Google CEO Sundar Pichai: AI’s Infinite Possibilities, Compute Scarcity Dilemmas, Future AI Products

Sundar Pichai 0:00 We are at early stages of the most consequential technology ever. This is not like fiber, it's not dark. We are using it

Alex Kantrowitz 0:06 AI researchers, for them, it's like the bigger the computer, the better the AI. You give the researchers the biggest possible computer, even if it is to the detriment of today's profits, like the Cloud business

Sundar Pichai 0:19 So the compute we have today is a function of decisions I made in twenty twenty-four. Today, obviously, when you sit and look at anything, everyone is short, not just us, other companies, and everyone wishes you had two X of what you had planned for

Alex Kantrowitz 0:36 Where's Google's Muse or its Dots product?

Sundar Pichai 0:40 Users both in consumer and enterprise will have access to kind of some multi-agent framework for them working all the time doing things. And so, you know, it feels like a moment of infinite possibilities

Alex Kantrowitz 0:54 Alphabet CEO Sundar Pichai joins us to talk about Google's plan to compete on the frontier of AI, the balance between cutting-edge AI research and the company's Cloud business, and what the future of the interface looks like. And Sundar is here with us in studio in Mountain View today. Sundar, great to see you. Welcome to the show.

Sundar Pichai 1:12 Thanks, Alex. Great to be here.

Alex Kantrowitz 1:14 So Google is back on the frontier with Gemini Four Argon. In plain speak, that means it is a world-leading model. It's benchmark breaking. It beats OpenAI and Anthropic's, uh, public models on a variety of benchmarks, including on coding, math, science, and knowledge work. Now, the conventional wisdom had been that Google had basically given up on the frontier, that it was gonna make these fast models that were good enough and use them in its products, and it wasn't pursuing frontier any-- AI anymore. But that was wrong

Sundar Pichai 1:47 I mean, i- very wrong. Uh, look, I, I, I think we are so committed to being at the frontier. I think it's in our, uh, DNA. Uh, we wouldn't do it any other way. Uh, we've been thinking about the AI frontier for, uh, well over a decade now. We definitely-- uh, the frontier is very dynamic. It's very, uh, competitive. Uh, it's very exciting. Uh, I couldn't be more pleased with, uh, how, uh, Argon has come together. We took our time with it. Uh, you know, we, we made sure we tested it safely and deployed it, uh, uh, carefully. Uh, we took a bit longer than our other models, given, given its capabilities. But I think across the board, be it for agentic work, knowledge work, coding, uh, creative tasks, uh, I think Argon is, uh, you know, one of, one of the, uh, really good frontier models. And, you know, in the first seventy-two hours since we launched, it's, uh, you know, almost up to twenty-five trillion tokens used, which is about three X, uh, what Gemini, uh, three point two had in the first seventy-two hours. So, uh, and we are capacity constrained as we are serving it. So, uh, excited, uh, but there are always areas, you know, both, uh, the frontier is just lasts-- uh, it's very dynamic, and you have to keep evolving the models. And there are areas which we can see we need to improve as well, so we'll be at, at work on all of that as well

Alex Kantrowitz 3:18 Which areas?

Sundar Pichai 3:20 Look, I, um, on any given model, y- you know, Argon will be across the board better at everything if you just look even two months back. But the space is so evolving. Um, but even on coding, for example, there are, there are areas, pockets where we, we know we need to do better, uh, and, you know, there's clear feedback, and so we'll, we'll make

Sundar Pichai 3:47 it better

Alex Kantrowitz 3:48 Let me at least make the argument for why standard models might be good enough for Google

Sundar Pichai 3:52 Yeah

Alex Kantrowitz 3:52 I'm gonna channel the-- what people say about this

Sundar Pichai 3:54 No

Alex Kantrowitz 3:55 Um, and that is that the frontier of AI today, um, is, is getting so good, uh, and the baseline of AI is getting so good that the frontier is really only valuable for a specific set of tasks. And if you have a standard model, you could actually build great products with a standard model. Take Meta Muse, for example.

Sundar Pichai 4:15 Mm-hmm

Alex Kantrowitz 4:15 Meta built Muse on, um, a good model, but not the best models

Sundar Pichai 4:19 Mm-hmm

Alex Kantrowitz 4:20 You know, if you need to do, like, biological research, um, maybe the frontier is really necessary. But the people who would say, "Google doesn't really need the frontier," they would say, "You just need those standard models, and you can put them in products like Maps and Gmail and, and Search." And, um, you know, again, take that Meta example, that would be sufficient. What do you think about that?

