Illia Polosukhin

Obviously, you know, all the other kind of challenges.

And, you know, when we go to companies, it's even more like the IP rights and all of those things.

And so this is where I think confidentiality privacy is really important because this would actually unlock ability to get a lot more context into these models and really enable them to be kind of more in a driver's seat and help with things.

And obviously there's...

UI and like building trust with a user that's required, but from like a kind of fundamental perspective, that's one of the aspects.

Exactly.

Yeah.

Like your emails, your calendar, your companies, you know, documents, you know, potentially like private IP, private medical data.

Like, I mean, imagine what you can do now if you just run like the AI model, like GPT-5 is actually really good at health data, right?

Like it may be better than some, you know, a big percentage of doctors now at things, but it doesn't have access to all the medical data, right?

And you don't want that data to leave where it is sitting right now.

So ideally, you bring the model to the data.

So how do we actually facilitate that?

So this is something that we're working on.

How do we actually create this effectively secure vault where AI and data can happen, right?

Where neither side is able to access each other, but then the result is available to the user.

Yeah, so I think like if we kind of look from a macro perspective, I mean, privacy is one aspect.

The other one is kind of this agency, right?

I think the biggest kind of mode collapse we can end up if the world ends up being looked through a single lens of a kind of single AI that controlled by a single company or or even worse person.

So what do I mean?