, just about. Tell us about the two new products that excites you, and what kind of revenue do you think they'll help you drive? Maybe those two questions. Go ahead.

<Yu Hu (17:10)>:

Yep. So the way I think about the stuff that we're disrupting is if you think about the the Yapper leaderboard market that's kind of a democratized way to essentially launch attention.
The two other ways and the two other things that we are very excited about one is a democratized the way to essentially form democratized the way to essentially help with capital formation and that's effectively a capital launchpad and I also think that that's probably where the industry is going because I think that a few major trends are happening right now is I think VC fund is going down

<Jason Kam (18:00)>:

Yeah, we're fucked.

<Yu Hu (18:00)>:

versus the last  I think liquidity is more fragmented in the market right now. I think over time probably the airdrop dollar is going to go down because there's just not enough liquidity that essentially sustains the frequent asset issuers. Especially for the airdrop dollar per project.

<Jason Kam (18:18)>:

Yep, agreed.

<Yu Hu (18:30)>:

But, and in some way, I also think that the airdrop market is...
Some were indirectly funded by VCs because a lot of the protocols not necessarily have PMF at launch. So it is all based on the belief that in the future, because they have money at hand in the future, they can build a viable business. So that's the value that people subscribe. The market subscribe to each of the protocol at launch, which essentially supported the price at launch, which essentially benefits a lot of

<Jason Kam (18:42)>:

That's true.

<Yu Hu (19:08)>:

the airdrop recipients. I think that over time probably that airdrop market is going to go down. At the same time, I think one market is going to go up is with the absence of or with the decline of the VC funding market that the community funding market is going to go up. Because a lot of the projects will be thinking that with the same kind of a circulation that I have in mind,
If I can't do a lot of the airdrops, maybe I just do more community rounds. So essentially to decentralize my holding.
So I think that's a big market that we kind of want to tap into. And the specific angle that we have is, think up until this point, there's no mechanism that really very heavily leverages AI technology to really help with that distribution. One of the things that we did on Yapper Leaderboard is everything is basically algo-driven.
So in the past, it's all manual, and people always wanted to kind of reward very loyal community members, right? But in the past, they couldn't do it because how would you even go about indexing all this data and then identifying the relevant people to incentivize a reward? The same thing actually goes to kind of the capillology part as well. If you think about community around, right now, there's just not enough data that's been properly indexed, provided by the people who are able to do this, to essentially map how all the people who are relevant. Imagine that you building a cross-chain protocol, then...

<Jason Kam (20:51)>:
Yep.

<Yu Hu (21:00)>:

A lot of the time, it's not really just about the dollar that you raise. It's actually about who you bring into the capital ⁓ you know cap  table and then be with you for the long period of time. And pre-TGE, post-TGE continue to be supporting you, creating mindshare, generating content for you, using your product, stuff like that.
And what we are specifically trying to provide is with all the data that we have, if we are able to come up with a way to essentially use AI to identify all the most relevant people and also use algorithms to optimize the round, then it will be huge value add.
And in terms of just optimizing the round, right? So you're thinking about a lot of different aspects to it. How do you even, like, historically people are all doing this on a manual basis. I think about how you see your structure in the round is all, I know these people, they're gonna be helpful.
you should get them into the  Round. Stuff like that. In the future, it can all be run by an algorithm because with algorithm, can identify, you can index the most comprehensive data, you can identify the most relevant people who are deeply aligned and deeply passionate about the stuff that you're doing, that the most relevant, and there's no bias in terms of who you know, stuff like that. And you can be well-balanced in terms of geographical coverage, can be well balanced in terms of skill set, coverage, all that kind of stuff. So that's really the stuff that we're trying to do.
That's pretty big. And I have so many follow up questions, but this is for both pre TGE private investments, as well as post TGE OTC rounds, or even just placements. Initially, what would you go to market with?

<Yu Hu (22:55)>:

I it can apply to both.

TBD, how we gonna be doing this? We have a few projects in the pipeline in terms of the pre-TGE and I also think that post-TGE could be a very big market as well, depending on how people are going about that.

<Jason Kam (23:19)>:

And then the vesting and the custody is enforced by you or do you work with any partners?

<Yu Hu (23:24)>:

So we'll be working with other partners.

<Jason Kam (23:27)>:

OK, OK, cool. And then in terms of the flexibility, the flexibility of this product comes on a couple of sides. Immediately off of my mind is when you speak about relevancy. It's relevancy both to the core product that they're building as well as the relevancy as defined by the founder. I might want to open up around to people who invest in my competitors because I want to have them talk about me.
How flexible would that be? And then secondly, if it's privates, how flexible would it be to tie the vesting or any type of terms, allocation size, to the actual sort of yaps or contribution that they have?

<Yu Hu (24:06)>:

Yep.

