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We had the same scenario in self-driving maybe three years ago. There were so many people doing self-driving. It looked like everyone was roughly the same, but they weren't. I could internally tell the difference that how far ahead Waymo was.
You can think of Waymo as a big robot. We are driving around everywhere. So we're making with our partners cars that way.
NVIDIA is R&D and their ability to drive that innovation. Their software stack is world class. So, you know, they have a lot of advantages as a company, and I have extraordinary respect for them.
Look, first of all, at a high level, NVIDIA is a phenomenal company. You know, Jensen is awesome. We have been working with NVIDIA now for a very, very long time, and we continue to do so, right? And we serve a lot of the Gemini traffic on GPUs as well, right? And so we give customers choice, et cetera. Internally, we train our Gemini models on TPUs, right?
I view that as one of the differentiated innovation opportunities we have ahead as a company.
I think we are well set up for that. I do think we are pushing the research frontier in a much broader way than most other people. Beyond just LLMs, transformer-based models, I mean, diffusion-based models, all those areas we are exploring in a deep, deep way, right?
we are deploying GPUs internally as well. I like that flexibility.
Internally, we train our Gemini models on TPUs, right?
On the $75 billion in CapEx for 2025, you know, obviously, the majority of that goes into servers, data centers, and so on, servers being the vast portion of it. I would say on looking at 2025 and looking at the compute part of the span, half of that is going towards our cloud business in 2025.
I've always viewed that full stack approach, you know, deep infrastructure, foundational, fundamental R&D on top of it. And then you build and innovate on top of that. And I think that approach will serve us well over time.
we are in our seventh generation of TPUs. And we built our first version in 2017.
our Flash series of models are a real workhorse in the industry, right?
We deliver the best models at the most cost-effective price point, right?
I think we are the largest podcasting service in the world.
Google is one of the largest enterprise software companies in the world now.
Last year, we exited a combination of YouTube and cloud at $110 billion.
I don't see any reason why AI, you know, just from a first principle standpoint, why won't AI do a better job there as well, right? And so I think, you know, I think we are comfortable that we can work the transition through.
We already, with AI overviews, you know, we are at the baseline of, you know, it's the same as without AI overviews. And so we've reached that stage. But from there, we can improve, right?
We have actually seen, like, you know, for a given query, the cost to serve that query has fallen dramatically in an 18-month time frame.
Google, with its infrastructure, I'd wager on that, right? And, you know, on our chances to do that better than pretty much anyone else.
ChatGPT has obviously had phenomenal success, you know, but I think it's still early days.
Obviously, we have a standalone Gemini app. I think we are making progress there, particularly with the introduction of Gemini 2.5 Pro. We have seen a real uptick and engagement and usage growth in the product.
In search, you know, maybe the most widely used Gen AI product today might be search with AI overviews, right?
YouTube has thrived since the moment TikTok has come in, right? And it was a whole new format. We did Shorts when we launched Shorts. Shorts absolutely didn't monetize anywhere near long form. But we just leaned into the user experience. And over time, when we figured out, monetization to follow.
It's like one of the original principles of Google, follow the user, all else will follow.
We just lean into the user experience. And over time, we figured out monetization to follow.
Look, there are acquisitions we debated, hard, game, close. Just give me one name. Or get in trouble. Maybe Netflix.
Google was really set up, I think the founder set up this kind of a deep computer science approach. And you take that and apply it to build things which can impact people on a day-to-day basis. And so it's that kind of a product and technical culture, which is the essence of the company.
Search is always, from the outside, people look at it and say, search, oh, it kind of looks easy to do. The craft of search is very hard. Over two decades, I think, we've had a real north star of understanding what users want in search. And, you know, you've been here. We are kind of a very metrics-driven company.
And we are bringing our cutting-edge models there, where the models are actually working to answer your questions, using search as a real native tool, right? And there are the queries. People are typing in queries, like literally long paragraphs, right? The average query length is somewhere two to three times. It's what we see in search as it existed two years ago. So we are seeing people respond.
We launched AI Overviews about a year ago. It's now being used by over 1.5 billion users in over 150 countries. It's expanding the types of queries people can type in. And we see empirically the nature of queries is expanded. So there are whole new use cases coming into search. We find for queries where we trigger AI Overviews, we see query growth. And the growth continues over time.
I think if you look at how much information means to people, I think they're going to, each person is going to have access to information in a way they've never had before. So it feels very far from a zero-sum construct to me.