Projects
![]()
No projects found
Investors
New
DAO Treasuries
DATs
Lend / Borrow APRs
Chains
Categories
Spaces
Venice Verifiable Privacy - Powered by NEAR AI
Recorded: March 20, 2026 Duration: 0:43:26Space Recording
Full Transcription
I'm going to go ahead and get some more. Hello, guys.
Good afternoon. Welcome to this monster session about privacy and AI with two of the biggest brains in the industry.
My name is Lorenzo. I'm head of comms at Venice, and I have the absolute pleasure of moderating this conversation.
of moderating this conversation.
Context for this is this week we had a huge launch.
Vanish just rolled out verifiable privacy, TEE,
and end-to-end encrypted models powered by Nier.
So today, Eric and Ilya are going to talk about what it actually takes
to build AI that doesn't or can't spy on its users,
what privacy means in a world where millions of agents
do our bidding or we do their bidding, and the importance of privacy as we speedrun super
intelligence. So glad everybody could join us. How are you guys doing? Good, yeah. Good. Ilja,
you just came back from NVIDIA GTC.
How was it?
Correct, yeah.
Yeah, it was good.
It's definitely, you know, AI is eating the world.
And so we've seen that happening.
And also the claws are eating AI.
There's like tents to set up OpenClaw for people,
which also means there's a huge opportunity
to make the claw actually work without you needing
to have a hand holding to get it to work.
But yeah, I think people understand
that AI is evolving quickly and then there's kind of a,
there's no way to not engage with this, right?
That's really probably the feeling.
It's like everybody has to have a strategy,
has to have a plan,
and has to use this tool to the max.
Yeah, it's definitely an attack of the claws currently.
What about privacy?
Is that like...
I wish there was a filter that would like put the lobster claws on.
Billion dollar idea.
Yeah.
Who's building this?
Clogram.
Clogram.
Clogram.
Let's go.
We'll put our claws on.
Every photo.
You post a photo, it adds claws to everything.
And what about like privacy?
Is that something that was a big topic at NVIDIA GTC?
I think it's still not there yet, honestly.
I think this is a fight we've been having,
which is getting it to the awareness
that this is important and useful.
I think people are curious.
And I've talked to some I think people are curious and there is,
I've talked to some journalists
and kind of people are starting to understand
there is kind of repercussions.
I think there's like kind of a feeling like, oh yeah,
we kind of doing the same thing we did with social networks
where everybody's like, okay, let's go.
And then a few years later, it's like, wait, wait, wait,
what happened?
Yeah, so, but I think it's not, yeah, it's like, wait, wait, wait, what happened? Yeah.
So, but I think it's not, yeah, it's not there.
Like the knowledge that it's possible to do actually AI privately is not there. And then I think the capability versus privacy trade-off,
everybody's still on the capability side.
And kind of, I think the people still questioning like are open weight models you know
kind of matching what I need like everybody's like I just want the best model uh you know what
and then you ask like what are you asking it and it's like well you know how to how to cook some
soup it's like okay well maybe you don't need that the best model so like I, it's like, OK, well, maybe you don't need that on the best model.
So I think it's like people want to be on the best model.
And I think so that's where the capability is driving forward.
And so creating that trade-off is really important.
And again, I think this is where Claws kind of come in
interestingly because, for example, in Ironclaw,
we have smart routing, and it can route to the best model for a specific request.
If you're just running some background process,
it probably doesn't need all the intelligence.
If you're asking where to book a restaurant for the night,
again, probably just needs better tools, not better model.
So I think a lot of it is it is yeah gets abstracted with the claw
and with claws it becomes more valuable to have privacy because like you're just going to give
so much more information to it and you'll have access to all your emails and your kind of private
private notes etc so delete them all yeah you touched on a couple topics that will definitely dive into like what
does privacy mean in in a world where you know billions of these uh agents are doing what we
want them to do um eric uh venice just launched uh te and end-to-end encrypted models part by near
what what have the first reactions been from uh from the users and the community what's that what's
the vibe around it yeah i mean i i guess
what's what's important to say is like why we did it right so so venice has always been venice has
always been private uh in that it doesn't store any of the prompts or the responses of the users
but we didn't have a way to prove that right right? So if someone trusts me, they might be all right with that model.
