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Web3’s TEE stack - iExec, Oasis, Phala
Recorded: July 15, 2025 Duration: 0:47:51Space Recording
Short Summary
The discussion centers on the rising significance of Trusted Execution Environments (TEEs) in the Web3 landscape, driven by advancements in hardware and the increasing demand for privacy in AI applications. Key insights include the integration of TE technology into various projects, the growth of AI use cases, and the call for developers to leverage new tools like Raffle for deploying secure applications.
Full Transcription
Tick, tick. Hello all, just waiting for everyone else to join.
A couple more speakers and we'll get started. Thank you. Okay, Anthony, I've sent you an invite to become a speaker.
If you could just accept that.
Thanks. Okay, I think we'll get started. So hello, everyone. I'm happy to be back hosting another
Spaces. It's been a little while for me. So I'm Blair. I'm from the communication team at iExec and this session we're going to be talking on the topic of TEEs.
So before I introduce the names of our speakers I'll just give you a bit of context on what we're
going to be talking about today. We're going to keep it quite short I think around 30 minutes so
yeah the topic as I said is going to be trusted execution environments.
And we thought about just jumping on and doing this following the recent report published by
Misari Research. So for anyone that's not familiar with Misari, they're clearly
in the top, the kind of one of the top sources for Web3 data, analysis reports summaries on everything around this fast-moving
industry helping people kind of make the right choices in tech or investments so i'll introduce
that for now but as we are talking on the subject of tees we've invited some of our fellow industry members.
So I'll start with Oasis.
So we should have Mate, Head of Partnerships at Oasis, joining us.
I'll let you introduce yourselves just in one moment.
We have Marvin Tong, CEO and co-founder of FALA.
And from the iExec team, we have the Head of Research and all things privacy enhancing technologies we have, Anthony. So as I said, I'll just introduce it and then
I'll let you guys speak in just a moment. So I talked about the Masari report. It's kind of the first of its kind speaking about trusted execution environments, TEs, and this hardware encryption technology for confidential computing.
Zik, Oasis and Thala were here to kind of, they were chosen as the main use cases, the main
innovators in this field of TEs when it comes to Web3. So I've introduced a little bit about
the Luminati report. We can talk about the content in it.
I have a few questions noted down here.
So if maybe Oasis can start by introducing yourself, Mate, and yeah, a little bit about your role at Oasis.
So hello, Mate, if you can hear me.
Hi there. Yeah, Kibler if you can hear me. Hi there.
Yeah, Kedler, can you hear me?
Yeah, all good on my side.
Perfect. Yeah, and we have to be here.
As you said, yeah, Matej, head of partnerships
at Oasis. I've been with
the team for about three years,
more than three years now, which I guess
it's a lifetime
in crypto.
But yeah, TEs are basically at our forefront from the start.
We've been working with them since our first launch,
where it was Sparcel, and then we moved to the EVN-compatible layer,
and then deploying the EVN-compatible confidential runtime called Sapphire,
which utilizes TE technology to achieve on-chain encryption, on-chain privacy.
And now with our latest stack, the Brothel framework, the runtime option logic,
where we're bringing verifiability to off-chain compute, utilizing TEs as well.
So yeah, this is kind of our forte on the beginning.
And we love to see how TEs are moving more and more
into the mainstream.
I think with the advent of AI and all of that,
it's really bringing everything closer to TEs
and everybody's seeing the benefits of them.
Yeah, so for anyone that hasn't actually
been aware of what trusted Acution environments are or TEs, so they're a
hardware based encryption. We have a lot of different types of
encryption when it comes to privacy preserving technologies and TEs are
really hardware based and to sum them up in one
line they are secure parts of the cpu um or at least in cpu based hardware encryption um where
it's a completely isolated part of the machine um that can run in complete privacy computation on sensitive data and code.
So, yeah, I'll continue on with our guests.
Marvin, are you there from Fala to give a couple of lines on context on Fala and TEs?
And I'll jump into the questions. Thanks.
