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The Diary of a CEOThe Diary of a CEO

Eric Schmidt: Why AI needs divas, fast fails, and a plug

Schmidt scaled Google from 100 million to 180 billion dollars. He explains AI misinformation risks, the chip and energy race, and a plug rule for safety.

Eric SchmidtguestSteven Bartletthost
Nov 14, 20241h 49mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:00 – 2:05

    Intro

    1. ES

      Someone was leaking information on Google, and this stuff is incredibly secret.

    2. SB

      So what are the secrets?

    3. ES

      Well, the first is- Eric Schmidt is the former CEO of Google. Who grew the company from $100 million to $180 billion. And this is how.

    4. SB

      As someone who's led one of the world's biggest tech companies, what are those first principles for leadership, business, and doing something great?

    5. ES

      Well, the first is risk-taking is key. If you look at Elon, he's an incredible entrepreneur, because he has this brilliance where he can take huge risks and fail fast. And fast failure is important, because if you build the right product, your customers will come. But it's a race to get there as fast as you can, because you want to be first, because that's where you make the most amount of money.

    6. SB

      So what are the other principles that I need to be thinking about?

    7. ES

      So here's a really big one. At Google, we have this 70-20-10 rule that generated $10, $20, $30, $40 billion of extra profits over a decade, and everyone can go do this. So the first thing is-

    8. SB

      What about AI?

    9. ES

      I can tell you that if you're not using AI at every aspect of your business, you're not gonna make it.

    10. SB

      But you've been in the tech industry for a long time, and you've said, "The advent of artificial intelligence is a question of human survival."

    11. ES

      AI is going to move very quickly, and you will not notice how much of your world has been co-opted by these technologies, because they will produce greater delight. But the questions are, "What are the dangers? Are we advancing with it, and do we have control over it?"

    12. SB

      What is your biggest fear about AI?

    13. ES

      My actual fear is different from what you might imagine. My, my actual fear is... That's a good time to pull the plug.

    14. SB

      This has always blown my mind a little bit. 53% of you that listen to this show regularly haven't yet subscribed to the show. So could I ask you for a favor before we start? If you like the show, and you like what we do here, and you want to support us, the free simple way that you can do just that is by hitting the subscribe button. And my commitment to you is, if you do that, that I'll do everything in my power, me and my team, to make sure that this show is better for you every single week. We'll listen to your feedback, we'll find the guests that you want me to speak to, and we'll continue to do what we do. Thank you so much. Eric, I've read about your career,

  2. 2:05 – 3:49

    Why Did You Write a Book About AI?

    1. SB

      and you've had an extensive, a varied, a fascinating career, a, a completely unique career. And that leads me to believe that you could have written about anything. You know, you've got some incredible books, all of which I've been through over the last couple of weeks here in front of me.

    2. ES

      I apologize. (laughs)

    3. SB

      No, no. But I mean, these are subjects that I'm just obsessed with. But this book in particular, of all the things you could have written about with the world we find ourselves in, why this? Why Genesis?

    4. ES

      Well, first, thank you for ... I've wanted to be on this show for a long time, so I'm really happy to be able to be here in person in London. Henry Kissinger, Dr. Kissinger, ended up being one of my greatest and closest friends. And 10 years ago, he and I were at a conference where he heard, heard Demis Hassabis speak about AI. And Henry would tell the story that he was about to go catch up on his jet lag, but instead, I said, "Go do this," and he listened to it. And all of a sudden, he understood that we were playing with fire, that we were doing something that we did not understand it would have the impact on. And that Henry had been working on this since he was 22, coming out of the army after World War II, and his thesis about Kant and so forth as an undergraduate at Harvard. So all of a sudden, I found myself in a whole group of people who were trying to understand, what does it mean to be human in an age of AI? When this stuff starts showing up, how does our life change? How do our thoughts change? Humans have never had an intellectual challenger of our own ability or better or worse. It's just never happened in history. The arrival of AI is a huge moment in history.

  3. 3:49 – 5:06

    Your Experience in the Area of AI

    1. ES

    2. SB

      For anyone that doesn't know your story, or maybe just knows your story from sort of Google onwards, can you tell me the sort of inspiration points, the education, the experiences that you're drawing on when you talk about these subjects?

    3. ES

      Well, like many of the people you meet, um, as a teenager, I was interested in science, I played with model rockets, model trains, the, the usual things for a boy in my generation. I was too young to be a video game addict, but I'm sure I would be today if I were that age. Um, I went to college, and I was very interested in computers, and they were relatively slow then. But to me, they were fascinating. To give you an example, the computer that I used in college is 100 million times slower, 100 million times slower than the phone you have in your pocket. And by the way, that was a computer for the entire university. So Moore's Law, which is this notion of accelerating density of chips, has defined the wealth creation, the career creation, the company creation in my life. So I can be understood as lucky, because I was born with a, with an interest in something which was about to explode. And when, when sort of everything happens together, everyone gets swept up in it. And of course, the rest is history.

  4. 5:06 – 6:49

    Essential Knowledge to Acquire at 18

    1. ES

    2. SB

      I was sat this weekend with my partner's little brother, who's 18 years old.

    3. ES

      Yes.

    4. SB

      And as we ate breakfast yesterday before they flew back to Portugal, we had this discussion with her family, um, her dad was there, her mom was there, Raph, the younger brother, was there, and my girlfriend was there. Difficult, because most of them don't speak English, so we had to use, funnily enough, AI to translate what I was saying.

    5. ES

      Of course. (laughs)

    6. SB

      But the big discussion at breakfast was, what should Raph do in the future?

    7. ES

      Yeah.

    8. SB

      He's 18 years old. He's got his career ahead of him. And the decisions he makes, as is so evident in your story, at this exact moment, as to what information and intelligence he acquires for himself will quite clearly define the rest of his life. If you were sat at that table with me yesterday, when I was trying to give Raph advice on what w- what knowledge he should acquire at 18 years old, what would you have said? And what are the principles that are s- sit behind that?

    9. ES

      The most important thing is to develop analytical critical thinking skills.I-- to some level, I don't care how you get there. So if you're a m- if you like math or science or if you like the law or if you like, you know, entertainment, just think critically. In his particular case, as a, as a 18-year-old, what I would encourage him to do is figure out how to write programming, uh, to write programs in a language called Python. Python is easy to use, it's very easy to understand, and it's become the language of AI. So the A- the AI systems, when they write code for themselves, they write code in Python. And so you can't lose as developing Python programming skills. And the simplest thing to do with an 18-year-old man is say, "Make a game."

    10. SB

      Mm-hmm.

    11. ES

      'Cause these are typically gamers, stereotypically. M- make a game that's interesting using Python.

  5. 6:49 – 7:49

    Is Coding a Dying Art Form?

    1. ES

    2. SB

      I, it's interesting 'cause I w- wondered if coding, you know, I think five, 10 years ago, everyone's advice to an 18-year-old is learn how to code. But in a world of AI where these large language models are able to write code and are, you know, increasing every month in their ability to write better and better code, I wondered if that's, like, a dying art form.

    3. ES

      Yeah. A lot of people oppose this, and that's not correct. It sure looks like these systems will write code, but remember, the systems also have interfaces called APIs which you can program them. So one of the large revenue sources for these AI models, 'cause these companies have to make money at some point, right-

    4. SB

      Mm-hmm.

    5. ES

      ... is you build a program, and you actually make an API call and ask it a question. Typ- typical example is give it a picture and tell me what's in the picture. Now, can you have some fun with that as an 18-year-old? Of course, right?

    6. SB

      Mm-hmm.

    7. ES

      So, so when I say Python, I mean Python using the tools that are available to build something new-

    8. SB

      Mm-hmm.

    9. ES

      ... something that you're interested

  6. 7:49 – 10:24

    What Is Critical Thinking and How Can It Be Acquired?

    1. ES

      in.

    2. SB

      And when you say critical thinking, how does one... What is critical thinking?

    3. ES

      Uh.

    4. SB

      And how does one go about acquiring that as a skill?

    5. ES

      Well, the first and most important thing about critical thinking is to distinguish between being marketed to, which is also known as being lied to, and being, being given the argument on your own. We have, because of social media, which I hold responsible for a lot of ills as well as good things in life, we've, we've sort of gotten used to people just telling us something and believing it because our friends believe it or so forth. And I strongly encourage people to check assertions. So you get people who say all this stuff, and I learned at Google all those years, somebody says something, I check it on Google. Do I... And, uh, you then have a question. Do you criticize them and correct them, or do you let it go? But you want to be in the position where somebody makes a statement. Like, did you know that only 10% of Americans have passports? Which is a widely viewed, but false statement. Um, it's actually higher than that, although it's never high enough in my view in America. But that's an example of an assertion that you can just say, "Is that true?" Right?

    6. SB

      Mm-hmm.

    7. ES

      And, and there's a, a long meme about American politicians where the Congress is basically full of criminals. Um, it may be full of one or two, but it's not full of, of 90.

    8. SB

      Mm-hmm.