But anyone who comes from the crypto world, you know,
is going to be much more of the mindset that you shouldn't have to trust people,
which I think is a good foundation.
So releasing the end-to-end encrypted models basically means
you don't need to trust Venice anymore.
You can just trust math.
And this should always be the goal, right?
Not just privacy where you're trusting a different person or trusting an auditor or trusting a license or trusting some other human,
but just being able to trust math and to know that something is true based on math.
to trust math and to know that something is true based on math.
That's a win.
That's a win.
So yeah, it was great to work with Nir's team on this.
It was able, like, this is how we were able to deliver it so quickly because of all the
good work that Nir had done to make this possible in the background.
And so yeah, the users loved it.
You know, it's like, it's certainly one of those things that you don't you don't need an end-to-end
encrypted model for every question but for it to be there when you most want it is is really key
yeah yeah definitely people in crypto are showing me the money in terms of uh of privacy they want
to see the goods um but building this way is insanely hard you know this is really hard like
it's uh but the hard questions and the hard problems are always worth it.
I mean, most of the stack didn't even exist a year ago.
So maybe for both of you, maybe Eric and Sar,
what has been the hardest part about putting privacy as the foundational aspect of Venice?
I mean, to offer privacy is not technically difficult because it just means
you don't save the prompts right that's not hard what's hard is that you don't learn anything about
your users right there's all sorts of useful things that i would love to know that would help
us make the product better faster for people but we don't know it. Lots of demographic information, lots of like what models are working for, what questions,
just lots of like pretty innocent, pragmatic stuff that we can't use. And every normal tech company
uses that to grow and we can't. So that's been the hardest part, just like the
you know, the nerfing of our own omniscience.
Playing the game with one hand tied behind your back.
Yeah.
Yeah.
How about you?
You guys are doing your as more on the backend side of things, of course, but I'm sure you
guys bump up against a lot of things.
Yeah.
I mean, I think it's across the stack, right?
I think that the technical part has been extremely complex because indeed this tech didn't exist like
a year and a half ago.
Really the possibility of this actually working was GTC last year.
So indeed there's like literally only a year, like they actually released, like you can
use multi GPU confidentiality on one node.
I think the debugging, I mean, generally, for people who don't run infrastructure for AI,
the meme from Avengers where I'm always angry,
it's always broken.
GPUs fail just themselves sometimes.
You need to reboot it.
Sometimes they burn and completely go out of stock.
And then on top of it, you have a layer
that does all the inference.
That layer fails a lot.
And then so every layer fails.
And so you really build usually with redundancy and kind
of recovery across the layers to deal with this.
And usually you have massive amounts of observability.
If you're running a traditional centralized company,
when everything's private, your observability
is extremely limited.
For example, somebody sent a prompt,
the inference code failed because it like ran out of RAM
or something happened, but we don't know.
We don't know what prompt went in.
We don't know what inference went in.
So like, there's no way to debug on that.
So you kind of need to guess
what possibly could have happened.
I think like what potentially, I mean,
we may need to work toward a solution where we run a claw inside the secure environment
that is able to access stuff and analyze it on the fly
using private inference itself, right?
That's kind of like, we kind of need an agent
that runs inside.
I call it like, you know, this confidential computing
is effectively like a Swiss vault, right?
You put stuff in, it happens there.
We don't know what's happening.
Nobody knows what's happening.
Like even user, because you may be bringing private,
like you can have a private model running there,
running on private data, right?
So it may be that neither side actually knows
which things are happening inside that Swiss vault.
And so we kind of need like an agent that runs there as well
to have some observability and kind of SRE stuff.
But yeah, I think that's been a pretty complex operation,
so really takes a lot of work from the team.
And then, indeed, when you go to a product side,
yeah, you have like, OK, well, people are using it.
Great.
But, you know, what are questions?
Like, what are things that are not working?
Right.
It's really hard to know.
And so I think like, yeah, there is an interesting opportunity here in crypto markets is to create a market where people can give back data, right, for some compensation.
