Eric Schmidt: Google
技术与编程商业与创业音乐与艺术AI 与机器学习生物与进化
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🎙️ 完整对话（736 条）
Lex Fridman (00:00.000)
The following is a conversation with Eric Schmidt.
以下是与埃里克·施密特的对话。
Lex Fridman (00:03.180)
He was the CEO of Google for 10 years
他担任谷歌首席执行官十年
Lex Fridman (00:05.140)
and a chairman for six more,
以及另外六人的主席，
Lex Fridman (00:06.780)
guiding the company through an incredible period of growth
带领公司度过了一段令人难以置信的成长时期
Lex Fridman (00:10.100)
and a series of world changing innovations.
以及一系列改变世界的创新。
Eric Schmidt (00:12.940)
He is one of the most impactful leaders
他是最有影响力的领导人之一
Lex Fridman (00:15.300)
in the era of the internet and the powerful voice
在互联网和强大声音的时代
Eric Schmidt (00:19.340)
for the promise of technology in our society.
为了技术对我们社会的承诺。
Lex Fridman (00:22.300)
It was truly an honor to speak with him
与他交谈真的很荣幸
Eric Schmidt (00:24.780)
as part of the MIT course
作为麻省理工学院课程的一部分
Lex Fridman (00:26.900)
on artificial general intelligence
论通用人工智能
Lex Fridman (00:28.660)
and the artificial intelligence podcast.
和人工智能播客。
Lex Fridman (00:31.900)
And now here's my conversation with Eric Schmidt.
现在这是我与埃里克·施密特的对话。
Lex Fridman (00:37.020)
What was the first moment
第一个瞬间是什么
Lex Fridman (00:38.020)
when you fell in love with technology?
你什么时候爱上科技的？
Eric Schmidt (00:40.900)
I grew up in the 1960s as a boy
我在 20 世纪 60 年代长大，还是个男孩
Lex Fridman (00:44.380)
where every boy wanted to be an astronaut
每个男孩都想成为一名宇航员
Lex Fridman (00:46.820)
and part of the space program.
和太空计划的一部分。
Lex Fridman (00:48.900)
So like everyone else of my age,
所以像我这个年纪的其他人一样
Eric Schmidt (00:51.340)
we would go out to the cow pasture behind my house,
我们会去我家后面的牛牧场，
Lex Fridman (00:54.340)
which was literally a cow pasture
Lex Fridman (00:56.260)
and we would shoot model rockets off.
Lex Fridman (00:58.540)
And that I think is the beginning.
Lex Fridman (01:00.820)
And of course, generationally today,
Lex Fridman (01:03.540)
it would be video games and all the amazing things
Eric Schmidt (01:05.760)
that you can do online with computers.
Lex Fridman (01:09.100)
There's a transformative, inspiring aspect of science
Lex Fridman (01:12.620)
and math that maybe rockets would bring
Lex Fridman (01:15.740)
would instill in individuals.
Eric Schmidt (01:17.420)
You've mentioned yesterday that eighth grade math
Lex Fridman (01:20.140)
is where the journey through mathematical universe
Eric Schmidt (01:22.180)
diverges from many people.
Lex Fridman (01:23.780)
It's this fork in the roadway.
Eric Schmidt (01:26.900)
There's a professor of math at Berkeley, Edward Frankel.
Lex Fridman (01:30.260)
He, I'm not sure if you're familiar with him.
Eric Schmidt (01:32.460)
I am.
Lex Fridman (01:33.300)
He has written this amazing book
Eric Schmidt (01:35.420)
I recommend to everybody called Love and Math.
Lex Fridman (01:37.700)
Two of my favorite words.
Eric Schmidt (01:41.460)
He says that if painting was taught like math,
Lex Fridman (01:46.700)
then the students would be asked to paint a fence,
Eric Schmidt (01:49.620)
which is his analogy of essentially how math is taught.
Lex Fridman (01:52.540)
And so you never get a chance to discover the beauty
Eric Schmidt (01:55.860)
of the art of painting or the beauty of the art of math.
Lex Fridman (01:59.260)
So how, when, and where did you discover that beauty?
Eric Schmidt (02:05.260)
I think what happens with people like myself
Lex Fridman (02:08.040)
is that your math enabled pretty early
Lex Fridman (02:11.380)
and all of a sudden you discover that you can use that
Lex Fridman (02:14.320)
to discover new insights.
