WEBVTT - Sundar Pichai

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<v Speaker 1>Over the past quarter century, one of the most significant

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<v Speaker 1>companies in the world has been Google. It has led

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<v Speaker 1>today not by its founders, but by a personal who

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<v Speaker 1>started in two thousand and four, rose up the ranks,

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<v Speaker 1>and is now the CEO.

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<v Speaker 2>His name is Sundar Pashai.

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<v Speaker 1>I sat down with him recently and the Google officers

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<v Speaker 1>of New York to talk about the future of Google

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<v Speaker 1>and also importance of artificial intelligence to the company. When

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<v Speaker 1>you joined Google, the alphabet hadn't yet existed. It was

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<v Speaker 1>two thousand and four. The company was started in nineteen

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<v Speaker 1>ninety eight, I believe. So how big was the company

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<v Speaker 1>in two thousand and four?

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<v Speaker 3>Two thousand and four, we were about just totally one

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<v Speaker 3>thousand people, I think, but we are growing pretty fast. Yeah,

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<v Speaker 3>we were about thousand people.

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<v Speaker 1>So when you why did you come to the company

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<v Speaker 1>in two thousand four?

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<v Speaker 2>Who attracted you to come here?

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<v Speaker 1>A small, little search engine company?

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<v Speaker 2>Search wasn't that big a deal then?

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<v Speaker 3>Probably I was using the product from the outside, and

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<v Speaker 3>you know, I clearly noticed how much better it was

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<v Speaker 3>as a product. And I was a what I call

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<v Speaker 3>a power user of the product, right, and I had

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<v Speaker 3>a lot of ideas in my head on how the

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<v Speaker 3>product could be made better. But more importantly, you know,

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<v Speaker 3>I gaining access to technology made a big difference in

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<v Speaker 3>my life, and so I always tell the power of

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<v Speaker 3>giving access to technology. The thing about Google which appealed

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<v Speaker 3>to me was you could be somewhere in rural Indonesia,

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<v Speaker 3>or you could be a professor at Stanford, and you

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<v Speaker 3>would get access to that information as long as you

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<v Speaker 3>had a computer and connectivity.

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<v Speaker 1>With respect to the company today, you obviously have had

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<v Speaker 1>some legal challenges. One legal challenge by the federal government.

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<v Speaker 1>They charged that your I guess your search engine was

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<v Speaker 1>I hate to use the word monopolistic, but I guess

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<v Speaker 1>they probably used that word. It's running the company more

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<v Speaker 1>complicated because you have this lawsuit you have to deal with.

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<v Speaker 3>With our scale and size, I think scrutiny is inevitable,

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<v Speaker 3>and you know we've always engaged very respect fully and

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<v Speaker 3>responsibly through these processes. Even in the current current ruling,

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<v Speaker 3>I mean, the ruling goes to great length to point

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<v Speaker 3>out that we have achieved success by innovating. Our competitors

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<v Speaker 3>acknowledge that we had the best searching search engine in

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<v Speaker 3>the world. We definitely disagree with the ruling but it'd

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<v Speaker 3>been still in the middle of the remedies phase. And

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<v Speaker 3>you know, we will appeal and this process will likely

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<v Speaker 3>take many years. And you know, I'm confident given that

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<v Speaker 3>you know, we are focused on innovating using technology, will

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<v Speaker 3>do well in the long run. And just last week

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<v Speaker 3>there was a European court ruling which overruled the earlier decision.

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<v Speaker 3>But the process had taken you almost ten years, right,

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<v Speaker 3>So these things take take a while.

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<v Speaker 1>So were you surprised that the US government after they

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<v Speaker 1>won that case, they filed another case against you? Were

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<v Speaker 1>you surprised that that happened? And you expect that'll go

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<v Speaker 1>on for a while too.

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<v Speaker 3>This one is not to do with our advertising on

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<v Speaker 3>our search engine. The other one is we provide an

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<v Speaker 3>ad platform for publishers to run advertising on their sites,

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<v Speaker 3>and so we provide a platform, and so this is

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<v Speaker 3>focused on that part of our business.

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<v Speaker 2>Part of our business.

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<v Speaker 3>Again, we are you know, that case is just getting underway,

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<v Speaker 3>so I expected to take take some time. And you know,

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<v Speaker 3>but look where we can figure out you know, constructive solutions.

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<v Speaker 3>I think we will where we think it really harms

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<v Speaker 3>our ability to innovate on behalf of our users or uh,

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<v Speaker 3>you know, we are going to be vigorous in defending

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<v Speaker 3>ourselves and it's going to take time for it to

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<v Speaker 3>play out.

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<v Speaker 1>Silicon Valley has been enamored with artificial intelligence AI. Everybody

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<v Speaker 1>thinks that they need to have AI starts, attach their

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<v Speaker 1>name or or be a leader in it. Chat GBT

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<v Speaker 1>got out to the public first, but you've been working

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<v Speaker 1>on it for a long time, maybe before open AI did.

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<v Speaker 1>Are you going to go more public with what you're

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<v Speaker 1>doing in artificial intelligence? And how is artificial intelligence going

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<v Speaker 1>to change your company?