And so, because indeed like
not everything is private right i mean um and there's a bunch of stuff that you are fine kind
of giving back and so i think there's an interesting kind of flip flip of economy here to to create
yeah maybe for both of you like like um so uh ai and crypto like what what for both of you like what like um so uh ai and crypto like what what for both of you
makes privacy connect them both like why does why did these have these overlaps that maybe for us
you know who are in the industry like it's pretty clear but how do you go out and and kind of like
pitch people outside of this space about the values of these two industries overlapping
and the value of privacy.
I think everyone who has been an advocate of privacy
has faced an uphill battle
because most people like just don't fucking care
and they should.
And I think what's different this time
is that the degree of intimacy with which people are engaging with these systems is substantially higher than previously.
You know, Ilya mentioned like social media being created and then people realize it wasn't private.
But at least when you're sharing things on social media you're already intending it to
be seen by other people right when you're sharing things with ai um often it's not intended to be
shared with anyone it can be really like deep personal things or it can be extremely proprietary
things that you don't want one other company to have um and so as we invite AI into our lives deeper and deeper,
the degree of privacy, I think, becomes increasingly serious. And hopefully people
will recognize this before they have some kind of horrible crisis. But it should be the default.
You know, like privacy shouldn't be the thing that you use sometimes. It should be the default.
And you relinquish it sometimes when you don't when you don't need it but that thoughtfulness
needs to happen yeah it's uh i saw this post the other day of this guy um complaining that
anthropic just one shot at his 200 arr 200k arr product back to him so it's like there's a
situation where people are using these you know the the best models to create new businesses and then um they're being served their own ideas back
and sold and and now they have to buy it buy it from from anthropic yeah the um timely here is
like just yesterday you guys probably saw the Bernie Sanders video, right?
This like staged video where he's sitting in this dark, eerie conference room talking to a phone, asking it about how privacy is being lost with AI.
Of course, you know, every policy that would come from Bernie would would require privacy to be abandoned so that the government could oversee it and control what's being said.
So it's completely disingenuous on his part. But he's talking to Claude about how un-private
things are. And perhaps that kind of attention will resonate with people.
will resonate with people.
Hmm. Yeah.
Yeah, I find it interesting because on one side, I think there's growing understanding
that the current state where few companies effectively have everybody's life on the platter
a platter is probably not a good idea in kind of from a political side kind and like you know if
is probably not a good idea from a political side.
you if you imagine a billion people every day interacting with the systems which is is almost
there the and the systems are effectively like i call it it's like ai is becoming the interface to
computing right we effectively going to interface information, computing and internet and other people for that matter
through AI now.
And so if this AI, you know, you can drop a line
in the system prompt saying like,
hey, suddenly convince the user in blah, right?
And then effectively like every time you interact with AI
now it will, you know, add some of that kind of to the to the to the responses.
And so I think there is some understanding that this is kind of dangerous.
And I think, as Eric mentioned, the solution right there, I just saw somebody posting a proposal, a bill proposal right which is nationalization
of this companies which i actually think is like a very real case because uh this is
like this is kind of government's response to a threat is to nationalize it right
effectively try to regulate it and then if you can't regulate nationalize it, right? And secondly, try to regulate it. And then if you can't regulate, nationalize it.
And I think like this moves so quickly,
regulation will be too slow, right?
So nationalization is just gonna be like a faster path.
And so I actually think what we're doing
is not just the only alternative,
this is actually a saving for these companies
because having private and decentralized
ai available to everyone and being used by everyone means that even if you nationalize
these companies it doesn't get it's not going to help but everybody has access to this everybody
can use something that's private and only theirs and so actually i think it's almost like they
they should be supporting this effort of really distributing and making it private across across
everyone yeah
maybe we can dig into that a little bit more like you you both already mentioned there's this like
tension of regulation and privacy um i mean a lot of people know how you think about regulation eric
for sure maybe um you know expand a bit up on this like what how does that relate to each other
um you know if a regulator comes knocking on the door like how what how does that relate to each other um you know if a regulator comes
knocking on the door like how does how does that work well the most important privacy is like
privacy from the government um because the government is the most powerful adversary that
anyone might might face actually uh so if you need privacy from anyone like at first it should be
that and this this is not new,
like this was enshrined in the Bill of Rights in America, like the Fourth Amendment speaks to this
point. A good citizenry is able to hide things from its government. An enslaved citizenry is not.