Eric Schmidt (02:16.560)
The great scientists will all tell a story,
Lex Fridman (02:19.100)
the men and women who are fantastic today,
Eric Schmidt (02:22.020)
that somewhere when they were in high school or in college,
Lex Fridman (02:24.600)
they discovered that they could discover
Eric Schmidt (02:26.060)
something themselves.
Lex Fridman (02:27.780)
And that sense of building something,
Eric Schmidt (02:29.860)
of having an impact that you own,
Lex Fridman (02:32.260)
drives knowledge acquisition and learning.
Eric Schmidt (02:35.460)
In my case, it was programming.
Lex Fridman (02:37.020)
And the notion that I could build things
Eric Schmidt (02:39.820)
that had not existed that I had built,
Lex Fridman (02:42.300)
that it had my name on it.
Lex Fridman (02:44.400)
And this was before open source,
Lex Fridman (02:46.160)
but you could think of it as open source contributions.
Lex Fridman (02:49.100)
So today, if I were a 16 or 17 year old boy,
Lex Fridman (02:51.780)
I'm sure that I would aspire as a computer scientist
Eric Schmidt (02:54.660)
to make a contribution like the open source heroes
Lex Fridman (02:58.060)
of the world today.
Eric Schmidt (02:58.920)
That would be what would be driving me.
Lex Fridman (03:00.380)
And I'd be trying and learning and making mistakes
Lex Fridman (03:03.700)
and so forth in the ways that it works.
Lex Fridman (03:06.620)
The repository that GitHub represents
Lex Fridman (03:09.940)
and that open source libraries represent
Lex Fridman (03:12.200)
is an enormous bank of knowledge
Eric Schmidt (03:14.900)
of all of the people who are doing that.
Lex Fridman (03:17.100)
And one of the lessons that I learned at Google
Eric Schmidt (03:19.540)
was that the world is a very big place
Lex Fridman (03:21.500)
and there's an awful lot of smart people.
Lex Fridman (03:23.540)
And an awful lot of them are underutilized.
Lex Fridman (03:26.300)
So here's an opportunity, for example,
Eric Schmidt (03:28.940)
building parts of programs, building new ideas
Lex Fridman (03:31.700)
to contribute to the greater of society.
Lex Fridman (03:36.540)
So in that moment in the 70s,
Lex Fridman (03:38.340)
the inspiring moment where there was nothing
Lex Fridman (03:40.660)
and then you created something through programming,
Lex Fridman (03:42.820)
that magical moment.
Lex Fridman (03:44.720)
So in 1975, I think you've created a program called Lex,
Lex Fridman (03:49.180)
which I especially like because my name is Lex.
Lex Fridman (03:51.460)
So thank you, thank you for creating a brand
Lex Fridman (03:54.620)
that established a reputation that's long lasting, reliable
Lex Fridman (03:58.260)
and has a big impact on the world and still used today.
Lex Fridman (04:01.180)
So thank you for that.
Lex Fridman (04:02.820)
But more seriously, in that time, in the 70s,
Lex Fridman (04:08.220)
as an engineer, personal computers were being born.
Lex Fridman (04:12.540)
Do you think you'd be able to predict the 80s, 90s
Lex Fridman (04:15.580)
and the aughts of where computers would go?
Eric Schmidt (04:18.900)
I'm sure I could not and would not have gotten it right.
Lex Fridman (04:23.180)
I was the beneficiary of the great work
Eric Schmidt (04:25.420)
of many, many people who saw it clearer than I did.
Lex Fridman (04:29.060)
With Lex, I worked with a fellow named Michael Lesk,
Eric Schmidt (04:32.540)
who was my supervisor.
Lex Fridman (04:33.980)
And he essentially helped me architect
Lex Fridman (04:36.300)
and deliver a system that's still in use today.
Lex Fridman (04:39.180)
After that, I worked at Xerox Palo Alto Research Center,
Eric Schmidt (04:42.220)
where the Alto was invented.
Lex Fridman (04:43.660)
And the Alto is the predecessor
Eric Schmidt (04:46.060)
of the modern personal computer or Macintosh and so forth.