Sundar Pichai 4:44 Look, I-- it's definitely not how I, I have thought about, uh, thought about it at all. Uh, I think we are deeply committed to driving the state-of-the-art and actually push what this technology can go, where it can go, uh, all the way from transformers. That's what-- uh, that's a journey we've been on. So you will see us continue to do that. I think when you, when you're at the frontier, you get an earlier look into the kind of, uh, emerging capabilities earlier than others, which helps you better prepare for the future. We are fortunate to have a, a wide set of opportunities across consumer and enterprise. Some of our Cloud customers for sure want the model at the frontier. I think the frontier models will be better at developing the next set of models in a, in a, in an era of, uh, recursive self-improvement. So I would argue-

Alex Kantrowitz 5:41 Mm-hmm

Sundar Pichai 5:41 ... it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our, uh, developers. It definitely tackles problems which our previous models could not do. And so being at the frontier puts you at the innovation frontier and, and, uh, helps you drive that as well There is room for models of all sizes and capabilities. We have always, that's why we did Flash, Flash Light, Flash, et cetera. And I agree with you that you can develop very good product experiences with, uh, with not necessarily the, the most frontier model because they, uh, tend to be slower and more expensive too. So I think, I think... But I-- we care about the parade of frontier and, and, uh, so we are committed to doing all of that well.

Alex Kantrowitz 6:35 You said that developing the frontier gives you a look into what's coming.

Sundar Pichai 6:38 Yeah.

Alex Kantrowitz 6:39 What do you see on the horizon?

Sundar Pichai 6:40 Uh, y- you know, the exciting, what makes this, uh, moment so exciting is you, you, you, you build something which you think is a culmination of, like, months of work and you put it out, you know you already see clear headroom ahead, right? I think... I mean, the frontier is going to... We, we've all been working on these agentic long horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things, right? And, and so that's an example of an exciting, uh, paradigm, uh, underway. And, and it's also clear to me that users, both in consumer and enterprise, will have access to kind of some multi-agent framework for them working all the time doing things. And so, you know, it feels like a moment of infinite possibilities.

Alex Kantrowitz 7:40 You mentioned, uh, recursive self-improvement. This is the models, uh, effectively making themselves better-

Sundar Pichai 7:45 Yeah

Alex Kantrowitz 7:46 ... maybe without humans in the loop. Um, people call it, like, an intelligence explosion or expect to hear this sound like foom, and then all of a sudden AI is just, like, this superhuman, uh, capability. And in fact, uh, I think Sergey was, um, doing this roundtable with researchers at DeepMind.

Sundar Pichai 8:03 Yeah.

Alex Kantrowitz 8:04 And he talked about with Argon, um, that the core, uh, one of the core innovations for Argon was relying more on the model to help develop the model, right? Um, we've seen what's gone on with AI models recently. They are not-- They are well-aligned, but they're not perfectly aligned, and the imperfections are a big problem. Um, obviously the tech world, and now the world more broadly, knows about the Hugging Face incident where OpenAI's bots, uh, broke containment and hacked into Hugging Face and did some crazy stuff. Google, uh, has also had a scenario where its bots, uh, got access, I think they were guessing passwords, and they got access to a site they shouldn't have. They stopped. But these models, there are, there's enough evidence that they're not doing exactly what we want them to be doing, that this idea of pursuing this recursive self-improvement or even, um, making the models better much faster, uh, is, it's sort of freaky. It, it makes me scared. Um, don't you think f- uh, there's reasonable worry here and there should be something done to, um, have the tech industry chill out about this?

Sundar Pichai 9:18 Well, maybe three parts to your question. Let's, first, let's talk about RSI itself, and-

Alex Kantrowitz 9:24 Mm-hmm

Sundar Pichai 9:24 ... you know, you, you're right, Sergey mentioned, um, uh, you know, RSI being, you know, critical contributor as we are developing Argon, and... But to be very clear, today, you know, in a continuum of, we are pretty far from, uh, you know, the end state of RSI or something like that, right? So today you have the, the right way to describe it is you have RSI loops along with AI researchers in various aspects of model development, right? So, you know, I would say you almost have agents helping AI researchers, uh, in, in some automated way, uh, work together to build these models. So I think, I think it's good to at least understand where we are today, and it's super exciting, and I expect that continuum to keep making progress as we go into next year. Uh, the second question is around safety. Look, I, the way we are, I mean, so safe- security comes from a difference in depth. You're talking about alignment. Obviously, you know, we all are doing a lot of work to m-make sure the models are, uh, as aligned as possible, but it's an active area of research and there are clear gaps. But that's not the only thing we rely on, right? So you have the work you do on alignment, but beyond that, you know, we, we put a lot of effort into, uh, real-time monitoring as these models are working, so making sure you have good telemetry into what's happening and so that you can intervene in real time if they are, if you see unexpected behaviors. And how you do that, uh, the architecture with which you do that, how do you make sure it's all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring? These are all areas of investment we are doing, uh, uh, doing. And obviously, when we deploy these models, giving customers, enterprises control, both with real-time monitoring, but their ability to decide where they deploy, what type of data these models ever have access to-