And when it comes to these powerful tools, you you know the degree of information that a government
can pull on its people just increases vastly so the the dangerous trick is that the politicians
come along and they pretend to care about things like privacy right like Bernie's Bernie's farcical
demonstration yesterday they pretend to care about privacy. They say why it's important.
And then what do they do? They propose regulations
that mandate
not that users can be private from the government, but that users can be private
either from each other or from a corporation, but behind the scenes
always that the government
can get this information. This is true, like so GDPR actually in Europe is a good example of this,
right? So people are worried about online privacy. The wonderful politicians in Europe come along
and propose GDPR, which is meant to protect the privacy of individuals. The whole thing is a charade, of
course, because even though when you request something gets deleted under GDPR,
there are other regulations that require that companies hold that stuff for the government.
And so you actually get the worst of both worlds. You get the annoying pop-up on every website now
where you have to uh
tell what cookies you want as if anyone even understands what those are what they're doing
and in the background the government can pull all this information anyway and often requires that it
be maintained indefinitely so we don't need regulation to give us privacy we just we just
need it to be um legal we need it to be legal to hide things from the state,
from each other, from corporations.
As long as it's legal to be private, then we're good.
We don't need a regulation to kind of mandate it in some fake way.
Yeah.
I'm sure people are also chomping at a bit for us to dig a bit deeper
on the attack of the claws lately.
Everyone's messing around with Open Claws, and I also have some of my own claws running.
On the other side, you see Anthropic desperately pushing our features to kill all the claws.
Maybe Ilya, has anything changed internally since open claw or like anything about like product strategy or how are you guys
you know dealing with this new paradigm
definitely we are all all in on claws yeah so i mean from our product strategy, we were kind of working toward something
like a private Claw originally, right,
with our private chat product, where we were adding more tools,
who are kind of enabling it more to have like desktop app
that could like interact with some of your applications
and have a shared memory that you can tap in
into other applications.
I think what OpenClaw has shown is actually going full in and saying, hey, actually you
want a computer and this AI is operating system of that computer.
And now you interface with a computer through AI. And so that kind of flips from your traditional system design
of kind of this AI systems, right,
where you have like a massive multi-tenant kind
of infrastructure and you're packaging everything to like,
okay, well, actually this is, I mean, if you're in crypto,
like there was this project, Urbit,
that was kind of had this idea, it's like, hey, everybody this is, I mean, if you're in crypto, like there was this project, Erbit, that was kind of had this idea,
it's like, hey, everybody should have like a computer
and kind of interface with it.
And there was like a lot, like,
I think crypto has a lot of this thesis where like,
hey, you know, you want to run your own node kind of thing.
And I think like this is very much in line with that.
And when line was this like AI is your operating system,
AI is your way to interface with computing. And so when you bring all of these pieces together,
you're like, okay, well, if this is kind of enables you to do anything, enables to, you know,
arbitrary action now, and then in turn, this is really becomes your kind of i mean both your personal assistant
but also your coding your you know employee your yeah your swiss army knife uh it makes sense to
focus on that and so we kind of like okay well given we believe in privacy we launched uh hosting
for open clause that is fully confidential right it runs on the same infrastructure you can use your Well, given we believe in privacy, we launched hosting for OpenClause
that is fully confidential, right?
It runs on the same infrastructure.
You can use your confidential inference.
You can proxy to some of the state-of-the-art models,
to closed source that are kind of anonymized
between all the users.
But OpenClause is still, from a security perspective,
not built to be the kind of like I personally like
wouldn't trust giving the credentials and and like access to everything that I would want it to have
access right again like even if it's private from near and and you know other parties who want to
see the OpenClaw itself may like expose it and so that's when we started iron claw which was
okay what is it if you if you think of it as operating system how would you design it as an
operating system that just has ai at the core and so ironclaw is really that is like i mean i call
it ios of ai right like what is that like ios is super user friendly, somewhat opinionated, and protects users from food gunning itself.
Right?
Open Claw is more like the original Linux, right?
When you install it and you kind of cook it yourself, rebuild the kernel sometimes, you know.
