Demis Hey. Good to see you. Good to see you too. Thanks for your. Today we're talking about Gemini three, the most intelligent flagship model from Google. If you had to explain it in one sentence, why is this launch It's important, I think, because, you know, it just continues the progression. I think we've been on with Gemini over the last couple of years, and we're really happy with the overall performance of this model. I think people are going to be very pleasantly surprised by it. I think it just continues the overall performance increase across the board. And you can see that from all the benchmarks, from reasoning to, tool calling, reliability, and creativity. I think it's better across, across all those measures. we rewind back to when Gemini 2.5. Was launched. To now with Gemini three. What breakthroughs have happened since where Gemini has gone to this level with the benchmarks? Yeah, well, we really focus quite hard on, I mean, 2.5 was a great model two. And we really we're really pleased with that. And you saw how well it did in the market. With developers and also in the Gemini app. But we wanted to improve things like tool calling and tool use. And just sort of the reliability of that. Of course, that's important for coding, which is one of the big use cases of these models. But it's also important for just general reasoning and generally how you use it. The other thing we did, I think we've done is, improve the style and the persona a lot. You know, I think it's more succinct, more to the point, more helpful. And at least I, you know, and and the internal testing shows people enjoy using, this model, even more. definitely a step up in coding reasoning before, like an everyday, normal tech worker that's not a developer who already uses Gemini today. What are the noticeable concrete things they'll still be able to do tomorrow that they couldn't before? Yeah, it depends what your use case is, but I think almost everything we've tried, like if you're brainstorming ideas or your, vibe coding, or you're just, you know, doing some creative writing or summarizing things, you should find it's meaningfully better. All of those things. More reliable. Much smarter. And I think stylistically better, too. I think the, the tool calling and things like this, you'll sort of feel it under the hood that it's, you know, using search better and it's, it's basically, more accurate on things because the tool calling is better and, and more reliable. So I think across the board you should just feel this is a much more if you're using it as a general Gemini app user, for example, you should feel it's just, across the board, much more capable. And more pleasant to to to work with and and and use. One thing that I didn't notice from any of the announcement was memory. I'm. love to hear take on this. I think Google has a real advantage across, you know, all the tools, given how much data you guys have across Gmail, YouTube, maps, everything else for the user. And for me, like candidly, the stickiest part of ChatGPT has been the small memory component they've added. How do you think about integrating that long term across Gemini? Yeah. We're really, sort of going deep into personalization and memory and context, and I think you'll this is part of the 3.0 era. You know, the Gemini three era is to is to kind of double down on those things. So you're going to start seeing a lot of discussing that a lot more as we move into the three, the Gemini three era. Obviously there's more models to come. There's the family to fill out, family of models to fill out, and we'll be doing that. And more features and capabilities that are already built into the model but will start, you know, exposing more and more in our products and our, developer, surfaces. So including, you know, kind of deep personalization and connection into, the other Google, the rest of the Google ecosystem, you know, Gmail and calendar and so on. And you're seeing bits of that already happening. But it's just sort of scratching the surface of what we have planned. And, and Gemini three is, is, is a, you know, really capable model that's able to do that. And, and again, things like tool calling and tool usage are going to be really important for reliably connecting in to these other, these other surfaces. It does seem very capable with all the benchmarks. I'm just like, I just wish it came sooner. Yeah. using tactically so often and you know, Gemini the beating, everything in benchmarks and it has all this access. I know it's hard to give a timeline on these things, but do you have any, like, rough estimates on when that real memory is going to start rolling out on 3.0? Yeah. We, you know, we we're we're in testing in in in. So the dogfood in all the time internally. Lots of different ideas around this. And when those things are polished enough and we feel a reliable enough, you know, we'll put them out as soon as we can. We know users want want it. We will start building more efficient versions of the model, you know, flash versions, these kinds of things which will allow us to serve it at scale. So, you know, we're very, that we're excited about the, the sort of prototyping we're doing. And you'll see the fruits of that very soon. The other thing I should mention is, I think that I'm super impressed by with these new model is the kind of multimodal capabilities Gemini is, you know, is always been really strong. Think best in class Sota on multimodal reasoning, multimodal understanding and generation things like nanite banana and and we're going to like, uplevel, you know, all of that with this new model. So I think there's going to be a lot I think, you know, general, the general public, the general user will see a lot of benefits of that. And we'll going to start plugging that into other surfaces. You know, with YouTube, AI studio and so on, where, you know, those, those will come through, shine through, I think those new kind of multimodal, capabilities. I'm excited to be fully testing out and see what the world does with the models as well. Alongside the the new model 3.0, you're launching Anti-Gravity, which is a new a genetic development platform, and it sounds like the platform enables every developer to have almost like an AI coworker. They can operate across the editor, terminal and browser now, but in your mind, what's the differentiator between anti-gravity and the other major? A genetic coding apps that are out there right now? You know, I think it's going to iterate over time, but I feel like we're really trying to reimagine the idea from an agent first perspective. You know, I think we sort of have the roadmap a way that's going where we want to take Gemini. Right. And and onto the head of that. Of course, you can use other models, too. It's anti-gravity. And I think we're trying to sort of reimagine that. And, and, and you know, the windsurf guys that