Yeah, sure.
Hi guys, Jam Jam.
This is Marvin from Phala Network.
I mean, like same here as Oasis and AdSec,
we've been building confidential compute
for a lot of years.
We started from 2019 and this is my sixth year in our fall.
And our, I mean like, yeah, I totally agree.
It's just a T is more like a security hardware based solution
for generic programming and coding and hosting
between sensitive business logic and sensitive data. And
it's not originally, you know, this technology is now
beautiful, scaling web three, you know, basically all of the
cheap manufacturing companies have their own trusted execution system like Intel, SGS, Intel, TDX, AMD, SEV.
Apple has their own CC and NVIDIA Confidential Compute.
Even ARM have trusted zone. So it's already been widely used in many traditional
development business years ago, like guys like us, right?
Like an off-court Oasis and exec realized we can utilize
these. not sure what happened there um can you still hear me guys
sorry i'm having you oh yeah yeah yeah i can hear you uh so uh when i was was kind of like...
Hello?
Yeah, all good. We can hear you.
Okay.
So, did I miss the whole part of the introduction?
No, no, it was all good.
It was all good.
I can maybe move on and answer.
Oh, sure, sure, sure.
I have a few more questions.
But that was super interesting what you're saying about many different types of confidential computing.
And we're really obviously going to be speaking specifically of trusted execution environments here.
And maybe I gave an opportunity for Anthony to speak for iExec.
So TEs, we've been talking about trusted execution environments, hardware encryption, protecting data in use for quite a while.
But it really seems we've been picked up and noticed by Missari recently that they're kind of becoming a bit more mainstream in Web3.
Anthony, what do you think is maybe different today?
What is making this kind of hardware encryption tease starting to get picked up now?
Is it an accessibility thing?
Or, yeah, interesting to your thoughts there, Anthony.
It's a mix of different things.
One thing is that the hardware has become better.
So we have now Intel TDX, which is a huge improvement compared to Intel SGX.
Intel SGX before that even got its own improvements.
So only like five or six years ago, you know, you had a T enclave that were just a few hundred
megabytes large, and you couldn't do actual competition there and right now you get
enclaves that can be several hundred of gigabytes large and that are a lot more easier to program
and at the same time we see that technologies like the ones we bring here and others actually
even lower the barrier of entry for developers so i iExec, for example, develops SDKs and tools
that make it very accessible for any developer
to port application to these enclaves when,
I mean, even if they don't know how this cryptography
or the tools work, when six years ago,
you would have had to have a PhD
in computer science and or cryptography
to actually just start using them.
So I think that's the reason why this is all
breaking barriers into a tree.
Okay, yeah, that's super interesting, actually,
just seeing how far they've kind of come
because before it was super idealistic.
We talked about, okay, yeah, we've always had data.
We've always had the types of encryption.
We can always encrypt data in storage.
We can also encrypt data in transit, but never in processing.
So when TEs came around, it was super exciting.
But what you're saying is basically it was more idealistic
because of the capacity or the throughput just wasn't really there,
and we have that now.
And, yeah, an interesting point on accessibility.
Maybe, Matej, from Oasis, you can kind of talk a bit more
about the TE tech and how it's matured into production-ready tools.
We've seen that you've released Sapphire and things like that.
Maybe what's your two cents on it, Mate?
Yeah, I think Anthony said it well, right?
Just the accessibility to everything is now being fairly commoditized
if we're looking at the solutions that we're making,
you guys as well.
It's enabling developers to utilize these without much of a difference
from utilizing any other GCP or AWS cloud to deploy their own stuff.
And obviously, it has a lot of benefits over deploying computing
your normal cloud instances.
You have the verifiability of the execution, you have the confidentiality from the vendors,
so you don't have to worry too much who's running your machines.
And I think the crypto ethos is always on trust verify, right? So when doing off-chain compute,
I think we shouldn't forget about that.
And when AI came into play,
obviously you're not able to run all the use cases
that AI can provide on-chain, right?