    9. ES

      But again, people believe this stuff because it sounds plausible. So if y- if somebody says something plausible, just check it.

    10. SB

      Mm-hmm.

    11. ES

      You have a responsibility before you repeat something to make sure what you're repeating is true. And if you can't distinguish between f- true and false, I suggest you keep your mouth shut, right? Because you can't run a government, a society without people operating on basic facts. Like, for example, climate change is real. We can debate over whether it's... H- how to address it, but there's no question the climate is changing. It is a fact. It is a mathematical fact. And how do I know this answer? Somebody will say, "Well, how do you know?" And I said, "Because science is about repeatable, uh, uh, experiments and also proving things wrong." So let's say I said that, um, climate change is real, uh, and this was the first time it had ever been said, which is not true. Then 100 people would say, "That can't be true. I'll see if he's wrong." And then, and then all of a sudden, they'd see I was right, and I'd get some big prize.

    12. SB

      Mm-hmm.

    13. ES

      Right? So, so the falsifiability of these assertions is very important. How do you know that science is correct? It's because people are constantly testing it.

  7. 10:24 – 13:40

    Importance of Critical Thinking in AI

    1. SB

      And why is this skill of critical thinking so especially i- important in a world of AI?

    2. ES

      Well, partly because AI will allow for perfect misinformation. So let's use an example of TikTok. TikTok can be understand... It's called the bandit algorithm in computer science, in the sense of the Las Vegas one-armed bandits. Do I stay in the bandit machine, and I keep on this slot machine, or do I move to another slot machine? And the, the TikTok algorithm basically can be understood as, "I'll keep serving you what you tell me you want, but occasionally, I'll give you something from the adjacent area." And it's highly addictive. So what you're seeing with social media, and TikTok is a particularly bad example of this, is people are getting into these rabbit holes where they, all they see is confirmatory bias. And, and the ones that are... I, I mean, if it's fun and, you know, entertaining, I don't care. But you'll see, for example, there are plenty of stories where people have ultimately self-harm or suicide because they're already unhappy, and then, and then they start picking up unhappy... And then their whole environment online is people who are unhappy, and it makes them more unhappy because it doesn't have a positive bias. So there's a really good example where, um, e- let's say in your case, you're the dad. You're gonna watch this as the dad with your kid, and you're gonna say, "You know, it's not that bad. Let me show you some... Th- th- let me give you some good alternatives. Let me get you inspired. Let me get you out of your funk." The algorithms don't do that unless you force them to. It's because the algorithms are fundamentally about optimizing an objective function, literally mathematically maximize some goal that it's been trained to.

    3. SB

      Attention.

    4. ES

      It just... In, in this case, it's attention. And by the way, part of it, part of we ha- we have so much, uh, outrage is because if you're a CEO, you want to maximize revenue. To maximize revenue, you maximize attention.... and the easiest way to maximize attention is to maximize outrage. "Did you know? Did you know? Did you know?" Right? And by the way, a lot of this stuff is not true. They're fighting over scarce attention. There was a recent article where... Th- there's an old quote from 1971 from Herb Simon, who was an economist at the time at Carnegie Mellon, who said that, um, e- economists don't understand, but in the future, the scarcity will be about attention. So somebody now, 50 years later, went back and said, "I think we're at the point where we've monetized all attention." Uh, an article this week, two and a half hours of videos consumed by young people every day, right? Now, there is a limit to the amount of video you can, you know, that y- 'cause you have to eat and sleep and hang out, but these are significant societal changes that have occurred very, very quickly. Um, when I was young, there was a great debate as to the benefit of television, and, you know, my argument at the time was, "Well, yes, we did, you know, we did, uh, you know, uh, rock and roll and, and drugs and all of that, and we watched a lot of television, but somehow we grew up okay." Right? So it's the same argument now with a different, uh, a different term. Will we, will those kids grow up okay? Um, it's not as obvious, because these tools are highly addictive, much more so than te- television ever

  8. 13:40 – 15:38

    When Your Children's Best Friend Is a Computer

    1. ES

      was.

    2. SB

      Do you think they'll grow up okay?

    3. ES

      I personally do because I'm in- I'm inherently an optimist. I also think that society, um, begins to understand the problems. A typical example is there's an epidemic of harm to teenage girls. Uh, girls, as we know, are, uh, more advanced than boys at those, uh, you know, below 18, uh, and the girls seem to get hit by social media at 11 and 12 when they're not quite capable of handling the, the rejection and the emotional stuff. And it's driven, uh, you know, emergency room visits, self-harm, and so forth to record levels. This is well-documented. So society is beginning to recognize this. Now, ph- uh, schools won't let kids use their phones when they're in the classroom, which is kind of obvious if you ask me. Um, so developmentally, uh, one of the core questions about the AI revolution is what does it do to the identity of children that are growing up? Your values, your personal values, the way you get up in the morning and think about life is now set. It's highly unlikely that an AI will change your programming, but your child can be significantly reprogrammed. Uh, one of the things that we talk about in the book is what happens when the best friend of your child from birth is a computer? What's it like? Now, by the way, I don't know. We've never done it before, but you're running an experiment on a billion people without a control, right? And so we have to stumble through this. So at the end of the day, I'm an optimist because we will adjust society with biases and values to try to keep us on a moral high ground human life. And so you should be optimistic for that because these kids, when they grow up, they'll live to 100. Their lives will be much more prosperous. I hope and I, I pray that there'll be much less conflict. Uh, certainly their lifespans are longer. Their, the likelihood of them being injured in, in, in, in wars and so forth are much, much lower statistically. It's a good message to kids.

  9. 15:38 – 18:38

    How Would You Reduce TikTok's Addictiveness?

    1. SB

      As someone who's led one of the world's biggest tech companies, if you were the CEO of TikTok, what would you do? Because, uh, y- I'm sure that they realize everything you've said is true, but they have this commercial incentive to drive up the addictiveness of the algorithm which is causing these echo chambers, which is causing the rates of anxiety and depression amongst young girls and young people more generally to increase. What would you do?

    2. ES

      So, so I have talked to them and to the others as well, and I think it's- it's pretty straightforward. There's sort of good revenue and bad revenue. When we were at Google, uh, Larry and Sergey and I, we would have situations where we would improve quality. You know, we would make the product better, and the debate was do we take that to revenue in the form of more ads, or do we just make the product better? And, and that was a clear choice, and I arbitrarily decided that we would take 50% to one, 50% to the other 'cause I thought they were both important.

    3. SB

      Mm-hmm.

    4. ES

      So... And the founders, of course, were very supportive. So Google became more moral and also made more money, right? All of the- the... There's plenty of bad stuff on Google, but it's not on the first page. That was the key thing. The alternative model would be, say, "Let's maximize revenue. We'll put all the really bad stuff, the lies and the cheating and the deceiving and so forth that draws you in and will drive you insane," and we might have made more money, but first, it was the wrong thing to do. But more importantly, it's not sustainable. Uh, there's a law, uh, called Gresham's law, uh, it's a verbal law obviously, um, where bad speech drives out good speech, and what you're seeing is you're seeing in online communities, which have always been, um, present with bullying and this kind of stuff, now you've got crazy people, in my view, who are building bots that are lying, right? Misinformation. Now, why do you do that? You've got... And, and there was a Fl- there was a hurricane in Florida, and people are in serious trouble, and you sitting in the comfort of your home somewhere else are busy trying to make their lives more difficult. What's wrong with you? Like, let them get rescued. (laughs)

    5. SB

      (laughs)

    6. ES

      You know, human life is important. But there's something about the, the human psychology where people, uh, people talk a- it's the w- there's a German word called schadenfreude. You know, there's a bunch of things like this that we have to address. I want social media and the online world to represent the best of humanity, hope, excitement, optimism, creativity, invention, solving new problems, as opposed to the worst, and I think that that is achievable.

    7. SB

      You arrived at Google at 46 years old, 2001?

    8. ES

      2001.

    9. SB

      2001. Um, you had a very extensive career before then working for a bunch of really interesting companies. Sun Microsystems is one that I know, um, very well. You've worked with Xerox-

    10. ES

      Mm-hmm.

    11. SB

      ... in California as well. Bell Labs was your first, um, sort of real job, I guess, at 20 years old, first sort of big tech job.What

  10. 18:38 – 20:57

    Principles of Good Entrepreneurship

    1. SB

      did you learn in this journey of your life about what it is to build a great company and what value is as it relates-

    2. ES

      (coughs)

    3. SB

      ... to being an entrepreneur?

    4. ES

      Um-

    5. SB

      And people in teams. Like if there were, like, a set of first principles that everyone should be thinking about when it comes to doing something great and building something great, what are those, like, first principles?

    6. ES

      So, so the first rule I've learned is that you need a truly brilliant person to build a really brilliant product, and that is not me. I work with them. So find someone who's just smarter than you, more clever than you, moves faster than you, changes the world, is better spoken, more handsome, more beautiful, you know, whatever it is that you're optimizing, and ally yourself with them, because they're the people who are gonna make, make the world different. Um, in one of my books, we use the distinction between divas and knaves.

