Logan Kilpatrick

you know, I need to email someone and book a trip and do whatever, et cetera, et cetera.

The context is spread across potentially the entire internet or some like unbounded state space that I by default don't actually know.

And what's cool about the live API and stream real time is basically all this context you need to solve the problem is in some case visible on my screen in some way.

Like during, throughout the day, all the context for me to do my job

you know, however many hours a day shows up on my computer screen.

The AI system doesn't need some other, you know, access to some other tools.

Like all the context is there.

It is connected to my computer.

It's already present.

So there's something really interesting about building infrastructure to do this.

And I think we're still early in like allowing and like building a bunch of products that make use of that.

But I'm excited.

And then the other use case you mentioned was around text to speech.

And we have a...

a state-of-the-art model uh for text-to-speech and it's it's really cool to see there's been a huge amount of demand um and wasn't the use case that i thought would be like particularly um would like grow particularly quickly but it actually is which has been really interesting to see there's like a huge amount of demand for like very native um audio sounding or like native human sounding uh text-to-speech video generation so you can go into ai studio and you can test this capability out and things like um

If folks have used Notebook LM, you could do these like podcast-like generations, which is really cool.

And there's lots of other use cases like that.

Very cool.

So you can make your own AI podcast in AI Studio?

Exactly.