Just the compute limitations of blockchains,
but we shouldn't forget that we should strive
towards similar trustlessness
when we're moving things off-chain.
So that's why Sapphire was the first iteration when we have on-chain privacy and on-chain
confidential compute.
And that launched, I think, back in 2023, I think.
So yeah, it's been running Mainnet now for more than two years has been going well and you
have a lot of benefits right from on-chain privacy as well you can now have native RNG you can store
you know keys wallet keys we have some solutions you know where they create wallets that you connect
to pass keys and the private keys are stored on-chain or encryption keys for files that are stored in different cloud solutions.
But yeah, with AI coming now to the forefront, we saw that the extension, the option extension
is really needed. So Raffle here is now the framework that we're focusing the most,
where we're not really the compute provider.
Compute provider can be anybody,
but it's the middle layer that enables developers
to easily deploy their apps in TEs
without any complexity of how to obtain the hardware,
how to deploy all of that.
And combining it with Sapphire, you also get a few nice things out of the box,
like RNG, Key Manager, that you have natively integrated with the Raffle Framework.
So, yeah, I think it's just the accessibility that all of our solutions are enabling for the developers to
not shy away from TEs but go head on you know towards using them. Yeah I agree, I completely
agree for you mentioned the really the importance and the evidence of really off-chain compute being a major thing that we need.
And that really needs this element of trust.
And it was the same with iExec.
In fact, when we first launched iExec,
we were very, very focused on the distributed decentralized computation.
But it was very obvious from very early that,
okay, once we're running things on remote distributed, maybe unknown or
untrusted machines, we really need that extra level of encryption of protection. And as you
were saying, with AI now being such a huge thing and having to talk about this kind of
compute, which happens elsewhere, it's really becoming, yeah, yeah as i said maybe obvious that we need
an extra layer of encryption when we're putting all this information into ai and it's being
run and processed somewhere else um so yeah super super interesting completely agree on that
and i'll pass them the mic over to to marvin um maybe you could talk a little bit more about the scale of things.
So I've seen in a lot of Fala's communications really talking about how many TE devices you've got globally and a huge focus on GPU now with obviously the need for that, for LLM's AI.
Yeah, can you speak a little bit about the scale side of TEs
and how that's advanced in the past years?
Yeah, sure.
Yeah, like a couple of years ago, right?
Like the initial problem we see for TE adoption is,
the first thing is developer friendly.
Because SGX is not built starting to virtual machine based business.
So it means like if developer want to build applications inside TE,
they have to find something like a Grameen, a very developer-friendly environment or OS,
to pivot their original program inside TE environment.
That's the first bottleneck.
The second thing is uh hardware accessibility so
uh of course like uh it's easy to acquire and operate you know uh uh your own server
but like based on the cloud's native technology trending,
it's against what developers are very familiar with.
If you're using TEE,
it's not so easy to run to security hardware,
pick up the right configurations,
set up the right configurations, set up the right environment,
and insert everything you need.
And then you can begin to work on it.
But the bigger problem is not single TE server,
it's about scalability.
So for example, like a manager over use that cloud flare
or cloud native services.
It means that like you only need to be focused on coding
and you leave the operation jobs,
the hard part to cloud infrastructures.
So, and when we are standing into security hardware-based
cloud operation, it's another story.
Many cloud do provide these services,
but there's still a lot of details and things are missing.
That's why our main focus is to solve problem A and B,
which is A, how people can easily set up their program
inside a virtual machine-based,
we call it a confidential VM, right?
Like a container so that they can basically, you know,
a container so that they can basically pivot
or move their original programs inside TE.
And B, when developers successfully run their demo,
how they can scale, right?
Like how does Kubernetes works?
How does load balance works?
How does database works inside TE.
So you want to tangle these very specific issues to make sure if they onboard, they can scale for
serious business. Because what we learned from 2022 to 2024 is,
I think many people have the impression that,
yeah, we can use TE, but it's kind of hard.