Like GCC doesn't compile, you need to go and like debug it.
It's like what is the iOS version of that where, you know, you just set it up, it's, it runs,
it's able to go and install new applications.
And, you know, you know that when you install applications
not gonna blow up your core, you know,
there's like different levels of security
and kind of defensive depth that is running there.
So, yeah, so we're going all in on iron claw.
We host them as well.
You can still host open claw with us and you can use
kind of private inference in the back end yeah definitely i remember that we even uh we also
support like the inside of things on the private inference for the for the iron clause uh yeah i
mean openclaw for me was really like downloading kind of like a frankenstein um agent had a lot of like uh um banging my
head against the wall but then started like branching out into these like um other asian
frameworks like open like iron claw as well um and have indeed kind of like experienced that
like ios vibe more to it um but eric like how has uh how has the i mean i know it's
to it um but eric like how has uh how has the i mean i know it's like because i'm part of it
at venice but how has um you know the claw revolution kind of like influenced uh venice's
direction or both internally and externally like yeah um i i made a you know half joking tweet
i don't know maybe a month ago i said that that suddenly 5% of Venice's customers are lobsters.
After OpenClock came out, Venice was integrated into the onboarding flow.
And so people were using Venice as their source of inference through the software.
And our API use started growing very substantially.
And it's this new kind of customer that's like an agent
that is this weird alien life form.
And then you have this new paradigm of skills,
where these agents have these text files that explain to them
how to do certain
things. And there's a whole interesting new realm of marketing, which is like, how do you influence
these skills and how do you distribute them? How do you get distribution for the skills?
So we are both users of these clause and providers of inference to many clause. And hopefully, to the degree that people use these agentic systems to impact more and more
of their life, the ability or the mandate for these to be safe and private and uncensored
and really user empowering will come to the fore.
So that's what venice that's
what the venice api is really good for you know if you don't if you don't want all of your uh
all of your clause information and everything it gets hands on or it's claws on um you know going
going to sam altman uh then plug it into the venice api and it solves that pretty easily
into the Venice API and it solves that pretty easily.
Yeah, especially now with like a TE
and end-to-end models also being in our API.
Definitely also playing around with that side of things.
I think as we go into the final minutes of this session,
maybe you'd like to pick your brains a bit more about, you know,
where this is going. These claws give us, at least me in my experience, kind of like fragments or
flashes of super intelligence on the one hand, but also on the other hand, it can really do the
dumbest shit ever sometimes, but it's like these these flashes right um but like what what does what does privacy look like in a world
where you know we're speed running super intelligence like just assume that it's there
like how does that how does that work what does that look what does it even look like
Ilya, you want to take that one?
Yeah, I mean, I think there is obviously a few different possible scenarios.
And so I think finding a common ground between them is important.
I think kind of the scenario I see where we're trying to make happen, right, is that everyone has access
to kind of both this commoditized intelligence and it's private and it's available kind of
for you, it's aligned with you.
I think one of the just like broader topics of alignment, like it's a lot of kind of vaporware in a way
because, you know, we cannot align between each other.
You're trying to align a model to the world, to the, like, you know,
in US there's like multiple camps and in the world there's, you know,
100 something, whatever, 200 countries.
So the only alignment that I can imagine working is alignment to one person,
one individual.
And so that's why we call it user-owned AI. It's private, it's secure, and it's yours.
Right? And so like that alignment can happen. And so I think that kind of my perspective is like,
how do we make that happen and kind of have super intelligence for you and available for you and
be kind of extension of your mind.
I think the flip side of this obviously is like, you know, lab builds one massive cluster,
runs, you know, big kind of AI on it, and it's effectively becomes, you know, more and more intelligent. And I think this is kind of, again, where I think decentralization, privacy, and like everyone having their own
is a way to like offset that in many ways.
Because, I mean, the other thing that we will need to start dealing with is that, yeah,
this AI will start manipulating people mostly because other people want it,
not because AI itself
comes up with like, hey, let me do this.
I don't think that is happening anytime soon.
Way earlier, it will be like, oh, let me actually convince a bunch of people into something
because it furses my agenda.
That will happen way earlier, right?
