Hannah Petrovic

But it's not a fixed level of capabilities what's driving the growth of the industry and the growth in revenue.

This ever-increasing amount of capabilities that we have, like we are building more and more, we're spending more and more in building more sophisticated machines.

And I think this is going to cut against the gradient of moving things to the edge.

Like all of these new exciting capabilities, like you're just going to want to run it on your data center.

So you just want to run it in your data centers for a very long amount of time.

Like Asim is talking about like, oh, I may be looking at a bill of $5,000 a year for running my agent.

And it's like, that seems very small compared to what these kind of machines could do in the future.

Like if you get to the point where these machines have an output, which is comparable to a worker, like how much will you pay?

to have a virtual co-worker who is really knowledgeable, who is available 24-7.

You might be willing to spend on the order of hundreds of thousands of dollars a year just to keep those kind of agents running.

And there is huge advantages to running them in a data center.

The biggest disadvantage here, the one that

The one that physics won't allow you to overcome is latency.

But right now, the model stars are already slow enough that I don't mind waiting like 200 milliseconds for the responses to get to me.

Like, it's fine.

They can take, they can take.

I leave my GPT-5 probe thinking in the background for 20 minutes and then I get back to the answer.

I'm not in a hurry.

Yeah, I think that for me, I came away with a more pessimistic view that I had.

But you might have picked up on the fact that I'm very bullish on artificial intelligence already.