So if we want to push them into security cloud,
security hardware instead of GCP or AWS,
we have to provide similar experience level service to, you know, just to make things easier.
And, you know, so, yeah, so the focus of FALA
is on these two major points,
like make things easy and make scalability easy.
So we are still doing that.
We haven't reached, you know, like one risk scores yet.
So a lot of things need to be there.
Awesome.
Yeah, well, it does sound like it's kind of always been an interesting tech.
TEs have always been very inspiring, especially to me.
But it sounds like there's always been these barriers to entries or these scaling issues, which between us, we're kind of all tackling.
So that's really good news. Thanks, guys.
guys i think i'm going to um shift the focus maybe zoom out on the context of te's and talk
about other pet's or privacy enhancing technology um because as we said uh tees are very much
hardware-based encryption but when we talk about pet's um or privacy technologies in general we might think of zks um even fhe homomorphic encryption
mpc um i'm wondering if we can maybe talk about the the differences or maybe the combination of
these other types of privacy that's technology zks or other um so maybe i'll start with you oasis then i'll go to anthony from
i exec and then fala um oasis we've seen uh ruffle and sapphire the kind of blend
tea with zk's can you talk um briefly on that from the oasis side
yeah for sure i mean from our side, we don't utilize ZKs.
I mean, if we look at ZK and ZK proofs,
these provide those remote attestations that can kind of mirror the proof without disclosed model, right?
But yeah, some people are saying ZKs are the only way because it's cryptography. Of course, we're relying to an extent to the vendor lock-in
and vendors not being malicious.
I think we need to be pragmatic here when it comes to utility versus ideology.
I don't think ZKs right now are ready for all the applications that we kind of envision
if we want to run uh fhe similarly but uh if i stay more on the zk side you know uh the the thing
is that zk and te are not really exclusive right there they can be used uh simultaneously right so
different things require different level of security, right?
So you could utilize, you know, ZK proofs for certain stuff,
you know, within a TE and then TE for less sensitive parts
of your application or your project, right?
So it's not like it's one or the other, you know,
but it just depends on your security needs
and what needs harder security through cryptography
and what is enough if you compromise,
let's say, on the vendor side of things.
So I would say a hybrid here, it's probably...
Yeah, sorry.
I think a hybrid here is probably the best solution, right?
Because, I mean, we spoke with a lot of ZK people,
and they moved to TEs because they want to build
encrypted or confidential compute stuff now,
not in five years
right uh and zk did you know uh go a lot further uh obviously with with the research that's being
done due to you know the applications in in crypto but still i would say for let's say the things that
we need in ai and i was going back to AI because I see it as a big meta,
right, in crypto now as well.
ZK probably is not there yet.
And, you know, having hybrid where TEs can do the majority
of the heavy lifting and you can use ZK for some very sensitive stuff
is probably the best approach, not trying to do just one or the other yeah that's really
interesting what you say about the kind of the zk crew or developers uh looking over to te's and
um yeah you said zk is very much uh about cryptography so it's much more kind of crypto
native in that way so maybe it was why a little bit it was a
little bit slower on the uptake the uh off-chain compute and hardware encryption like tees um
oh for sure interesting um anthony if you're there could you maybe talk about um what's your
two cents on these uh synergies of tees plus zk i i agree with everything that Matthias said.
I do agree that we need to find hybrid approaches.
There are certain spaces where TEs can accelerate
ZK proofs and also probably accelerate FHE.
The other end, I mean, the other way around is true too.
There are places in TEs where, you know, we need some bit of Ziki Proofs or MPC or FHC to protect against some, you know,
side channel attacks or some, you know, things like backdoors that could maybe possibly still be there.
