Logan Kilpatrick: evaluation

Transcript context

…And I think what's been really fun from the modeling standpoint there is one thing that we did with Gemini 3 that we're really continuing, I think, with the 3.5 line is really bringing the model to all of our products. So 3.5 Flash will be in Gemini App. It will be in AI mode in Search. It's also powering anti-gravity. It's also powering agentic experiences in AI Studio in Gemini Spark. And so I think really this idea of how do we build a model And then how do we build it in partnership with the harness such that it actually works across all of these product surfaces, which actually have very different users and very different goals, I think is actually really... Really awesome. It's really hard too. I think it's actually gotten harder to do. I think it's almost like it was maybe tongue in cheek. It was kind of easy before because you just launched the model on a couple of services and sort of it wasn't that bad. I feel like now it's like you're sort of you have the constraints of the very wide array of Google products that are just like. for totally different users and sort of I think actually that credit to the model team sort of like trying to find the fine line for all these different places because we're not just building for search, we're not just building for developers, we're not just building for cloud customers, it's not just for the Gemini app, it's like all of them at the same time, which is just exceptionally a lot of work to pull off that story on a consistent basis, which like from Gemini 3 forward has been the story, which is which is exciting. I think one other thing I'll say is like one thing that's cool about this IO too is what we're doing across modalities. So, you know, I think Logan said agent, agent, agent, which I think is true. This IO is really about bringing models to action in that kind of real world sort of use cases. But I think what's also cool is we have the flash model, which is really about building these kinds of coding and agentic use cases. We have Omni, which is really about kind of what is this like multimodal vision look like. And then also actually Gemini Live is getting an upgrade too. Gemini Live is getting faster, it's getting smarter, the model is much better at detecting background noise. So it really does actually feel like a partner in a lot of ways. And I think it's kind of cool that we're also able to draw this through line across the different ways you might want to interact with a model and the different kinds of ways you might want to consume content, which I think is also really cool.…

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