Lex Fridman (04:50.180)
And the Altos were very rare.
Lex Fridman (04:52.300)
And I had to drive an hour from Berkeley to go use them.
Lex Fridman (04:55.260)
But I made a point of skipping classes
Lex Fridman (04:57.380)
and doing whatever it took to have access
Lex Fridman (05:00.960)
to this extraordinary achievement.
Eric Schmidt (05:02.500)
I knew that they were consequential.
Lex Fridman (05:04.900)
What I did not understand was scaling.
Eric Schmidt (05:08.260)
I did not understand what would happen
Lex Fridman (05:09.860)
when you had 100 million as opposed to 100.
Lex Fridman (05:12.820)
And so the, since then,
Lex Fridman (05:14.200)
and I have learned the benefit of scale,
Eric Schmidt (05:16.260)
I always look for things
Lex Fridman (05:17.460)
which are going to scale to platforms, right?
Lex Fridman (05:19.660)
So mobile phones, Android, all those things.
Lex Fridman (05:23.060)
There are, the world is in numerous,
Eric Schmidt (05:25.820)
there are many, many people in the world,
Lex Fridman (05:27.380)
people really have needs.
Eric Schmidt (05:28.500)
They really will use these platforms
Lex Fridman (05:29.940)
and you can build big businesses on top of them.
Lex Fridman (05:32.560)
So it's interesting.
Lex Fridman (05:33.400)
So when you see a piece of technology,
Eric Schmidt (05:34.860)
now you think, what will this technology look like
Lex Fridman (05:37.300)
when it's in the hands of a billion people?
Eric Schmidt (05:39.020)
That's right.
Lex Fridman (05:39.900)
So an example would be that the market is so competitive now
Eric Schmidt (05:44.940)
that if you can't figure out a way
Lex Fridman (05:46.940)
for something to have a million users or a billion users,
Eric Schmidt (05:50.780)
it probably is not going to be successful
Lex Fridman (05:53.100)
because something else will become the general platform
Lex Fridman (05:56.820)
and your idea will become a lost idea
Lex Fridman (06:01.060)
or a specialized service with relatively few users.
Lex Fridman (06:04.260)
So it's a path to generality.
Lex Fridman (06:05.900)
It's a path to general platform use.
Eric Schmidt (06:07.660)
It's a path to broad applicability.
Lex Fridman (06:10.060)
Now there are plenty of good businesses that are tiny.
Lex Fridman (06:12.660)
So luxury goods, for example.
Lex Fridman (06:14.900)
But if you want to have an impact at scale,
Eric Schmidt (06:18.500)
you have to look for things which are of common value,
Lex Fridman (06:21.340)
common pricing, common distribution
Lex Fridman (06:23.300)
and solve common problems.
Lex Fridman (06:24.740)
They're problems that everyone has.
Lex Fridman (06:26.140)
And by the way, people have lots of problems.
Lex Fridman (06:28.100)
Information, medicine, health, education and so forth.
Eric Schmidt (06:31.140)
Work on those problems.
Lex Fridman (06:32.940)
Like you said, you're a big fan of the middle class.
Eric Schmidt (06:36.780)
Because there's so many of them.
Lex Fridman (06:37.820)
There's so many of them.
Eric Schmidt (06:38.740)
By definition.
Lex Fridman (06:40.140)
So any product, any thing that has a huge impact
Lex Fridman (06:44.380)
and improves their lives is a great business decision
Lex Fridman (06:47.460)
and it's just good for society.
Lex Fridman (06:48.860)
And there's nothing wrong with starting off in the high end
Lex Fridman (06:52.340)
as long as you have a plan to get to the middle class.
Eric Schmidt (06:55.420)
There's nothing wrong with starting with a specialized
Lex Fridman (06:57.580)
market in order to learn and to build and to fund things.
Lex Fridman (07:01.020)
So you start with a luxury market
Lex Fridman (07:02.540)
to build a general purpose market.
Lex Fridman (07:04.460)
But if you define yourself as only a narrow market,
Lex Fridman (07:07.500)
someone else can come along with a general purpose market
Eric Schmidt (07:10.940)
that can push you to the corner,
Lex Fridman (07:12.340)
can restrict the scale of operation,
Eric Schmidt (07:14.260)
can force you to be a lesser impact than you might be.
