Illia Polosukhin

And then the other thing is just like how to manage context, how to manage this other kind of challenges that the current models have.

And then, yeah, as they evolve, you can kind of evolve the system as well.

Yeah, so maybe just to expand on OpenClaw.

So one thing that people don't realize when they use Anthropic OpenAI, or even worse, you use something else for inference, OpenClaw actually sends all your secrets to those services as well.

Yeah.

So somewhere in Entropic and OpenAI logs, they have everybody's access keys, API keys, and bearer tokens to access your Gmails and your Notions and your... It's actually insane that we're doing that.

Yeah.

And so first of all, Ironclad fixes that, like the keys never touch LLM.

So even if you're using it with those centralized providers, which you shouldn't, but at least the keys are not going ever into LLM.

So that's something we'd like, just like, that's just the only sane thing to do.

Yes, yes.

But what NeoAI has been working on actually for the past year is actually developing how do we do private AI?

So how do we actually offer AI where neither we, model provider, hardware provider is actually able to access what you are using

the AI inference with.

And so we have Near AI Cloud, which is inference cloud.

You can use open-weight models.

And so it runs in secure enclaves.

It actually uses, and this is kind of what I was referring in the beginning, it uses our multi-party computation network, which is part of Near that is used for encryption, decryption, for backups, for all the kind of internal machinery.

And that's what gives you this kind of

knowledge that like, hey, there's no single party who can go and decrypt your data.