    7. SB

      Mm-hmm.

    8. ES

      And a diva, and we use the example of Steve Jobs, who clearly was a diva, opinionated and strong and argumentative and would bully people if he didn't like them, but was brilliant when he was, and he was a diva. He, he wanted perfection. Right? Aligning yourself with Steve Jobs is a good idea. Uh, the alternative is what we call a knave, and a knave, which you know from British history, is somebody who's acting on their own, um, their own account. They're not, they're not trying to do the right thing. They're trying to benefit themselves at the s- at the, at the cost of others. And so if you can identify a person in one of these teams, th- they're just trying to solve the problem in a really clever way, and they're passionate about it, and they want to do it. That's how the m- world moves forward. If you don't have such a person, your company's not gonna go anywhere. And the reason is that it, it's too easy just to keep doing what you were doing, right? And, and innovation is fundamentally about changing what you're doing. Up until the t- this generation of tech companies, th- th- most companies seemed to me to be one-shot wonders. Right? They would have one thing that was very successful, and then it was sort of, um, it was typically follow an S-curve and nothing much would happen. And now I think the, that people are smarter, people are better educated, you now see repeatable waves. A good example being Microsoft, which is, you know, an older company now, uh, founded in basically '81, '82, something like that. So let's call that 45 years old. But they've reinvented themselves a number of times, right? In a, in a really powerful way.

  11. 20:57 – 22:01

    Founder Mode

    1. SB

      We should probably talk about this then, um, before we move on, which is, what you're talking about there is that sort of founder, m- things people now refer to as founder mode, that founder energy, that high conviction, that sort of-

    2. ES

      Mm-hmm.

    3. SB

      ... disruptive thinking, um, and that ability to reinvent yourself. I was looking at some stats last night, in fact, and I was looking at how long companies stay on the S&P 500 on average now, and it went from 33 years, to 17 years, to 12 years average tenure. And as you play those numbers forward eventually in sort of 2050, an AI told me that it would be about eight years. (laughs)

    4. ES

      (laughs) Well, uh, I, I'm not sure I agree with the founder mode argument, and the reason is that it's great to have a brilliant founder and in, um, a- and there's this, i- it's actually, like, more than great. It's, like, really important, and, and we need more s- brilliant founders. Universities are producing these people, by the way. They do exist, and they show up every year, you know, another Michael Dell at the age of 19 or 22. These are just brilliant founders, uh, obviously Gates and Ellison and m- sort of my generation of brilliant founders, uh, Larry and Sergey and so forth.

  12. 22:01 – 24:27

    The Backstory of Google's Larry and Sergey

    1. SB

      For anyone that doesn't know who Larry and Sergey are-

    2. ES

      Sorry.

    3. SB

      ... and doesn't know that sort of early Google story, um, can you give me a little bit of that backstory, but then also introduce these characters called Larry and Sergey for anyone that doesn't know?

    4. ES

      So Larry Page and Sergey Brin met at Stanford, um, in, they were on a grant from, believe it or not, the National Science Foundation as graduate students. And Larry Page invented a algorithm called PageRank, uh, which is named after him. Um, and he and Sergey wrote a paper, which is still one of the most cited papers in, in the world, and it's essentially a way of understanding priority of information. And mathematically, it was a Fourier transform of the way people normally did things at, at the time. And so they wrote this code. I don't think they were that good a set of programmers, you know, they sort of did it. They had a computer. They ran out of power in their dorm room, so they, um, borrowed the power from the dorm room next to and plugged it in, and they had the data center in the bedroom, you know, in the dorm. Classic story. Um, and then they moved to a, uh, building that was owned by, um, the sister of a girlfriend at the time, and that's how they founded the company. Their first investor was a, a, one of the founder of Sun Microsystems, his name was Andy Bechtolsheim, who just said, "I'll just give you the money 'cause you're obviously incredibly smart."

    5. SB

      How much did he give them?

    6. ES

      $100,000, or may- yeah, I think or maybe it was a million. But in any case, it, it ultimately meant, became many billions of dollars. So it gives you a sense of this early founding is very important. So the founders then set up in this little house in Menlo Park, which ultimately we bought at Google, you know, as a mo- as a museum. And they set up in the garage, and they had Google Wor- Google world headquarters in neon made, and they had a big headquarters, um, with the four employees that were sitting below them and the computer that Larry and Sergey had built. Larry and Sergey were very, very good software people, and obviously brilliant, but they were not very good at hardware. And so they built the computers using corkboard to separate the CPUs. And if you know anything about hardware, hardware generates a lot of heat, and the corkboard would catch on fire. So eventually, when I showed up, we started building proper hardware with proper har- hardware engineers. But it gives you a sense of the scrappiness that, that was so characteristic. Um, and, you know, today, uh, well, they are people of enormous impact on society, um, and I think that will continue, um, for many,

  13. 24:27 – 25:33

    How Did You Join Google?

    1. ES

      many years.

    2. SB

      Why did they call you in, and at what point did they realize that they needed someone like you?

    3. ES

      Well, Larry said to me, uh, now these were ve- they were very young. He looked at me and says, "We don't need you now. But we'll need you in the future."

    4. SB

      ... (pause) will need you in the future?

    5. ES

      Yeah. So it, one of the things about Larry and Sergey is that they thought for the long term. So they didn't say Google would be a search company. They said the mission of Google is to organize all the world's information. And if you think about it, that's pretty audacious 25 years ago. Like, how are you gonna do that? And so they started with web search eventually, and Larry had studied AI quite extensively, and he began to, to work and ultimately he, uh, acquired, uh, with, with all, all of us obviously, uh, this company called DeepMind here in Britain, which essentially is the, um, the first company to really see the AI opportunity. And pretty much all of the things you've seen from AI in the last decade have come from people who were either at DeepMind or competing with DeepMind.

  14. 25:33 – 28:50

    Principles of Scaling a Company

    1. ES

    2. SB

      Going back to this point about principles then, before we move further on, um, as it relates to building a great company, what are some of those founding principles? We have lots of entrepreneurs that listen to this show. One of them you've expressed is this need for the divas, I guess, these people who are just very high conviction and can kind of see into the future. What are the other principles that I need to be thinking about when I'm scaling my company?

    3. ES

      Well, the first is to think about scale. Uh, I think a current example is look at Elon. Um, Elon is an incredible entrepreneur and an incredible scientist, and if you study how he operates, he gets people by, I think, sheer force of personal will to over perform, to take huge risks, which somehow he, he has this brilliance where he can make those trade-offs and get it right. So these are exceptional people. Now, in our book, with Genesis, we argue that you're gonna have that in your pocket. But as to whether you'll have the judgment to take the risks that Elon does, that's another question.

    4. SB

      Mm-hmm.

    5. ES

      The, one of the other ways to think about it is an awful lot of people talk to me about the companies that they're founding, and they're, they're a little widget. You know, like, "I wanna make the camera better," or, "I wanna make the dress better," or, "I wanna make book publishing cheaper," or so forth. These are all fine ideas. I'm interested in d- in ideas which have the benefit of scale. And when I scale, I say scale, I mean the ability to go from zero to infinity in terms of the number of users and demand and scale. Um, uh, there are plenty of, plenty of ways of thinking about this, but what would be such a company in the age of AI? Well, we can tell you what it would look like. It would have apps, one on Android, one on iOS, maybe a few others. Those apps will use powerful networks, and they'll have a really big computer in the back that's doing AI calculations. So, future successful companies will all have that.

    6. SB

      Mm-hmm.

    7. ES

      Right? Exactly what problem it solves, well, that's up to the founder. But if you're not using AI at every aspect of your business, you're not gonna make it. And the distinction pro- as a programming matter is that when I was doing all of this way back when, you had to write the code. Now, AI has to discover the answer.

    8. SB

      Mm-hmm.

    9. ES

      It's a very big deal. And of course, this was, a lot of this was invented at Google, you know, 10 years ago. But basically, all of a sudden, an analytical programming sort of what I did my whole life, you know, writing code and, you know, do this, do that, add this, subtract this, call this, so forth and so on, is gradually being replaced by learning the answer, right? So for example, we use the example of translate, language translation. Uh, the, uh, the current large language models are essentially organized around predicting the next word. Well, if you can predict the next word, you can predict the next sequence in biology. You can predict the next action. You can predict the next thing the robot should do. So all of this stuff around large language models and deep learning, it has come out, the transformer paper, GPT-3, uh, ChatGPT, which for most people was this huge moment, is essentially about, um, predicting the next word and getting it right.

  15. 28:50 – 33:02

    The Significance of Company Culture

    1. ES

    2. SB

      In terms of company culture and how important that is for the success and prospects of a company, how do you think about company culture and how significant and important is it? And, like, when and who sets it?