And because in W3, we need to be extra paranoid compared to the rest of the world.
we need to be extra extra paranoid compared to the rest of the world so um yeah i think the
the end message is uh you should not trust one technology uh entirely right
exactly um and that's the good thing about web3 it's kind of the interoperability between
everything many teams are doing things very well and combined when we define that interoperability between everything. Many teams are doing things very well and combined when we
do find that interoperability, that's when we can go the furthest, I think. So talking about TEs
specifically in certain use cases, mainly just because it's something that excites me a lot is of course AI
confidential agents privacy preserving logic within AI maybe you can have a
quick roundtable of where we see T is playing the most important role in this kind of AI that is now part of every minute of our lives now, it feels like.
So maybe I exec, Anthony, while you're still on the mic to talk about agent approach to the use of confidential computing TEs in AI agent logic.
And then potentially I execs use throughout the whole AI pipeline,
even if it's not directly agents.
Yeah, the thing is, so I don't know if everyone is comfortable with what an AI agent is.
Personally, I'm not.
I still think that this is a domain that is being defined every day.
And in three or five years, we'll reflect and realize that what agents are today are not really what this will be tomorrow. From what I understand right now, an agent is something that kind of thinks and acts by himself or in autonomy.
And what I derive from that is,
okay, so now these AIs, they're not just answering questions,
they're making decisions.
They're making decisions on my behalf.
They might be making decisions on, you know,
how to open my windows or my shades,
how to drive my car, how to invest my money, how to manage the security of my system.
And because there are a ton of us in that and because they can act on my behalf or on the
behalf of someone even more powerful than me, they should be accountable. We should know why they act the way they act.
And there should be some gatekeeping.
So there should be limits about what they can do or they cannot do.
And T's are very good for that.
So if I give my passwords or my private key to an agent,
I want to make sure that my private key is safe with them.
So I don't want anyone to be able to go look into the file
system and take that key.
But also, I want my AI to be, let's say,
like kept in track so it cannot be corrupted,
cannot be convinced to do things that I don't want it to do.
So every gatekeeping mechanism that I've been in place, I want to make sure that they remain in place.
And also, TEAs are very good for that.
So that's where I see the application of TEAs for agent.
You probably want to put your agent, its memory, its logic, but also its data in a very close container isolated from
the rest of the world and where anyone can lurk into, you know, act.
Yeah, that's a super interesting point, really.
More than just data privacy, you're really talking about the governance and the verifiability
of AI and what TE is very good for.
You mentioned the opening, it might be responsible for opening our windows. Well, yeah, we want to
make sure that it's doing that at the right time for the right logic and TE is good for that
verifiability and sureness, let's say, of the decision making. Super interesting. For me, I've always used the example
from a pure privacy approach.
And it might be a bit simplified,
but we talk about AI agents
and someone used the example of,
well, what if we had an agent
that was essentially our therapist
where we tell our deepest, darkest secrets to,
we want to ensure that this data is not going to be leaked and that's super easy to understand example but I really like yeah what
you said about the verifiability of like why it's making the decisions it's doing just beyond the
the encrypted data that's being processed.
Super interesting.
Thanks, Anthony.
So Marvin from Fala, maybe could you talk on the subject of AI? Of course, AI needs a lot of heavy computing power, specifically GPUs.
We know TEs, there was a lot of research and focus on CPUs at first.
Where are we going with GPU-orientated trusted execution environments?
Maybe you can talk a little bit about that.
Sure, like, 80% of our use cases are coming from AI today.
Most of them are developers who are trying to build
a verifiable agent or autonomous agent,
which means the agent can execute jobs without further instructions.
They can run by themselves.
And private agents for consumer and enterprise.
So I would say in an agent perspective,
like verifiability,
auditable use cases
and private focus use cases are definitely the best practice for TEs.
For the use case beyond agent, you know, it's more about data collection like VANA.
There are several other projects using TEs to encrypt the data they collect for further usage of AI models and co-training. Third Peak, they use GPU TE to make sure private model can be used in private enterprise when it comes to sensitive integration.
And of course, inferences.
If you check out, if you're using OpenDotter Like it's an aggregator of many model
based on different inference providers,
and it's a very popular one.