Alex Kantrowitz 11:32 Mm-hmm

Sundar Pichai 11:32 ... et cetera. So all that work is very, very important, and we are doing a lot of that with, uh, with Argon. So I think a- as an industry, we need to constantly up our game and take the time to do all this well, including dedicating the compute required to, to make sure you can safely deploy these models. The third part is, you know, uh, is it all enough? And, you know... So I think, I think this is why I think, you know, there's a lot of conversations in the industry, and I think it's reasonable to be worried, but, you know, I won't- The right way to approach, uh, something you worry about it is early on thinking about what more we can do. And I think all of us are you, you, you know, I think as an industry, I think you're definitely, uh, seeing an increased levels of work on alignment, uh, testing for safety, et cetera, as we deploy these models. I think the next step would be developing better standards so there are cross-industry standards of how we do these things, including ability to, uh, evaluate using independent evaluators. You know, if you look at areas like financial controls, we have like accounting standards, we have independent auditors, et cetera, right? So those are all the next natural steps for us as an industry to work towards this, and regulation will end up playing a role as we go through all of that as well.

Alex Kantrowitz 12:58 Okay, technology question for you. Um, Google is somewhat unique in that you research the language or the LLM side of the equation, which started with, you know, the transformer language, uh, and then you also pursue world models. And, you know, there are some AI research efforts out there like OpenAI that have basically determined that the LLM is the path to AGI, and they've actually, um, subset part of their world model research, which is like the AI model that tries to understand the physical world. Uh, but you're pursuing both. So talk a little bit about why you make-- why you find the world model side to be important.

Sundar Pichai 13:39 You know, I mean, uh, as humans, you obviously perceive the world around you and, you know, you're taking all those inputs, um, you know, making sure these models are able to understand the laws of physics, uh, simulate the world in high fidelity. All that I think are key enabling blocks for intelligence. And, and I think I see a working-- we are working across all possible applications of this. Uh, you know, take an area like robotics. It's not an accident Argon, if you look at, uh, you know, embodied reasoning benchmarks, Argon is state-of-the-art, right?

Alex Kantrowitz 14:14 Mm-hmm.

Sundar Pichai 14:14 I think it literally sold on many of these benchmarks. And that all comes from, you know, our experience building world models as well. So inherently, I would expect, you know, there will be architectures which will converge all of this in the future, but I think it's for us, we view this as today, um, you know, in this jagged frontier that is intelligence, we want to be at the frontier of all the, uh, all the possible approaches, and I think that will, uh, help us both drive better research, better insights, and develop a much better, uh, you know, AGI model, uh, you know, is how we think about

Sundar Pichai 14:56 it.

Alex Kantrowitz 14:56 Yeah, I looked at your, your Twitter after the Argon, uh, announcement, and it's all just like real world applications.

Sundar Pichai 15:02 That's right.

Alex Kantrowitz 15:03 It's not like text or, uh, you know, an, a model generating text. Okay. I, I wanna talk to you about the way that you balance, uh, allocating, uh, compute, which is your most precious resource, between cloud and AI research. This is a big topic about Google. Um, I've had people suggest to me that Google should, uh, get out of the AI research game and, um, you know, take all of its cloud computing resources and its chips and just sell that. And you look at the world of business right now, and Nvidia, which is like just doing that effectively, uh, $5 trillion company. Um, there's a push and pull between cloud that wants to, you know, sell these, the, this computing resource at a high markup, uh, and AI research that needs a very big computer to make the best AI. Now, you've said a big part of your job is figuring out how to allocate compute. Um, w- how do you do this, and how do you balance these two?

Sundar Pichai 15:59 Look, I think we are, um, look, uh, the ground zero for us is making sure we are investing in the compute that's needed to be at the AI frontier. So that is, you know, miss-- in twenty fifteen I set the company to be AI first. So AI is that key horizontal ingredient across everything we do, all the way from search to cloud to Waymo to everything we do. So I think that is ground zero for us, uh, making sure both for research and developing the models that we have enough compute needed. Beyond that, look, we have these independent businesses which each have their own long-range plans, and so they, they're using those long-range plans to project forward, and we plan for compute for all of them. And so the cloud team, you know, they have a business, and they have a projection, and they have demand signals. They've committed contracts. So with that help, we can plan on a long-term compute trajectory for them. Um, I think we are fortunate to have this wide set of opportunities. I think there's no company in the world which isn't making trade-offs at any given moment in time. But the first principles we operate on is to making sure we have enough compute to invest in the frontier, and that's non-negotiable, and everything else works, uh, works on top of that.

Alex Kantrowitz 17:25 Right.