<Yu Hu (24:10)>:
very very flexible you can basically structure however you want this to be and you can also tap into both the social side as well as the on-chain side as well so one of the benefits of Kaito being a platform that has both a substantial amount of social information and the on-chain wallet connections and linking is we're able to have much more holistic user profile data. If you want to be targeting traders in Korea that have used a certain DEX protocol or that kind of stuff, we can essentially target those people instantly. so the amount of... obviously in a bit we can talk about kind of the own product, but this is kind of the ultimate premise in terms of how...

<Yu Hu (25:04)>:

basically the algorithm driven user targeting can be so precise that with the distribution that we have, can basically structure this in a most optimized way. So in a nutshell, it can be very, flexible. And at the same time, it can even introduce, because we have the analytic side of things, it can even introduce very, very interesting dynamics where you can have differentiation and different

<Yu Hu (25:34)>:

terms for different people based on proof of work post round. So you can even structure something like everyone will be getting at certain valuation. But if you are willing to put up the put in the work after the round, then you essentially over time will essentially get more favorable terms, either additional bonus or a status investing or that kind of stuff. So a simple example could be if you come and raise a yap

<Jason Kam (25:50)>:

Yes.

<Yu Hu (26:04)>:

round and every single Yapper can essentially come in at X dollar of value. Let's say for example 300 value, 300 FDV, 300 million FDV. But over time if you are willing to put in the work and continue to be generating mind share, Yapper about us, et cetera, and then based on your performance over a long period of time then
if you are basically ranked top 50 over a one year period, then basically your effective valuation can come down to 100 million. So then it solves a big issue in terms of people...
Basically, in the same round, people are paying the same price, but after the round, not necessarily everyone is contributing the same value to the deal. So you can essentially have a whole new different mechanism with the analytics that we have.

<Jason Kam (26:48)>:

Yeah.

<Jason Kam (27:00)>:

That's very cool. what's your tick rate and how's traction with this so far when you talk to projects?

<Yu Hu (27:10)>:

So can't disclose that, but what I can say is I think will be a very big flagship product for us heading into basically Q2 and Q3.

<Jason Kam (27:14)>:

Neither? Okay, okay, okay fine.

<Jason Kam (27:31)>:

And what's pushback from teams that you talk to that it seems very enticing? And if they are hesitant, are they like, this is so new, we want to see somebody else do it first? What's the hesitation, if any?

<Yu Hu (27:46)>:

Yeah, so interestingly, it's the other dynamics. It's the opposite of that. Basically, people are really keen to be number one launching with Kaito. Because I think our brand positioning is Kaito is always doing something new in this space. And people want to be associated, want to be the first one doing with Kaito. It's the same as how we are doing the Kaito own stuff. It's the same as when we kind of
launched the Apple leaderboard, the first few projects are always getting outsized sort of attention and being kind of considered as the innovator in the space. So the same dynamics actually applies here. So we actually haven't been very vocal and public about this new product, but...

<Jason Kam (28:36)>:

Hmm.

<Yu Hu (28:37)>:

Basically, we are in this market, essentially, have a very, very deep relationship with pretty much every single pre-TGE company that's launching in the space. it's very much a lot of our clients are like, yes, we want to do this.

<Jason Kam (28:55)>:

Interesting. So this is like a different echo, but it's like interesting. And the public market OTC would happen much later, it seems like.

<Yu Hu (29:00)>:

Yeah, it's different.

<Yu Hu (29:04)>:

Yeah, so I mean,
I do think there's different kind of differentiation and different dynamics, all that kind of stuff. And I think it's very much kind of just an extension of what we are already doing and essentially offering a service to the project as an alternative in terms of how they can be thinking about, you know, various different ways. And eventually, I think this is going to be very synergistic and complementary because at the end of the day, know, when people are very very close to TGE, then why are we, why are people kind of raised in a pre-TGE realm? There are only any two purposes. One is, one is basically decentralizing ownership.

<Jason Kam (29:55)>:

Mm-hmm.

<Yu Hu (29:56)>:

and getting the high quality people to be in the capital cap table and be for the long run. And the other one is also just raising awareness, sort of using that as a marketing event as well, Which is very adjacent to what we're doing in terms of the Yapper leaderboards and stuff.

<Jason Kam (30:18)>:

Hmm. That's fun. I wish you all success. This seems like it's a big product. I mean, I'm assuming it will be a tick rate based model for your revenue, like $10 million size round, tick rate, revenue. Is that?

<Yu Hu (30:33)>:

Yeah, so.
The way that we think about the fee model here is, let's say for example, if you want to raise 10 million, and then we want to have a new different fee model and a different mechanism for this to be interesting. So the way we think about this is, for example, X percent of, let's say overall we take, the network would essentially take either, let's say, as an example, we take 5 percent, and then maybe part of that is stable and part of that is in token. But instead of Kaito taking a token, we redistribute all the tokens to all our stakers. So the specific dynamics there is we can have like 10 different LaunchPad, you know, protocols that launch through us and then they all have future tokens that they're going to distribute to the network.
but we don't take the tokens, we don't think about divesting the tokens, all that kind of stuff. We essentially reserve the tokens for all the sKAITO token holders, and then they need to signal alignment with the project that they like. And then to be able to, in the future, get the tokens. So that becomes a dividend model, effectively, but...

