You can listen to the Sundar Pichai, CEO of Alphabet | The All-In Interview using Speak’s shareable media player:
Sundar Pichai, CEO of Alphabet | The All-In Interview Podcast Episode Description
(0:00) David Friedberg welcomes Alphabet CEO Sundar Pichai
(2:18) Will AI kill search?: Google disrupting itself, evolving search to follow the user
(15:32) Infrastructure advantage, foundational model differentiation
(25:08) Future of human-computer interaction, hardware, competitive landscape in AI
(35:29) Energy constraints in AI
(41:20) Google’s progress in quantum computing and robotics
(47:56) Culture, coddling, and talent recruitment in the age of AI
(56:50) Does he consider Alphabet a holding company searching for Google’s next $100B business?
Follow Sundar:
https://x.com/sundarpichai
Follow the besties:
https://x.com/chamath
https://x.com/Jason
https://x.com/DavidSacks
https://x.com/friedberg
Follow on X:
https://x.com/theallinpod
Follow on Instagram:
https://www.instagram.com/theallinpod
Follow on TikTok:
@theallinpod
Follow on LinkedIn:
https://www.linkedin.com/company/allinpod
Intro Music Credit:
https://rb.gy/tppkzl
https://x.com/yung_spielburg
Intro Video Credit:
https://x.com/TheZachEffect
This interactive media player was created automatically by Speak. Want to generate intelligent media players yourself? Sign up for Speak!
Sundar Pichai, CEO of Alphabet | The All-In Interview Podcast Episode Top Keywords
Sundar Pichai, CEO of Alphabet | The All-In Interview Podcast Episode Summary
In this podcast episode, the discussion centers around the transformative role of AI in a major tech company, highlighting its impact across various business sectors such as search, YouTube, cloud services, and autonomous vehicles. The speaker emphasizes the company’s strategic positioning as a leader in AI technology, which is seen as a horizontal force capable of enhancing all aspects of the business. The conversation touches on the company’s culture, noting a shift from early perks like free food and massages to a focus on innovation and accountability. The speaker reflects on the importance of maintaining a positive and empowering work environment to foster creativity and progress.
The episode also explores the competitive landscape, with mentions of other tech giants and their leaders, such as Meta, Microsoft, and OpenAI. The speaker acknowledges the challenges posed by these competitors but remains confident in the company’s infrastructure and talent as key advantages. The discussion includes insights into the evolving nature of search and human-computer interaction, predicting a future where AI plays a central role in accessing information.
Actionable insights include the importance of maintaining a clear mission focus, empowering employees, and continuously innovating to stay ahead in the industry. The speaker also highlights the need for companies to adapt to technological shifts, such as the transition to mobile and the rise of AI, by leaning into innovation rather than viewing it as a dilemma.
Recurring themes include the significance of AI as a transformative technology, the need for a strong company culture that supports innovation, and the importance of strategic leadership in navigating competitive pressures and technological advancements. Overall, the episode conveys an optimistic outlook on the future of AI and its potential to drive significant progress across various sectors.
This summary was created automatically by Speak. Want to transcribe, analyze and summarize yourself? Sign up for Speak!
Sundar Pichai, CEO of Alphabet | The All-In Interview Podcast Episode Transcript (Unedited)
Speaker: 0
00:04
We’re sitting here at the Googleplex with the CEO of Alphabet, Sundar. Thanks for being here.
Speaker: 1
00:09
Great to have you here, David. Look forward to it.
Speaker: 0
00:11
Is Google at risk of being truly disrupted from AI?
Speaker: 1
00:15
Recently, we are testing it in labs. This whole new dedicated AI experience called AI mode coming to search.
Speaker: 0
00:20
OpenAI has Ram. Ai has Elon. Yeah. Meta has Zuck. Microsoft has Satya. Are you willing to kinda share your perspectives on those four competitors?
Speaker: 1
00:30
I think maybe only one of them has invited me to a dance, not the others.
Speaker: 0
00:33
Biggest regret?
Speaker: 1
00:35
Look, there are acquisitions. We debated hard, came close.
Speaker: 0
00:39
Just give me one name.
Speaker: 1
00:41
We’ll get in trouble. Maybe Netflix. We just lean into the user experience, and over time, we figured out monetization to follow.
Speaker: 0
00:49
It’s ai one of the original principles of Google Yeah. Follow the user. All of the people follow.
Speaker: 1
00:54
Yeah. There you go.
Speaker: 0
00:55
I’m doing all of it. Ai, besties. I think that was another epic discussion. People love the interviews. I could hear and talk for hours. Absolutely. We crushed your questions in May. We are giving people ground truth data to underwrite your own opinion. What’d you guys say? That was fun. I’m doing all in.
Speaker: 0
01:13
I’m really excited for this conversation. You and I started working at Google on the same day in 02/2004.
Speaker: 1
01:20
I didn’t quite realize that.
Speaker: 0
01:21
We’re both
Speaker: 1
01:22
at the same time.
Speaker: 0
01:23
Same Noogler class. We had the the hats on that same week
Speaker: 1
01:25
Yeah. On the
Speaker: 0
01:26
Ai, all hands. I’m now a podcaster. You’ve done a little bit differently.
Speaker: 1
01:30
You’re more than
Speaker: 0
01:32
a podcaster.
Speaker: 1
01:32
Yeah. But, you’re very good at podcasting too.
Speaker: 0
01:34
Well, I appreciate it.
Speaker: 1
01:36
I think I respect the other stuff you’ve done as well.
Speaker: 0
01:38
So No. I appreciate it. But in your tenure at Google, you ran Chrome, Chrome OS Ai, Google Maps, and it’s been ten years now since you’ve been the CEO here at Google Now Alphabet. Amazing, and congratulations. Under your tenure as CEO, the stock has gone up by four and a half x to a $2,000,000,000,000 market cap today.
Speaker: 0
01:59
You’ve grown revenue from 20,000,000,000 a quarter to nearly a hundred billion a quarter. It’s been a really, like, incredible run to see someone that kind of started as a a PM and Yeah. You know, grew your way into this incredible role. So congrats. Have you liked the job?
Speaker: 1
02:15
No. Look. I mean, I love building products.
Speaker: 0
02:18
Yep.
Speaker: 1
02:19
And in some ways, you know, Google was really set up I think the founders set up this kind of a deep computer science approach, and, like, you take that and apply it to build things which can impact people on a day to day basis. And so, you know, it’s that kind of a product and, technical culture, which, you know, is is the essence of the company.
Speaker: 1
02:42
So I love doing that, and, you know, there’s not a single week which goes by, but I I feel like I don’t get to do that. So those are the parts I really enjoy. But, obviously, you know, running a company of this scale where you impact, so many people. I think it’s a privilege, so enjoyed every part of it.
Speaker: 0
02:58
You’re at a pivotal moment in the company’s history today. Have you read the innovator’s dilemma?