So what we are doing there is that
we provide zero trust inferences,
which means we won't collect the prompt data
from the inference endpoint user.
And so, yeah, I would say in inference and, you know,
modal inference and the GPU TEs will be utilized based on privacy.
And for, you know, modal co-training and fine-tuning
is aimed to make sure both model provider party and
the usage party keep in a secret by themselves.
But in the meanwhile, they can work together.
Based on these use cases,
I think that he's already been widely used,
widely adopted in AI space.
And the special topics I want to mention here is the use case.
Like traditionally, we thought like traditional enterprise business,
like healthcare, financial trading
is the first practice
special use cases.
But in the real world,
I think even generic SaaS solutions are trying to
onboard more private enterprise in the AI integration pipeline
and privacy already seems like the bottleneck of onboarding more users. So yeah, I would say
yeah, just that TE can play a big part of it. Yeah, that's something at iExec we are super excited about.
It's TEs, not just for the end user, but throughout the whole kind of AI pipeline, if we can call it that,
from training inference to the protection of the end user's data that they're feeding into it.
Yeah, super, super interesting.
Lots of potential there.
Matej, maybe I'll invite you to speak on specifically T's in AI.
A couple of months ago, I was following the WT3 AI agent use case example.
Anything, any notes you want to put in that for specific use cases
yeah uh definitely so from our side we're very bullish on you know like two verticals uh
for crypto and t applications so that's ai and defy right and i think trading agents kind of
um yeah combine the two perfectly right so you So you have people, you know, always want to, you know,
I think the initial incentive for a lot of people coming to crypto
is, you know, trying to make money.
And I think the evolution of, you know, trading crypto
is different to, you know, what we have in Threadfy.
And automation, you know, is something that a lot of people also would like to have,
but maybe they don't have knowledge or resources.
So we can try to commoditize a little bit this part of the stack as well.
Crypto is moving really fast,
so agents will probably be taking over the majority
of trading here and this is our way of you know going into showing what our tech can do um you
know and enable users enable users to see how easily it is to deploy an agent that can be
autonomous that can be verifiable i mean on the making money side you know the strategies are
always tricky people you know that the strategies are always tricky.
People, you know, that have profitable strategies, usually they don't want to share them.
So the strategy part is something that each individual usually needs to come to its own, come to, yeah, by himself. But the good thing is, you know, that through TEs and privacy,
by himself. But the good thing is
that through TEs and privacy
you can also have
strategy being private as it is
with WT3 but at the same
time have it verifiable
about the results of the strategy and then
people can join
in and participate with
the agent
dedicate funds to it. The agent
gets
some sort of profit share from trading the stack.
So there's a lot of different use cases and applications.
People can run their own or you can join some agents trading.
The problem is that I saw just real quick, in the past,
I think there was quite a lot of hype last year
when we had some Telegram bots that you could kind of trade off or they
could even trade on your behalf but there was no verifiability there so you you couldn't really
see what's happening you know if the developer can bug you or not here you know the the integrate key
manager uh that raffle enables know, you can really make sure
that the wallet was spawned inside the agent, right?
So nobody else has access to admin controls.
You can see who can make changes to the enclave.
So, you know, just bringing that verifiability
to the agency site and WT3 is kind of the first good example
of how that can be achieved.
Yeah, thanks for that, Matei. It's interesting throughout this whole conversation, we've talked
a little bit about the problems we've resolved. So accessibility tools there, you no longer need
a computer science PhD to integrate these TEs into applications. Matei, you kind of identified
another problem. Well, sometimes the monetization strategy is not evident. Mate, you kind of identified another problem.
Well, sometimes the monetization strategy is not evident.
Okay, you have the tech, but how are you going to use it?
And the need for governance.
So we're coming to the end of the hour.
So maybe just invite you all to put some closing thoughts,
a bit of a challenging one.
What do you see is next for Tease in Web3?
Maybe we've already discussed it going on,
but what do you think is still missing?
What's next?