<Jason Kam (31:53)>:

And well, it's not dividend because they have to do something to get it.

<Yu Hu (31:58)>:

They just stake

<Jason Kam (32:00)>:

but they have to signal alignment. They have to say something.

<Yu Hu (32:02)>:

But they have to do it. They don't have to do the work. Basically they just park their sKAITO to the specific project so it's Yeah, but but but that way the the reason why we want to do it that way is because We don't necessarily want to do the kind of the BNB model where? You know every single kind of a BNB holder is

<Jason Kam (32:12)>:

Interesting, okay.

<Jason Kam (32:24)>:

Hmm.

<Yu Hu (32:29)>:

is undifferentiated and you basically get tokens for every single project that's being launched. But actually we want to force all token holders to signal alignment to any specific project and then they become aligned with any specific project. And there's also kind of a very interesting market efficiency angle there, which is also kind of how we think about the whole InfoFi narrative.

<Jason Kam (32:54)>:

Yeah. Yeah.

<Yu Hu (32:55)>:

We believe that token holders are to be efficient in allocating their capital. So as they basically allocate, they're also constantly thinking about the future value of the tokens, et cetera, all that kind of stuff. There's a dynamic balance there.

<Jason Kam (33:00)>:

Yeah.

<Jason Kam (33:07)>:

Mm-hmm.

Yes, obviously that portion would be as the additional interest and sKAITO is tradable, I'm guessing.

<Yu Hu (33:22)>:

Well, sKAITO is basically just a derivative of $KAITO

<Jason Kam (33:25)>:

Yeah, so then it like it opens up yield up. It's interesting. OK, I could see that. That's cool.

<Yu Hu (33:29)>:

And then there's going to be even more interesting dynamics there because we now have a Pendle pool. So for every S-client order, there's PT and YT. So.

<Jason Kam (33:39)>:

Yes, exactly.

and you just go into pre-market, would the trading be done at your platform or is it somewhere else?

<Yu Hu (33:47)>:

No, no, no, this is not pre-market. But essentially, if you have the YT token, then YT can essentially stake with all of these different Launchpad products, which entitles you to get the future tokens.

<Jason Kam (34:04)>:

Yes.

<Yu Hu (34:04)>:

And all of a sudden it becomes the same playbook that, you know, backing, you know, for example, Q1 2024, and people are speculating in the future price of the token, and then by the way, it's essentially, you know, to get exposure to the token.

<Jason Kam (34:14)>:

I get that.
get that exactly. I mean, you stake, you stake $KAITO that's your PT. And then you get a YT when you stick with a project. Let's say you get sKAITO YT mega ETH, but that's tradable and you know exactly how much you're getting kind of. And would that trading be done on your platform or is it be done on Pendle or something? Cause you. Okay. Okay. Yeah. Yeah. Interesting. Cause  that backward implies.

<Yu Hu (34:23)>:
Yes.

<Yu Hu (34:37)>:

we can essentially make a market for it as well.

<Jason Kam (34:46)>:

I mean, it's really illiquid, but it implies what valuation people think mega ETH will trade-up. Interesting. It seems like you should make a lot of money out of this and kind ponzies up the sKAITO thing. I think people who owns the sKAITO could be really happy. Tell me more.

<Yu Hu (35:01)>:

There's going to be lot of speculation and basically should be people thinking about different valuation for different tokens, how you structure YT, PT, all this. It's going to be very, very interesting.

<Jason Kam (35:09)>:

That's cool. Yeah. Yeah. Yeah. And obviously, the sKAITO holders who are whales already would be pushing the projects that they invest in to do around on you because they're cool.

<Yu Hu (35:22)>:

Yes. And that becomes a kind of a flywheel as well because essentially by decentralizing the benefits and the fees, we create more stakeholders for each of the Launchpad projects. Then, you know, that becomes a very, interesting dynamic.

<Jason Kam (35:46)>:

Yes, investing there will be on the same level as the folks who invest based under Yapper point. Okay. Okay. Tell me more about their own product.