Lex Fridman (07:17.820)
So it's very important to think in terms of broad businesses
Lex Fridman (07:21.020)
and broad impact.
Lex Fridman (07:22.340)
Even if you start in a little corner somewhere.
Lex Fridman (07:26.260)
So as you look to the 70s but also in the decades to come
Lex Fridman (07:30.980)
and you saw computers, did you see them as tools
Lex Fridman (07:34.860)
or was there a little element of another entity?
Lex Fridman (07:40.260)
I remember a quote saying AI began with our dream
Eric Schmidt (07:44.660)
to create the gods.
Lex Fridman (07:46.140)
Is there a feeling when you wrote that program
Eric Schmidt (07:48.620)
that you were creating another entity,
Lex Fridman (07:51.300)
giving life to something?
Eric Schmidt (07:52.820)
I wish I could say otherwise,
Lex Fridman (07:54.660)
but I simply found the technology platforms so exciting.
Eric Schmidt (07:58.740)
That's what I was focused on.
Lex Fridman (08:00.460)
I think the majority of the people that I've worked with,
Lex Fridman (08:03.380)
and there are a few exceptions, Steve Jobs being an example,
Lex Fridman (08:06.700)
really saw this as a great technological play.
Eric Schmidt (08:09.980)
I think relatively few of the technical people understood
Lex Fridman (08:13.700)
the scale of its impact.
Lex Fridman (08:15.380)
So I used NCP, which is a predecessor to TCPIP.
Lex Fridman (08:19.620)
It just made sense to connect things.
Eric Schmidt (08:21.180)
We didn't think of it in terms of the internet
Lex Fridman (08:23.780)
and then companies and then Facebook and then Twitter
Lex Fridman (08:27.020)
and then politics and so forth.
Lex Fridman (08:29.180)
We never did that build.
Eric Schmidt (08:30.740)
We didn't have that vision.
Lex Fridman (08:32.860)
And I think most people, it's a rare person
Eric Schmidt (08:35.300)
who can see compounding at scale.
Lex Fridman (08:38.020)
Most people can see,
Eric Schmidt (08:39.060)
if you ask people to predict the future,
Lex Fridman (08:40.580)
they'll give you an answer of six to nine months
Eric Schmidt (08:43.060)
or 12 months,
Lex Fridman (08:44.500)
because that's about as far as people can imagine.
Lex Fridman (08:47.500)
But there's an old saying,
Lex Fridman (08:48.700)
which actually was attributed to a professor at MIT
Eric Schmidt (08:50.860)
a long time ago,
Lex Fridman (08:52.060)
that we overestimate what can be done in one year
Lex Fridman (08:56.380)
and we underestimate what can be done in a decade.
Lex Fridman (09:00.100)
And there's a great deal of evidence
Eric Schmidt (09:02.460)
that these core platforms at hardware and software
Lex Fridman (09:05.580)
take a decade, right?
Lex Fridman (09:07.740)
So think about self driving cars.
Lex Fridman (09:09.420)
Self driving cars were thought about in the 90s.
Eric Schmidt (09:12.100)
There were projects around them.
Lex Fridman (09:13.340)
The first DARPA Grand Challenge was roughly 2004.
Lex Fridman (09:17.100)
So that's roughly 15 years ago.
Lex Fridman (09:19.700)
And today we have self driving cars operating
Lex Fridman (09:22.060)
in a city in Arizona, right?
Lex Fridman (09:23.940)
It's 15 years and we still have a ways to go
Eric Schmidt (09:26.620)
before they're more generally available.
Lex Fridman (09:31.620)
So you've spoken about the importance,
Eric Schmidt (09:33.780)
you just talked about predicting into the future.
Lex Fridman (09:37.100)
You've spoken about the importance of thinking
Eric Schmidt (09:39.940)
five years ahead and having a plan for those five years.
Lex Fridman (09:42.860)
The way to say it is that almost everybody
Eric Schmidt (09:45.980)
has a one year plan.
Lex Fridman (09:47.500)
Almost no one has a proper five year plan.
Lex Fridman (09:50.940)
And the key thing to having a five year plan
Lex Fridman (09:52.780)
is to having a model for what's going to happen
Eric Schmidt (09:55.260)
under the underlying platforms.