    3. ES

      So I'll give, well, it's almost always set, company cultures are almost always set by the founders. Uh, I happen to be on the board of the Mayo Clinic. The Mayo Clinic is the largest healthcare system in America. It's also the most highly rated one. And they have a rule which is called the, uh, the needs of the customer come first, which came out of the Mayo brothers who've been dead for like 120 years. Um, but that was their principle. And w- I, when I initially got on the board, I started wandering around and I thought, "This is kind of a stupid, you know, stupid phrase, and nobody really does this." And they really believe it, and they repeat it, and they repeat it, right? So it's true in non-technical cultures, in that case, it's the healthcare se- for service delivery. You can drive a culture even in non-tech. In tech, it's typically an engineering culture. And if I had to do things over again, I would have even more technical people and even fewer non-technical people, and just make the technical people figure out what they have to do.

    4. SB

      Mm-hmm.

    5. ES

      Um, and I'm sorry for that bias, 'cause I'm not trying to offend anybody. But the fact of the matter is that technical people, if you build the right product, your customers will come. If you don't build the right product, then you don't need a sales force. Why are you selling an inferior product? So in, in the How Google Works book and ultimately in The, uh, Trillion Dollar Coach book, which is about Bill Campbell, we talked a lot about how the CEO is now the chief product officer, the chief innovation officer, because 50 years ago, you didn't have access to capital, you didn't have access to marketing, you didn't have access to sales, you didn't have the access to distribution hours. I was meeting today with an entrepreneur who said, "Yeah, you know, we'll be 95% technical." And I said, "Why?" He said, "Well, we have a contract manufacturer."... and our products are so good that people will just buy them. This happened to be a- a- a technical switching company. Um, and they said, "It's only 100,000 times better than its competitors." And I said, "It will sell."

    6. SB

      Mm-hmm.

    7. ES

      Unfortunately, it doesn't work yet.

    8. SB

      Yeah.

    9. ES

      That isn't the point. But if they achieve their goal, people will be lined ups outside the door. So as a matter of culture, you want to build a technical culture with values about getting the product to work, right? And w- working meet is not... Another thing you do with, with engineers is you say, they, they make a nice presentation to you, and they go, "Oh, that's a... that's very interesting, but you know, I'm not your customer." Your customer is really tough, because your customers wants everything to work, and free, and work right now, and never make any mistakes. So give me their feedback, and if their feedback is good, I love you.

    10. SB

      (laughs)

    11. ES

      And if their feedback is bad, then you better get back to work and stop being so arrogant.

    12. SB

      Hmm.

    13. ES

      So what happens is that in- in the invent- in the invention process within firms, people fall in love with an idea, and they don't test it. One of the things that Google did, and this was largely Marissa Mayer, way back when, is one day she said to me, "I don't know how to judge user interface."

    14. SB

      Marissa Mayer was the previous CEO.

    15. ES

      She was the CEO of Yahoo! And before that, she ran all the consumer products at Google, uh, and she's now running a- another company in, uh, in the Bay Area. But the important thing about Marissa is she said, "I can't..." I- I said, "Well, you know, the UI, the user interface is great," at the time, and it was, certainly was. And she said, "I don't know how to judge the user interface myself, and none of my team do, but we know how to measure." And so what she organized were A/B tests, you test one, test another. So remember that it's possible using these networks to actually kind of figure out, 'cause they're highly instrumented, uh, dwell time, how long does somebody, uh, uh, h- how long does somebody watch this, how important it is. If you go back to how TikTok works, uh, one of the things, the signals that they use include the amount of time you watch, commenting, um, forwarding, uh, sharing, all of those kinds of things. And those, you can understand those as analytics that go into an AI engine and makes a decision as to what to do next, what to make viral.

    16. SB

      Mm-hmm.

  16. 33:02 – 36:42

    Should Company Culture Change as It Grows?

    1. SB

      And on this point of, um, culture at scale, is it right to expect that the culture changes as the company scales? Because you came into Google, I believe, when they were doing sort of $100 million in revenue, and you left when they were doing, what, z- 180 billion or something staggering?

    2. ES

      Yeah.

    3. SB

      But is it right to assume that the culture of a growing company should scale from when there was 10 people in that garage to when there's 100?

    4. ES

      So when I go back to Google to visit, and they were kind enough to give me a badge and treat me well, of course, um, I hear the echoes of this. Um, I was at a lunch where there was a lady running search and a gentleman running ads, you know, the- the- the successors to the people who worked with me, and I- I asked them, "What's it going?" And they said the same problems, you know, the same problems have not been solved, but they're much bigger.

    5. SB

      Mm-hmm.

    6. ES

      And so when you go to a company, I suspect, um, I was not at, near the founding of Apple, but I was on the board for a while. Um, the founding culture you can see today in their obsession about user interfaces, their obsession about being closed, and their privacy and secrecy, it's just a different company, right? I'm not passing judgment. Um, setting the culture is important, the echoes are there. What does happen in big companies is they become less efficient for many reasons. The first thing that happens is they become conservative because of they're public and they have lawsuits. And, um, a famous example is that Microsoft, after the antitrust, um, uh, case in the '90s became so conservative in terms of what it could launch that it really missed the web revolution for a long time. They- they have since recovered, and I, of course, was happy to exploit that as a competitor to them when- when we were at Google. But- but the important thing is when... Big companies should be faster because they have more money and more scale, they should be able to do things even quicker, but in my industry anyway, the- this tech startups that have a new clear idea tend to win because the big company can't move fast enough to do it. Another example, we had built something called Google Video. I was very proud of Google Video, and David Drummond, who was the, uh, general counsel at the time, came in and said, "You have to look at this YouTube people." I said like, "Why?" Right? Who cares? And it turns out, "They're really good and they're more clever than your team." And I said, "That can't be true," you know, typical arrogant Erik. And we sat down and we looked at it, and they really were quicker, even though we had an incumbent. And why? It turns out that the incumbent was operating under the traditional rules that Google had, which was fine, and the competitor, in this case YouTube, was not constrained by that. They could work at any pace and they could do all sorts of things, intellectual property and so forth. Ultimately, we were sued all, over all of that stuff, and we ultimately won all those suits. But it's an example where there are these moments in time where you have to move extremely quickly. You're seeing that right now with generative, uh, technology, so the AGI, the- the generative revolution, generate code, generate videos, generate text, generate everything. All of those winners are being determined in the next six, 12 months, and then once th- once the slope is set, once the growth rate is, you know, quadrupling every, uh, six months or so forth, it's very hard for somebody else to come in. So- so it's a race to get there as fast as you can. So when you talk to the- the great venture capitalists, they are, they're fast, right? We'll look at it, we'll make a decision tomorrow, we're done, we're in, and so forth, and we want to be first, because that's where they make the most amount of money.

    7. SB

      We were talking, before

  17. 36:42 – 38:15

    Is Innovation Possible in Big Successful Companies?

    1. SB

      you arrived, I was talking to Jack about the- this idea of like harvesting and hunting.... so harvesting what you've already-

    2. ES

      Yeah.

    3. SB

      ... sowed and hunting for new opportunities. But I, I've always found it's quite difficult to get the harvesters to be the hunters at the same time.

    4. ES

      So, so harvesting and hunting is a good metaphor. Um, I'm interested in entrepreneurs. And so what we learned at Google was ultimately if you want to get something done, you have to have somebody who's entrepreneurial in their approach in charge of a small business. And so, for example, Sundar, when he became CEO, had a model of which were the little things that he was gonna emphasize and which were the big things. Some of those little things are now big things, right? And, and he managed it that way. So one way to understand innovation in a large company is you need to know who the owner is. Larry Page would say over and over again, "It's not gonna happen unless there's an owner who's gonna drive this." And he was supremely good at identifying that technical talent, right? That's one of his great founder strengths. So when you talk about founders, not only do you have to have a vision, but you also have to have, uh, either great luck or great skill as to who is the, the person who can lead this. Inevitably, those people are highly technical in the sense that they can... and very quick-moving, and they have good management skills, right? They understand how to hire people and deploy resources. That allows for innovation. Um, most of the... If I, if I look back in my career, each generation of the tech companies failed, including, for example, Sun, at, at the point at which it became noncompetitive with the future.

  18. 38:15 – 42:37

    How to Structure Teams to Drive Innovation

    1. ES

    2. SB

      Is it possible for a team to innovate while they still have their day job, which is harvesting, if you know what I mean? Or do you have to take those people, put them into a different team, different building, different P&L, and get them to focus on their disruptive innovation?

    3. ES

      There are almost no examples of doing it simultaneously in the same building. Uh, the Macintosh was famously, um, Steve, in his typical crazy way, had the, this very small team that invented the Macintosh, and he put them in a little building next to the big building, uh, on Bob Road in, in, um, Cupertino. And they put a pirate flag on top of it. Now, was that good culturally inside the company? No. Because it created resentment in the big building. But was it right in terms of the revenue and path of, of Apple? Absolutely.

    4. SB

      Why?

    5. ES

      Because the Mac ultimately became the platform that established the UI. The user interface ultimately allowed them to build the iPhone, which of course is defined by its user interface.

    6. SB

      Why couldn't they stay in the same building?