<Yu Hu (35:55)>:

Yeah, I mean, so ultimately the own product is trying to solve the kind of the distribution problem that people are having. the way I think about the own product is, Yapper leaderboard is basically Yapp to Own. But in crypto, there's so much more than just Yapp to Own. There are...
For example, trading, there's for example referral, there's for example incentivize the usage. The basic kind of different categories of incentive or campaigns. So essentially you're to be tapping into those. And by leveraging the distribution channel that we already have in two parts, one is we have.
For example, 200,000 monthly active Yappers at the same time, a million registered users on the platform. So we can directly reach out to every single user that's pretty much active in crypto today. But at the same time, we can also distribute through the Yappers to essentially go to not just crypto Twitter, but all the other social media platform as well. So for example, if you want to target the Korean market, and not every single Korean is going to be
looking at Twitter all day, but actually by targeting all the Korean Yappers who all have some sort of Twitter presses, they can then redistribute through their Telegram channels to essentially reach out to those users.
The underlying premise of the Kaito own product is to solve the distribution problem because people can't use very specific digital ads or any sort of targeting. And that's where every single product is struggling with. They don't know how to effectively spend their incentive dollar. They don't have a very... Yeah, go ahead.

<Jason Kam (37:49)>:

Maybe to make it clear, because I'm a little confused. If I'm a Yapper today, I show on Twitter, and I use TikTok, I use Telegram, I use all these social products. And then I want to get paid through MegaETH, through Yapper. Walk me through flow of how I get paid. Let's say TG or TikTok or something.

<Yu Hu (38:12)>:
Yeah, so for example, we can, through the platform, we can distribute a referral code.
and you basically get the referral code that's personalized to you and then you can redistribute this referral code to all the other people that sign up through you. So we can track specifically all these people are kind of onboarding through you specifically. And as platform, we can basically design different campaigns and that's kind of a referral to earn, right? So for example, for trade to earn, it can be very simple. We can be working with whatever wallet providers, whatever exchanges, whatever upcoming

<Jason Kam (38:31)>:

Hmm.

<Yu Hu (38:51)>:

you know, DEX competitors, you know, competitors and stuff, we can be either the first degree distributor in terms of directly distributing to the users or we can be the second degree distributor in terms of we distribute to the KOLs or the Yappers and then KOLs will then distribute to all the other people. And then the platform can take basically a success fee or referral fee or whatever.

<Jason Kam (38:57)>:

Yep.

<Jason Kam (39:10)>:

I see. I see.

<Yu Hu (39:21)>:

And then again, we can have the same interesting dynamics where whatever the fees that the platform is making can essentially redistribute to the stakers who are believing or have vested interest in a particular campaign.

<Jason Kam (39:36)>:

I see. So for example, if you work with Binance, mean, Binance gives you a huge ref like, mean, everybody can refer already. And then, and then that basically goes to all the Yappers. They all of a sudden have a quest, like a ref link of their own. It's like sign up to Binance and trade. And then Binance see a revenue go up. They basically pay you the fees and then you pay the fees to the Yappers that distributed based on their ref code. And you take a small slice in between, I'm guessing.

<Yu Hu (39:42)>:

Yup. Yup.

<Yu Hu (40:00)>:

Yeah. Yeah. And typically, always kind of the upper coming competitors that's trying to grab market share. they're basically a ton of a... I think the specific edges that we have is one is on distribution.
We're one of the very few platforms that have the highest quality of users. Think about every single, it's not just kind of a KOLs and not just kind of a users. We have all the builders, we have the core of the CT and the entire, basically the highest quality of people in crypto are basically registered users. So the average dollar value of a

<Jason Kam (40:28)>:

Hmm.

<Yu Hu (40:54)>:

so that you can reach out so it is very, high here.

<Jason Kam (40:56)>:

Hmm. And the earn feature basically is tied to the SaaS service you already sell to these businesses. They already have a budget with you and you're like, hey, you want to try this earn product. that how you sell? Hmm. Got it. Hmm.

<Yu Hu (41:05)>:

Yes, and also the YAP leaderboard clients. and they can combine the two things together as well. So for example, if you are already setting aside, let's say 50 basis point of the token for Yapper campaign, you can essentially pair that up with a referral campaign. Right? So all of a sudden it's not just.

<Jason Kam (41:25)>:

That's very cool.

<Yu Hu (41:29)>:

You're not just incentivizing people to be yapping about you, but actually with a very, very clear call to action, which is yap about me, but also send this referral, get as many people on board as possible. And that becomes a much more holistic campaign that we can do.

<Jason Kam (41:36)>:

Yeah, sign up through.

<Jason Kam (41:42)>:
Hmm. Would the, with the users, cause it seems like you are not only profiling projects, but you're kind of also profiling users. Like as a, a Yapper on your platform starts contributing, naturally they'll have more affiliation with some projects over the other. Would there be at some point that the Yappers will have individual project based sort of, I wouldn't call it ranks, but just like affiliation or loyalty points, kind of something like that associated with single projects.

<Yu Hu (42:15)>:

I mean, they already have in a way that because we have like all these Yapper leaderboards and they would appear on certain Yapper leaderboards, but not on others. So there's exactly a ton of information that we have in terms of what are some of the typical projects that they will be interested in, typical narrative that they will be interested in. So, and we also have that people's own chain behaviors and stuff like that. So it's really kind of a holistic

<Jason Kam (42:19)>:
Yep.