Lex Fridman (09:56.900)
So here's an example.
Eric Schmidt (09:59.980)
Moore's Law as we know it,
Lex Fridman (10:01.140)
the thing that powered improvements in CPUs
Eric Schmidt (10:04.260)
has largely halted in its traditional shrinking mechanism
Lex Fridman (10:07.580)
because the costs have just gotten so high.
Eric Schmidt (10:10.340)
It's getting harder and harder.
Lex Fridman (10:12.160)
But there's plenty of algorithmic improvements
Lex Fridman (10:14.580)
and specialized hardware improvements.
Lex Fridman (10:16.580)
So you need to understand the nature of those improvements
Lex Fridman (10:19.660)
and where they'll go in order to understand
Lex Fridman (10:21.940)
how it will change the platform.
Eric Schmidt (10:24.300)
In the area of network connectivity,
Lex Fridman (10:26.060)
what are the gains that are gonna be possible in wireless?
Eric Schmidt (10:29.400)
It looks like there's an enormous expansion
Lex Fridman (10:33.380)
of wireless connectivity at many different bands.
Lex Fridman (10:36.900)
And that we will primarily,
Lex Fridman (10:38.660)
historically I've always thought
Eric Schmidt (10:39.860)
that we were primarily gonna be using fiber,
Lex Fridman (10:42.080)
but now it looks like we're gonna be using fiber
Eric Schmidt (10:43.940)
plus very powerful high bandwidth
Lex Fridman (10:47.380)
sort of short distance connectivity
Eric Schmidt (10:49.320)
to bridge the last mile.
Lex Fridman (10:51.460)
That's an amazing achievement.
Eric Schmidt (10:53.060)
If you know that,
Lex Fridman (10:54.440)
then you're gonna build your systems differently.
Eric Schmidt (10:56.900)
By the way, those networks
Lex Fridman (10:57.780)
have different latency properties, right?
Eric Schmidt (10:59.640)
Because they're more symmetric,
Lex Fridman (11:01.620)
the algorithms feel faster for that reason.
Lex Fridman (11:04.980)
And so when you think about whether it's a fiber
Lex Fridman (11:07.860)
or just technologies in general,
Lex Fridman (11:09.860)
so there's this barber wooden poem or quote
Lex Fridman (11:14.180)
that I really like.
Eric Schmidt (11:15.860)
It's from the champions of the impossible
Lex Fridman (11:18.240)
rather than the slaves of the possible
Eric Schmidt (11:20.340)
that evolution draws its creative force.
Lex Fridman (11:23.220)
So in predicting the next five years,
Eric Schmidt (11:25.980)
I'd like to talk about the impossible and the possible.
Lex Fridman (11:29.220)
Well, and again, one of the great things about humanity
Lex Fridman (11:32.280)
is that we produce dreamers, right?
Lex Fridman (11:34.720)
We literally have people who have a vision and a dream.
Eric Schmidt (11:37.780)
They are, if you will, disagreeable
Lex Fridman (11:40.100)
in the sense that they disagree with the,
Eric Schmidt (11:42.740)
they disagree with what the sort of zeitgeist is.
Lex Fridman (11:45.780)
They say there is another way.
Eric Schmidt (11:48.020)
They have a belief, they have a vision.
Lex Fridman (11:50.280)
If you look at science, science is always marked
Eric Schmidt (11:54.060)
by such people who went against some conventional wisdom,
Lex Fridman (11:58.380)
collected the knowledge at the time
Lex Fridman (12:00.220)
and assembled it in a way that produced a powerful platform.
Lex Fridman (12:03.660)
And you've been amazingly honest about,
Eric Schmidt (12:08.300)
in an inspiring way, about things you've been wrong
Lex Fridman (12:11.260)
about predicting and you've obviously been right
Eric Schmidt (12:13.860)
about a lot of things, but in this kind of tension,
Lex Fridman (12:18.860)
how do you balance, as a company,
Eric Schmidt (12:21.260)
in predicting the next five years,
Lex Fridman (12:23.580)
the impossible, planning for the impossible,
Lex Fridman (12:26.300)
so listening to those crazy dreamers, letting them do,
Lex Fridman (12:30.380)
letting them run away and make the impossible real,
Eric Schmidt (12:34.140)
make it happen, and slow, you know,
Lex Fridman (12:36.940)
that's how programmers often think,
Lex Fridman (12:38.740)
and slowing things down and saying,
Lex Fridman (12:41.560)
well, this is the rational, this is the possible,
Eric Schmidt (12:44.600)
the pragmatic, the dreamer versus the pragmatist,
Lex Fridman (12:48.380)
so it's helpful to have a model
Eric Schmidt (12:51.380)
which encourages a predictable revenue stream
Lex Fridman (12:56.020)
as well as the ability to do new things.