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<v Speaker 3>I mean it is. It's been a big focus for

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<v Speaker 3>us as a company. One of the first things I

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<v Speaker 3>did as CEOs to pivot the company to be focused

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<v Speaker 3>on AI AI first. You know, we've developed a lot

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<v Speaker 3>of the core underlying technology, a lot of its powers

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<v Speaker 3>search today. So part of what has helped us keep

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<v Speaker 3>search about everyone else is by incorporating a lot of

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<v Speaker 3>AI in how we do search. The current moment around

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<v Speaker 3>generator AI is what's captured people's imagination. We are incorporating

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<v Speaker 3>that in search in a deep way. So today if

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<v Speaker 3>we go to Google and type a query in we

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<v Speaker 3>give for many queries, we give something called an AI

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<v Speaker 3>overview and you get a nice summary on top which

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<v Speaker 3>we are summarizing the top results and giving context around

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<v Speaker 3>it using AI. It's been very well just people love it,

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<v Speaker 3>and so it's you know, it's one direction in which

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<v Speaker 3>we are using AI. Table of our product we have.

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<v Speaker 3>Our models are called Gemini, and people can also talk

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<v Speaker 3>to Gemini directly. And I just feel like we're at

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<v Speaker 3>very very early stages of what is probably the most

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<v Speaker 3>profound shift in technology we will ever see as humanity.

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<v Speaker 2>So it's an exciting time today.

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<v Speaker 1>If I want to do a search, I suppose I

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<v Speaker 1>look your name up on a search and it'll come

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<v Speaker 1>up with your bio and so forth, and then maybe

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<v Speaker 1>articles written about you will appear on this and then

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<v Speaker 1>maybe those articles will guide me to let's say, an

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<v Speaker 1>advertising site or something.

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<v Speaker 2>But with AI, some.

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<v Speaker 1>People are worried that your AI will basically have all

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<v Speaker 1>the information, and therefore they won't they the advertisers won't

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<v Speaker 1>have anybody coming to their site any longer.

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<v Speaker 2>So how do you address that issue?

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<v Speaker 3>Today we've past twenty five years. People come to Google

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<v Speaker 3>because they're not only looking for what they want, but

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<v Speaker 3>they enjoy the richness and the diversity of what exists

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<v Speaker 3>on the bat right, So people are clicking through and

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<v Speaker 3>going to a lot of sites. That is important for us.

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<v Speaker 3>That's what makes this thriving ecosystem. So even if as

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<v Speaker 3>we are evolving the product with AI, one of our

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<v Speaker 3>core design principles has been making sure it works that way, right,

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<v Speaker 3>and so we are prioritizing approaches which will send traffic

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<v Speaker 3>to publishers and in the case of commercial queries, advertisers

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<v Speaker 3>will also benefit as well. But that's you know, we

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<v Speaker 3>think about it holistically because I think that's what allows

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<v Speaker 3>people to create great content and create that virtual cycle.

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<v Speaker 1>So advertisers are they concerned that somehow the AI search

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<v Speaker 1>function you have might get them bypass.

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<v Speaker 3>The way we think about it is users, when they

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<v Speaker 3>come looking for information, there is an aspect of it

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<v Speaker 3>where they're looking for commercial information. It's naturally in the

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<v Speaker 3>user's intent, and when their intent is commercial, you know,

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<v Speaker 3>advertising turns out to be very very relevant information. There

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<v Speaker 3>was a core insight behind how we monetize Google Search

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<v Speaker 3>that adds a valuable information when users have a commercial intent.

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<v Speaker 3>That doesn't change just because there's a new underlying technology. Right,

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<v Speaker 3>people are always looking for commercial information and providers of

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<v Speaker 3>that information. Merchants, businesses are trying to reach users, and

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<v Speaker 3>so that dynamic will continue to exist.

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<v Speaker 1>So Google is more or less the search engine part

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<v Speaker 1>of your company. Alphabet has other parts. Let me ask

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<v Speaker 1>you about some of them.

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<v Speaker 3>I could, so maybe if I could step back. You know,

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<v Speaker 3>Google has many businesses beyond search, right, So you have

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<v Speaker 3>Google Search, but think about Google Cloud, where we provide

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<v Speaker 3>software at all enterprises. It's YouTube, there is YouTube and

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<v Speaker 3>so on. There's Android and so on. So think of

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<v Speaker 3>Google as our you know, Internet related businesses. Okay, and

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<v Speaker 3>then we're using technology still. But we have other long

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<v Speaker 3>term bets. Weimo was a bet on autonomous self driving

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<v Speaker 3>cars and that's been a long term bet. We have

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<v Speaker 3>Wing which is a drone delivery company. We have Calico,

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<v Speaker 3>which is pursuing long term drug discovery for difficult to

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<v Speaker 3>treat diseases, etcetera. So these are longer term bets, and

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<v Speaker 3>that's what we call as other bets.

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<v Speaker 1>Okay, So Waimo is a long term bet, I assume,

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<v Speaker 1>But have you been in one of those cars.

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<v Speaker 2>All the time?

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<v Speaker 1>You know?

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<v Speaker 3>I make sure to go periodically and take a ride

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<v Speaker 3>in Wemo is phenomenal the progress I've seen every six months.