Sundar Pichai 17:27 I think what you're seeing in these conversations is if you sit now, remember, we are building our own compute, our own data centers, so there's long lead times. So the compute we have today is a function of decisions I made in twenty twenty-four. Even if you think back to a year from today, last year, the agentic coding takeoff hadn't happened. So today, obviously, when you sit and look at anything, everyone is short, not just us, other companies, and everyone wishes you had two X of what you had planned for. I think that comes with the territory, right? And like, you know, at any given moment in time, we are planning for what we would need two to three years out in the future. So I think, I think you're going to find some decisions you make may look suboptimal two years out, right? Depending on where the state of the art is. So, so that, you know, I don't spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is a, is cutting-edge in terms of compute access, right?

Alex Kantrowitz 18:35 Mm-hmm.

Sundar Pichai 18:36 And after that, we plan for all our businesses. I think it's great we can provide our compute to other people too, like we have, we have done. It allows us to scale that up, get real tests for it in the widest application set possible, you know, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well.

Alex Kantrowitz 18:57 Um, you know, briefly, there was a, a podcast where, uh, Ben Horowitz relayed that Andy Jassy had said something like, "Compute is sold out till 2028."

Sundar Pichai 19:06 Yeah.

Alex Kantrowitz 19:06 Are you seeing the same thing?

Sundar Pichai 19:08 Um, you know, I think it's, uh, yeah, it's a reasonable... Like, you know, if, if today a customer is coming out and asking us for compute in, uh, '27, that is, uh, incredibly difficult to do. Um, you know, there, there's, uh, part of the reason even last year we went out and leased some short-term compute was to accommodate some customers and help them out. Uh, but yes, yeah, we- I think we are all dealing with similar, similar timelines.

Alex Kantrowitz 19:37 Um, one bubble question.

Sundar Pichai 19:39 Mm-hmm.

Alex Kantrowitz 19:39 Uh, there's talk of how every technology shift has seen overbuilding.

Sundar Pichai 19:44 Mm-hmm.

Alex Kantrowitz 19:45 Um, railroads.

Sundar Pichai 19:47 Mm-hmm.

Alex Kantrowitz 19:47 Fiber.

Sundar Pichai 19:47 Mm-hmm.

Alex Kantrowitz 19:48 Um, do you think there's overbuilding here?

Sundar Pichai 19:53 Uh, it depends on the timeframes you're looking at. Uh, are we, you know, this level of build, you know, if I take a long enough timeframe, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber, it's not dark. We are using it. We are capacity constrained on a daily basis. Um, the applications, the underlying technology is improving rapidly, right? But running a company, I... The way I work through the moment is you look at your demand signals, you look at your, uh, like, committed revenue opportunities that you're getting in the forms of contracts. You balance that with, like, the underlying technical capability, our internal evals, how we are using it internally, the model trajectories, and based on all that, you take a disciplined approach, a confident, aggressive, but, you know, a disciplined approach to plan out, plan out compute. But when you talk about the broader economy as a whole, you're, you're ha- having people operate with very various levels of, uh, uh, risk and, and so, you know, so it's tough for me to f- I focus on what I can control as a company and, and plan through it. Uh, if your question is, is the, uh, can there be an overbuild? Yes, because, you know, you can have some constrained components, and remember, what matters is a square set of everything you need to build out that compute.

Alex Kantrowitz 21:25 Memory, electricity, electricians.

Sundar Pichai 21:27 Yeah.

Alex Kantrowitz 21:27 Like land.

Sundar Pichai 21:28 There are like 2,000 components-

Alex Kantrowitz 21:29 Yeah

Sundar Pichai 21:30 ... or more, right? And so, so you could be c- you could get constrained at some point. There could be things which cause bottlenecks and, you know, and then you could have, uh, overbuilds. There could be external shocks, right, to the economy, et cetera. So there are macro risks. Uh, all, all, all that is possible at any given time, but, you know, y- you... Am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes.

Alex Kantrowitz 22:01 Okay, one more on this. Um, you know, if you're gonna do both, uh, there's been a line of thinking out there that, uh, AI researchers, for them, it's like the bigger the computer, the better the AI. And if, you know, you're someone... I was in the room when you said that AI would be as profound as fire and electricity, and, uh, we all laughed at the time, and I kind of regret that laugh now. Um, but if you're someone that actually believes that, then th- the thinking would be, um, you give the researchers the biggest possible computer, even if it is to the detriment of today's profits, like the Cloud business. Your thoughts?

Sundar Pichai 22:41 We're all doing some form of that, right? I think, uh, our Cloud business is, at any given moment in time, foregoing short-term revenues because we are making compute trade-offs to support frontier AI development. So I think what you're saying is, is, is true already, right? And, and, uh, but you, you know, you wanna be thoughtful, right? Even our AI researchers, uh, you know, some constraints are also good. That's what inspires creativity, you know? That's what helps you come with the more efficient algorithmic breakthrough, maybe to use less memory, et cetera. So, you know, so, uh, what we are committed is, uh, to invest what's needed to stay at the frontier, right? That's how I think about it.