Speaker: 1
03:04
You know, Ai I I I’m obviously very, very familiar with the concept. I don’t think I’ve read the book, actually, but but, you know, it’s one of those things which is so much in the ether. You think you know it. You know? Ai
Speaker: 0
03:14
I say it in jest because that’s the talk of the town, the talk on Wall Street, the talk in Silicon Valley. Is Google getting disrupted in this moment? AI seems to create a fundamentally different paradigm for human computer interaction.
Speaker: 1
03:27
Mhmm.
Speaker: 0
03:28
Consumers are asking AI questions through chat interfaces. They’re getting complete answers. They’re engaging with AI systems in a way that they traditionally didn’t do with the classical search interface. Is Google at risk of being truly disrupted from AI is the core search business, which the ad revenue in search is about a $200,000,000,000 run rate Mhmm.
Speaker: 1
03:47
Out
Speaker: 0
03:47
of 360,000,000,000 of your total revenue, most of your profits. And it seems like Google’s in a really challenging quandary where if you disrupt yourself too quickly, all of that revenue can go away, can be really impactful. So is Google being disrupted by AI at this moment, or is Google leading?
Speaker: 1
04:05
It’s a good frame, a good question to talk about. You know, I’ve definitely, you know, for almost a decade, you know, one of the first things I did was to think of the company as AI first. It was very clear to us. We had Google Brain underway in 2012. We acquired DeepMind in 2014.
Speaker: 1
04:22
’20 ’15, when I became the CEO, I said, look, the technology is really evolving. The reason we were excited to be approach our work as AI first, is because we really felt that AI is what will drive the biggest progress in Search. And so Ai think even the last couple of years, I viewed this as an extraordinary opportunity for Search.
Speaker: 1
04:44
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. And we are seeing it empirically when people are using search.
Speaker: 1
05:03
Obviously, there are a couple of major things, we have done with search. You know, transformers drove some of the biggest innovations in search with BERT and Meh, dramatically improved search quality. We we launched Ai overviews about a year ago. It’s now being used by over one and a half billion users, in over a 50 countries.
Speaker: 1
05:25
It’s expanding the types of queries people can type in, and we see it empirically. The nature of queries has expanded. So there are whole new use cases coming into search. We find for queries where we trigger AI overuse, you know, we see query growth, and the growth continues over time.
Speaker: 1
05:45
You know, getting the feedback from AI overviews, we are you know, we we’ve recently been testing it in labs. This whole new dedicated AI experience called AI mode coming to search. We’ll speak about it more at Google IO. And in AI mode, you can have a full on AI experience in in search, including follow on conversational queries.
Speaker: 1
06:05
And we’re 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 and there, the queries, people are typing in queries, like, literally long paragraphs. Right? The average query length is somewhere two to three ai.
Speaker: 1
06:25
It’s what we see in, search as it existed, two years ago. So we are seeing people respond. In search is always from the outside, people look at it and say search, oh, kinda 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, we you know, you’ve been here.
Speaker: 1
06:47
We we are kind of a very metrics driven company. We kinda know what works. Users are our North Shah. And empirically we see that people are engaging more and using the product more, right? So all that, to your question about innovators dilemma, I think the dilemma only exists if you treat it as a dilemma, right?
Speaker: 1
07:08
Like, you know, sai for meh, all along in technology, you have these massive periods of innovation and you lean into it as hard as you can. It’s the only way to do it. You know, when mobile came, everyone was like, well, you know, it’s like you’re not gonna have the real estate.
Speaker: 1
07:23
Like, how will vatsal work? All that stuff. You know, mobile was a transition which ended up working great. I can give great examples. Right? Like, TikTok has come in.
Speaker: 1
07:33
YouTube has thrived since the moment TikTok has come in. Right? And, it was a whole new format. We we, did Shorts when we launched Shorts. Shorts absolutely didn’t monetize anywhere near long form, but we just lean into the user experience. And over time, we figured out monetization to follow.
Speaker: 1
07:55
So, you know, to me, you know, you don’t think about it as a dilemma, like, you know, because users, you have to innovate to stay ahead, and you kinda lean in that direction.
Speaker: 0
08:04
It’s ai one of the original principles of Google. Follow the user. All else will follow.
Speaker: 1
08:10
There you go.
Speaker: 0
08:10
And I think the the Google is dead disruptor narrative has, as you point out, been kind of repeated a number of times. Today, people are pointing specifically, and I appreciate your points about there’s new search experiences coming. The search experience, it sounds like, is going to evolve. Oh, yeah.
Speaker: 0
08:27
As people look at standalone apps, they compare Gemini as a standalone app to chat GPT, to the meta experience, the stats that came out in the recent court testimony that had some data revealed from March. I don’t know where the data came from, but it said the, Gemini AI app had 350,000,000 monthly users compared to ChatGPT at 600 and Meta AI at 500.
Speaker: 0
08:49
Is that the wrong way to think about it, that the Gemini standalone app isn’t the future or the AI bet that Google’s making? But it sounds like there’s gonna be much more of a kind of timed out integration into how the search experience evolves. And what happens to Gemini?
Speaker: 1
09:02
You know, in search, you know, maybe the most widely used Meh Sai product today might be search with Ai or views. Right? You know, people people are using it intensely. Obviously, we have a stand alone Gemini app. I think I think, we arya making progress there. Particularly with the introduction of Gemini 2.5 Pro, We have seen a real, uptake in engagement, and usage growth, in the product. We have a lot more to come.
Speaker: 1
09:32
Just in the last few weeks, we have shipped deep research and updated Canvas, audio overviews. You can now go and generate v do video generation with VO two straight in the Gemini app, on Android phones with Gemini Live. You know, you can screen share. It can talk to what’s on your screen. So the the you know, there’s a lot coming that way and, you know, users are responding.
Speaker: 1
09:57
Look, I ChargeGPD shah obviously had phenomenal success. You know, but but I think it’s still early days and, you know, we are definitely seeing traction, seeing growth. To me, what matters is if you innovate, our users responding and using it more, and that seems to be the case. So it’s in our hands to continue innovating.
Speaker: 1
10:18
Right? I think it’s a fiercely competent moment. But I would say across our products, people are coming and using and consuming information across search, using the Gemini model increasingly in YouTube, in the Gemini app, and so on. So I think I think it’s a much broader view we have.
Speaker: 0
10:36
If I were to think about the unit economics of Mhmm. Google’s business, there’s a cost to serve a search query, and there’s revenue per search query, ad revenue per search query. How is that number changing, or how will that change in this kind of evolution and search towards more of an AI interface?
Speaker: 0
10:55
Because I’ve got to assume that to serve an AI driven query is much more expensive than to serve a search ai.
Speaker: 1
11:03
Look. This is something I think, you know, people are really worried about, two years ago, but, you know, I’ve always felt to the extent that something is about the cost of serving it. Google with its infrastructure, I’d wager on ai. Sana our chances to do that better than pretty much anyone else.
Speaker: 1
11:22
And we’ve actually seen ai a given query, the cost to serve that ai has fallen dramatically in a eighteen month ai frame. What is probably more of a constraint is latency, I would say. So it’s less the cost per query. I think our ability to serve the experience at the right latency, you know, search has been near instant.
