Travis Kalanick

So yes, I'm sort of like coming from my very specific experience.

But if you believe there's network effects with the scale of data that you have and the scale of customers and the revenue, that's this cash that's coming in that you redeploy into compute.

And so say there's network effects of large compute.

I'd be very worried if I'm open AI and seeing somebody growing faster at the same size.

Freeberg, when you look at this race between these two giants, maybe your thoughts on the flywheel as it relates, as Travis is pointing out, to advantages in compute, reinforcement learning, and then also the ability to fundraise.

One of the great things that Travis and the team did was, as they were pulling away, they

They just sucked all the oxygen out of the room by using capital as a weapon.

So your thoughts, Dave, on this high stakes game?

Because there's also a point at which, and I'll just end on this, there's a point at which you could run off the cliff.

You raise so much money and you deploy it so fast and the revenue doesn't catch up to it.

And then you go public and the markets don't believe the story.

So your thoughts, Freeberg?

Yeah, but here's where I go, just real quick, Dave, is...

mad respect on a 120 or $130 billion raise.

I mean, this is obviously next level, but you can use capital and investment to acquire scale and network effects associated with it.

But if somebody is getting that scale with revenue and let's call it contribution margin, contribution profit, efficiency will outstrip subsidy.

And you can't just keep raising $100 billion things forever.

That's where the train will stop.

And if Anthropic is funding theirs through revenue and other folks are funding it through investment, there's like a short-term, that's a short-term solve.

But the long run is whoever is scaling their actual usage and system and ultimately with contribution profit that then soaks up the need for investment.