Alex Kantrowitz 23:35 I wonder what you think the future of the interface looks like, the way that we use computing in the future as AI starts to roll out. I was speaking with Greg Brockman, the president of OpenAI, about this a couple of months ago. He had a very interesting quote. Uh, he said, "What is the interface that you want? What is the product that you want? The answer is that you want no interface. You want no product. You want this to be what's the interface between you and me?" Basically saying, just talking, that if AI is that smart, there shouldn't be, like, a s- you know, maybe a screen or just so many buttons and things that you have to touch. Um, what is your view of what the interface looks like in the age of AI?

Sundar Pichai 24:13 The way I think about it is, uh, I do feel, you know, we-- computing historically has been humans adapting to computing With AI, it'll be the other way about. The technology will adapt seamlessly to how humans live and go about their day-to-day lives. So there's an aspect of it, um, you know, you want that AI to be able to speak to it when you want it to. It has context, it can, uh, be persistently running somewhere, give you continuity. You're not dealing with a lot of complexity. It's natural. Uh, all that makes sense to me. That doesn't mean it won't have an interface, however, to me. Um, look, today, for example, I mean, nowadays, I just, even in my phone, like, you know, the, the Gemini voice models are so good I can just press, press the microphone button. I can just ramble. That's why we call it Rambler, right? I can ramble. It kinda intelligently corrects with my personal context. So even my friends' names, like weird names, it kinda gets it right, even if it first guesses it wrong. It's amazing. It's that I, I'm not going and e- backspace editing once I, once I finish saying it, right? It's remarkable how good it's gotten. But there are gonna be moments you will need an interface. You know, you may want to be entertain yourself. You may wanna watch a video. Like, you know, so you may ask your AI to create something, and you'll wanna watch it, consume it, right? So I think the way I think about it is you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology's adapting to how you're working at any given moment in time.

Alex Kantrowitz 26:02 Yeah, I'm just gonna, um, play the OpenAI hits.

Sundar Pichai 26:04 Yeah.

Alex Kantrowitz 26:04 [chuckles] 'Cause, um, you know, last year you sent them into a code red.

Sundar Pichai 26:08 Yeah.

Alex Kantrowitz 26:08 I'm sure you know. Um, Gemini, uh, was doing very well, and OpenAI battened down the hatches. Um, and I was speaking with Sam Altman about the challenge from Google. What he said was he thought OpenAI would fend you off because they're building AI native, and I don't know if he said it specifically like this, but he implied Google is bolting on AI to existing products. What is your view of whether, um, you know, a bolt-on, I wonder if you would accept that framing, uh, can compete with an AI native product?

Sundar Pichai 26:42 Look, first of all, uh, I mean, it's a very dynamic moment. We are all pushing each other. Uh, I, I think-

Alex Kantrowitz 26:48 Mm-hmm

Sundar Pichai 26:48 ... OpenAI has pushed us hard as a company too. So this is not just, uh, you know, we, we are doing something to them alone, et cetera. Far from it.

Alex Kantrowitz 26:55 Yeah, you went into code red too. I mean, I know it's disputed about whether it was-

Sundar Pichai 26:59 But we've all-

Alex Kantrowitz 26:59 ... but a version of this

Sundar Pichai 26:59 ... I mean, it's been a, the AI moment all of a sudden to respond with varying levels of urgency at any given moment in time. Look, I, um, I think, you know, we, we are constantly building new products as well. I mean, Gemini was built from the ground up-

Alex Kantrowitz 27:15 Mm-hmm

Sundar Pichai 27:15 ... like, like as a product, the Gemini app I'm talking about. Or, you know, tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that, right? So you can always flip these questions back.

Alex Kantrowitz 27:32 Right.

Sundar Pichai 27:33 Right? So I don't think, I don't think of it that way. I mean, I think of it as you wanna build world-class product experiences, [chuckles] uh, that are AI native, and they are winning. And, uh, and some of it is adapting product, some of it is rethinking new experiences. So they will all be part of, uh, how you approach this moment.

Alex Kantrowitz 27:52 Talk a little bit about the way that you see the business of this AI interface in the future. So, um, for instance, if I'm asking my agent to go out and do something for me, and, um, it suggests a product, should it... I, I mean, maybe even if disclosed, does it get a cut of the sale if I make the sale? Or when you think about the way that you're gonna make money from these products, what's the plan?