Speaker: 1
11:44
So how do you, think about that frontier has been more of a question. The cost per query is not what I think will end up, you know, I think I think we’ll be able to we’ve we’ve done the transition well. That’s that’s not a primary driver of how it’ll impact things. Yeah.
Speaker: 0
12:00
And do you have a point of view on ad revenue per AI query?
Speaker: 1
12:04
You know, we already with AI overviews. You know, we we are at the baseline of, you know, it’s it’s the same as without AI overviews. And so we’ve we’ve reached that stage in a so so but from there, we can improve. Right? And I think, you know, I’ve always felt, you know, the reason ads have worked well in search is because commercial information is also information.
Speaker: 1
12:27
People in when they have that intent are looking for that most relevant information. So 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? Ai? And so I think we are comfortable that we can work the transition through.
Speaker: 1
12:47
Some of it may take time, but all indicators are that we’ll be able to do it well.
Speaker: 0
12:51
Over ai.
Speaker: 1
12:52
Over time. But, you know, it’s already, you know, already AI overviews. When we show ads, we’ve kind of reached the baseline now.
Speaker: 0
12:58
Do you feel that pressure on Wall Street and the board and, like, what’s the tension that you feel as a leader in trying to manage this transition on the product, on the revenue model, for an organization of this scale? I don’t know how many leaders have done it successfully in the history of business. Where do you feel the tension? Where do you feel the pressure?
Speaker: 0
13:19
And how much leeway are you being given by the founders and the board to do what’s needed here?
Speaker: 1
13:24
Two things. I mean, the main, it’s a moment of acceleration. Right? So if anything, the good thing about these moments is you don’t even have time a lot of times to think about, you know, some of those questions. You are, I think I think a lot about making sure we have the best models.
Speaker: 1
13:39
We are at the we arya pushing the frontier as a company, and I think the last few months have shown the breadth and range of what we are doing. You know, we are there, and we have to continue to stay there. So for me, you know, you you think and you worry a lot more about execution from within. That’s all. You know, are we are we executing?
Speaker: 1
13:59
Are we moving fast? Are we innovating? And I think, you know, over the past twelve months, I think we’ve really picked up pace as a company and, you know, to to meet the moment. So that’s where I do spend a lot of time. Look.
Speaker: 1
14:11
As a as a CEO, one of the first things I did in 2015, in addition to being AI first was to really bet big on, you know, we had great products like YouTube. We had workspace and cloud, but really turning them into robust businesses, ai, as well as great products. Last year, we exited a combination of YouTube and cloud at $110,000,000,000 Ai think, you know, people don’t internalize that Google is one of the largest enterprise software companies in the world now.
Speaker: 1
14:40
And and so look, I think And
Speaker: 0
14:42
the largest media company.
Speaker: 1
14:44
You know, in in some ways. Right? And, you know, definitely we are doing a podcast. I think we are the largest podcasting service in the world. And so, you know, so I I feel like, you know, as a company, we are set up well. For the first time, we have this cross cutting technology.
Speaker: 1
14:58
You know, to to our earlier point, thinking of us as a deep computer science company, what better technology than AI, which horizontally can impact all aspects of our business? Search, YouTube, cloud, Waymo, and the other new things we are doing. So it feels like an exciting time.
Speaker: 1
15:15
So not a lot of what, know, we’ve continued to do well in search. We are doing well in these other businesses. And so to me, it feels like, you know, one of the biggest opportunities ahead as a company too. I think the next decade ahead looks to me as exciting as the past decade.
Speaker: 1
15:32
So As
Speaker: 0
15:33
I think about my time at Google, right below us in the garage, Urs and his team were building these super secret shipping container data centers. They had these, like, data center in a box that you could ship anywhere. As long as you had access to water and power, it could connect to the Internet, and you could scale data center capacity all over the world.
Speaker: 0
15:54
That was twenty years ago. It’s always seemed to me that one of Google’s core and not well understood advantages was its infrastructure advantage, something that Google’s invested in to its core from the beginning. Can you tell me a little bit about where you view Google’s infrastructure advantage playing out in the AI competitive landscape today?
Speaker: 0
16:19
How does it translate into cost, speed, product quality, and where do you guys think about investing the 70,000,000,000 of CapEx this year in the chip layer, in the networking, the data center?
Speaker: 1
16:34
We can unpack both. Right? Like, where our CapEx is going. But on your first part, right, like, one of the ways, you know, we look at the Pareto frontier of performance and cost. Google literally is on the Pareto frontier. So we deliver the best models at the most cost effective price point. Right? Like, you know and our flash series of models are a real workhorse, in the industry.
Speaker: 1
16:58
Right? And and part of why we are able to do that, is because, you know, we train and serve our models on our infrastructure, including TPUs. Right? And we are in our seventh generation of TPUs, and, we built our first version in 2017. I remember talking about it at Google IO.
Speaker: 1
17:19
Probably people didn’t pay attention to it because, like, you know, why are you building sai specific machine learning x rated chip? Look. It plays out everywhere to your earlier question on cost per query and search. The reason we feel comfortable we can serve it at that scale, is because we are constantly innovating through e generation, including chips which are really, really good at inference.
Speaker: 1
17:40
Right? And Ironwood, which is our latest in our TPUCs, a single part of Ironwood is over 40 exaflops. Right? And and so the scale of these things are incredible. And and we have thought about our info all the way from subsea cables to the scale at which we do infrastructure is unparalleled.
Speaker: 1
18:00
And I I’ve always viewed that full stack approach, you know, deep infrastructure, foundational meh r and 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 ai. But it really, you know, empirically plays out in, you know, the the cost at which we are able to provide our models.
Speaker: 1
18:24
Part of the reason we’ve had a lot of traction with Gemini 2.5 c is not only are they great models, but we are offering it at a very attractive value. And we can do that because, you know, we we keep we we are driving our infrastructure cost down. On the $75,000,000,000 in CapEx for, 2025, you know, obviously, majority of that goes into servers, data centers, and so on, servers being the vast portion of it.
Speaker: 1
18:54
I would I would say on on looking at 2025, and looking at the compute part of the, speak, half of that is going towards our cloud business in 2025. And, obviously, there is a very different, it’s a very different business to search and so on. So, a lot of it is to power the innovations in, from Google DeepMind pushing the frontier.
Speaker: 1
19:21
And we’re doing it across many dimensions, right, not just large language models, but, you know, even there, doing it across not just text, images, video, etcetera, building, world models. Right? So there’s just a lot of, innovation which we are pushing on the frontier, obviously, to support our core products ai Search, YouTube, Gemini, etcetera.
Speaker: 1
19:41
But 50% of the compute goes towards Google Cloud.
Speaker: 0
19:44
Let’s just talk about chips for a second. This is a big part of the conversation as NVIDIA’s got the real market monopoly in AI ai what everyone says. Do TPUs provide a wholesale replacement for your need for NVIDIA in the supply chain, or is NVIDIA still a core part of the mix in the data center for training versus inference, in LLMs versus other models?
Speaker: 0
20:06
Maybe just share your your understanding of where, like, the mix evolves to for you guys.