    7. ES

      It, it just doesn't work. You, you can't get people to play two roles. The incentives are different. If you're gonna be a pirate and a disruptor, you don't have to follow the same rules. So, um, there, there are plenty of examples where you just have to keep in- inventing yourself. Now, what's interesting about cloud computing and s- essentially cloud services, which is what Google does, is because the product is not sold to you, it's delivered to you, it's easier to change. But the same problem remains. If you look at Google today, right, it's basically a search, a search box, and it's incredibly powerful. But what happens when that interface is not really textual, right? Google will have to reinvent that.

    8. SB

      What do you mean? Sorry.

    9. ES

      And it's working on it. Tech, it'll be... The system will somehow know what you're asking.

    10. SB

      Okay.

    11. ES

      Right? It will, it does- it will be your assistant. Um, and again, Google will do very well, so I'm in no way criticizing Google here. But I'm saying that even something as simple as the search box will eventually be replaced by something more powerful. It's important that Google be the company that does that. I believe they will.

    12. SB

      And I, I was thinking about it, b- you know, the example of Steve Jobs and that building with the pirate flag on it. My brain went, um... There are so many offices around the world that were trying to kill Apple at that exact moment that might not have had the pirate flag, but that's exactly what they were doing in similar small rooms.

    13. ES

      Mm-hmm.

    14. SB

      So what Apple had done so smartly there was they owned the people that were about to kill their business model. And this is quite difficult to do. And part of me wonders if, in your experience, it's a founder that has that type of conviction that does that.

    15. ES

      It's extremely hard for non-founders to do this in corporations, because if you think about a corporation, what's the duty of the CEO? Many... There's the shareholders, there's the employees, there's the community, and there's a board. Trying to get a board of very smart people to agree on anything is hard enough. So imagine I walk into you and I say, "I have a new idea. I'm going to kill our profitability for two years. It's a huge bet, and I need $10 billion." Now, would the board say yes? Well, they did to Mark Zuckerberg. He spent all that money on, um, essentially VR of one kind or another. Doesn't seem to have produced very much. But at exactly the same time, he invested very heavily in Instagram, WhatsApp, and Facebook, and in particular in the AI systems that power them. And today, Facebook, to my surprise, is a very significant leader in AI, having released this, uh, language ca- or version called LLaMA f- 400 billion, which is curiously an open source model. Open source means it's available freely for everyone. And what, what Facebook an- and Meta is saying is, "As long as we have this technology, we can maximize the revenue in our core businesses."

    16. SB

      Mm-hmm.

    17. ES

      So there's a good example. And, uh, and Zuckerberg's obviously an incredibly talented entrepreneur. Um, he's now back on the list of, uh, the most rich people. Um, he's figured it, you know, in everything he was doing, and he managed to lose all that money while making a different bet. That's a unique founder. The same thing is almost impossible with a hired CEO.

    18. SB

      How

  19. 42:37 – 45:25

    Focus at Google

    1. SB

      important here is focus, and what's your, your sort of opinion of, um, the importance of focus from your experience with Google, but also looking at these other companies? Because, uh, you, when you're at Google and you have so much money in the bank, there's so many things that you could do and could build. Like an endless list. You can take on anybody and, and basically win in most markets.How do you think about focus at Google?

    2. ES

      Focus is important, but it's misinterpreted. In Google, we spent an awful lot of time telling people we wanted to do everything, and everyone said, "You can't pull off everything," and we said, "Yes, we can. We have the underlying architectures. We have the underlying reach. We can do this if we can imagine and build something that's really transformative." And so the idea was not that we would somehow focus on one thing like search, but rather that we would pick areas of great impact and importance to the world, many of which were free, by the way. This is not necessarily revenue-driven, and that worked. I'll give you another example. There's an old saying in business school that you should focus on, on what you're good at, and you should simplify your product lines, and you should get rid of product lines that don't work. Intel famously had a, uh, their t- term is called Arm. It's a risk, uh, chip, and this particular RISC chip was not compatible with the architecture that they were using for most of their products, and so they sold it. Unfortunately, this was a terrible mistake, because the architecture that they sold off was needed for mobile phones with low memory, th- with small batteries and, and heat problems and so forth and so on. And so that decision, that fateful decision, now 15 years ago, meant that they were never a player in the mobile space. And once they made that decision, they tried to take their expensive and ex- expensive and complex chips, and they kept trying to make cheaper and smaller versions. But the core decision, which was to simplify, simplified to the wrong an- outcome. Today, if you look at... I'll give you an example. The NVIDIA chips use an Arm CPU, and then these two powerful, uh, GPUs. It's called a B200. They don't use the Intel chip. They use the Arm chip because it was, for their needs, faster. I would never have predicted that 15 years ago. So at the end, maybe it was just a mistake, but maybe they didn't understand, in the way they were organized as a corporation, that ultimately, battery power would be as important as computing power, right? The amount of battery used, and that was the discriminant. So one way to think about it is if you're going to have these sort of simple rules, you better have a model of what happens in the next five years. So the way I teach this is just write down what it'll look like in five years.

  20. 45:25 – 48:40

    The Future of AI

    1. ES

      Just try.

    2. SB

      What, what will it look like in five years? Your company or your-

    3. ES

      Whatever it is, right? So let's talk about AI. What will be true in five years?

    4. SB

      That it's gonna be a lot smarter than it is now.

    5. ES

      It'll be a lot smarter, but how many companies will there be in AI? Will there be 5 or 5,000 or 50,000?

    6. SB

      50,000?

    7. ES

      How many big companies will there be? Will there be new companies? What will they do? Right? So I just told you my view is that eventually, you and I will have our own AI assistant, which is a polymath, which is incredibly smart, which helps us guide through the information overload that it is today. Who's gonna build it? Make a prediction. What kind of hardware will it be on? Make a prediction. How fast will the networks be? Make a prediction. Write all these things down and then have a discussion about what to do. The, what is interesting about our industry is that when something like the PC comes along or the internet, and I lived through all of these things, they are such broad phenomena that they really do create a whole new lake, a whole new ocean, whatever metaphor you want. Now, people have said, "Well, wasn't that crypto?" No. Crypto is not such a platform. Crypto is not transformative to daily life f- for everyone. People are not running around all day using crypto tokens rather than currency. Crypto is a specialized market. By the way, it's important and it's interesting. It's not a horizontal transformative market. The arrival of alien intelligence in the form of savants that you use is such a transformative thing, because it touches everything. It touches you as a, a producer, as a star, as a narrative. It touches me as an executive. Um, it will ultimately help people make money in the stock market. People are working on that. There's so many ways in which this technology is transformative. To start, you, in your case, when you think about your company, whether it's little, you know, itty-bitty or a really big one, it's fundamentally how will you apply AI to accelerate what you're doing? Right? In your case, for example, here you have, uh, I think the most successful show in the UK, uh, by far, right? So how will you use AI to make it more successful? Well, you can ask it to distribute you more, right, to make, uh, narratives, to summarize, uh, to, to come up with new insights, to suggest, uh, to have fun, to create contests. There are all sorts of ways that you can ask AI. Um, I'll give you a simple example. If I were a politician, thankfully I'm not, um, and I knew my district, I would say, uh, to the computer, "Write a program." So te- I'm saying to the computer, "You write a program which goes through all of the constituents in my interest, d- figures out roughly what they care about, and if, and then send them a video which is labeled, you know, of me digitally, so I'm not fake, but it's kind of like my intention, where I explain to them how important I, as their constituent, have made the bridge work," right? And you sit there and you go, "That's crazy." But it's possible. Now, politicians have not discovered this yet, but they will. Because ultimately, politicians are on a human connection, and the quickest way to have that communication is to be on their phone talking to them about something that they care about.

  21. 48:40 – 51:53

    Why Didn’t Google Release a ChatGPT-Style Product First?

    1. ES

    2. SB

      When ChatGPT first launched and they sort of scaled rapidly to 100 million users, there was all these articles saying that, um, the founders of Google had rushed back in and it was a crisis situation at Google and there was panic, and there was two things that I thought. First is, is that true? And second thing was...How did Google not come to market first with a ChatGPT style product?