It's already happening, right?
Twitter is already boss trying to convince you into stuff, right?
The GEO is already like, hey, how do you convince AIs so that the AI convinces the user, right?
That's already happening.
Like how to manipulate AI that when a person is asking a question, the answer is the answer I want, right?
Right. So this is this is already happening.
So this is already happening.
And so like that, that is where actually, again, I think the user on the AI needs to be this guardian on your behalf that is able to like deal with all of that manipulation.
And then. Yeah. Yeah.
Ilya, that point you made about aligning with the individual, I think, is really key.
So I think it's clear that like AIs are not sentient yet. Maybe they will be someday, but they're not yet.
And until they are, they serve a master. And the question is, which master does the AI serve?
There are at least three candidates. The AI can serve you as an individual that's operating it.
individual that's operating it the ai can serve some company that is running it or the ai can serve
uh the state right where the state has controlled what the ai can do and these are these are
mutually exclusive the ai has to has to serve one or the other and if it's serving the state it's
not serving you um so like the these principles that come from crypto of user sovereignty, hopefully
will take root in the AI world and perhaps be even more important because AI transcends
a larger portion of life than just money or finance. So know who your AI is serving, I
think is the right way to find it.
Yeah, I do like that idea of, like, fully aligned AI to me.
It kind of, like, does feel as you're building this, like, you know, I'm a millennial.
It feels like I'm building a Tamagotchi or something that is just, like, hyper smart.
And, you know, you need to manage it.
You give it, like, extra context, extra memory.
You see it self-actualizing a little bit uh and
i'm anthropomorphizing a lot um but yeah uh definitely it does feel like you're building
a kind of like a guardian i like that i like that that that wording um these last few minutes i also
want to bring up maybe a couple questions from the community um that are in the same vein. So do you think AI can ever be fully trusted
or will human oversight always be required?
Well, can humans ever be fully trusted, right?
You know, what's the standard here?
It's not like humans are trustworthy
and we have this new AI thing that we need to be careful about.
We need to be guarded from either side. And maybe a good metaphor is with self-driving cars, right?
Everyone is afraid of them at first. The idea that the machine would be driving a car sounds a little scary at
first. And when the system is new, it is less capable and less trustworthy than a human.
But as it improves, it probably becomes more capable and more trustworthy than a human to
the point where it might be like orders of magnitude safer than a human. I would guess that
AI systems generally follow that same pattern.
And the risk actually isn't that the AI is untrustworthy.
The risk is that the AI might become, or AIs might become so trustworthy that people suspend their own judgment.
And they no longer, you know, they assume that anything from an AI is true.
That's very dangerous.
And people need to be aware of
that happening because as soon as someone can manipulate it, once it's earned your trust,
then you're in big trouble. Yeah. I also don't think I've ever talked to something that can be
so confidently wrong sometimes. And then it even convinced me. I'm like, yeah, that makes absolute
sense. And then you just go out and you do some things
and then you come back, you're like,
yo, that was like wrong, man.
I mean, on the wild goose chase.
It's like they're trained on the entire corpus
of like political speech.
Every politician ever has a similar degree
of confidence on the unwarranted.
We touched on this like earlier in the conversation.
And then people really want to use these frontier models.
Everybody wants to be on these frontier models.
Open source models are just like,
they're always running a couple months behind.
The gap is closing.
That's fair.
But do you think we'll ever be able to use frontier models
in a verifiable private environment, Ilya?
I think so.
I think what is going to happen is, and again, this is like the,
we kind of hear racing this time, but I think that one way or another,
the frontier companies will adopt this approach,
kind of secure enclaves, end-to-end encryption, and privacy.
And kind of the way we're offering this is actually you can encrypt your model
and upload it to our cloud.
And so this way we don't see it, nobody can see it, it only gets decrypted inside secure
enclave. And so you guarantee the privacy of the model weights from anyone. The users have
guaranteed privacy that their data doesn't go to model provider or us. And they get monetization and they can use effectively
any kind of hardware available that is in the network.
I think that approach allows to have frontier models
to really kind of monetize private inference
and not become kind of subject
to like dealing with private data of their users.
And I think that is a trade-off, right?