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<v Speaker 3>The last time I was in the car, the third

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<v Speaker 3>time I was in it. You know, I was on

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<v Speaker 3>my phone in the back seat. Once in a while,

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<v Speaker 3>I tell myself, you know, look, I'm in a self

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<v Speaker 3>driving car. It's amazing even how people sometimes look in

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<v Speaker 3>Some people are curious, some people are kind of.

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<v Speaker 2>Like they used to it. You wear a helmet when

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<v Speaker 2>you're in there. Your confect.

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<v Speaker 3>Not at all, you know, quite the contrary. It's it's

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<v Speaker 3>pretty relaxing.

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<v Speaker 2>You know.

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<v Speaker 3>We've been surprised at how much okay, people like the

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<v Speaker 3>experience we are now. We've scaled up towe hundred thousand

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<v Speaker 3>paid rights every week in the In the US, we

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<v Speaker 3>recently announced a partnership with Uber, so you can use

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<v Speaker 3>the Uber app, for example in Atlanta to Haila waymocard.

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<v Speaker 1>You have a business, that's the cloud business you mentioned earlier.

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<v Speaker 1>I think Amazon got to the cloud first and other

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<v Speaker 1>big tech companies got there later. How significant is cloud

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<v Speaker 1>to you now? And are you the person kind of

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<v Speaker 1>drove the cloud business here?

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<v Speaker 3>I mean it was one of the big areas.

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<v Speaker 2>You know.

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<v Speaker 3>I bet On, I say, became CEO in twenty fifteen,

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<v Speaker 3>and you know, we realized Google was built in the cloud.

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<v Speaker 3>Google Search, Google Maps, Gmail, everything works. We are a

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<v Speaker 3>native cloud company and we are one of the best

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<v Speaker 3>cloud infrastructure in the world. So we made it decision

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<v Speaker 3>to really provide it to everyone else. And you know,

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<v Speaker 3>we brought in CEOs who had real background to do that.

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<v Speaker 3>Our current CEO, Thomas Korean, has really helped scale the business.

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<v Speaker 3>Last quarter we had over ten billion dollars in revenues.

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<v Speaker 3>I think we're probably the number fourth largest software company

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<v Speaker 3>in the enterprise now, so it's one of our most

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<v Speaker 3>robust businesses. And in fact, I announced in one of

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<v Speaker 3>our earnings called recently that we will exit twenty twenty

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<v Speaker 3>four in YouTube and cloud at one hundred billion dollars runderrate.

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<v Speaker 3>And these were businesses which we've built from scratch over

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<v Speaker 3>the past decade.

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<v Speaker 1>So we've talked about cloud, which was a novelty ten

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<v Speaker 1>years ago or so, and now AI is a bit

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<v Speaker 1>of a novelty. What the areas in the future that

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<v Speaker 1>you think will be the next great tech interest for

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<v Speaker 1>Solicon Valley and other people is quantum computing?

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<v Speaker 2>One of them, you know.

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<v Speaker 3>Would view quantum one of those foundational technologies like AI

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<v Speaker 3>over time, you know, quantum, you know, you know, it's

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<v Speaker 3>fundamentally thinking about how to design different computers than classical computers.

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<v Speaker 3>So I would view it as just like aids are

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<v Speaker 3>underlying technologies, but these technologies are going to hopefully enable many,

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<v Speaker 3>many amazing applications on top of them, you know AI.

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<v Speaker 3>You know, that's why compared AI to fire or electricity.

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<v Speaker 3>You know, it's going to cut across every sector everywhere,

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<v Speaker 3>and people are going to be able to read think

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<v Speaker 3>think of AI as you're getting really intelligent decision making

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<v Speaker 3>systems to deploy everywhere.

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<v Speaker 1>Let's talk about your background for a moment. So where

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<v Speaker 1>were you born.

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<v Speaker 3>I was born in India in a city called Chennai

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<v Speaker 3>in the south of India.

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<v Speaker 1>And did you grow up you know, in middle class

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<v Speaker 1>kind of.

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<v Speaker 3>You know, it was a comfortable middle class life in India,

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<v Speaker 3>you know. But one of the things was technology wasn't

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<v Speaker 3>always around and we had to wait for a while

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<v Speaker 3>before you know, we were on a waiting list. At

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<v Speaker 3>that time, only the government made phones and this was

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<v Speaker 3>a rotary phone. So it was a five year wait

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<v Speaker 3>list to get a phone, right, and so we got

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<v Speaker 3>the rotary phone changed our lives we were one of

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<v Speaker 3>the few people in our neighborhood to have it. People

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<v Speaker 3>would come to our homes to make calls to the

0:12:19.080 --> 0:12:21.840
<v Speaker 3>loved ones. I recall, you know, I would have to

0:12:22.320 --> 0:12:24.559
<v Speaker 3>it would before our trip to find the black test

0:12:24.600 --> 0:12:26.880
<v Speaker 3>results for my mother. Sometimes I would go all the

0:12:26.920 --> 0:12:29.439
<v Speaker 3>way to the hospital and they would say, no, it's

0:12:29.440 --> 0:12:31.520
<v Speaker 3>not ready, come back tomorrow. And with the phone, I

0:12:31.559 --> 0:12:34.959
<v Speaker 3>could call and get that information right away. So it really,

0:12:35.520 --> 0:12:37.040
<v Speaker 3>you know, showed me the part of technology.