<Yu Hu (42:44)>:

user profile, the yapp profiling that we have.

<Jason Kam (42:45)>:
That's cool.

<Yu Hu (42:49)>:

And I think by the time that this gets published, we already would have launched our feeds feature on the platform as well. Cause at the end of the day, know, Kaito is, you know, information product as well. So we want people to be going through the feeds on Kaito across like different social media or that kind of stuff, everything related to crypto.

<Jason Kam (43:00)>:

Welcome.

<Yu Hu (43:19)>:

Thanks!
And we will essentially have personalized fees for everyone, stuff like that. And in the future, we're also going to be having a mobile version. So iOS, for example, which we already have on the institutional side, on the pro side. So we're going to be on the retail side. So in the future, everyone's going to get personalized notification in terms of, hey, what are some of the deals that's going to be interesting to you? This kind of product can be a very good opportunity because you are

<Jason Kam (43:34)>:

Yep. Yep.

<Yu Hu (43:50)>:

high back in a day and this thing is very much up and coming you know versus that

<Jason Kam (43:57)>:

Hmm, makes sense. That's cool. So we talked about two things. There's a third thing, like info as an asset. Can talk about that?

<Yu Hu (44:04)>:

Yeah, so information as an asset is basically the underlying premise of InfoFi is that information can be priced and traded as well.
So we had a first partnership with Noise. So they are building on MegaEth. And that essentially allowed people to be trading narrative, trading pre-TGE mindshare, all that kind of stuff. So historically, in terms of a pre-TGE mindshare, the rational is simple. So currently, if you want a long MegaEth, there's no way that you can do it.

<Jason Kam (44:32)>:

Hmm.

<Yu Hu (44:43)>:

If you want to have a view on, you know, certain stuff, there's no way you can do it until the point that they basically get listed on some sort of pre-market, which is just a few days before the trading.
but that becomes a vehicle where people can essentially express certain views. The same thing actually goes to kind of a narrative, with even, in my view, with even stronger proposition there. So like back in the day, everyone wanted to learn AI narrative. For example, I think about Q4 last year. But majority of the people got burned very badly because you basically should pick the wrong asset. Yeah.

<Jason Kam (45:13)>:

Hmm.

<Jason Kam (45:22)>:

Yeah, the coins are shit too. But anyways.

<Yu Hu (45:25)>:

And but but imagine that you can actually long different narratives, which is the easiest thing for people to understand. Like if I just want a long stable coin mind share stuff like that, I can basically just trade that, which is a mega trend that's also being manifested in traditional finance as well. For example, Fidelity will be coming up with a basket of tokens, not tokens, but obviously equities because people realize

<Jason Kam (45:30)>:
Yep.

<Yu Hu (45:55)>:

that nobody wants to due diligence on the video. People just want to trade what they understand. They want to trade trends or this kind of stuff. so we're going to start with all of these, but then in the future, a lot of the stuff can be tradable and you can be expressing your view on the popularity of a singer. There could be, you know, different trends they can be trading and all that kind of stuff.

<Jason Kam (46:05)>:

Hmm.

<Yu Hu (46:25)>:

all of a sudden it creates a whole new market that allows people to express their views.

<Jason Kam (46:32)>:

Interesting. I'm guessing that product would be using your Mindshare index as the underlying. And that oracle basically tell us the PNL of this PERP platform, whereby there will be an LP pool that takes the counteracting side of whatever longs and shorts of the PERP position people take. And then the deviation of the PERP price will be the funding they pay. Is that roughly the right way to think about it?

<Yu Hu (46:59)>:

Yeah, that's roughly it. There are obviously different ways. And if you think about the Polymarket model, they allow people to bet on stuff that will eventually have a definitive outcome. Right, either it be elections, sports events, all that kind of stuff.

<Jason Kam (47:01)>:

Okay. mean, it's yeah.

<Yu Hu (47:25)>:

But a lot of the stuff doesn't really have a definitive outcome. For example, if you're betting on whether certain singer is going to be very popular in the future, how do you even go about quantifying that? Right. But.

<Jason Kam (47:39)>:

Yeah.

<Yu Hu (47:41)>:

leveraging the information markets, can actually basically index all the social media content, then that becomes the source of truth in terms of whether that, the manager becomes a source of truth in terms of the popularity of that particular singer. And also at the same time, the interesting factor there is when people are trading Memecoin, people are really just trading narrative and the popularity of certain topics. But

<Jason Kam (47:58)>:

Yeah.

<Yu Hu (48:09)>:

The issue with lot of the Memecoin was there is just so many idiosyncratic token distribution and some of the other stuff that's in that. There's a lot of insider allocations and stuff that's just non-transparent. But...
If you think about from an information market perspective, because everyone is effectively an insider, that makes nobody an insider. Because people collectively form the market.