Speaker: 1
20:11
Look. First of all, ai level, NVIDIA is a phenomenal company. You know, Jensen is awesome. We 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, etcetera. Internally, we train our Gemini models on TPUs. Ai?
Speaker: 1
20:34
And and and we serve it that way across our products, but, we use both. And, I do think look. I I do think everyone in the industry is going to try and do something like that, but, but, you know, it’s it’s, you know, NVIDIA’s arya and d, and and their ability to drive that innovation, their software stack is world class.
Speaker: 1
20:55
So, you know, they have a lot of, advantages as a company, and I have, extraordinary respect for them. You know, but we’ve always had, you know, we are committed. You know, we are actually deploying GPUs internally as well. I think I like that flexibility and and, but I I I we are also long term committed to the TPU direction as well.
Speaker: 1
21:15
So I think it’s a good combination to have both, and and I think we push each other, you know, and drive the frontier forward.
Speaker: 0
21:24
Just going back, so there there’s an infrastructure advantage inherent in all of the investment that’s been made for twenty plus years and the continued investment. A lot of folks have said that some of the performance in foundational LLMs is kind of starting to plateau. And as a result, we’re seeing a less kind of differentiated landscape amongst the competitors, and that’s should be a consideration for Google. That’s the outside kind of narrative.
Speaker: 0
21:49
Can you share a little bit about and then I wanna come back to non LLM models
Speaker: 1
21:53
where
Speaker: 0
21:53
there’s other advantages for Google in a minute. But maybe just on this point, how much more, of an opportunity to continue to evolve LLMs is there? Where does Google’s advantage lie in maintaining better performance in the models over time?
Speaker: 1
22:09
I think maybe it was Andre Karpathy who used the term AJI, which is like he called it artificial jagged intelligence. Right? So I think the progress is not going to be always smooth. Right? Like, you you go through these periods. It looks like something saloni, and then you see a paradigm breakthrough, etcetera. And it’s been going like that for a while.
Speaker: 1
22:29
I think obviously over the last couple of years, you know, all of us scaled up on pre training. And then there was a lot of momentum with post training and then with inference compute, and and and now, you know, this progress with how do you take all that and stitch together in agentic workflows and, you know, and and and so on.
Speaker: 1
22:49
So I do think there’s a lot of progress, and it feels pretty continuous to me. Right? I think it’s both true progress gets harder, which I think will distinguish the elite teams at least on the foundational side. You know, I think I think I think that that might be a factor.
Speaker: 1
23:09
I felt the the heart of the problem is Ai think, you know, we are well set up for that. I think I think we are well set up for that. I do think we arya, pushing the research frontier in a much broader way than most other people beyond just LLMs, transformer based models, diffusion based models, all those areas we are exploring in a deep, deep way.
Speaker: 1
23:36
Right? Sai, and, you know, there’s always the chance that we may reach a point where, you know, you quite don’t get that returns to the additional compute you’re gonna put in, but I quite haven’t seen it yet. Right? The progress looks maybe harder because you’re now dealing with a lots more compute.
Speaker: 1
23:56
So you’re really running into the loss of like, can I actually get as many electricians as I can to build the data centers sai the speak? Ai, you know, all of that stuff. But I haven’t seen, or at least talking to our researchers, haven’t seen anything fundamentally, hey. Like, we arya not gonna be able to move past it, this point or something like that.
Speaker: 0
24:16
Does Google have a data advantage with YouTube or other products or services? Are you able to train on that data in a way that others can’t?
Speaker: 1
24:24
I think we have the opportunity to create much better experiences for people. I think people use products like Gmail, Calendar, Docs, YouTube, Search, etcetera. So with their permission, taking that personal context into account, I think we can deliver much better experiences.
Speaker: 1
24:40
We are working on that, but it’s it’s something on which we have to deliver. But I view that as one of the, differentiated innovation opportunities we have ahead as a company, but it’s something we are thoughtfully working on. We’ll make progress there.
Speaker: 0
24:55
That makes a lot of sense. If search evolves, and I’ve been using a lot of voice AI tools, I find them incredible. I can have a conversation, access the news Yeah. Dive deep on a topic. It’s just it’s so incredible. What do you view the future of human computer interaction being five to ten years from now as AI evolves, as computing evolves, am I looking at a screen?
Speaker: 0
25:21
Am I typing in a chat? Am I using an AirPod and just getting audio? Am I doing audio plus a screen? Is it just a personalized interface and there’s no even concept of the web? What what does the future look like for accessing information and pursuing my interest in life as a human using compute?
Speaker: 1
25:39
That’s a great question. I do think, you know, the answer has got to be you know, we’ve always humans have adapted to computing and it’s always been that way. But over time, the answer will be that you need to do less of the hard work, less of the adaptation, and computing kind of works for you. Right?
Speaker: 1
25:57
And that’s the holy grail, I think. And And we are making progress, right? Be it touch, be it voice, everything inches us towards this future. For example, when I wear AR glasses, I already wear glasses. Sai it’s not that, you know, but the AR glasses aren’t quite as comfortable as my normal glasses, but they’re getting there.
Speaker: 1
26:20
It’s obvious to me that vatsal push it to that next level of seamlessness where it kind of is ambiently there and doing stuff for you. So I think that’s the air of the air, you know, the air of, how it’ll you know, it has to be more seamless and just be there for you. You know, will it be ai Neuralink down the line? Right?
Speaker: 1
26:40
You know, like, you know, when I when I wanna understand something, you know, is it is it that seamless? Right? You know, I I think all of that is a possibility. But I think in the immediate world, given you’re going to have really natively multimodal models, which can take, you know, audio, vision, language, all of that and be there in your, line of view.
Speaker: 1
27:07
So I think when AR really works, I think that’ll wild people. I’m not talking about immersive displays. I’m talking more about AR glasses. Right? And I think I think that paradigm looks very interesting to me having used it.
Speaker: 1
27:22
You can kind of feel that next leap, right, where, I think we’ll all enjoy using it in a way. But you still have a little bit of system integration challenges to work through. So we have maybe couple ai away to get to that sweet spot, what smartphones were in around 02/2006, ‘2 thousand ‘7. So but maybe that’s the next leap. Right?
Speaker: 1
27:44
And and so probably that’s what’s exciting for me.
Speaker: 0
27:47
Are you spending a lot of time on hardware?
Speaker: 1
27:49
Yes. Right. I think we are definitely excited about be it AR classes, the next form factors. You know, robotics is another area, all that. And we obviously build pixel phones. You know, people vast data centers. So we are definitely in the physical world. You can think of Waymo as a big robot.
Speaker: 1
28:11
We are ai around everywhere. So we’re making, with our partners cars that way. So definitely, yes.
Speaker: 0
28:18
I just sana zoom out and look at there’s this competitive landscape that’s emerged for Google that maybe maybe it’s always been challenging. Maybe there’s always been competitors, but they’re getting a lot of money, and they’re investing a lot of money more than ever to compete with Google.
Speaker: 0
28:35
How have the founders of Google, I’ve seen both of them recently, sounds like Sergei’s spending time here. They both independently shared with me that this is the most exciting thing they’ve ever seen in computer ai, and it’s transforming everything. How engaged are they? How much time do you spend with them? And what’s your relationship like there?
