Illia Polosukhin

And now we're actually writing this exponential.

And I think now we're in inflection point from a resource and attention perspective because there's just so much...

kind of focus on this now that I effectively never been.

And I think because of this is just the rate of, rate of innovation is so much higher, right?

Like the amount of, you know, money put in a compute, like all of those things are just like, you know,

The numbers are crazy comparative to like five, seven years ago where, you know, you would train on like a single GPU and you feel super cool.

And now you're like, hey, 100,000 GPU cluster.

Like, what is this?

Amateur hour?

Yeah.

Yeah, so I think generally we're in a section from kind of rate of research and innovation that's happening.

Obviously, it's hard to predict different levels of kind of quality of models and also just adoption.

Some of the adoption is being dragged by just, you know, there's a lot of industries who are still using pen and paper.

Yes, AI is getting better at, you know,

computer vision as well and you can you can potentially use it with that but uh obviously if your workflow is not even like digital you can't even like ai is not going to be that much help yeah totally um but i think like generally that that the we are kind of definitely on exponential and so um as i said we're living we're living in interesting times

You realize this is like a, probably a trillion dollar question, right?

Yeah.

I guess selling the subscription is that, uh, uh,

So, I mean, obviously I have my hypotheses.

Sure.