    3. ES

      Well, remember that Google also-- that's the old question of h- why did you not do Facebook. Well, the answer is, we were doing everything else. Right? So, my defensive answer is that Google has eight or nine or 10 billion user clusters of activity, which is pretty good. Right? It's pretty hard to do. Right? I'm very proud of that. I'm very proud of what they're doing now. Um, my own view is that what happened was Google was working in the engine room, and a team out of OpenAI figured out a technology called r- RLHF. And what happened was when they did GPT-3, and GP, the T is transformer, which was invented at Google. When they did it, they had sort of this interesting idea, and then they on- then s- they sort of casually started to use humans to make it better. And RLHF refers to the fact that you use humans at the end to do A/B tests where humans can actually say, "Well, this one's better," and then the system learns recursively from human training at the end. That was a real breakthrough, right? And, uh, I joke with my OpenAI friends that you were sitting around on, on Thursday night, and you turn this thing on, and you go, "Holy crap, look how good this thing is." It was a real discovery, right, that none of us expected. Certainly I did not. Um, and once they had it, um, the OpenAI people, Sam and Mira and, and so forth will talk about this, they didn't really understand how good it was. They just turned it on, and all of a sudden they had this huge success disaster 'cause they were working on GPT-4 at the same time. It was an afterthought. And it's a great story because it just shows you that even the brilliant founders do not necessarily understand how powerful what their, what they've done is. Now today, of course, you have GPT-4o, um, basically a very powerful model from OpenAI. You have Gemini 1.5, which is clearly in, clearly roughly equivalent if not better in certain areas. Um, the Gemini is more multimodal, for example. And then you have other players, LLaMA, the LLaMA architecture, LL- L-L-A-M-A. Uh, does not stand for llamas. It's large language models. Um, out of Facebook and a number of others. Uh, there's a startup called Anthropic, um, which is very powerful, founded by one of the inventors of GPT-3, um, and a whole bunch of people. And they formed their company knowing they were gonna be that successful. The, it's interesting, they actually formed as part of their incorporation that they were a public benefit corporation, because they were concerned that it would be so powerful that some evil CEO in the future would force them to go for revenue as opposed to w- uh, world, world goodness. So the teams, when they were doing this, they understood the power of what they were doing, and they anticipated the level of impact, whi- and they were right.

  22. 51:53 – 55:42

    What Would Apple Be Doing if Steve Jobs Were Alive?

    1. ES

    2. SB

      Do you think if Steve Jobs was at Apple, they'd be on that list?

    3. ES

      Um-

    4. SB

      How do you think the company would be different?

    5. ES

      Well, uh, Tim has done a fantastic job in Steve's legacy. And what's interesting is normally the successor is not as good as the founder, but somehow Tim, having worked with Steve for so long and having set the culture, having Steve having, they've managed to continue to focus on the user with this incredible safety focus in terms of apps and so forth and so on. And they've remained a relatively closed culture. I think all of those would have maintained had Steve su- you know, tragically died, uh, and he was a good friend. But the, the important point is, S- Steve, Steve believed very strongly in what are called closed systems, where you own and control all your intellectual property. And he and I would battle over open versus closed, 'cause I came from the other side, and I did this with respect. I don't think they would've changed that.

    6. SB

      And they've changed that now?

    7. ES

      No. I think still-

    8. SB

      They haven't changed it.

    9. ES

      ... Apple is still basically a single company that's vertically integrated. The rest of the industry is largely more open.

    10. SB

      I think everyone, especially in the wake of the recent l- launch of the iPhone 16, which I've got somewhere here, um, has this expectation that Apple would, if Steve was still alive, taken some big bold bet in some... And I think about, you know, Tim's tenure, he's done a fantastic job of keeping that company going, running it i- with the sort of principles of Steve Jobs. But has there been many big, bold, successful bets? A lot of people point at the AirPods, which have a gre- a great product. But I think AI is one of those things where you go, "I wonder if Steve would've understood the significance of it," and-

    11. ES

      Steve was that smart that he, I would never... You know, he's an Elon level intelligence. Um, when, when Steve and I worked together very closely, which was what, 15 years ago before his death, um, he was very frustrated at the success of MP4 over, uh, MOV, um, f- format files, and he was really mad about it. And I said, "Well, you know, maybe that's because you were closed," (laughs) and QuickTime was not generally available. He said, "That's not true. My team, you know, our product is better," and so forth. So his, his core belief system, he's an artist, right? And, and given the choice, we used to have this debate where, do you want to be Chevrolet or do you want to be Porsche? Do you want to be Chev- you know, General Motors or do you want to be BMW? And he said, "I want to be BMW." And during that time, Apple's margins were twice as high as the PC companies. And I said, "Steve, you don't need all that money. You're generating all this cash. You're giving it to your, to your shareholders." And he said, "The principle of our profitability and our value and our brand is this, is this luxury brand," right? So that's how he thought. Now, would, how would, how would AI change that? Everything that he would have done with Apple today would be AI inspired, but it would be beautiful. That's the great gift he had.

    12. SB

      ... 'cause, uh, I think Siri was almost a glimpse at, at what AI now kind of looks like. It was a glimpse at what the, I guess, the ambition was. We've all been chatting to the Siri thing, which is, I think most people would agree is kind of like largely useless unless you're trying to figure out something super, super simple. But now I, this weekend, as I said, I sat there with my, my girlfriend's family there, speaking to this voice-activated device, and it was solving problems for me almost instantaneously that are very complex and translating them into French and Portuguese.

    13. ES

      Welcome, welcome to the replacement for Siri. And again, would Steve have done that quicker? I don't know. Uh, it's very clear that the first thing Apple needs to do is have Siri be replaced by an AI and

  23. 55:42 – 58:53

    Hiring & Failing Fast

    1. ES

      call that Siri.

    2. SB

      Hiring. We- we're doing a lot of hiring in our companies at the moment, and we're going back and forth on what the most important principles are when it comes to hiring, making lots of mistakes sometimes, getting things right sometimes. What do I need to know, as an entrepreneur, when it comes to hiring?

    3. ES

      Startups, by definition, are huge risk-takers. You have no history. You have no incumbency. You have all these competitors, by definition, and you have no time. So in a startup, you wanna, you wanna, um, prioritize intelligence and quickness over experience and sort of stability. You want to take risks on people. And the great... And part of the reason why startups are full of young people is because young people often don't have the baggage of executives that have been around for a long time. But more importantly, they're willing to take risks. So, it used to be that you could predict whether a company was successful by the age of the founders, and in that 20 and 30-year-old period, the company would be hugely successful. Startups, um, wiggle. They try something, they try something else, and they're very quick to discard an old idea. Corporations spend years with a belief system that is factually false, and they don't actually change their opinion until after they've lost all the contracts.

    4. SB

      Mm.

    5. ES

      And if you go back, the, all the signs were there. Nobody wanted to talk to them. Nobody cared about the product, right? And yet they kept pushing it. So, um, if you're a CEO of a larger company, what you want to do is basically figure out how to measure this innovation so that you don't waste a lot of time. Bill Gates had a saying a long time ago, which was that the most important thing to do is to fail fast, right? That the charac- And from his perspective, as the CEO of Microsoft, founder of Microsoft, um, that he wanted everything to happen, and he wanted to fail quickly, and that was his theory.

    6. SB

      And do you agree with that theory?

    7. ES

      Yeah, I do. Fast failure is important because you can say it in a nicer way, but fundamentally, um, at Google, we have this 70-20-10 rule that Larry and Sergey came up with. 70% on the core business, 20% on adjacent business, and 10% on other.

    8. SB

      What does that mean? Sorry. Adjacent bus-

    9. ES

      So core, core business means search ads. Adjacent business means something that you're trying, like a cloud business or so forth, and the 10% is some new idea. So Google created this thing called Google X. The first product it built was called Google Brain, which was one of the first machine learning architectures. This actually precedes DeepMind. Google Brain was used to power the AI system. Google Brain's team of 10 or 15 people generated 10, 20, 30, $40 billion of extra profits over a decade. So that pays for a lot of failures.

    10. SB

      Mm-hmm.

    11. ES

      Right? Then they had a whole bunch of oth- other ideas that seemed very interesting to me that didn't happen for one or another, and they would cancel them. And you, you'd, and then the people would get reconfigured. And one of the great things about Silicon Valley is it's possible to spend a few years on a really bad idea and get canceled, if you will, and then get another job having learned all of that. My joke is the best CFO is one who's just gone bankrupt, because the one thing that CFO is not going to let happen is to go bankrupt again.

  24. 58:53 – 1:04:02

    Microcultures at Google & Growing Too Big

    1. ES

    2. SB

      Yeah. Well, on this point of culture as well, Google, as such a big company, must experience a bunch of micro-cultures.

    3. ES

      Oh yeah.

    4. SB

      One of the things that I've always, I've kind of studied it as an, as a cautionary tale, is the story of TGIF at Google-

    5. ES

      Mm-hmm.

    6. SB

      ... which was this sort of weekly, all-hands meeting where employees could ask the executives whatever they wanted to. And the articles a- around it say that it was eventually sort of changed or canceled because it became unproductive.

    7. ES

      It's more complicated than that.

    8. SB

      Okay.

    9. ES

      So Larry and Sergey started TGIF, uh, which I obviously participated in, and we had fun. Uh, there was a sense of humor. It was all off the record. Um, a, a famous example is the VP of sales, whose name was Omid, um, was always predicting lower revenue than we really had, which is called sandbagging. So we got a sandbag, and we made him stand on the sandbag in order to present his numbers. It was just fun, humorous, you know? We had skits and things like that. Um, at, at some size, you don't have that level of intimacy, and you don't have a level of privacy. And what happened was, there were leaks. Uh, eventually, there was a presentation, I don't remember the specifics, where the pres- presentation was ongoing, and someone was leaking the presentation live to a reporter, and somebody came on stage and said, "We have to stop now." I think that was the moment where the company got sort of too big.