Speaker: 1
28:54
They are, you know, obviously fortunate to have both of them involved in their own unique ways, deeply. I talk to them all the time. Look. I think both Larry and Sergey, I you know, you know, credit to them. They always envision, like, where AI would be. I think, you know, I think I think their ability to understand trends and, and, you know, I I swear I’ve had conversations maybe as early as, like, fifteen, twenty years ago about moments like this with them.
Speaker: 1
29:25
I think they are both would argue that this is the most exciting ai in the field. And they both engage in their own ways. I think Sergei is definitely spending time with the Gemini team at a, you know, in a pretty hardcore way, like, you know, sitting and coding and spending time with the engineers.
Speaker: 1
29:46
And that gives the energy to the team, which I think it’s unparalleled. Right? Like, to have a founder sitting there looking at loss curves, giving feedback on model architectures, how can we improve post training, etcetera. I think I think, you know, it’s a it’s a rare rare place to be.
Speaker: 1
30:04
But, you know, my favorite conversations are sometimes when the three of us sit and talk, the combination of I mean, they’re very nonlinear thinkers. So I feel like it expands the conversation into ways, which you always don’t speak, and out of it, which comes interesting ideas.
Speaker: 1
30:21
So I think I always have access to that. But I think I’ve worked with them, for such a long time. You know? It the you know, there is friendship, respect, vatsal dialogue. We love doing that, and, and I think it’s, we’ll I’ll always have that.
Speaker: 0
30:36
Your competitors out there have active founders. OpenAI has Ram. XAI has Elon.
Speaker: 1
30:43
Yeah.
Speaker: 0
30:43
Meta has Zuck, and, Microsoft has Satya. Are you willing to kinda share your perspectives on those four competitors, both the companies and the leaders?
Speaker: 1
30:53
Look, it’s a obviously, by by definition, it’s a very impressive group. Right? And, I think I think you’re talking about some of the best companies, some of the best entrepreneurs, all that. Look, I I, you know, shows how, both how much progress we are going to see because you’re basically talking about many people, who are working hard to drive that progress.
Speaker: 0
31:20
Right.
Speaker: 1
31:20
So to the earlier question when you were talking about, are we gonna see progress? The answer has got to be yes because of the, you know, the the the unique types of people here pushing progress. Right? Sai, look, each of them, they’re they’re different people. I I’m fortunate to know all of them, and I think maybe only one of them has invited me to a dance, not the others. Ai? But, I just look.
Speaker: 1
31:44
I spent time with Elon maybe two weeks ago, when I talked to him and his ability to build future technologies into existence. I think it’s just unparalleled. So, like, look. These are phenomenal people. I respect all of them. You know, there’s partnerships involved. There’s competition involved.
Speaker: 1
32:01
But if I were to step back and say, you know, at the end of the day, I love, you know, driving technology progress in a way that impacts people positively. When you think about areas like health care and and other important areas, education, you know, like, we are now talking about this is why AI is so profound.
Speaker: 1
32:25
So the opportunity is what excites me. I think, you know, all of us are going to do well in this scenario. That’s how I think about it.
Speaker: 0
32:32
Right. I think that’s what a lot of people don’t grok, and I think this is an important point. Everyone out there says there’s competitors, there’s a winner, and everyone else is a loser. But this is an entirely new world that’s gonna be a lot bigger than the world we had last year. Yeah.
Speaker: 0
32:46
And, everyone’s building down their own path, but there’s gonna be
Speaker: 1
32:49
I think about it.
Speaker: 0
32:50
A lot of success. It’s not just that who’s gonna beat whom in the in the marketplace.
Speaker: 1
32:55
When the Internet happened Right. Google wasn’t even around.
Speaker: 0
32:58
Right.
Speaker: 1
32:59
Right? So we obviously so the the other thing you can say is there are companies we don’t even know, haven’t been started meh. Their names aren’t known, might be extraordinarily big winners in the AI thing. Right? So it’s it’s going to be AI is a much bigger
Speaker: 0
33:18
Yeah.
Speaker: 1
33:19
Landscape, opportunity landscape than all the previous technologies we have known.
Speaker: 0
33:23
Combined.
Speaker: 1
33:23
Combined. Yeah. And so, you know, so which is why I think it’s all about, you know, the companies which will end up doing well arya will do well because you’re able to innovate and execute with the best talent in a that’s that ends up being the driver.
Speaker: 0
33:37
Well, let’s talk about that. Yeah. And let’s talk about the unknown competitor DeepSeek popped up. Tell me about your impressions of the model, the performance, the rumors about the next model. Yeah. And what does that tell you about what’s going on in China and what’s going on that we’re not seeing?
Speaker: 1
33:52
Look. I think the main moment from DeepSik was, look, always. You know, if you if you ai follow the AI research and scan through papers and read them, no nobody who does that would underestimate China. Right? Like, you know, so when you look at the amount of research output from China, right, they have extraordinary talent.
Speaker: 1
34:15
And and and so but I do think all of us had to adjust our priors a little bit after the deep speak moment, which was like, well, they are even closer to the frontier than most people maybe assume, you know. And so I think I think there was a moment. I think internally for us, I think externally people are very impressed and rightfully so with how efficient their models were.
Speaker: 1
34:39
Interestingly for us internally, we benchmarked it to flash and, you know, flash was, as efficient or, you know, you could argue in some ways better. So, you know, I think I think to our earlier conversations, I I do think this is more maybe internal baseball for us. We were benchmarking and saying, look, it’s good to sai, because they had to work in a hardware constrained way, I think, which is what drove a lot of their innovations and efficiency improvements.
Speaker: 1
35:06
And so I was pleased with that, But, you know, it tells you that the frontier is is, evolving rapidly. There are more players closer to it than people fully realize, and it’s gonna be a very dynamic moment, in the industry. I think China will will will be, very, very competent among the AI frontiers, just what I always assumed.
Speaker: 0
35:31
And much of the narrative, and I think probably the fact around the ability to deploy AI at scale is one that is predicated on availability of electricity. Mhmm. Even Elon, and I’ve been talking about this for a while on my podcast, but Elon this week is saying, hey, I need a terawatt of compute.
Speaker: 0
35:51
Terawatt is roughly the power production or the electricity production capacity of the entire United States. US is going from one to two between now and 2040. China’s going from three to eight, and there’s probably upside given all the new electricity production technologies that they’re rolling out now, which will be additive to that?
Speaker: 0
36:08
How much is electricity generation gonna play a role in who is gonna economically benefit from AI over the next ten to fifteen years? And where ram The US compared to China? And maybe where is Google?
Speaker: 1
36:21
Meh, look, you’re, definitely, hitting on, you know, what is, you know, when you when you look at any system, you wanna find where the constraint is because that’s what, like, gates the whole system. And you are rightfully identifying, the most likely constraint for, AI progress and and hence, by definition, GDP growth and all that stuff. Right?