Lex Fridman (12:58.660)
So in Google's case, we're big enough
Lex Fridman (13:00.540)
and well enough managed and so forth
Eric Schmidt (13:02.340)
that we have a pretty good sense of what our revenue will be
Lex Fridman (13:05.200)
for the next year or two, at least for a while.
Lex Fridman (13:07.900)
And so we have enough cash generation
Lex Fridman (13:11.540)
that we can make bets, and indeed,
Eric Schmidt (13:14.700)
Google has become alphabet,
Lex Fridman (13:16.780)
so the corporation is organized around these bets,
Lex Fridman (13:19.500)
and these bets are in areas of fundamental importance
Lex Fridman (13:22.740)
to the world, whether it's artificial intelligence,
Eric Schmidt (13:26.720)
medical technology, self driving cars,
Lex Fridman (13:29.700)
connectivity through balloons, on and on and on.
Lex Fridman (13:33.300)
And there's more coming and more coming.
Lex Fridman (13:35.980)
So one way you could express this
Eric Schmidt (13:38.020)
is that the current business is successful enough
Lex Fridman (13:41.500)
that we have the luxury of making bets.
Lex Fridman (13:44.580)
And another one that you could say
Lex Fridman (13:45.940)
is that we have the wisdom of being able to see
Eric Schmidt (13:49.140)
that a corporate structure needs to be created
Lex Fridman (13:51.580)
to enhance the likelihood of the success of those bets.
Lex Fridman (13:55.260)
So we essentially turned ourselves into a conglomerate
Lex Fridman (13:58.860)
of bets and then this underlying corporation, Google,
Eric Schmidt (14:02.100)
which is itself innovative.
Lex Fridman (14:04.280)
So in order to pull this off,
Eric Schmidt (14:05.900)
you have to have a bunch of belief systems,
Lex Fridman (14:08.060)
and one of them is that you have to have
Eric Schmidt (14:09.580)
bottoms up and tops down.
Lex Fridman (14:11.460)
The bottoms up we call 20% time,
Lex Fridman (14:13.580)
and the idea is that people can spend 20% of the time
Lex Fridman (14:15.780)
whatever they want, and the top down
Eric Schmidt (14:17.740)
is that our founders in particular
Lex Fridman (14:19.700)
have a keen eye on technology
Lex Fridman (14:21.740)
and they're reviewing things constantly.
Lex Fridman (14:23.880)
So an example would be they'll hear about an idea
Eric Schmidt (14:26.540)
or I'll hear about something and it sounds interesting,
Lex Fridman (14:28.700)
let's go visit them.
Lex Fridman (14:30.380)
And then let's begin to assemble the pieces
Lex Fridman (14:33.060)
to see if that's possible.
Lex Fridman (14:34.780)
And if you do this long enough,
Lex Fridman (14:35.980)
you get pretty good at predicting what's likely to work.
Lex Fridman (14:39.780)
So that's a beautiful balance that struck.
Lex Fridman (14:42.020)
Is this something that applies at all scale?
Eric Schmidt (14:44.420)
It seems to be that Sergey, again, 15 years ago,
Lex Fridman (14:53.060)
came up with a concept called 10% of the budget
Eric Schmidt (14:56.840)
should be on things that are unrelated.
Lex Fridman (14:58.980)
It was called 70, 20, 10.
Eric Schmidt (15:00.860)
70% of our time on core business,
Lex Fridman (15:03.540)
20% on adjacent business, and 10% on other.
Lex Fridman (15:06.780)
And he proved mathematically,
Lex Fridman (15:08.700)
of course he's a brilliant mathematician,
Eric Schmidt (15:10.580)
that you needed that 10% to make the sum
Lex Fridman (15:13.860)
of the growth work.