we're working on, they x windsurf people, you know, they're obviously experts in there. So this is we're very excited about this area. We're using it internally, you know, which is the first step. Right. And and people are really enjoying using it. And the productivity is you know, gains are impressive there. But I think we're still at the beginning of that. Right. As it, as the systems become more capable, which we're obviously expecting them to be. What does it really mean to kind of reimagine that whole experience? And obviously, I'm talking beyond white coding here, which is more for the amateur coder, right? Let's call it what is the professional coder one from their, they've set up and I think anti-gravity is, is, is, is our first attempt at trying to sort of answer that and build a roadmap towards that. And then of course, you've got things are I studio that's more maybe for the. Casual developer or single developer, right? Or prosumer, let's call it. So I think we're going to have different surfaces depending on, the level of professionalism and whether you're working in a team, this kind of thing. And I think anti-gravity is, you know, people are really going to enjoy that. So I take average more for that professional coder. Rather the vibe coder. I think that's what we're coming aiming for, though, of course, you know, any developer will have, you know, hopefully many, many types, you know, all types of developers will use it. And speaking of using tools internally, this is the really curious question I have. I heard Google's using AI to generate a lot of new code now. But. Are there like internal tools or models that you guys have access to, that you're not released to the public just so you guys can really get the the early benefits of these products or how do you guys think about that in terms of like testing tools internally before releasing them and or. Keeping it to yourself to get a leg up over a competition. Yeah. We look we have we have lots of experimental, models and tools all the time. So and we also have tools that are you know, at this time, too expensive to serve at scale. You know, you could think of like Jeannie as being an example of a model like that, right? We we would love to give access to that. But it's it's expensive to serve currently. Obviously, we're working on that, with future versions of the model. Some of our deep think models, you know, are only available in ultra because because the ultra tier, because they're also very expensive to serve. So we're continually trying to optimize for those things. And then generally when that when we're able to, it's more of a physical constraint with the compute, when we're able to, we generally put those models for everyone to use as soon as we're actually able to do it, from a serving point of view, efficiently enough. So it's more that is the is that is the dominating factor. We also, of course, do have lots of research ideas and research models going on all the time. You know, that's part of the ordinary course of being a. A kind of frontier lab with a very deep and broad research bench, I would say probably broader and deeper than anyone else's. And, and, and so that we're always trying to pioneer, you know, the next AlphaGo, the next Transformers, what's coming down the line. Our obviously world models is one of those things. So we're always experimenting and some of those things, you know, when they're ready that will put them out, into the into the general public. Then there's also other things too, like hardware and software developments going on, things like, you know, glasses assistant and stuff like that, that we're also, you know, iterating on and, and it starts off experimental before we're ready to, to, you know, show the general the world, in general about it. Are you guys slowly getting quicker on these releases though? Because I noticed. With 3.0. For example, you guys are launching in search. Yeah. are you guys just slowly getting faster? How are you thinking about that? Yes. Yeah. That's great support actually. So we worked really hard. I think 2.5 was the first. Real version of that where we had, you know, world class models. So to model and, deep integrations into the main Google surfaces very, very quickly. Right. And I think you saw that at IO, which is what I think a lot of people were impressed. IO I think with three point, you know, Gemini three, we're taking it to the next level and, and SIM shipping, as you say, with such an AI mode and so on. And I think that's the direction, you know, we've worked really hard over the last, few months, I think to, to you can think of Google DeepMind as being the engine room of Google. Right? So we we've tried to make sure we're plugged into all the PPAs and powering up every big product. And there's so many amazing products at Google for maps to YouTube to, to, to search, and of course workspace. And we want all of those, the goodness of everything that we're doing with Gemini and the underlying models to, to really power amazing new capabilities and features in these products that billions of people use every day and love. And I think we're we're seeing that flywheel really starting now. I think we're still only midway in that evolution is a lot more exciting stuff to come. And I think we can we can go even faster. I mean, I think search is a is, poster child for how we want it to be, and then we now need to do that across the board. Speaking of. Useful apps within Google's. Whole ecosystem. Gemini The Gemini app has just hit 650 million monthly active users. Yeah. Yeah. Thanks. We're very proud of that. me really quickly. But I'm really curious. Like, at the scale you're at now, is there any, like, specific use cases you're seeing, across the Gemini app other than coding that are really useful to your users? Yeah. We're seeing, actually, I think I think, the Gemini app is really good for multimodal. So I think with nano banana, that was a big, driver of usage for us. From very fun things like planning your, you know, surprise birthday party invites whatever to like in certain part territories, like making little figurines, to so there's so many fun things one can do comics. So I think using, the multimodal capability, something pretty unique. That Gemini app is good at. And, you know, I think, that's driven a lot of interest and I think that will continue. And then we're also doubling down and thinking through on things like education and health and other stuff that we know. Users like to use chat bots for, and we want to be, absolute best in class in that. And I think Gemini three is going to be the foundation stone for that. But I think yeah, multimodal and and at least for me I love brainstorming with these things these these these things, whether it's like naming a project to, you know, sort of, sense checking an idea. And I think, that the app is, is really good