Speaker: 1
36:44
So I do worry about it a lot. But, you know, the answers are, you know, sometimes you run into challenges which are, you know, you have to solve, you know, you’re running into physics barriers or something like that. This is not a problem like that. Right? Like, we already know the technologies that can work to supply the demand we need.
Speaker: 1
37:08
So it’s more to me an an, execution challenge. Right? I would I would phrase the energy problem as, it’s obviously multifaceted. But I think ai it really embracing, we shouldn’t have innovators dilemma in the energy sector, right? So we should lean into all the possible innovations ahead, and there are many of them. Obviously, first of all, people, perpetually, I think, will underestimate solar. Right?
Speaker: 1
37:37
You know, solar plus batteries will end up being huge. You know, obviously, the amount of innovation that’s going into nuclear, geothermal, all of that arya, opportunities to, embrace and small, I’m not mentioning. But I think, you know, upgrading the grid, solving for transmission, permitting to make all of that progress faster.
Speaker: 1
38:03
And then ai, I think we meh be workforce constrained, ai, to my earlier point, ai? I think we are all, if you look at the number of electricians leaving the workforce, versus suddenly all of us, and if you project out this demand, there’s a huge mismatch, right? So literally how, you know, how do you make sure there is incentives and workforce development to address shortages like that over the next decade will end up being important policies.
Speaker: 1
38:36
I think we are fortunate, you know, people like Secretary Wright and secretary Burgum, I mean, they are very, I think, deeply aware, of the issue, and I think they are, hitting hitting the problem hard. But I definitely think it’s solvable, but I think we all have to put our mind towards it.
Speaker: 0
38:53
But for your business today, you don’t see electricity constraining growth in the business in this moment or in the projectable future?
Speaker: 1
39:00
No. I wouldn’t say that. Right? Like, just for example, we are supply constrained this year in our cloud business. Right? And when we are all of us are simultaneously looking to scale up data centers. Right? Sai we are running into real constraints. The way the constraints play out today is delays in projects because of permitting or, you know, not having access to electricians.
Speaker: 1
39:25
All of that is realities all of us are dealing with. Right? So if this trend line continues, the pace at which we are all ramping up, and, obviously, for it to continue, we all have to generate the returns on it and, you know, and and so it has to really impact the economy in a more substantive way sai they go hand in hand.
Speaker: 1
39:43
If the trend continues, these constraints will be much more visible, I think. Today, we are all working through these constraints. So I think there are real constraints today, but I speak it to for us to be competitive with China, etcetera, I think we have to solve these constraints in the near future.
Speaker: 0
40:01
What does that look like then? Fast forward fifteen years, the US has 25% of the electricity of China. Mhmm. Is China just bigger GDP in that moment? Is the pie gonna grow for everyone? You know, how do we kinda think about?
Speaker: 1
40:16
Ai. You know, the way I’ve assumed is that US has always there’s never been a time where US just doesn’t meet these moments. Right? So to me, I look at it and say, it just means that, you know, the capitalist solutions will innovate through this moment. Right? That’s why people are working hard to build SMRs and, nuclear fusion, etcetera. So I’ve kind of assumed we will meet that moment.
Speaker: 1
40:39
And if we don’t or if if the if the lines don’t match, I think the conversations will get louder and louder till we meet the moment. That’s that’s the way I internalize it.
Speaker: 0
40:49
There’s a history of Google investing in innovative technologies and being ignored or being told that they don’t make much sense. Good luck. The TPU is a great example. The acquisition of DeepMind is a great example. The investment in infrastructure is a great example. The insane continued investment forever in Waymo Yeah. Is a great example.
Speaker: 0
41:12
And suddenly it looks like Waymo’s on track to be a hundred billion dollar business, and this is actually gonna work. Mind blowing persistence and patience.
Speaker: 1
41:22
By the way, we have we are doing that same patient approach in many other areas.
Speaker: 0
41:26
That’s my next question.
Speaker: 1
41:27
Quantum is one.
Speaker: 0
41:28
So tell me about quantum. Yeah. Yeah. I thought
Speaker: 1
41:30
that but you know, but
Speaker: 0
41:30
because everyone ignores quantum. You’ve had this investment for some time. Why is quantum so important? Because, again, I wanna use the historical data that it does it seems like a small bet, good luck. But what is quantum evolved to from a compute perspective for humanity? And when does that happen, do you think?
Speaker: 1
41:48
Obviously, quantum has gotten a lot more attention in the last twelve months or sai, but we have been work just like Waymo, we work through these things, whether there’s attention from the outside or not because we arya working on these things out of conviction on the long term trends. Right? So it’s it comes from those first principles.
Speaker: 1
42:05
Obviously the universe is fundamentally quantum, to do any kind of large scale simulations in a way that truly represent nature, you would need some versions of quantum computing. I think to me, quantum feels like where AI was around, you know, 2015. So I would say in a five year tyler frame, you would have that moment where some a really useful practical computation, you know, is done in a quantum way far superior to classical computers.
Speaker: 1
42:44
And that’ll be that moment. Ai think which will really show the promise of the industry. I’m absolutely confident that we will get there when I see the progress and I can pattern match to progress in the other fundamental areas we have worked on. So it really doesn’t feel like obviously, look, these are very challenging areas. You may hit a constraint. I do think a lot of people are making announcements in quantum.
Speaker: 1
43:09
So in some ways it’s tough to distinguish them. We had the same scenario in self ai, 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.
Speaker: 1
43:25
I feel that way about our quantum effort too. I think there are a lot of announcements, meh lot of noise in the industry. There arya few good people, but like, you know, you know, but I I do think we are, at the at the frontier there. And so, you know, I’m I’m pretty excited about it in a three to five year time frame, but we’ll be patient and get there.
Speaker: 0
43:45
Yeah. Do you wanna speculate on a business in quantum?
Speaker: 1
43:48
Look. I I we are committed to, you know, in almost all these cases, our goal would be to, you know, demonstrate more and more useful practical algorithms and show progress on that and and give access to it through cloud. Right? And and I think, you know, I always sai, it’s tough to project innovation on top of a platform. Right?
Speaker: 1
44:14
Nobody could say just because you had smartphones and GPS and payments, something like Uber would get invented. So you couldn’t linearly sit and project Uber from the underlying innovation. That’s how the world works. And so, for me, quantum is that foundational, again, just like AI, there’s gonna be extraordinary innovations on top of it.
Speaker: 0
44:32
We don’t know the algorithms yet. It’s almost like trying to predict how people would use personal computers in 1977 or something. That’s right. That’s right. We’re very early.
Speaker: 1
44:40
Yeah.
Speaker: 0
44:40
And, you know, some of the the constraints in quantum are that there aren’t quantum computers to test them out, the new algorithms test them out. There’s a lot of theory in quantum algorithm development, but not a lot of testability experimentation at this point.
Speaker: 1
44:53
We arya working on all of that too. I think we’ll have more exciting moments to share this year. Sai look forward to making
Speaker: 0
44:59
that happen. That that’s what’s interesting. It will expand people’s minds of the potential of what you can actually do. Right now, no one really knows how to think about quantum Yeah. Where it’s gonna take us. But those announcements, I think, are gonna be really prescient.