Lex Fridman (15:14.700)
And it turns out he was right.
Lex Fridman (15:18.620)
So getting into the world of artificial intelligence,
Eric Schmidt (15:20.940)
you've talked quite extensively and effectively
Lex Fridman (15:25.380)
to the impact in the near term,
Eric Schmidt (15:28.780)
the positive impact of artificial intelligence,
Lex Fridman (15:32.020)
whether it's especially machine learning
Eric Schmidt (15:34.140)
in medical applications and education,
Lex Fridman (15:38.580)
and just making information more accessible, right?
Eric Schmidt (15:41.600)
In the AI community, there is a kind of debate.
Lex Fridman (15:45.860)
There's this shroud of uncertainty
Eric Schmidt (15:47.700)
as we face this new world
Lex Fridman (15:49.020)
with artificial intelligence in it.
Lex Fridman (15:50.460)
And there's some people, like Elon Musk,
Lex Fridman (15:54.260)
you've disagreed, at least on the degree of emphasis
Eric Schmidt (15:57.660)
he places on the existential threat of AI.
Lex Fridman (16:00.700)
So I've spoken with Stuart Russell,
Eric Schmidt (16:02.540)
Max Tegmark, who share Elon Musk's view,
Lex Fridman (16:05.340)
and Yoshua Bengio, Steven Pinker, who do not.
Lex Fridman (16:09.180)
And so there's a lot of very smart people
Lex Fridman (16:11.860)
who are thinking about this stuff, disagreeing,
Eric Schmidt (16:14.620)
which is really healthy, of course.
Lex Fridman (16:17.180)
So what do you think is the healthiest way
Eric Schmidt (16:19.100)
for the AI community to,
Lex Fridman (16:22.020)
and really for the general public,
Eric Schmidt (16:23.860)
to think about AI and the concern
Lex Fridman (16:27.700)
of the technology being mismanaged in some kind of way?
Lex Fridman (16:32.920)
So the source of education for the general public
Lex Fridman (16:35.060)
has been robot killer movies.
Eric Schmidt (16:37.380)
Right.
Lex Fridman (16:38.220)
And Terminator, et cetera.
Lex Fridman (16:40.860)
And the one thing I can assure you we're not building
Lex Fridman (16:44.500)
are those kinds of solutions.
Eric Schmidt (16:46.620)
Furthermore, if they were to show up,
Lex Fridman (16:48.420)
someone would notice and unplug them, right?
Lex Fridman (16:51.140)
So as exciting as those movies are,
Lex Fridman (16:53.140)
and they're great movies,
Eric Schmidt (16:54.700)
were the killer robots to start,
Lex Fridman (16:57.500)
we would find a way to stop them, right?
Lex Fridman (17:00.500)
So I'm not concerned about that.
Lex Fridman (17:04.060)
And much of this has to do
Eric Schmidt (17:05.980)
with the timeframe of conversation.
Lex Fridman (17:08.540)
So you can imagine a situation 100 years from now
Eric Schmidt (17:13.300)
when the human brain is fully understood
Lex Fridman (17:15.920)
and the next generation and next generation
Eric Schmidt (17:18.140)
of brilliant MIT scientists have figured all this out,
Lex Fridman (17:20.940)
we're gonna have a large number of ethics questions, right?
Eric Schmidt (17:25.140)
Around science and thinking and robots and computers
Lex Fridman (17:28.060)
and so forth and so on.
Lex Fridman (17:29.700)
So it depends on the question of the timeframe.
Lex Fridman (17:32.260)
In the next five to 10 years,
Eric Schmidt (17:34.780)
we're not facing those questions.
Lex Fridman (17:37.220)
What we're facing in the next five to 10 years
Eric Schmidt (17:39.100)
is how do we spread this disruptive technology
Lex Fridman (17:42.140)
as broadly as possible to gain the maximum benefit of it?
Eric Schmidt (17:46.500)
The primary benefits should be in healthcare
Lex Fridman (17:48.980)
and in education.
Eric Schmidt (17:50.860)
Healthcare because it's obvious.
Lex Fridman (17:52.320)
We're all the same even though we somehow believe we're not.
Eric Schmidt (17:55.780)
As a medical matter,
Lex Fridman (17:57.340)
the fact that we have big data about our health
Eric Schmidt (17:59.180)
will save lives, allow us to deal with skin cancer
Lex Fridman (18:02.700)
and other cancers, ophthalmological problems.