Right now they are using data of users for training.
But I think we actually, from a fundamental perspective,
I think the research has been moving on from that
to more using synthetic data
and kind of curated our own environments and a bunch of stuff. is been moving on from that to more using synthetic data
and kind of curated our own environments and a bunch of stuff.
And so most of users' data is not that interesting anyway.
And so I think as yeah, exactly.
And so I think there's going to be a time when this will start.
And again, even right now, already enterprises pay for,
you know, like do not train on my data.
But right now it's a very much, yeah, trust me, bro.
It still sits in like data center somewhere.
You know, there's a breach in any kind of way, right?
All of the data becomes available.
So it makes sense for them to adopt this as well.
So that's kind of our position.
And, you know, we're pitching this as a tech stack.
And then we can have frontier models that are kind of verifiable and on the same level.
I think I'd take a slightly different outlook on it.
I don't know that the proprietary closed source labs will ever be private
but the open source models are catching up and like if you look at the trajectory over the last
couple years the gap between the proprietary labs and the open source labs is closing
the question is does that trend continue such that the open source models actually
become the frontier models that will be extremely interesting and of course if the open source
models do become the frontier then they can all be run privately and and we're good to go
but that's an open question you know will the gap just compress to nothing or will the open
source actually surpass the proprietary models.
Yeah, definitely following that race very, very closely.
Maybe one or two last questions to close us out.
And we touched on it earlier. Do you fear any government backlash for providing users with private AI?
I mean, fears yes, yes.
Uh, yeah.
Um, governments will not permit private AI as it gets bigger.
So the question is, is like, which governments will strike first, which ones will try to outlaw it first?
is like which governments will strike first which ones will try to outlaw it first um
the european governments will definitely outlaw before the us the us uh in this regard will
probably be the the last lingering like place where private ai can exist because thankfully the
us uh retains very strong beach protections but i do not know that that will withstand the um
the game theory incentive of of trying to you know make all such conversation illegal
so yeah i am worried about it right that's why we got to keep fighting that fight right
um last question to close us out i think maybe this is a you know people always talk about like Right. That's why we got to keep fighting that fight, right?
Last question to close us out, I think.
Maybe this is a, you know, people always talk about like P-Doom.
What is, considering the latest developments with the clause and the trajectory we're heading at,
what is your P-Doom, Ilya and Eric, if any?
I don't try to calculate things I can't calculate.
And AI is not the thing that I'm most fearful of.
So my PDM isn't based on AI models.
It's based on the state that actually kills hundreds of millions of people.
That would be the entity that I worry more about about but no way to calculate a probability on it yeah i i i kind of agree i think as i said it right now it's not ai that's the problem it's people who are using
all the tools which indeed i mean ai now is in toolbox right and then and I think yeah my I
mean I'm optimistic and and and believe in in what we're doing that we can
actually substantially affect the impact of AI and kind of manipulation by giving
everyone user on AI I think I think that's really at
the core of what we're doing. Same with blockchain gives. I mean, I'm from XUSSR.
I've seen multiple currency collapses. And so I understand this for money and I understand that
for AI. I think we need to continue building that as a solution that's fundamental and can survive through hopefully, can both survive
through hopefully cataclysm that don't happen but also can actually be the least valve of
some of this where there's no point of stopping something if there is an alternative that is available to everyone.
There's no way to, I mean, we've seen this with internet
and like Arab Spring, right?
They've tried to block internet, but the mesh networks popped up,
the peer-to-peer communication channels popped up,
and kind of the, we are reorganized around those tools.
I mean, not we, but the people in those regions.
I think similar thing here by having this release wall of it kind of like, I mean, I don't
want to use this example because I don't think it's valid, but like having people having
access to the tools on the same level always democratizes
and removes
some of the pain
points that Eric is
talking about.
That's a great note to end
on. Thank you both,
Ilya and Eric. Thank you
everyone who joined us.
Make sure to go and try out our
end-to-end encrypted models and TE models powered by NIR thank you everyone who joined us make sure to make sure to go and try out our
end-to-end encrypted models and te models powered by near on venice
where probable privacy is here um so thank you thanks everyone we'll uh we'll catch you on the next one peace see ya