Speaker: 0
45:09
And then I’m assuming all your friends will show up and say, we’ve got a quantum effort now too. Tell me about robotics. I think this was gonna be the year of the robot. We see so many models being trained on simulation data or real world ai of observational data that are then being used to control physical systems. Call it physical AI.
Speaker: 0
45:29
Call it robotics. Mhmm. Lots of start arya. Lots of big companies. Google bought Boston Dynamics and a bunch of other robotic companies.
Speaker: 0
45:36
I think Andy Rubin was overseeing these for a while. And then you sold them off and decided it was too early. What’s your point of view on the opportunity in robotics today? How does Google play here?
Speaker: 1
45:47
We are definitely for robotics, you know, we again have probably, you know, one of the most advanced frontier arya and d teams in the world now. You know, and and the Gemini robotics efforts around vision language action models, etcetera, are world class. I do think, you know, robotics, you know, so we are now thinking through how we either partner or where we actually bring products out. You are right.
Speaker: 1
46:16
We we tried the application layer too early, where I think robotics wasn’t really being influenced by AI as much. But now it’s it’s really the combination of AI plus robotics that gives that next sweet spot. Right? And and so we are, making plans there. Nothing to share today, but you will see us make more announcements in the space.
Speaker: 1
46:38
But we are definitely, foundationally driving, the underlying, models, and we are building state of the art models there. We are working with partners and testing it. You know, when I look at the progress of humanoid robots, etcetera, I mean, they are, you know, in the past, I would say, well, these are this this is obviously, you know, you can see how junky they are.
Speaker: 1
47:04
Now I have to take five seconds to look at it and say closely and say, is this fake or is this an actual robot doing it? Right. Right? Like, already I’m in that moment. And so and so you can see the progress, in the field underway.
Speaker: 1
47:18
So I think, you know, we are probably two to three years away from that magical moment in robotics too. And so so that’s the next exciting phase.
Speaker: 0
47:26
Is there a good way to think about it that Google could potentially develop the Android for robotics and ultimately have a broad play here?
Speaker: 1
47:33
Yeah. We have intrinsic. So one of our bets is effectively doing that. So, supporting robotics manufacturers. You know, we we are committed to having the Ai as a model, you know, will will take all modalities into account, work very, very well for robotics. It’s definitely something we are committed to being on. How we actually bring products out, first party versus third party, etcetera, is where we are thinking.
Speaker: 0
47:58
I wanna talk a little bit about culture, which seems to be a key differentiator on the ai of competitive landscape. I go back to thinking about Google offering free food, massages at work, 20% time as a way to attract and win in the early days of the talent wars in Silicon Valley, Early 2 Thousands, and and and that persisted.
Speaker: 0
48:18
But what happened is it grew and it became more meh, and the narrative is that Google ended up creating a culture that kind of moved away from more accountability and performance and was much more about coddling employees. Can you just comment on kind of your observations ai the evolution of Google over the twenty years that you’ve been here and what you’ve tried to do lately as a leader, how you think about the culture you wanna foster and what you’re doing about it.
Speaker: 1
48:44
Look. I think it’s important to step back and say, you know, the underpinnings of a culture in which you really invest in employees and and you empower them, And even some of the perks was to create a culture where it’s positive, optimistic, you’re in an innovation mindset.
Speaker: 1
49:05
People are talking to each other. Maybe by giving lunch here, people are all sitting and talking ideas through lunch. You’re cross pollinating, imagine. Sai, that is the thesis of it. Not that we are trying to give lunch to people, right?
Speaker: 1
49:17
And so I tyler today feel, we still get a lot of innovation in the company at all levels of the company. And I think people wake up, and say, well, I can go do this notebook ram, etcetera, are great examples. Ai so people do that all the time. So I think empowering employees has been and is and will be a source of strength for Google. Right?
Speaker: 1
49:43
I think we can attract higher caliber people who feel like they have agency to do that. Right? And but that doesn’t mean like, I think people shouldn’t confuse that with like today, for example, you can take something like Google DeepMind. I think there is all the way from Demis and others, extraordinary leadership team, be it Ai, Jeff, Oriole, Noem, Mesopra, all these leaders have strong opinions on how to drive that frontier forward, and and that’s happening too.
Speaker: 1
50:11
Right? So I think it’s important to strike a saloni, balance, between the two. I think when you empower employees a lot, in some ways, like, you know, we have allowed for more free speech than other companies. That’s one way you can think about it. So you’re gonna hear voices.
Speaker: 1
50:25
Sometimes you can hear like what is effectively 500 people in the company, but that doesn’t represent the company as a whole. So in some ways we are different from other companies and can confuse it on the outside, I think. But I think overall, look, we have a clear sense of where we are going. I think we wanna empower people all in the service of our mission.
Speaker: 1
50:47
So if anything, you know, over the past few years and you are ai, there are moments, not just us, but as an industry, I think. I think some of the other things became more of the focus than the mission of the company and why we are all here. Right? Like, we are we are not all here in the company to resolve our personal differences or something.
Speaker: 1
51:07
We are here because you’re excited about, innovating in the service of the mission of the company and the impact you can have. And so bringing that focus back, that’s something I’ve been very deliberate about for the past few years. And I think it needs reinforcing. I think one of the lessons for me was we all grew so much that you assumed everyone always understood those underpinnings.
Speaker: 1
51:32
But then when you added so many people, you realize you have to go back and repeat that a lot, to to help people internalize that. We’ve done that and we do that all the time. I think moments like this help a lot too. The current moment is just genuinely both so exciting and so intense. It actually reminds me a lot of early Google. Right?
Speaker: 1
51:54
You know, when I walk into the GDM Building, you know, some of our earliest engineers are all sitting there working together. People come in five days a week at a minimum. Right? And so you have that intensity and you have that ai. And I feel that same sense of optimism.
Speaker: 1
52:13
So that’s what I’m focused on. To me, that’s the hard coreness which matters. Ai are people smart people really working with a passion, and that’s where that intensity comes from. And and you have to work hard to create that. And, you know, there are pockets of the company if that doesn’t happen. You figure out what are the changes you need to make, to to do that. Right?
Speaker: 1
52:35
And sometimes, for example, I recreated the notion of labs. Right? And and and because I said, well, there are things that are possible with 10% teams, and so we need to go and do that again. And and there are quite a few projects, both we have shipping and are underway to come, which will be an outcome of those efforts as well.
Speaker: 1
52:57
So, you know, your culture your values are enduring. Culture is something you’re constantly tweaking to make sure you’re true to your values. And so by definition, there’s gonna be drift and, you know, you work hard to, sai it back.
Speaker: 0
53:13
Was there a moment in the last ten years where you sai, I’ve gotta spend more time on this?
Speaker: 1
53:18
Oh, for sure. Look, I think COVID was such a big distortion to our way of working. Ai fundamentally, Google was designed to be a culture in which people were seeing each other, engaging with each other. So losing that continuity, right, I I think definitely impacted our culture.