    10. SB

      Hmm. I, I, I heard about a story that, um... Because from what I had understood, this might be totally wrong, but it's all just things that Google employees have told me, was that there wasn't many sackings, firings at Google. There wasn't many layoffs. There wasn't really a culture of layoffs. And I guess, I guessed in part, that's because the company was so successful that it didn't have to make those extremely, extremely tough decisions that we're seeing a lot of companies make today. I reflect on Elon's running of Twitter. When he take, took over Twitter, the, you know, The sa- The fre- The story goes that he went to the top floor and basically said, "Anyone who's willing to work hard, is committed to these values, please come to the top floor. Everyone else, you're fired." Um, this sort of extreme culture of culling and people being sort of activists at work, um-And I wanted to know if there's any truth in that.

    11. ES

      There's some. Um, in, in Google's case, um, we had a position of, why lay people off? Just don't hire them in the first place. It's much, much easier. And so, in my tenure, the only layoff we did was, uh, 200 people in the sales structures right after the 2000 epidemic, and I remember it as being extremely painful. Right? It was the first time we had done it. So, we took the position, which was different at the time, that you shouldn't have an automatic layoff. Uh, what would happen is th- that there was a belief at the time that every six months or nine months, you should take the bottom 5% of your people and lay them off. Problem with that is you're assuming the 5% are correctly identified.

    12. SB

      Hmm.

    13. ES

      And furthermore, even the lowest performers have knowledge and value to the corporation that we can ... So we took a, a very much more positive view of our employees, w- and the employees liked that. And we obviously paid them very well and so forth and so on. I think that the, the cultural issues ultimately have been addressed, but during, there was a period of time where there were, um, because of the freewheeling nature of, nature of the company, there were an awful lot of internal distribution lists which had nothing to do with the company.

    14. SB

      What does that mean?

    15. ES

      They were distribution lists on topics of war, peace, politics, so forth.

    16. SB

      What's a distribution list?

    17. ES

      A distribution, like an email dist- think of it as a, a, a message board.

    18. SB

      Okay.

    19. ES

      J- roughly speaking, think of it as message boards for employees. And at one- I remember that at one point, somebody discovered that there were 100,000 such mess- message boards. And the company ultimately cleaned that up, because companies are not like universities, in that there are in fact all sorts of laws about what you can say and what you cannot say and so forth. And so for example, the majority of the employees were, uh, Democrats in the American political system, and I made a point, even though I'm a Democrat, to try to protect the small number of Republicans, 'cause I thought they had a right to be employees too. So you have to be very careful in a corporation to establish what, what does speech mean within the corporation? And, um, what you, what you are hearing as wokeism is really can be understood as, what are the appropriate topics on work time, in, in a work venue, should you be discussing? My own view is stick to the business, and then f- please feel free to go to the bar, scream your views, talk to everybody. You know, I'm a strong believer in free speech. But within the corporation, let's just stick to the corporation and its goals.

    20. SB

      'Cause I was hearing these stories about, I think in more recent times, in the last year or two, of people coming to work just for the free breakfast, pro- protesting outside that morning, coming back into the building for lunch.

    21. ES

      As e- as best I can tell, that's all been cleaned up. Mm.

    22. SB

      I did also hear that that h- it had been cleaned up.

    23. ES

      Yeah.

    24. SB

      Because I think it was addressed in a very high conviction way, which meant that it, it was, um, seen to.

  25. 1:04:02 – 1:04:39

    Competition

    1. SB

      How did, how do you think about competition? For everyone that's building something, how much should we be focusing on our com- competition?

    2. ES

      I strongly recommend not focusing on competition, and instead focusing on building a product that no one else has. And you say, "Well, how can you do that without knowing the competition?" Well, if you study the competition, you're wasting your time. Try to solve the problem in a new way, and do it in a way where the customers are delighted. Um, running Google, we seldom looked at what our competitors were doing. What we did s- we spent an awful lot of time is what is possible for us to do? What can we actually do from our current situation? And sort of the running ahead of everybody turns out to be really important.

  26. 1:04:39 – 1:05:17

    Deadlines

    1. ES

    2. SB

      What about deadlines?

    3. ES

      Well, uh, Larry established the principle of, um, OKRs, which were objectives and key results. And every quarter, Larry would actually write down all the metrics, and he was tough. And he would say that, "If you got to 70% of my numbers, that was good." And then we would grade based on, are you above the 70% or are you below the 70%, and it was harsh, and it worked. You, you have to measure to get things done in a big corporation. Otherwise, everyone kind of looks good, makes all sorts of claims, feels good about themselves, but it doesn't have an impact.

  27. 1:05:17 – 1:06:28

    Business Plans

    1. ES

    2. SB

      What about business plans? Should we be writing business plans as founders?

    3. ES

      Google wrote a business plan. It was, uh, run by a fellow named Salar, and I saw it years later, and it was actually correct.

    4. SB

      Hmm.

    5. ES

      And I told Salar that, that this is probably the only business plan ever written for a corporation that was actually correct in hindsight. So, what I prefer to do, uh, and this is how I teach it at Stanford, is try to figure out what the world looks like in five years, and then try to figure out what you're gonna do in one year, and then do it. Right? So if you can basically say, "This is the direction. These are the things we're going to achieve within one year," and then run against that as hard goals, not simple goals, but hard goals, then you'll get there. And the general rule, at least in a consumer business, is if you can get an audience of 10 or 100 million people, you can make lots of money. Right? So if you give me any business that has no revenue and 100 million people, I can find a way to, to monetize that with advertising and sponsorships and donations and so forth and so on. Focus on getting the user right, and everything else will follow. The Google phrase is, "Focus on the user, and everything else is handled."

  28. 1:06:28 – 1:09:12

    What Made Google’s Sergey and Larry Special?

    1. ES

    2. SB

      Sergey and Larry.

    3. ES

      Mm-hmm.

    4. SB

      You worked with them for-

    5. ES

      20 years.

    6. SB

      Many decades, yeah, two decades. What made them special?

    7. ES

      Frankly, raw IQ. They were just smarter than everybody else.

    8. SB

      Really?

    9. ES

      Yeah. And, uh, uh, in Sergey's case, his father was a very brilliant Russian mathematician. His mother was also highly technical. His family's all very technical. And he was clever. He's a clever mathematician. Uh, Larry, a different personality, but similar. So an example would be that Larry and I are in his office and we're writing on the whiteboard a long list about what we're gonna do and he says, "Look, we're gonna do this and this." And I said, "Okay, I agree with you, I don't agree with you." We make this very long list. And Sergey is out playing volleyball.And so, he runs in, in his little volleyball shorts and his little shirt all sweaty, and he looks at our list and said, "This is the stupidest thing I've ever heard." And then he suggests five things. And he was exactly right. So, we erased the whiteboard, and then he of course went back to play volleyball, and that became the strategy of the company. So, over and over again, it was the, it was their brilliance and their ability to see things that I didn't see that I think really drove it.

    10. SB

      Can you teach that?

    11. ES

      I don't know. I think you can teach listening and, um, but I think most of us get caught up in our own ideas, and we are always surprised that something new happened. Like, I've just told you that I'm, I've been in AI a long time. I'm still surprised at the rate, uh, my favorite current product is called Notebook LM.

    12. SB

      Mm-hmm.

    13. ES

      And for the, uh, listeners, Notebook LM is an experimental product out of Google DeepMind, basically Gemini. Um, it's based on the Gemini backend, and it was trained with high quality podcast voices.

    14. SB

      It's terrifying.

    15. ES

      And you basically give it a, so what I'll do is, um, I'll write something, and again, I don't write very well, and I'll ask Gemini to rewrite it to be more beautiful. Okay, I'll take that text and I'll put it in Notebook LM, and it produces this interview between a man and a woman, um, who don't exist. And for fun, what I do is I play this in front of an audience and I wait and see if anyone figures out that the humans are not human. It's so good, they don't figure it out.

    16. SB

      We'll play it now.

    17. NA

      So, this is the big thing that everyone's making a big fuss about. You can go and load this conversation. Now, it's gonna go out and create a conversation that's in a podcast style, where there's a male voice and a female voice, and they're analyzing the content and then coming up with their own kind of just cr- uh, creative content. So, you could go and push play right here.

    18. ES

      We are back Thursday, get ready for week three.

    19. SB

      The injury report this week.

    20. ES

      Was a doozy.

    21. SB

      It's a long one.

    22. ES

      Yeah, it is.

    23. SB

      And it has the potential to really shake things up.

  29. 1:09:12 – 1:12:17

    Navigating Media Production in the Age of AI

    1. SB

    2. ES

      So for that, to me, Gem- uh, Notebook LM is my ChatGPT moment of this year.

    3. SB

      Hmm. It was mine as well.

    4. ES

      Okay.

    5. SB

      And it's much of the reason that I was, um, deeply confused.

    6. ES

      Okay.

    7. SB

      Because as a podcaster who's building a media company, we have an office down the road, 25,000 square feet. We have studios in there. Um, we're building audio, video content at this, in the dawn of this new world where the cost of production of content goes to, like, zero or something.

    8. ES

      Yes.

    9. SB

      And I'm trying to navigate how to play as a media owner.