Sundar Pichai 28:18 I think, you know, obviously, I'm gonna put enterprise aside. I think I-

Alex Kantrowitz 28:25 Okay. Yeah, consumer question

Sundar Pichai 28:26 ... uh, so, you know, if, if it's consumer, look, I think there are... Consumers are gonna increasingly value this technology. They're gonna meaningfully... I mean, take software developers today. I think developers are willing to pay for these coding models, right? And because it really help makes them more productive. Nobody would want to code the way they were coding three years ago or even, like, same time last year. So I think when you're delivering value, there's value to be had. I think history of consumer product shows if you build a consumer product, uh, I've never seen examples where consumer products really scale to billions of users, where people are using it intensely and hasn't had monetization to go along with it. If you're providing value to people, there is inherent value to be had.

Alex Kantrowitz 29:18 Totally.

Sundar Pichai 29:18 And so the nature of it may change, right? I think y- you're asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are gonna see value in that, and there's gonna be some mechanism by which it gets fleshed out. That's what an efficient, uh, system does. But I think what matters is that you're building those world-class consumer experiences, right?

Alex Kantrowitz 29:48 Mm-hmm.

Sundar Pichai 29:48 And so, um, am I answering your question? I just wanna make sure.

Alex Kantrowitz 29:53 Yeah, definitely.

Sundar Pichai 29:54 Yeah.

Alex Kantrowitz 29:54 Um, I promised myself one product feature request and one only.

Sundar Pichai 29:59 Yes.

Alex Kantrowitz 29:59 Here it goes. Um, is it possible to make search in Gmail powered by Gemini as good as search in Gmail that you access when you plug Gmail into your ChatGPT interface? What's going on here?

Sundar Pichai 30:18 Um, I think, you know, we, we have- One of the exciting things we announced recently is in a unified Gemini agent, uh, for enterprise, which we, we've announced, and we're bringing that to consumers, right? So these are, uh, persistent agents which run twenty-four/seven in the cloud. Like, you're spinning up a micro VM effectively for every query. Um, and, you know, from the runtime, the harness, the model, it's all a headless service, right? And it'll work everywhere, and it, it has your context with you.

Alex Kantrowitz 30:56 Mm-hmm.

Sundar Pichai 30:58 You can address this agent whether you're in wo-workspace, in Search, you know, in Gemini, all of it. So I think agents are going to drive this unification from a customer experience which, which people are looking for.

Alex Kantrowitz 31:14 Yep.

Sundar Pichai 31:14 And you are right. When we- when you have a broad product portfolio and you're moving forward fast, there are always areas where you're moving forward faster than some other areas. That, that, that's, that's, uh, valid feedback, right? And, uh, but we are putting a lot of time and effort into making sure as we build out our agentic experience, that unification and that capability works well across all these surfaces.

Alex Kantrowitz 31:38 Okay, that's a good answer to the interface question too.

Sundar Pichai 31:40 Yes, it is. Yeah.

Alex Kantrowitz 31:41 Uh,

Alex Kantrowitz 31:42 when people have thought about where Google, uh, plays next, a question comes up, you know, "Where's Google's Muse or its Dots product?" Uh, those have kinda come out of nowhere recently, and, uh, they've taken off.

Sundar Pichai 31:57 Yeah.

Alex Kantrowitz 31:57 You have a version of that. Um, do you, do you anticipate creating a new product that competes with, let's just say Muse, for instance?

Sundar Pichai 32:08 Um, look, uh, we already today-- So the way we have envisioned this, in fact, we, we, we describe Gemini, our goal with Gemini app to be a personal, proactive, and powerful assistant, right?

Alex Kantrowitz 32:23 Right.

Sundar Pichai 32:23 That's what, that's what we are working towards. And you saw us describe the early versions of it at Google I/O, um, uh, Google I/O this year with Spark. But effectively, already, you know, if you open the Gemini app as a pro or an ultra user, you see chat and task.

Alex Kantrowitz 32:40 Mm-hmm.

Sundar Pichai 32:40 And, and, and, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. And what we announced recently in our enterprise e-event, we are bringing that to consumers as well. But over time, so you will soon in Gemini, uh, you will be able to ask something, and that will... It's a continuum. You know, you don't need to think about whether you're asking a chat or a, a agentic task. It'll just kind of automatically, uh, do the right thing, and it can work persistently on the background securely and get things done for you. Already empirically, when I look at what's coming into Gemini in our app, about last year you would have tagged them, and most of them would have been chats. But as, you know, a steadily growing percentage is already agentic tasks-

Alex Kantrowitz 33:36 Mm.

Sundar Pichai 33:36 -in Gemini. And so, so yes, we are gonna bring, um, you know, personal agents to our consumers. It'll work in the Gemini app. It'll work in Google Search. It'll work in Gmail. You can, you can address it, call it, et cetera. But we will, you know, we, we wanna make sure we're getting it right. It'll be powered by Argon, and so we are very excited to, uh, bring it to our users.

Alex Kantrowitz 33:59 I've got that Pro subscription. I'm in tasks, so I'm looking forward to using it more. Uh, all right. Couple of random questions. Uh, Google's committed and invest- in-invested and has committed, um, tens of billions of dollars, uh, to Anthropic. Uh, what do you see in Dario that makes you wanna have such a deep commitment and investment to him?