for that to. You said something there that was really interesting, that Gemini might be like the cornerstone for the health questions. Is there any, like, more detail you could get into that? Because obviously your background with health. Yeah, yeah, we've got all these sort of other projects if you like, like co scientist and we've, we've done a lot of work on this. We've got a system called Amy Medical Diagnostic kind of system that there are more in the science team. And we'd like to do is bring all of those capabilities into the main, you know, Gemini. So that's where, you know, we're looking at that. We I would love it to be, what all scientists use, to kind of riff ideas on what to do some research. And I think, you know, three Gemini three is a is a good foundation stone for that. And you'll start seeing, rolling out those capabilities, you know, the various forms of Gemini three, including things in research and deep things that are built on top of it. And but now with the extra reliability that Gemini three has, Due to the reasoning and tool calling and so on, that should come through in, citations and understanding literature. And, and again, Gemini should be amazing for that because it's multi it's so good multimodal and a lot of health and education questions. And what you just want to do with it are multimodal right. Here's a diagnostic image. What is it. What does it mean. Here's a paper. Here's here's the figure and the tables. What does that mean with the text. Or vice versa. You know, in education, I got to make a poster about this subject, you know, help me lay that out. Right. And generate, the visuals for that. I think that is what I'm hoping. And we, we're expecting people to use, the Gemini three, systems for and including, of course, the Gemini app, primarily. I'm very excited for that. Especially on the AI and healthcare and education. Both are very Yeah. Looking ahead and again, you might not have an answer. This is just kind of further down the road. But are you open to and or looking at using AI for proactive preventative? Health care at all. We are looking at that, in the science team and health teams, like some kind of, you know, medical grade thing, but that would need obviously additional, approvals and checks and balances with the regulators and so on. So you have to be careful. Obviously, Gemini app is not a medical grade, tool. Right. It's for personal use. And, you still need to consult a doctor and all of those things, but it could be really useful in places where, you know, poor parts of the world where there isn't very good primary, health care or education. Right. And we're very excited about that. And I know you're very interested in this Rowan as well. And so we think and because of Google's reach and distribution and Android and things like that, which already, you know, are kind of lifelines in some of those places, I think that we can, you know, could be very good to at least get a basic level of care and, and knowledge to those, to those kinds of people and, and which could make a difference to them. Right. And I think we can continue to kind of improve that with our and then look to, these more medical grade applications where and see when are we ready. For something to be like a doctor's, you know, assistant or companion or research assistant or something like that? I think we still need some more levels of reliability and. I think we're on the right direction with Gemini three, but there's still a lot more I would say that's needed, and we're researching that heavily. As you know, it's a core passion of mine, right? Science and medicine are using, our systems for that. And of course, Gemini. We'd love that to be the, the main foundation stone. And that is the plan for those additional, capabilities to be built on. So. You know, we're very excited about that. I'm very passionate about that, as you know, and also with our work with isomorphic and so on. And, and, you know, I'm pleased with the progress we've made with Gemini three, but it's just the beginning of that. We need a lot more if we want to be, really reliable. So those types of, Use cases. That's going to help billions of people. I'm very excited for it. So switching gears here a little bit to just the real world work, what we currently have with Gemini. Another thing that stood out with the launch was, Gemini agents. Within the app, which is new, which allows you to connect to things like Gmail, which was already there before, but now it gives you tailored steps and actually allows you to execute tasks like sending emails directly within Gemini. As we kind of get towards this. Assistance that. He's almost your life assistant. Directly in Gmail. What's your like dream vision for this? Like Digital Coworker? Do you want Gemini to be like this standalone assistant type platform like that people use every single day and work like slack? Or is it just like a separate tool? Yeah, I would love it to be. You know, we have this idea of a universal assistant, which is, you know, a future version of Gemini, right? That's that's that's that's, useful in your everyday life. Every moment of your life where it's a kind of. It's a it's a great, assistant. For anything you might be doing productivity wise, but also in your leisure time, you know, recommending you cool things. Giving you ideas about things, riffing with you on things, and maybe also comes across multiple devices. Right. So it's on your computer in your browser, but it's also it's a work, it's a home, but it's also, you know, comes with you on your phone and maybe some other devices like, like a smart glass. And I think that is the future. I feel very strongly about that. That's the future. And I think you need a really capable based, multimodal model, like, like Gemini to be able to do that, because you've got to understand the physical world around you and the context that you're in. And of course, to call, and use all these other applications, starting with all the, you know, the amazing Google ones like maps and workspace and email and so on. But then eventually becoming fully general so it can call any, any tools. And then I think we're into a new era where, where you have, you know, just like, if you have a really good personal assistant in real life, those of us lucky enough to have really good personal assistants bringing that helpfulness to everybody's lives. Right. And, and, I think that's going to be, a real, boon for your, you know, what you want to do with your time. So eventually, I hope eventually we'll get time back through this. Right? And our attention spans back as well, even more importantly, so we can actually spend it on the things we love doing and we want to be doing, rather than the things we just have to be doing. I am very excited for it. I think that's all the time we have here, but thank you so much for your time. Great. Thanks.