Michael Intrator

And that's really what we began to focus on.

That was the lead into training.

That was the lead into training.

And now the world has gone through this moment where we've moved from research

And now the world has gone through this moment where we've moved from research

into the productization of this.

into the productization of this.

It's beginning to work its way in from the fringe of organizations into the core of what they do.

It's beginning to work its way in from the fringe of organizations into the core of what they do.

And you can see that every day in the amount of inference compute that is being driven through our infrastructure layer, which is just massive.

And you can see that every day in the amount of inference compute that is being driven through our infrastructure layer, which is just massive.

I always think of inference as the monetization of the investment in artificial intelligence.

I always think of inference as the monetization of the investment in artificial intelligence.

So when we see our compute being used to stand up the massive scale of inference that's hitting our compute every day, and like, you know, inference is when people ask the model a question,

So when we see our compute being used to stand up the massive scale of inference that's hitting our compute every day, and like, you know, inference is when people ask the model a question,

it comes back with an answer, that's an inference.

it comes back with an answer, that's an inference.

Or when you ask the model a question and then to go do something, that's inference, right?

Or when you ask the model a question and then to go do something, that's inference, right?

And that's actually where you have the opportunity to really drive value outside of the model itself, but into the real world.