Illia Polosukhin

And yeah, there's some search, some other tools, but there's a very limited context that the model has.

Yeah.

And I think this is really probably the bigger bottleneck for actual adoption in personal and even more importantly, kind of work environments.

And I think one of the areas where, I mean, to bring it back to what we're working on, where I think is limitation, it's...

like there's kind of both sides are a little bit scared of of allowing this to happen so like i'm as a user scared of like allowing access to all of my data 100 and then the company is actually on the other side also a little bit scared of like getting all of the user data and be responsible for you know something goes wrong and so that's true and who knows what it is yeah

Yeah, like, again, you know, there's a HIPAA compliance, right?

If you're taking on medical data, like, for example, all of the AI companies now, people uploading their medical data there, and they're not HIPAA compliant.

So this is like a big question there, right?

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.