Sundar Pichai 34:20 Very early on, uh, when we looked at the founding team of Anthropic, it was very clear to us, um, you know, this was a world-class team which was involved in some of the earliest GPD models. And so we were quickly able to assess that, you know, they, they would be at the frontier. And so we've always tried to identify, uh, a-and partner with companies which would be at the cutting edge of technology. We've done that with SpaceX. We have done that with Anthropic, and, uh, you know, that's what we saw. And, uh, we had a chance to partner. Some of the partnerships turned in the construct of our, uh, TPUs as well. So I, I, uh, so I think, uh, that, that's how we approach

Sundar Pichai 35:03 it.

Alex Kantrowitz 35:04 Okay. With, with Apple, you had a partnership with them to license Gemini to them, uh, to help improve Siri. Is that partnership expanding, contracting, standing still?

Sundar Pichai 35:14 I mean, we are, uh, uh... Look, both, for both us and Apple, that partnership was about translating the capabilities of AI into better experiences for, uh, uh, for, for users. And, uh, you know, I thought H-Apple has done a, uh, a phenomenal job of incorporating. They customize these models and build it into, uh, Siri, and, uh, it's been great to see the reception, and, uh, so we are committed to doing more.

Alex Kantrowitz 35:43 You're gonna do more with them?

Sundar Pichai 35:44 There's nothing specific to comment, but, you know, I mean, it's a, it's a partnership that's working well.

Alex Kantrowitz 35:49 Uh, data centers in space, uh, you've announced that you have, uh, you're doing more there. What have you learned so far about the feasibility of that project?

Sundar Pichai 36:00 I mean, it's a, it's a very exciting project. You know, projects like this remind me, I still recall that moment in, uh, in the desert, uh, for the DARPA Grand Challenge, watching the Stanley car, uh, you know, compete in it, uh, which ended up being the basis for Waymo, uh, right? And so you're always, with all these technologies, you're, you're at a moment in time where it looks a bit like sci-fi, but, you know, ten to twenty years down the line, it's actually working, uh, in a meaningful way. I feel the same with space. You know, we- I've always believed in betting big on these technologies. Quantum has been an, a great example of it. Uh, we are probably 10 years into the journey. Waymo, we are about almost 20 years into the journey. Space, we are two to three years into the journey, right? And, uh, it's, it's clear to me that i- it, it's an approach which will make a lot of sense in the future, uh, being in sun synchronous orbits with, uh, universe, you know, 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. But having said that, I mean, this is a challenging project. The team has disciplined milestones, and so it was a super exciting milestone to send the TPUs up to space. And sometime as we are speaking, we are expecting a hello world moment, uh, from them. And so I look forward to, uh, uh, you know, uh, to seeing that happen, and we'll continue investing here too.

Alex Kantrowitz 37:32 You've re- you recently, was it maybe last year, you said that 25% of code, uh, written within Google was written by AI. What's the number today?

Sundar Pichai 37:41 I mean, we are far... I think we have almost... That number in our world today is, like, meaningless in the sense that every part of code we now touch-

Alex Kantrowitz 37:51 Mm-hmm

Sundar Pichai 37:51 ... is, uh, influenced by AI deeply. What's now what we are exa- uh, we are tracking with Argon, for example, we are now able to see it's been a point of inflection. People are using Argon to really go tackle complex projects, right? And including projects which affects millions of lines of code. So we have definitely, in the four weeks since we have launched Argon, we have seen a 30% increase in, uh, CLs and, and, and more importantly, uh, almost a similar increase, you know, one-third, uh, one-third decrease in, like, rollbacks, right? And so I think people are writing code more productively and better code with it, uh, code with it. So I think, uh, I think, so we are tracking it with newer metrics now.

Alex Kantrowitz 38:41 Um, you know, talking about the opposition to data centers, and how do you feel that? Um, and if you can't build data centers in the US the way that you want to, where else do you go?

Sundar Pichai 38:54 We're, you know, we are very committed to building our data centers very responsibly. I think if, when I look at our largest data centers in some of the communities where we have been the longest, uh, you know, I, I visit them, I talk to people.

Alex Kantrowitz 39:08 Mm-hmm.

Sundar Pichai 39:08 You know, people who, who would come and tell us their kids have gone to college because of our investments in these communities. And so, and we've grown in those communities. And so I think to me, this is about doing it right, you know, being, engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover the 100% the cost of our power needs, uh, for these projects. It's understanding the impact on the, on neighborhoods and making sure you're working early to address them, et cetera. So I think done rightly, uh, you know, I think, I think, uh, you can continue making progress. But, you know, we-- this is obviously we, we are constantly taking feedback into account and, and, and so on. I do worry not everyone operates, uh, the same way. Um-

Alex Kantrowitz 40:01 Yeah, people have been surprised by data centers showing up in their backyard.

