Illia Polosukhin

Building another company that will be building AI is kind of counterintuitive because that's exactly what everybody else is doing.

I'll be the benevolent guy.

So how do we build that?

Well, we kind of need a few components to come together, right?

First, we need privacy.

Either way, all this needs to be private.

All the data should be stored on you, all your memory, all the context, all the tool usage, et cetera, should be all yours, including model inference.

And so you need kind of this privacy confidentiality.

Then you need a model where ideally we know what the inputs are.

Again, right now, we're sadly in a world where we have few open source models.

They all come from China, which there's nothing wrong in theory about this, but we have no idea what they are trained on.

So we, again, don't know what the biases are.

And there's this concept of sleeper agents where you can actually train in a specific way the model where it will not show up in benchmarking, it will not show up in normal usage, but in a specific context under specific conditions, it will change its output.

Right.

So you can actually literally train like very specific activations.

There's some research on that.

And so like, again, we have no idea if that was trained like that or not.

I mean, I'm assuming not, but we don't know.

And so it is especially like if you're using it for financial, for medical, for legal, for any of these reasons, like you actually have no confidence in the outcome.

So ideally, we should have a model where we know what went in, all the inputs and how it was trained.