0:12:37.200 --> 0:12:38.600
<v Speaker 1>So where did you go to college?

0:12:38.920 --> 0:12:43.120
<v Speaker 3>I went to a college called the Indian Institute of Technology.

0:12:43.320 --> 0:12:45.920
<v Speaker 3>It's a set of you know, a few institutions which

0:12:45.960 --> 0:12:49.120
<v Speaker 3>are primarily focused on engineering. And what did you major in,

0:12:49.840 --> 0:12:52.040
<v Speaker 3>you know, what's today called material science?

0:12:52.520 --> 0:12:55.160
<v Speaker 2>And I astribute that, Okay, I did.

0:12:55.000 --> 0:12:58.000
<v Speaker 3>Okay, you know I had a chance to you know,

0:12:58.040 --> 0:13:03.200
<v Speaker 3>I really got interested in computers and semiconductors through my degree,

0:13:03.280 --> 0:13:06.920
<v Speaker 3>and so I really, you know, was motivated by what

0:13:07.000 --> 0:13:09.400
<v Speaker 3>was happening in Silicon Valley. I literally wanted to be

0:13:09.559 --> 0:13:12.320
<v Speaker 3>in the place where semi connectors were developed, and that's

0:13:12.360 --> 0:13:13.840
<v Speaker 3>why I had a chance to come to Stanford.

0:13:14.000 --> 0:13:17.000
<v Speaker 1>You went to Stanford get a master's degree in engineering.

0:13:17.360 --> 0:13:19.600
<v Speaker 1>That's right, And did you get a scholarship or how

0:13:19.640 --> 0:13:20.440
<v Speaker 1>to get you afford that?

0:13:20.840 --> 0:13:23.839
<v Speaker 3>I mean, it was very fortunate to get a full scholarship.

0:13:24.720 --> 0:13:26.240
<v Speaker 3>You know, I was a teaching assistant.

0:13:26.360 --> 0:13:28.520
<v Speaker 1>Had you left the United had you left the India

0:13:28.520 --> 0:13:29.000
<v Speaker 1>before that?

0:13:29.120 --> 0:13:29.840
<v Speaker 2>Had you ever been.

0:13:29.679 --> 0:13:32.320
<v Speaker 3>Out coming to the US was the first time I

0:13:32.360 --> 0:13:33.200
<v Speaker 3>was ever on a plane?

0:13:33.920 --> 0:13:36.120
<v Speaker 1>Okay, So you got your master's degree and then you

0:13:36.200 --> 0:13:38.040
<v Speaker 1>went to Wharton to get your MBA.

0:13:38.280 --> 0:13:40.079
<v Speaker 2>I had only seen the West coast. I wanted to

0:13:40.120 --> 0:13:41.160
<v Speaker 2>see more of the US.

0:13:41.840 --> 0:13:46.079
<v Speaker 3>I through fall, I came to the East coast, loved

0:13:46.080 --> 0:13:48.880
<v Speaker 3>the seasons, so I just wanted to spend time back

0:13:49.000 --> 0:13:53.200
<v Speaker 3>back east and so you know, it was also you know,

0:13:53.240 --> 0:13:56.000
<v Speaker 3>my goal with it was to get exposed to you know,

0:13:56.679 --> 0:14:00.640
<v Speaker 3>I had a deep engineering and scientific background, so chance

0:14:00.720 --> 0:14:02.640
<v Speaker 3>to get exposed to other walks of life out does

0:14:02.640 --> 0:14:07.600
<v Speaker 3>a business work, get exposed to people from finance, from economics,

0:14:07.720 --> 0:14:09.160
<v Speaker 3>and so that was all part of what I was

0:14:09.200 --> 0:14:09.600
<v Speaker 3>looking for.

0:14:09.640 --> 0:14:11.480
<v Speaker 1>So you got your MBA from Whorton, that's them.

0:14:11.520 --> 0:14:11.960
<v Speaker 2>What did you do?

0:14:12.760 --> 0:14:12.960
<v Speaker 1>You know?

0:14:13.600 --> 0:14:15.880
<v Speaker 3>Pretty much very soon after that, I ended up at Google,

0:14:15.880 --> 0:14:18.520
<v Speaker 3>but I spent a short time at mckinzi before that.

0:14:18.679 --> 0:14:20.560
<v Speaker 1>Yeah, so are your parents alive.

0:14:21.200 --> 0:14:23.320
<v Speaker 2>They are, and you know, I think they must be

0:14:23.360 --> 0:14:24.080
<v Speaker 2>pretty proud of you.

0:14:24.080 --> 0:14:26.400
<v Speaker 1>You're the CEO of Google and Alphabet that they call

0:14:26.440 --> 0:14:29.360
<v Speaker 1>you all the time with advice or what do they do?

0:14:29.400 --> 0:14:29.840
<v Speaker 2>You know? Both?