<Jason Kam (48:45)>:

Yeah. I mean, this is an interesting effort. I, I'll be really curious to how it's because I, right off the bat, I can think of three questions, three problems. The mind share are, mean reverting because anything that's hyped got died down over time. The Yappers themselves can manifest the reality by just like tweeting. So they can kind of almost manipulate the market. And then the ultimate LP pool will run into this like insider, like toxic flow situation where.

<Yu Hu (48:46)>:

and happy.

<Jason Kam (49:13)>:

I'm going to bet size, of course, because I'm the project founder that's going to cost this wave of mind share. Would you rank this as the most excited effort that you have out of the three, or is this like a we're experimenting kind of thing?

<Yu Hu (49:30)>:

I think it will be a... So maybe let me answer the questions first and I'll talk about my view. So first things first is depend like the manipulation, the degree to which that certain things can be manipulated really depends on the market itself. if theoretically, if we're indexing every single social media in terms of the popularity of a singer, then...

<Jason Kam (49:34)>:

Yeah, yeah, yeah, yeah, Yeah.

<Yu Hu (49:59)>:

Effectively because the market is so big None of the guys will have our size impact in terms of determining that unless you basically bribe the entire market then obviously everything eventually is subject to manipulation, but if if the cost of manipulation is too high then basically wouldn't it wouldn't be viable and so that will be kind of you know, the ways to go about, but obviously like different markets will have different dynamics there. What's the other one? What's the other one that you mentioned?

<Jason Kam (50:39)>:

Yeah, I thought that you would get toxic flows. if, if, uh, if I'm long AI and I'm, yeah. Yeah.

<Yu Hu (50:43)>:

because of mean reversion? I mean, in a way that people can argue memecoins have mean reversion as well because everything's gonna go to zero eventually. Yeah, so I mean, I don't think there's any difference.

<Jason Kam (50:51)>:

That's right. Yeah, I could see that. I could see that.

<Jason Kam (50:59)>:

Yeah. If you were to rank the three efforts, before I go there, is there anything else that we haven't talked about that outside of the three that like, man, this is going to really jumpstart revenue for us off this current level?

<Yu Hu (51:12)>:

It's the possibility of going much beyond crypto. Because, I don't know, we probably talked about this last year. One of the grand visions of what Kaito really tries to build is something that indexes every single social media in the world.

<Jason Kam (51:25)>:

Hmm.

<Yu Hu (51:37)>:

The specific problem that I see in this space or in today's world is a traditional search engine is becoming less and less impactful because Google now does, for example, you will be saying that you use a Grok, for example, a lot, right? Because a lot of the useful information is on social media. It's very different from even just five years ago. But at the same time, every single social media is an isolated platform.
Twitter doesn't want other people to be indexed in it. The data, Instagram doesn't want that, all that kind of stuff. The specific problem they're trying to solve and the grand vision or the kind of the long term vision that we have for the whole InfoFi economy is we believe that the only way to break that barrier to essentially index the whole...
people call it the world garden for the whole internet is incentivizing users directly. People getting paid so that they will share their data with you. And then you don't do that by just indexing their data and then just give them money.

<Jason Kam (52:41)>:

Yep.

<Yu Hu (52:51)>:

To be able to have a sustainable business model, all of the stuff that you take from them needs to be generating revenue and generating sustainable business model as well, which is effectively what we have experimented in crypto Twitter. So incentivizing everyone to be sharing their data with us, but we create a whole new economy to have all the Yappers to be constantly being paid.

<Jason Kam (53:19)>:

Yep.

<Yu Hu (53:20)>:

It creates this whole new economy that's much more efficient than some of the old alternatives that existed in the market. And imagine that we bring this beyond...
Twitter and then you know this because we use the kind of the probe before you know that we already index a ton of other social media platforms and all that kind of stuff from a technology perspective We can do it that if we were able to do this first within crypto across TikTok so many projects want to be incentivizing yappers on TikTok to the  branch out we can do this on Instagram it's going to be relevant for a lot of the specific brands within crypto as well

<Jason Kam (53:39)>:

Yeah. Yeah.

Hmm.

<Jason Kam (53:52)>:

Mm-hmm.

<Yu Hu (54:01)>:

YouTube, all this kind of stuff. Telegram, Line, there's different kind of social media, stuff like that. And then ultimately bring this beyond crypto as well. Because if it works in a specific vertical, it should also work in other verticals. And imagine, imagine ultimately if we have...

<Jason Kam (54:04)>:

Yeah.

<Jason Kam (54:12)>:

Hmm.

<Jason Kam (54:20)>:

obviously.