And yeah, specifically maybe for your projects,
what do you invite the listeners to go and check out
either for your projects if they want to test
as a developer or as an end user
and discover the
discover like the benefits of TEs. So Anthony, very quickly, what do you think is next for TEs
in Web3? What's missing and what can people do today if they want to go to TE?
What's missing? Nothing. I think everything is there and I invite people to try the tooling and the house tooling,
obviously.
I have generator.
What's next?
I don't know.
More real life applications.
I think the groundwork is here.
Now it's up to me.
Yeah.
But we're confident.
Yeah.
We're confident.
We've all spoken about our ready-to-use tools.
iExec obviously has the iApp generator,
deploying TEs into an app with a few clicks.
Any developer can do it.
Yeah, so we're pretty confident for the future in general.
More use cases to come.
Stay tuned.
Okay, Marvin, any closing thoughts?
Yeah, like I think we are in the middle of a stage that if AI will become AGI, right, I think there's only 20% of the progression left.
And it will be adopted in many business.
So bottom neck for them to using AI is to
dealing with the compliance problem and data problem.
So build trustless AI or trustworthy AI is
a must have path to go there.
And based on that, I think TE is essentially the infrastructure for that.
And another thing is that TE will be merged very well.
Obviously, the other cryptographic solutions,
which also include, you know, ZK, you guys talked about,
and PC, and probably FHC, but I don't know.
But definitely a lot of blockchain legacy design.
So there's a training that TDT will be the container
to run together with the other cryptographic solutions.
And yeah, but there's still a lot of work
haven't been done yet.
So I think work together in some open-sourced project
is a will massively huff on that.
Yeah, so yeah, that's my next forecast. project will massively help on that. Yeah.
So, yeah, that's my next forecast.
Yeah.
Interesting.
Yeah.
That's super interesting.
So, I mean, I completely agree for AI.
TE is there and it should be, I'm confident it can be the standard for AI.
I think we're all agreeing on that.
And yeah, interesting, your last point,
actually, what's next for open source and things like that. Okay, Matej, I think you already gave
quite a nice summary at the end, but anything else you would like to add or anything you'd
like to point the listeners to next? Yeah, I mean, I'll echo Anthony. We just need to see what's next.
We need to see more apps actually utilizing the tech.
We're also going to be looking towards developing more high-level services
that utilize CEs to enable software transition towards that.
And listeners can go to raffle.app,
and they can try out to deploy their own app in a TE we have
a few templates ready if they don't know what to build themselves if they do have
an idea they can go through through that as well and you can easily monitor your
apps your machines there so yeah go check it out and let's see more tea apps yes
awesome thank you Mate well um thank you, Matej from Oasis, Fala and iExec, of course.
If you want to find out a little bit more about what TEs are, how they are being used in blockchain protocols,
in blockchain protocols, how iExec, Oasis and Fallon Network are kind of leading the way
for Web3 XT powered infrastructure for confidential computing, verifiable privacy at scale.
Highly encourage you to look into the Mursari report. It's called TE, the hardware backbone
for next gen on-chain experience.
Super nice deep dive.
I think you can even listen to it
as audio transcription
if you choose to.
But yeah, really nice deep dive
on our three projects
and the kind of importance
for this type of privacy preserving tech
hardware encryption within Web3.
And I'm sure that will inspire you.
Other than that, you know where to go for Fala, Oasis, and I exec.
Check out our Discords.
And, yeah, we've all got very accessible tools to get hands-on to this tech
that wasn't so accessible a few years ago.
Yeah, very confident. Check out the Musari report. And, yeah, thank you. Yeah, very confident.
Check out the Musari report.
And yeah, thank you everyone for listening.
Thank you again, Mate, Marvin and Anthony for joining.
Thank you for hosting.
Yep, I wish you all an excellent week
and a privacy preserved life.
Okay, thanks everyone.
You too. Bye bye. Thanks guys. Thank you guys. Bye bye. life okay thanks everyone thank you Thank you.
Host
Oasis
from
Oasis Network