0:14:30.000 --> 0:14:32.760
<v Speaker 3>You know, I'm fortunate. I'm very close to them. I

0:14:32.840 --> 0:14:37.800
<v Speaker 3>see them almost every week. But my dad is you know,

0:14:37.920 --> 0:14:41.960
<v Speaker 3>kind of it shows me amazingly. He's eighty two. He

0:14:42.080 --> 0:14:46.400
<v Speaker 3>relentlessly reads everything about you know, he's tried to keep up.

0:14:46.680 --> 0:14:49.800
<v Speaker 3>He's not a software engineered by training. But a few

0:14:49.880 --> 0:14:53.720
<v Speaker 3>years ago you wanted to know what a API is,

0:14:53.880 --> 0:14:56.400
<v Speaker 3>and he has learned it. So he tracks news closely,

0:14:56.560 --> 0:14:58.000
<v Speaker 3>and so he just talked to me about it.

0:14:58.240 --> 0:15:01.640
<v Speaker 1>Eighty two is young. The present United States is still young.

0:15:01.720 --> 0:15:04.520
<v Speaker 1>There you go and your mother, you talked to her.

0:15:04.560 --> 0:15:08.200
<v Speaker 3>All the time, and you know she's I got my

0:15:08.280 --> 0:15:11.000
<v Speaker 3>love of reading from a very young age from from her.

0:15:11.400 --> 0:15:14.800
<v Speaker 3>Due to financial circumstances, you know, she she was working

0:15:14.840 --> 0:15:17.600
<v Speaker 3>as a stenographer. She stopped working to support the family.

0:15:18.440 --> 0:15:23.240
<v Speaker 3>But you know she was a voracious reader, and that's

0:15:23.240 --> 0:15:24.760
<v Speaker 3>where I got my love of reading from.

0:15:24.800 --> 0:15:28.280
<v Speaker 1>And so and did you meet your wife at Wharton

0:15:28.480 --> 0:15:29.680
<v Speaker 1>Stanford or where?

0:15:30.040 --> 0:15:30.280
<v Speaker 2>Back?

0:15:30.360 --> 0:15:33.880
<v Speaker 3>You know, we both went to I at Indian Industry

0:15:33.920 --> 0:15:36.320
<v Speaker 3>of Technology. She was you know, at the time they

0:15:36.320 --> 0:15:38.600
<v Speaker 3>were in that many women, So she was she was

0:15:38.640 --> 0:15:41.680
<v Speaker 3>a pioneer in her own way of breaking through. And

0:15:41.720 --> 0:15:44.080
<v Speaker 3>so I met my wife and undergraduate.

0:15:44.640 --> 0:15:46.560
<v Speaker 1>Okay, and so now we're married.

0:15:46.600 --> 0:15:49.440
<v Speaker 2>How long over twenty five years? Five years? And you

0:15:49.480 --> 0:15:51.320
<v Speaker 2>have two children? Two children, that's right?

0:15:51.360 --> 0:15:54.080
<v Speaker 1>And do they run around Silicon Valley bragging saying my

0:15:54.240 --> 0:15:56.560
<v Speaker 1>father is the CEO of Google or they don't?

0:15:57.200 --> 0:15:59.160
<v Speaker 3>Quite the contrary. I think, you know, they're trying to

0:15:59.200 --> 0:16:02.640
<v Speaker 3>find their own boys. And you know, we hardly talk

0:16:02.680 --> 0:16:05.040
<v Speaker 3>about my role or anything in the context of my family.

0:16:05.240 --> 0:16:07.400
<v Speaker 1>Let's say you go at a restaurant Silicon Valley with

0:16:07.440 --> 0:16:09.920
<v Speaker 1>your wife. Do people come up with resumes all the

0:16:09.960 --> 0:16:11.960
<v Speaker 1>time or ideas for funding things?

0:16:11.960 --> 0:16:15.760
<v Speaker 2>How does that work? Ah? Yeah? People less less that

0:16:15.880 --> 0:16:16.680
<v Speaker 2>as part.

0:16:16.720 --> 0:16:18.720
<v Speaker 3>You know, maybe people want to picture or want to

0:16:18.760 --> 0:16:21.920
<v Speaker 3>say hello, and so that does happen, particularly in Silicon Valley,

0:16:23.120 --> 0:16:27.640
<v Speaker 3>but you know, doesn't always happen. I've kept a reasonably

0:16:28.440 --> 0:16:29.760
<v Speaker 3>private life, so that helps.

0:16:29.760 --> 0:16:33.600
<v Speaker 1>I think, how do you avoid being sclerotic when you

0:16:33.640 --> 0:16:35.360
<v Speaker 1>have a company that now has one hundred and eighty.

0:16:35.200 --> 0:16:36.320
<v Speaker 2>Two thousand employees.

0:16:36.720 --> 0:16:39.400
<v Speaker 1>How do you get innovative ideas to get to the

0:16:39.440 --> 0:16:41.040
<v Speaker 1>top without bureaucracy killing it.

0:16:41.880 --> 0:16:45.320
<v Speaker 3>Look, I think you have to enable uh, you know,

0:16:45.520 --> 0:16:48.040
<v Speaker 3>you have to empower small teams to move fast and

0:16:48.080 --> 0:16:48.840
<v Speaker 3>get things done.