<Yu Hu (54:26)>:

Basically, know information and data from every single social media platform where essentially we can also incentivize people to be linking their identities and all these kind of stuff because Today none of the type of forms can be talking to each other. I take those never going to be talking to Twitter They're never going to be sharing their any of the data together But if we as a third party platform can actually incentivize all the users to be linking their identities together Then we can be the best platform for any brands and marketing activities

<Yu Hu (54:56)>:

to be basically routing through us. And then we can control where it is kind of the most optimized distribution for all these economic activities to be happening.

<Jason Kam (55:09)>:

Yeah. I guess the question, there are two steps to it. One is sort of real world businesses through you, like paying influencers, showing them. And then the step before that is crypto entities paying through you to any user on any platform paying them. How soon would, you know, Bera be able to like, you know, pay TikTok influencers and Instagram?
And then secondly is, I'm guessing you already solved the sort of, you can already know what kind of video they post because the relevancy of that content is obviously relevant to kind of what they want. Yeah.

<Yu Hu (55:47)>:

Yep. Yeah. So, I mean, in terms of the crypto adoption in various different social media, that will be pretty soon. Because I can tell you it will be in Q3. Sorry, in Q2. So it will be this quarter. Yeah.

<Jason Kam (55:56)>:

How soon?

<Jason Kam (56:01)>:

OK. like imminent. Great. OK.

<Yu Hu (56:05)>:

Yeah, very, very imminent. Because at the end of the day, we already index majority of the platforms. Like, we already index YouTube, already index Telegram, index Discord, all this kind of stuff. But the next one we're going to be launching is going to be TikTok. So we're going to have like TikTok leaderboard, stuff like that. And then, if, even if today, for example, if I asked you,

<Yu Hu (56:31)>:

who's the biggest TikTok crypto influencer? Nobody can give any, nobody has any idea even. Nobody doesn't even, nobody knows where to even start. Which was the case.
before we launched all these  leaderboard, community leaderboard, all that kind of stuff. Because people have a rough idea in terms of the very top of the market, but then the long tail, people just have complete no idea. And that is where indexing the AI comes in. We can essentially create public leaderboard, evaluate people's influence, effectiveness, all that kind of stuff.

<Jason Kam (57:00)>:

Hmm.

<Jason Kam (57:13)>:

and obviously the sort of video and analysis that you will do through the AI would be able to, okay, that's cool. honestly, dude, like I think that's that along, if I'm not mistaken, just to summarize the capital launch pad and this effort that goes beyond just Twitter, earn, earn seems to be a really good feature at to the existing list of products. And then the mind share trading we'll see if it works. seems like it's early, but, those two that I mentioned seems to be the biggest revenue driver for you.

in like the next six months. Okay.

<Yu Hu (57:44)>:

I think the information as an asset, which is the market stuff, is going be a wildcat. If it works, then it's going to be very big because trading is going to be obviously a huge revenue dollar. But TBD, if that works. But effectively, even if you look at fantasy top, right?

<Yu Hu (58:08)>:

that's effectively trading influence. And there are people who are basically betting big on certain stuff.

<Yu Hu (58:16)>:

So, and I think that, know, memecoin trading is effectively kind of a, there's different kind of a mechanism that we can tap into it as well. Like even just for example, having a, I don't know whether we're going to do it, but like if we have like a different way of doing the initial distribution for the memecoin launch, stuff like that, there are lot of the potential possibilities there as well. Yeah.

<Jason Kam (58:37)>:

Can you go a few minutes over because there are some really important, OK, great. Of all of these efforts, including the sort of 10 million from Research AR and API plus 20 million from the existing sort of the platform, of all of these new efforts also as they funnel through revenue, which part of it goes to the token and which part of it goes to the equity?

<Yu Hu (59:01)>:

Yeah, so the way that we think about everything now is all holistic. So basically, to think about the whole revenue stuff that we're generating and then routing everything through token buyback.

<Jason Kam (59:15)>:

OK, and that's discretionary. You have done 14 million annualized so far.

<Yu Hu (59:20)>:

14 million annualized so far and recently we are salaried.

<Jason Kam (59:24)>:

Okay, any and it's purely discretionary, I'm guessing.

<Yu Hu (59:29)>:

Purely discretionary, but at the same time there is basically an ongoing commitment in terms of, we'll basically be doing this on a daily basis.

<Jason Kam (59:41)>:

OK, OK, good to know. And then what other token syncs are there aside from I can stake my Kaito?

<Yu Hu (59:50)>:

So the way we think about alignment and the network value distribution is in two forms. One is token buyback, which is effectively redistributing value to everyone who's holding Kaito token. The other part is through sort of drops. So the stuff that we talked about in terms of Kaito earn, in terms of Kaito Launchpad, all that kind of stuff is effectively creating additional values to the token holders, which no one is talking about today because obviously, having been launched, we haven't talked much about that. But effectively,

<Jason Kam (60:16)>:

Yep.