Sundar Pichai 40:04 So I think, I think those are all important to-

Alex Kantrowitz 40:06 Mm-hmm

Sundar Pichai 40:07 ... uh, as an industry, we should continue to do better. But part of the reason for, in a 20-year timeframe, we are thinking about things like da- data centers in space is making sure we, you know, we are able to put these data centers where, you know, where maybe the trade-offs will be different.

Alex Kantrowitz 40:24 Is there an unproven discipline in AI right now that Google is working hardest to crack? So people have talked about continuous learning, getting these AIs to continue to update after they get released, as opposed to forget a- through every session.

Sundar Pichai 40:38 Look, there are multiple parallel bets. I mean, you saw with Argon we have a, a million output tokens, right? You know, uh, you know, with our Gemini models early on, we had a one million context window on the input side, right? These are all, uh, examples of breakthroughs we are constantly working on. You know, how do you think about synthetic data? How do you think about continual learning? There are, uh, how do you think about more efficient architectures? So part of... We do dedicate a, a, a meaningful percentage of our compute to these research bets too.

Alex Kantrowitz 41:15 Mm-hmm.

Sundar Pichai 41:15 And so it's always, uh, uh, you know, it always goes hand in hand, including our world models, et cetera, right?

Alex Kantrowitz 41:22 Right.

Sundar Pichai 41:23 So those are all bets we are, uh, uh, placing on. Sometimes as part of these bets, there are ideas that emerge which just make their way into the mainline models, and so maybe, you know, uh, you don't, uh, uh, you know, fully, fully, uh, talk about it. But, you know, I, I think we have multiple bets in these areas.

Alex Kantrowitz 41:42 Okay, I wanna end with this. Um, to be involved in the tech industry the way that you are, there's a, there's a certain inherent optimism-

Sundar Pichai 41:49 Mm-hmm

Alex Kantrowitz 41:49 ... to it, right? A belief that, uh, if you build, you will improve the world. And this is, you know, something deep within the tech industry. Now, there are sides to that, right? If you-- It requires betting, oftentimes, like betting a lot and hoping that the thing that you're working on is gonna come to fruition, uh, in the way that you want it to be. Uh, but it doesn't always work that way. I'll give you an example. Um, I was just visiting El Salvador for the first... Well, I, I went in a five-year bracket, and I saw, um, in this one town, uh, just a, a amazing amount of, uh, enthusiasm for Bitcoin and the blockchain, and there was a construction happening, and it was booming, and then it didn't happen the way that, that folks expected. Uh, and this visit was basically a ghost town with a lot of unfinished construction projects. Um- I think that, that to, to do what you do, there-- it requires, you know, a type of optimism that says it's worth going for, you know, even if, um, the bets don't pan out and, uh, and there could be consequences there. So I'd, I'd just love to hear your perspective on... You spoke about this at your Stanford commencement address, about the need for optimism, um, but it's a nuanced form of optimism, right? So I'd love to hear your perspective on, um, sort of how you maintain that and, and is it like a pure optimism or is it a, a couched optimism in a way?

Sundar Pichai 43:13 Look, I think, uh, uh, I genuinely have a deep conviction that, uh, you know, that, you know, improving technology and improving access to technology makes people's lives better. It's been my personal experience in my life, so out of which comes that deep conviction optimism. But with that, I've always felt, you know, humanity's journey is always about working hard to harness the technology to make it work well for society. So the optimism is not an optimism that you just build whatever you want, whenever, you know? No. You, you work hard to make sure you're building technology in the service of humanity to, to make, uh, the human condition better. And, and that's got to be the defining goal as we are approaching it. And with that framework, I'm very, very optimistic. And I think we are in very early stages of the kind of progress that we are going to see on many areas. You know, we are all talking about areas like healthcare and stuff, but, you know, I think a lot of the progress is ahead, and the ability to make things in a fundamentally cheaper way on, on many, many things where things are, things have been getting expensive for a long, long time, discovering new materials, et cetera, which really bend the curve. I think, I think it's tough to step today and understand the impact of all that, but they're gonna be very profound. So I'm very optimistic. Uh, but, you know, we have to be rightfully concerned about all the ways this technology can go wrong, and that's how you make sure you, you, you solve those concerns. So I think, I think they both go hand in hand.

Alex Kantrowitz 45:00 Well, Sundar, uh, I know you don't do many of these. I really appreciate you spending the time with me today, and it was great to get a chance to see you and speak with you again.

Sundar Pichai 45:07 Thanks, Alex. I appreciate it. Thanks.

Alex Kantrowitz 45:09 Bye everybody. Thanks so much for listening and watching, and we'll see you next time on Big Technology Podcast. [outro music]