0:16:49.120 --> 0:16:49.320
<v Speaker 2>Right.

0:16:49.400 --> 0:16:52.600
<v Speaker 3>You have your big products, they are constantly improving, and

0:16:52.640 --> 0:16:55.000
<v Speaker 3>you have to make sure you're constantly investing in and

0:16:55.040 --> 0:16:59.040
<v Speaker 3>innovating on our core products. But you have to allow

0:16:59.040 --> 0:17:02.400
<v Speaker 3>in the system away for small teams to build new things,

0:17:02.760 --> 0:17:04.919
<v Speaker 3>and sometimes you have to be deliberate about it. Early

0:17:04.960 --> 0:17:08.600
<v Speaker 3>on at Google, we had a structure called Google Labs,

0:17:09.400 --> 0:17:11.560
<v Speaker 3>and you know, in which you could have small teams

0:17:11.560 --> 0:17:15.480
<v Speaker 3>with resources to go build new things. We are doing

0:17:15.520 --> 0:17:17.959
<v Speaker 3>that again now and we again have created a new

0:17:17.960 --> 0:17:20.520
<v Speaker 3>Google Labs team, And just recently they launched a product

0:17:20.520 --> 0:17:23.320
<v Speaker 3>called Google Notebook, in which you can go put a

0:17:23.320 --> 0:17:28.000
<v Speaker 3>set of documents and then AI kind of learns it.

0:17:28.160 --> 0:17:30.480
<v Speaker 3>You can ask questions, you can even tell it to

0:17:31.880 --> 0:17:35.639
<v Speaker 3>summarize it as a podcast, conversational podcast back to you, right,

0:17:35.720 --> 0:17:38.960
<v Speaker 3>and you know it's breadtaking if you use it. So,

0:17:39.040 --> 0:17:42.880
<v Speaker 3>but these are entirely new product built from scratch. And

0:17:42.960 --> 0:17:46.320
<v Speaker 3>so Google Photos was a product built from scratch too,

0:17:46.359 --> 0:17:50.800
<v Speaker 3>So you have to empower small teams to move the

0:17:50.880 --> 0:17:53.760
<v Speaker 3>velocity of a startup and cut through the processes you

0:17:53.800 --> 0:17:54.840
<v Speaker 3>have in a large company.

0:17:55.359 --> 0:17:56.800
<v Speaker 2>Let's talk about the company today.

0:17:56.920 --> 0:17:59.159
<v Speaker 1>So, as I mentioned earlier, you have I think it's

0:17:59.160 --> 0:18:02.159
<v Speaker 1>one hundred and eighty three one thousand employees, and the

0:18:02.240 --> 0:18:06.359
<v Speaker 1>company has a market capitalization today of about two and

0:18:06.400 --> 0:18:07.360
<v Speaker 1>a half trillion or something.

0:18:07.440 --> 0:18:09.920
<v Speaker 2>Yeah, it's over two trillion dollars. Yeah, over two trillion dollars.

0:18:10.000 --> 0:18:13.159
<v Speaker 1>So the market capitalization is doubled since you've been the CEO,

0:18:13.760 --> 0:18:16.080
<v Speaker 1>and the stock prices more than doubled since you've been

0:18:16.080 --> 0:18:19.639
<v Speaker 1>the CEO. So do you tell the founders, look, you've

0:18:19.680 --> 0:18:21.600
<v Speaker 1>done a great job, and maybe they should give you

0:18:21.600 --> 0:18:22.960
<v Speaker 1>a big piece of the company or something.

0:18:24.400 --> 0:18:28.080
<v Speaker 3>I'm very fortunate to be compensated. Well, look, I think

0:18:28.960 --> 0:18:32.760
<v Speaker 3>for me, Look, as a technologist, you know, I feel

0:18:32.840 --> 0:18:37.680
<v Speaker 3>like I'm at the front friend, drow Of, you know,

0:18:37.840 --> 0:18:40.840
<v Speaker 3>dreamt about things like AI for a long time. To

0:18:40.960 --> 0:18:44.439
<v Speaker 3>actually see it getting built now and to see this

0:18:44.560 --> 0:18:47.560
<v Speaker 3>transition play out in front of us, to me, you know,

0:18:47.560 --> 0:18:49.320
<v Speaker 3>that's the most motivating thing I could ask for.

0:18:49.520 --> 0:18:51.720
<v Speaker 1>I also know that Google in the early days had

0:18:51.800 --> 0:18:54.800
<v Speaker 1>a policy of free food for its employees, and I

0:18:54.840 --> 0:18:56.680
<v Speaker 1>sampled some of your free food at lunch today.

0:18:56.680 --> 0:18:59.840
<v Speaker 2>It was very good. You obviously have to spend a

0:18:59.840 --> 0:19:00.320
<v Speaker 2>lot of money.