<Yu Hu (60:36)>:

you know, that's also going to come as well. So if I think about the return of holding Kaito token today, obviously one thing, there is a staking yield, which is roughly 16 % today. And the biggest difference of, I'll say this staking yield versus all the other, the majority of the other kind of staking programs in the market right now is a none of the team and investor tokens are able to participate, which is you know, none of the basically unvested tokens are able to, you know, basically put in there. And B is the entirety of the staking rewards are basically funded through the buyback program. So in a way that this is not inflationary, this is just disproportionately rewarding the stakers.
Jason Kam (01:00:28.443)
benefiting stakers
Yu Hu (01:00:31.486)
And so that's clearly sustainable. And if you look at the entire issuance of the token, the whole network is also in a net sink stage because...
Jason Kam (01:00:31.685)
I get that.
Yu Hu (01:00:44.238)
you know, currently we're obviously using a ton of revenue to be acquiring, you know, Kaito tokens in the open market. So people don't run into the issue of if I stay here, I get constantly diluted because the network is issuing 10 % inflation on an annual basis at the same time as all the other stuff going on. So it's actually additive in terms of the return. So you'd be thinking about if you're a state court, you'd be thinking about 16 % in terms of
Yu Hu (01:01:15.051)
in terms of the staking reward. Plus, at this rate, we're talking about 3 to 4 % of the entire, for example, token supply sink. And this is not just calculating the circulating. This is kind of the entire token supply in terms of the annual sink. But obviously, in terms of circulating, it will be a much bigger number.
Yu Hu (01:01:42.54)
And then that kind of should be added towards the return that people should be thinking about by holding Kaito, by staking Kaito. And then that comes to added benefit of any whatever drops and dividends that people were doing for the network.
Jason Kam (01:01:49.329)
Yeah, that's cool.
Jason Kam (01:01:59.567)
Yeah. And the relationship, I'm guessing, YAPS turns into tokens in the future. What about the NFT holders? Yeah.
Yu Hu (01:02:07.534)
Yaps has already turned into tokens, basically. Yaps effectively tokenize influence.
Jason Kam (01:02:11.695)
OK, so the yaps are just mindshare effectively.
Yu Hu (01:02:19.778)
in the network, you are able to directly monetize by signaling influence, like getting deals and having some sort of mechanism that we haven't announced in terms of getting direct benefits in the ecosystem. So it's almost like if you are a big influencer on
Yu Hu (01:02:42.414)
Facebook or TikTok or Instagram. This is just a better signal in terms of your follower and kind of influence. That won't be tradable because it shouldn't be. And it's just like Facebook did an airdrop to all the content creators in the early days.
Jason Kam (01:02:48.583)
I see.
Jason Kam (01:02:52.099)
I see that that will that won't be tradable that won't be tradable. Makes sense. Okay.
Jason Kam (01:03:05.807)
Makes sense. And then the NFTs, how does that tie to all the value creation?
Yu Hu (01:03:11.052)
So the way we think about the two assets, token is going to represent the ownership of the network. so over time, it will be decentralized. And then the NFT is basically a representation of the community.
So we want more people to be holding the NFT, which is the reason why...
we introduce a new mechanism where the NFT becomes a multiplier for whatever the benefits that you can get. So the ideal state is sKaito token holders, or Kaito token holders essentially want at least one Genesis NFT, and all the Yappers will also want at least one Genesis NFT, so that everyone essentially gets a multiplier in whatever the stuff that they do in the whole InfoFi network that we're building.
Jason Kam (01:04:08.669)
Got it. And then the marginal benefits of stacking decreases as the more end to you. Last question I have, I've taken plenty of your time. I guess we talked about all these growth efforts, right? Some of them are more exciting than the others. I wouldn't ask you for your guidance, of the 33 million annualized today, looking into year end 2025, is there a level of annualized revenue or annualized burn or whatever KPI you track would make you happy?
Yu Hu (01:04:37.772)
Yeah. I mean, so one thing that I've said publicly or I've done publicly is I basically acquired a million KAITO tokens in the open market and then put them on the self-imposed lock. And then within that lock, I put two milestones publicly. One is a 50 million target and the other one is a 100 million target. And I put those targets, annualized revenues target, yeah.
Jason Kam (01:05:03.279)
an annualized revenue target.
Yu Hu (01:05:07.246)
And so clearly we're thinking it is possible and it's achievable for the network to essentially get to 100 million. Otherwise I'm just burning my tokens effectively. that's kind of a, yeah. that's, you know, that's basically, I wouldn't put a kind of a time lock on that, but essentially that's what we're working towards. And I think that if we're successful on...
Jason Kam (01:05:19.995)
Yeah, it's benefit to all of us.
Yu Hu (01:05:35.246)
basically everything that we set out to do, it should be much bigger than a hundred million.
Jason Kam (01:05:41.749)
Very cool. Members, do you have any questions? Let's give you three seconds. Really appreciate your time, man. We haven't done it in English in the past, but this is fun. Thank you. OK. I'm sure everybody would appreciate it.