    10. ES

      So, so first place, you're, you're, what's really going on is you're moving from scarcity to ubiquity. You're moving from scarcity to abundance. So, one way to understand the world I live in is it's scale computing generates abundance, and abundance allows new strategies. In your case, it's obvious what you should do. You're a really famous podcaster, and you have lots of interesting guests. Simply have this fake set of podcasts criticize you and your guests, right? You're, you're essentially just amplifying your reach. They're not gonna substitute for your, uh, honest brilliance and charisma here, but they're going to accentuate it. They will, they will, they will be entertaining. They will summarize it and so forth. It amplifies your reach. If you go back to my basic argument that AI will double the productivity of everybody or more. So in your case, you'll have twice as many pod- podcasts. What I do, for example, is I'll write something and I'll say, I'll have it respond. And then to Gemini, I'll say, "Make it longer."

    11. SB

      (laughs)

    12. ES

      And it adds more stuff. And I think, "God, I do this in like 30 seconds." Then how powerful? In your case, take one of these, uh, lengthy interviews you do, ask the system to annotate it, to amplify it, and then feed that into fake podcasters and see what they say. You'll have a whole new set of audiences that love them more than you, but, but it's all from you.

    13. SB

      Mm-hmm.

    14. ES

      That's the key idea here.

    15. SB

      I worry because there's gonna be potentially billions of podcasts that are uploaded to RSS feeds all around the world, and it's all gonna sort of chip away at, you know, the, the moat that I've-

    16. ES

      So, so, uh, many people have believed that, but I think that evidence is it's not true. Um, when I started at Google, there was this notion that celebrity would go away and there would be this very long tail of micro markets, you know, specialists, because finally, you could hear the voices of everyone, and we're all very democratic and liberal in our view. That's the, what really happened was networks accentuated the best people and they made more money, right? You went from being a local personality to a national personality, to a global personality. And the globe is a really big thing, and there's lots of money and lots of players. So you, as a p- as a celebrity, are competing against a global group of people, and you need all the help you can to maintain your position. If you do it well, by using these AI technologies, you'll become more famous, not less famous.

  30. 1:12:17 – 1:17:39

    Why AI Emergence Is a Matter of Human Survival

    1. ES

    2. SB

      Hmm. Genesis, I, um, I've had s- a lot of conversations with a lot of people about the subject of AI. Um, and when I read your book, and I've watched you do a series of interviews on this, some of the quotes that you said really stood out to me. One of them I wrote down here, which comes from your book, Genesis, it's on page five. "The advent of artificial intelligence is, in our view, a question of human survival."

    3. ES

      Yes. That is our view. So...

    4. SB

      Why is it a question of human survival?

    5. ES

      AI is going to move very quickly. It's moving so much more quickly than I've ever seen, because of the amount of money, the number of people, the impact, the need. What happens when the AI systems are really running key parts of our world? What happens when AI is making the decision? My, my simple example, you have a car.... which is AI controlled, and you have a emergency or, uh, a lady's about to give birth or something like that, and they get in the car and there's no override switch because the system is optimized around the whole as opposed to his or her emergency. But we as humans accept various forms of efficiency, including urgent ones versus system- systemic efficiency. You could imagine that the Google engineers would design a perfect city that would perfectly operate every self-driving car on every street, but would not then allow for the exceptions that you need in such a, uh, in such an important issue. So, that's a trivial example, uh, and one which is well understood of how it's important that these things represent human values, right? That w- we- we have to actually articulate what does it mean. So my favorite one is all this misinformation. Um, democracy's pretty important. Democracy is by far the best way to, to live and operate societies. Look at, there are plenty of examples of this. None of us want to work in essentially an authoritarian dictatorship. So you better figure out a way where the misinformation components do not screw up proper political examples. Another example is this question about teenagers and their deve- their mental development and growing up into these societies. I don't want them to be constantly depressed. There's a lot of evidence that dates around 2015 when all the social media algorithms changed from linear feeds to targeted feeds. In other words, they went from time to, "This is what you want. This is what you want." That hyper-focus has ultimately narrowed people's, um, political views as I- as we discussed, but more importantly, it's produced more depression and anxiety. And so all the studies indicate that basically if you time it to roughly then, when people are coming to age, they're not as happy with their lives, their behaviors, their opportunities for this. And the best explanation is it was an algorithmic change. And remember that these systems, they're not just collections of content. They are algorithmically deciding, you know, the algorithm decides what the outcome is for humans. We have to manage that. Um, what we say in many different ways in the book is that you have sort of a choice of whether the, um, the algorithms will advance. That's not in question. The question is, are we advancing with it and, uh, do we have control over it? Um, there are so many examples where you could imagine an AI system could do something e- e- more efficiently, but at what cost? Right? Um, I should mention that there's this discussion about something called AGI, uh, artificial general intelligence, and there's this discussion in the press among many people that AGI occurs on a particular day, right? And this is sort of a popular concept that on a particular day, five years from now or 10 years from now, this thing will occur and all of a sudden we're gonna have a computer that's just like us but even quicker. That's unlikely to be the path. Much more likely are these waves of innovation in every field, better psychologists, better writers. You see this with G- ChatGPT already, better scientists. There's a notion of an AI scientist that's working with the AI real scientist to accelerate the development of more AI science. People believe all of this will come, but it has to be under human control.

    6. SB

      Do you think it will be?

    7. ES

      I do. And part of the reason is I and others have worked hard to get the governments to understand this. It's very strange. In my entire career, which has g- gone on for, you know, 50 years, the, um, we've never asked for government for help, because asking the government for help is basically just a disaster in the view of the tech industry. In this case, the people who invented it collectively came to the same view that there need to be guardrails on this technology because of the potential for harm. The most obvious one is, how do I kill myself? Give me recipes to hurt other people. That kind of stuff. There's a whole community now in this, in this part of the industry, which are ca- are called trust and safety groups, and what they do is they actually have humans test the system before it gets released to make sure the harm that it might have in it is suppressed. It literally won't answer the question.

  31. 1:17:39 – 1:21:01

    Dangers of AI

    1. SB

      When you play this forward in your brain, you've, you've been in the tech industry for a long time, and from looking at your work, you, it feels like you're describing this as the most sort of transformative-

    2. ES

      Mm-hmm.

    3. SB

      ... potentially harmful technology that humans have really ever seen, you know, maybe alongside the nuclear bomb, I guess, but some would say even potentially worse because of the nature of the intelligence and its autonomy. You must have moments where you, you think forward into the future and your thoughts about that future aren't so rosy.

    4. ES

      Well, I-

    5. SB

      Because I have those moments.

    6. ES

      Yes. But, but let's, let's think, let's answer the question. I said think five years. In five years, you'll have two or three more turns of the crank of these large models. These large models are scaling with ability that is unprecedented. There's no evidence that the scaling, as laws as they're called, have begun to, to stop. They will eventually stop, but we're not there yet. Each one of these cranks looks like it's a factor of two, factor of three, factor of four of capability. So let's just say turning the crank, all of these systems get, uh, 50 times or 100 times more powerful. In and of itself, that's a very big deal 'cause those systems will be capable of physics and math. You see this with O.1 and, um, and OpenAI, all the other things that are occurring. Now, what are the dangers? Well, there's... the most obvious one is cyber attacks. There's evidence that the raw models, these are the ones that have not been released, can do what are called day zero attacks as well or better than humans. A day zero attack is an attack that's unknown. They can discover something new. And how do they do it? They just keep trying 'cause they're computers and they have nothing else to do. They don't sleep. They don't eat. They just turn them on and they just keep going.Um, so the- the- so cyber is an example where everybody's concerned. Another one is biology. Viruses are relatively easy to make, and you could imagine coming up with really bad viruses. There's a whole team, I'm part of a commission, we're looking at this to try to make sure that doesn't happen. I already mentioned misinformation. Another probably negative, but we'll see, is the development of new forms of warfare. I've written extensively on how war is changing, and the way to understand historic war is that it's the, stereotypically the- the soldier with the gun, you know, on one side and so forth, World War trenches. You see this, by the way, in Ukra- in the Ukraine fight today, where the Ukrainians are holding on valiantly against the Russian onslaught. But it's sort of, you know, mano-a-mano, you know, man against man, sort of all of the stereotypes of war. So in a drone world, which is the sort of the fastest way to build new robots is to build drones, you'll be sitting in a command center in some office building connected by a network, and you'll be doing harm to the other side while you're drinking your coffee. Right? That's a change in the logic of war. Um, and it's applicable to both sides. I don't think anyone quite understands how war will change, but I will tell you that in U- in the Russian-Ukraine war, you're seeing a new form of warfare being invented right now. Right? Um, both sides have lots of drones. Tanks are no longer very useful. A $5,000 drone can kill a $5 million tank. Um, so it's called the kill ratio. So basically, it's drone on drone. And so now people are trying to figure out how to- how to have one drone destroy the other drone, right? This will ultimately take over war and conflict in our world in

  32. 1:21:01 – 1:23:45

    AI Models Know More Than We Thought

    1. ES

      total.

Episode duration: 1:49:36

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