0:19:00.320 --> 0:19:02.679
<v Speaker 1>You've got one hundred and eighty two thousand employees, so

0:19:02.800 --> 0:19:05.840
<v Speaker 1>giving them lunch or breakfast or dinner every day, or

0:19:05.840 --> 0:19:09.080
<v Speaker 1>for many of them every day, you must have a calculation, says,

0:19:09.119 --> 0:19:11.439
<v Speaker 1>are we spending this much on food? We're getting this

0:19:11.560 --> 0:19:14.960
<v Speaker 1>much higher productivity? And how do you assess that? And

0:19:14.960 --> 0:19:16.960
<v Speaker 1>why do you think other companies don't give away food

0:19:17.040 --> 0:19:17.800
<v Speaker 1>as much as you do?

0:19:18.560 --> 0:19:20.919
<v Speaker 3>Look quite the contrar I think in technology, if you

0:19:21.760 --> 0:19:24.000
<v Speaker 3>go to the Bay Area, I think a set of

0:19:24.040 --> 0:19:26.480
<v Speaker 3>things which Google has done as part of now standard

0:19:26.680 --> 0:19:31.400
<v Speaker 3>modern workplaces in the area. But you know, people value

0:19:31.440 --> 0:19:37.640
<v Speaker 3>in person collaboration to us. You know, I can recalled

0:19:37.720 --> 0:19:40.760
<v Speaker 3>several times, you know, when I was working at Google

0:19:40.800 --> 0:19:45.320
<v Speaker 3>early on, being in cafes, meeting someone else, talking, getting

0:19:45.359 --> 0:19:46.760
<v Speaker 3>excited about something, and.

0:19:46.720 --> 0:19:48.679
<v Speaker 2>So it sparks creativity, It creates a.

0:19:48.680 --> 0:19:53.280
<v Speaker 3>Community, and I think the benefit that comes out of it,

0:19:53.359 --> 0:19:55.480
<v Speaker 3>you know, far dwarfs.

0:19:55.040 --> 0:19:56.159
<v Speaker 2>The costs associate with it.

0:19:56.200 --> 0:19:59.640
<v Speaker 1>Google is regularly considered be one of the most favorable

0:19:59.640 --> 0:20:03.879
<v Speaker 1>places to work for employees, always high end surveys, and

0:20:03.920 --> 0:20:05.879
<v Speaker 1>so I assume you've got lots of people who always

0:20:05.880 --> 0:20:08.919
<v Speaker 1>want to come here. How many people a year try

0:20:08.960 --> 0:20:10.200
<v Speaker 1>to apply for jobs at Google?

0:20:10.320 --> 0:20:10.399
<v Speaker 2>Is?

0:20:10.400 --> 0:20:12.680
<v Speaker 1>I assume it's a million people or something more than that.

0:20:12.880 --> 0:20:15.960
<v Speaker 3>What I'm proud of is the metric I look at

0:20:16.040 --> 0:20:19.560
<v Speaker 3>is when we make an offer, what percentage of people

0:20:20.480 --> 0:20:21.440
<v Speaker 3>accept the offer?

0:20:21.920 --> 0:20:25.359
<v Speaker 2>And you know it is percentages. It's almost close to

0:20:25.440 --> 0:20:26.240
<v Speaker 2>ninety percent, right.

0:20:26.280 --> 0:20:28.679
<v Speaker 1>So typically, if somebody wants to get a job, somebody's

0:20:28.720 --> 0:20:30.440
<v Speaker 1>watching this and says, I want to work at Google,

0:20:30.520 --> 0:20:33.520
<v Speaker 1>what are you looking for? High IQs, high work quotient?

0:20:33.840 --> 0:20:35.440
<v Speaker 1>And it used to be said that you had a

0:20:35.600 --> 0:20:38.120
<v Speaker 1>very complicated interview process. I don't know if you still

0:20:38.160 --> 0:20:39.920
<v Speaker 1>have that. But what's the best way to get a

0:20:40.000 --> 0:20:41.560
<v Speaker 1>job here for an entry level person?

0:20:42.520 --> 0:20:44.440
<v Speaker 3>Look, we are you know, it depends on whether you're

0:20:44.480 --> 0:20:48.000
<v Speaker 3>an engineering or something else, but you know we are.

0:20:48.119 --> 0:20:50.000
<v Speaker 3>You know, if you're an engineering, we are looking for

0:20:51.440 --> 0:20:55.040
<v Speaker 3>really good programmers, people who understand computer science well and

0:20:55.320 --> 0:20:58.760
<v Speaker 3>you know, can be dynamically, you know, are willing to

0:20:58.800 --> 0:21:02.720
<v Speaker 3>learn and grow up themselves into new situations and do well.

0:21:03.200 --> 0:21:06.919
<v Speaker 3>But we are really looking for you know, you know,

0:21:07.520 --> 0:21:09.760
<v Speaker 3>superstar software engineers.

0:21:09.840 --> 0:21:10.760
<v Speaker 2>Right, So, when.

0:21:10.640 --> 0:21:12.639
<v Speaker 1>You're doing a search yourself, I suppose you want to

0:21:12.640 --> 0:21:15.560
<v Speaker 1>get information. Do you ever have frustrations that you can't

0:21:15.560 --> 0:21:17.760
<v Speaker 1>get what you want? I mean, sometimes I can't find

0:21:17.760 --> 0:21:20.000
<v Speaker 1>what I want, But I'm not the CEO of Google,

0:21:20.040 --> 0:21:22.119
<v Speaker 1>so I assume you can have better access to the

0:21:22.160 --> 0:21:23.080
<v Speaker 1>search than I can.