Speaker: 1
53:39
So when we have we have gotten people back, in a three two model and some teams are, you know, work, beyond that, I think it’s been important. I’ve I’ve spent time to get those connections back. Like, you know, for example, GDAM, we were intentional in creating a physical space where we can get all of them back in the same building, both in London, both in Mountain View.
Speaker: 1
54:02
And and and taking our newest building, you know, with that kind of a tent like roof structure and putting all the people in and being intentional about it has made a massive difference.
Speaker: 0
54:15
Have you found a shift in your ability to recruit top talent? A lot of great talent has started other great companies. Yeah. Other great companies in Silicon Valley have recruited folks. I know there’s always a talent war going on, but has there been a tyler shift for Google in the last period of time because of some of the underlying advantages in AI or some of the cultural changes that are underway?
Speaker: 1
54:38
The talent market, you know, we go through these fierce moments for talent. AI is one of them. And whenever there are these Google, you know, obviously, we we are fortunate to have some of the most talented employees. So we are a source. I’m equally proud of the fact that I think Googlers are left to start over 2,000 companies. Right? And and so, you know, there is a virtuous cycle.
Speaker: 1
54:59
I think people come back. We acquire companies. I think all of that keeps the company, fresh. But in the current AI moment, look, Ai think we are both holding on to critical talent. We are recruiting.
Speaker: 1
55:11
But, you know, I always look at the tip of the tree of, are we able to attract the best PhD researchers coming out of the top programs? And the answer is yes. You know, and and there are people who have left, who’ve come back. And so I feel good about the position we are, but you work at it hard every week, every month, and so on.
Speaker: 0
55:30
Do you think this is gonna change in the future with how we do education and how AI plays a role in education? Are you gonna be able to identify, recruit, and then teach and train talent out of high schools and at an earlier age, and the traditional kind of college education system is gonna change because of Ai, on the job training?
Speaker: 1
55:51
There’s a lot of potential to change. I just there’s a part of me which feels maybe we’ve all misunderstood what colleges are arya, and maybe colleges are about the community and people getting together and exchanging. So it you know, there may be intangibles, which which would still maybe make the, you know, it more valuable than, like, we all perceive it to be.
Speaker: 1
56:14
But, but the way I think about it is you’re gonna get extraordinary talent at more places around the world. That’s the way I think about it because people have access to with Ai. So you don’t need to be in a few certain places to be that, that great, great talent. So I think the nature of that changes.
Speaker: 1
56:35
By the way, I think it’s an important thing to internalize. We often talk about talent. We’ve always been able to recruit the best talent, in the country, but now there’s extraordinary talent emerging in other parts of the world too. So I Ai think it’s something not to lose line of sight and, you know, maybe that’s the way I would think about it.
Speaker: 0
56:54
So just taking a step back, zooming back, I had a conversation ten years ago with Larry Page where he talked about the transition from Google to Alphabet. Alphabet is gonna be this holding company. It’s gonna discover or develop the next hundred billion dollar revenue business.
Speaker: 0
57:08
At the time, I think Google wasn’t quite at a hundred billion. There have been a lot of these investments in Other Bets since that time. Do you still think about Alphabet as a holding company? Are there still multiple businesses that you wanna kind of stand up and foster and have this kind of holding company model?
Speaker: 0
57:25
Is that still hold, or is Google really the core engine that’s gonna continue to evolve and continue to have ancillary businesses that are, you know, somewhat adjacent to Google?
Speaker: 1
57:36
Lance are two ways. Right? So I think the way we are not a holding company in the sense that we are we are not just, like, looking to invest capital in other attractive businesses. That’s that’s not who we are. Right? We are, you know, from a foundational technology basis, if you can take that technology and that arya and d we do and identify problems in which we can innovate and bring a differentiated value proposition, we’ll do that.
Speaker: 1
58:08
Right? So that’s the way we approach. And so the the structure is an outcome of that. Right? So and which means you will have businesses, on paper they may look like very disparate, but there is a common strand underneath them, right?
Speaker: 1
58:24
So like, I mean, VAMO is gonna keep getting better because of the same work we do in Gemini and AI over time as Google Cloud to search to YouTube to isomorphic to robotics, etcetera. So that is the unifying layer, ai? And then it’s a continuum. Is Google Cloud a Google business or an Alphabet business, right? We segment it out, right?
Speaker: 1
58:50
And so the branding matters less, I think, Right? We’ll have a range of companies. Some of them will leave an IPO out because maybe that’s the best way they can make progress. So all of that is a possibility. But what I think I, the founders, think about is like the underlying innovation by which so we think of the units of quantum, ai, you know, alpha fold and hence isomorphic, ai, you know, self driving and and building the way more ai, and, hence, all the businesses on top of it.
Speaker: 1
59:24
So it’s more maybe maybe that’s how we think about it. Ai.
Speaker: 0
59:28
Does x still play a big role in driving innovation and you continue to invest there?
Speaker: 1
59:31
Yeah. Look, I think, if anything, x or time, look, lot of lot of these innovations did come out of x. Right? And so, including Waymo, you know, the early incarnations of Google Brain. Right? Yeah. So so I think, x as an incubator, allows us to, you know, push the boundaries.
Speaker: 1
59:53
They’re thinking about, tapestries, thinking about the grid problem, that are, you know, extraordinary, but it’s all rooted in computer science, physics, kind of a deep, technology arya and d. And I think that’s the foundation across everything we do.
Speaker: 0
01:00:12
As we wrap up, I wanna ask you one last question to hopefully frame your experience of the last ten years as CEO. Biggest regret, biggest mistake, and what you’re most proud of.
Speaker: 1
01:00:25
Proud is all look. I I think I think we have, as a company, I think there aren’t that many companies which can push the technology frontier. Like, you don’t hear of companies winning Nobel ai often. That level of foundational r and d we do and then apply it to create businesses and value.
Speaker: 1
01:00:42
I think I think we’ve done an extraordinary job at that, and we aspire to do that. Ai really proud of that. I think we are pretty unique as a company that way. A lot of small regrets, by nature I tend to look forward and I learn from mistakes we make, but look there are acquisitions.
Speaker: 1
01:01:00
We debated hard, came close, and, you know, some of them are
Speaker: 0
01:01:06
Just give me one name. I think you’re out.
Speaker: 1
01:01:09
We’ll get in trouble. Maybe Netflix. Right? Like, we debated Netflix at some point super intensely inside. So you go through these moments, ai? And sai, and I wouldn’t call it regrets, but you always look back ai like, in a world of butterfly effects, there were alternate paths, but maybe they are in a different part of the multiverse.
Speaker: 0
01:01:30
Yes. Yes. I always, tell people Ai I think they underappreciate the role that Bell Labs played in driving innovation and ultimately human prosperity in the early twentieth century. And I do think a lot of people underappreciate the role that Alphabet is playing in driving innovation across so many different lanes, which drives prosperity, businesses, competition, all that stuff aside, the innovation that’s being driven out of Alphabet continues to impress and benefit us all, and so I wanna thank you for your leadership and the time, Simba.
Speaker: 1
01:02:03
Thanks, David. Real pleasure ai.
