Tulsee Doshi: belief

Transcript context

…Speaking of possible research breakthroughs, what happened to that diffusion coding model? I was excited to see apps materialize in like 3 seconds in front of my eyes and it's been quiet on that front. Diffusion is awesome. It is super fast. I think we are still testing and experimenting with it in a number of different ways, trying to figure out like what is the best way to put this out into the world? Where is it most useful? But I will say actually part of the reason why we've also been investing in Flashlight is like Flashlight is an incredibly fast model. And actually if you look at the 3.5 Flash model we're releasing right now on artificial analysis, it benchmarks at like, I think 280 tokens per second, which is like crazy fast. In fact, it's actually so fast that like sometimes in anti-gravity, like by the time I want to cancel, like it's too late. And so I think like we already are like, I think trying to figure out where do you start getting to Logan's point a different answer, like the diminishing returns and where do you see that value proposition is I think part of the question too. But we are continuing to push on diffusion research. Our researchers who are working on diffusion are doing some pretty awesome stuff. I was in a meeting with them the other day about some results that they have. I mean, I think they're still pushing the frontier of kind of quality and speed in ways that are really, really cool. So I think we're going to see that play out really well. Yeah, and I'm excited. I feel like it's a research exploration. I feel like that was also, obviously there was the application where you could sort of test it last year at IO, but I think the framing was like, we're doing interesting research. This is sort of like a look behind the curtain of the interesting research we're doing. And hopefully it manifests in models maybe one day or just us informing our perspective of what works and what doesn't. So yeah.…

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