0:21:23.600 --> 0:21:27.000
<v Speaker 3>No, there are one of the reasons I'm so excited

0:21:27.000 --> 0:21:31.360
<v Speaker 3>about AI improving searches. You know, we're constantly people don't

0:21:31.359 --> 0:21:35.720
<v Speaker 3>always formulate the right queries. You know, we are constantly

0:21:35.760 --> 0:21:38.200
<v Speaker 3>working to make search easier to use. So for example,

0:21:38.880 --> 0:21:42.239
<v Speaker 3>you can now you know, speak with search as well

0:21:42.280 --> 0:21:46.200
<v Speaker 3>as take pictures and ask search questions. In many countries,

0:21:46.200 --> 0:21:49.480
<v Speaker 3>for example, in places like India, a large volume of

0:21:49.480 --> 0:21:52.520
<v Speaker 3>our queries actually come by people just talking to search.

0:21:53.320 --> 0:21:55.600
<v Speaker 3>And you know, because people get phone not everyone is

0:21:55.600 --> 0:21:58.800
<v Speaker 3>comfortable typing in these phones. They just talk talk to Google.

0:21:59.480 --> 0:22:01.120
<v Speaker 2>Similarly, what we call visual search.

0:22:01.160 --> 0:22:02.760
<v Speaker 3>We have a product called Google Lens and you can

0:22:02.800 --> 0:22:05.520
<v Speaker 3>take a picture and ask questions. We get billions of

0:22:05.600 --> 0:22:09.040
<v Speaker 3>queries through visual search. Humans interact with the world in

0:22:09.160 --> 0:22:12.920
<v Speaker 3>very natural ways. We see things, we hear things, we speak,

0:22:13.640 --> 0:22:16.280
<v Speaker 3>and so that's an example of how we can search,

0:22:16.560 --> 0:22:19.800
<v Speaker 3>make search better, and AI can play it all. I

0:22:19.960 --> 0:22:23.480
<v Speaker 3>constantly am challenging our product find things we could be

0:22:23.520 --> 0:22:25.679
<v Speaker 3>doing better than I'm emailing my teams.

0:22:25.720 --> 0:22:28.280
<v Speaker 1>So, leaving the US government aside, what do you see

0:22:28.280 --> 0:22:31.840
<v Speaker 1>as the biggest challenge to Google an alphabet going forward?

0:22:31.960 --> 0:22:35.760
<v Speaker 1>Is it competitors coming along, is it a new technology

0:22:35.800 --> 0:22:38.360
<v Speaker 1>that you're not in yet coming along and being very important,

0:22:38.840 --> 0:22:44.200
<v Speaker 1>or just keeping your organization efficient and not bureaucratic.

0:22:44.480 --> 0:22:45.880
<v Speaker 2>What do you see as the biggest challenges?

0:22:46.359 --> 0:22:51.400
<v Speaker 3>Look, one of the things I would say, because we've

0:22:51.440 --> 0:22:54.879
<v Speaker 3>always been a foundational technology company and we are working

0:22:54.920 --> 0:22:57.760
<v Speaker 3>on these technologies which can apply across many things. I

0:22:57.760 --> 0:22:59.440
<v Speaker 3>think one of the things which is unique to Google

0:22:59.480 --> 0:23:02.159
<v Speaker 3>and Alphabet is, you know, we have a chance to

0:23:02.160 --> 0:23:07.480
<v Speaker 3>go do many things, but being disciplined doing a few

0:23:07.520 --> 0:23:10.760
<v Speaker 3>things and doing them well and doing it with the

0:23:11.080 --> 0:23:14.920
<v Speaker 3>relentless focus on innovation and doing it as efficiently as possible.

0:23:14.960 --> 0:23:17.720
<v Speaker 3>As a company with discipline, you know what leads to

0:23:17.760 --> 0:23:21.200
<v Speaker 3>long term success. And so so I think that's what

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<v Speaker 3>I think about, right, you know, where all can we

0:23:24.760 --> 0:23:27.880
<v Speaker 3>do it ourselves as a company? Where do we partner

0:23:27.880 --> 0:23:30.280
<v Speaker 3>and enable others? That's why Google Cloud has been a

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<v Speaker 3>big part of our focus because there are many sectors

0:23:33.160 --> 0:23:35.119
<v Speaker 3>in which the best way we can help the world

0:23:35.200 --> 0:23:39.240
<v Speaker 3>and have a good business doing so is by providing

0:23:39.280 --> 0:23:42.639
<v Speaker 3>our technology and solutions to others, and so you know,

0:23:42.640 --> 0:23:43.679
<v Speaker 3>it's getting that balance.

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<v Speaker 2>Druck.

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<v Speaker 1>Thanks for listening to hear more of my interviews. You

0:23:47.480 --> 0:23:51.560
<v Speaker 1>can subscribe and download my podcast on Spotify, Apple, or

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<v Speaker 1>wherever you listen.