Dylan Patel

But like, you know, it's like this whole like idea of like ML research, you spend a lot of time on compute training

doing what effectively were useless things besides teaching yourself what's the right thing to do and what's the wrong thing to do.

And semiconductor manufacturing is the same way.

And actually, all process manufacturing is the same way.

If you're iterating super fast and you're trying to get better and better and better, or you're optimizing a process on a chemistry or whatever it is, you try, you fail, you learn, you do.

In semiconductor manufacturing, maybe it's just running tens of thousands of wafers.

And so your R&D cost of your main fab that is running the R&D is very, very high.

And it's producing zero economic value besides that it's teaching you how to do the next node, which then you can deploy at volume.

And that is what actually makes the money.

Well, you know, way back when monkeys were, you know, before we became humans, we were territorial.

So, you know, and me having two bananas makes me better than you.

When we think about the power structures, like you mentioned a really interesting one.

Does Anthropic hold all the cards in this Cursor relationship?

Cursor has like nearly a billion dollars of revenue now if you do current month times 12.

That's a ton, but their margins are what they are and they're sending most of it back to Anthropic.

Some people say their margins may be negative.

I think they're slightly positive.

But regardless, they're sending most of it back to Anthropic.

Yeah.

But then Anthropic is taking all the gross profit dollars and putting them into compute for training.