Jaime Sevilla

The methodology, how we actually got into it.

And a lot of it was based on numbers that we could find in the past historically, and then trying to predict what would happen in the rest of 2025.

So for example, the sales and marketing, we had some data that 2024 was 1 billion in sales and marketing.

And then in

H1 of 2025, that was 2 billion, for example.

So we can build a picture using constraints in this way.

And from that, you can try and understand the costs of the company as a whole.

And we broke it down into many categories, as you can tell in the piece.

But each of those as well, I tried to break down further into the different separate components so that we could realistically understand whether or not it was feasible or a realistic approximation at least.

Yeah, spot on with the numbers there.

The other thing I would like to also consider is that AI is also creating a flywheel in the development space of itself.

So I'm wondering how that might affect R&D down the line, given that R&D is such a huge development cost to the company for the next model.

That's just a thought there.

Yeah.

So in Meta's earnings in October, they commented that their AI tool

driven ads were essentially bringing in 60 billion of revenue in ARR.

So there is a considerable uplift already in the ad space there, but it's, this will be the first time that it will be in the chat one.

And it was also the Meta were able to keep people on like Instagram, on YouTube, not YouTube, Instagram and Facebook longer.

So people were seeing more of these ads as well.

Yeah.