Eric Schmidt (18:05.500)
There's people working on psychological diseases
Lex Fridman (18:08.420)
and so forth using these techniques.
Eric Schmidt (18:10.260)
I can go on and on.
Lex Fridman (18:11.700)
The promise of AI in medicine is extraordinary.
Eric Schmidt (18:15.840)
There are many, many companies and startups
Lex Fridman (18:17.980)
and funds and solutions
Lex Fridman (18:19.480)
and we will all live much better for that.
Lex Fridman (18:22.140)
The same argument in education.
Lex Fridman (18:25.580)
Can you imagine that for each generation of child
Lex Fridman (18:28.540)
and even adult, you have a tutor educator that's AI based,
Eric Schmidt (18:33.020)
that's not a human but is properly trained,
Lex Fridman (18:35.900)
that helps you get smarter,
Eric Schmidt (18:37.140)
helps you address your language difficulties
Lex Fridman (18:39.280)
or your math difficulties or what have you.
Lex Fridman (18:41.340)
Why don't we focus on those two?
Lex Fridman (18:43.300)
The gains societally of making humans smarter and healthier
Eric Schmidt (18:47.300)
are enormous and those translate for decades and decades
Lex Fridman (18:51.460)
and we'll all benefit from them.
Eric Schmidt (18:53.900)
There are people who are working on AI safety,
Lex Fridman (18:56.300)
which is the issue that you're describing
Lex Fridman (18:58.060)
and there are conversations in the community
Lex Fridman (19:00.660)
that should there be such problems,
Lex Fridman (19:02.500)
what should the rules be like?
Lex Fridman (19:04.380)
Google, for example, has announced its policies
Eric Schmidt (19:07.540)
with respect to AI safety, which I certainly support
Lex Fridman (19:10.140)
and I think most everybody would support
Lex Fridman (19:12.300)
and they make sense, right?
Lex Fridman (19:14.140)
So it helps guide the research
Lex Fridman (19:16.300)
but the killer robots are not arriving this year
Lex Fridman (19:19.540)
and they're not even being built.
Lex Fridman (19:22.540)
And on that line of thinking, you said the time scale.
Lex Fridman (19:26.720)
In this topic or other topics,
Eric Schmidt (19:30.440)
have you found it useful on the business side
Lex Fridman (19:34.560)
or the intellectual side to think beyond five, 10 years,
Lex Fridman (19:37.480)
to think 50 years out?
Lex Fridman (19:39.360)
Has it ever been useful or productive?
Eric Schmidt (19:41.960)
In our industry, there are essentially no examples
Lex Fridman (19:45.160)
of 50 year predictions that have been correct.
Lex Fridman (19:48.840)
Let's review AI, right?
Lex Fridman (19:50.400)
AI, which was largely invented here at MIT
Lex Fridman (19:53.060)
and a couple of other universities in the 1956, 1957,
Lex Fridman (19:56.440)
1958, the original claims were a decade or two.
Lex Fridman (20:01.320)
And when I was a PhD student, I studied AI a bit
Lex Fridman (20:05.180)
and it entered during my looking at it,
Eric Schmidt (20:07.680)
a period which is known as AI winter,
Lex Fridman (20:10.360)
which went on for about 30 years,
Eric Schmidt (20:12.760)
which is a whole generation of science,
Lex Fridman (20:14.720)
scientists and a whole group of people
Eric Schmidt (20:16.640)
who didn't make a lot of progress
Lex Fridman (20:18.400)
because the algorithms had not improved
Lex Fridman (20:20.160)
and the computers had not approved.
Lex Fridman (20:22.060)
It took some brilliant mathematicians
Eric Schmidt (20:23.840)
starting with a fellow named Jeff Hinton
Lex Fridman (20:25.360)
at Toronto and Montreal who basically invented
Eric Schmidt (20:29.460)
this deep learning model which empowers us today.
Lex Fridman (20:33.020)
The seminal work there was 20 years ago
Lex Fridman (20:36.060)
and in the last 10 years, it's become popularized.
Lex Fridman (20:39.960)
So think about the timeframes for that level of discovery.
Eric Schmidt (20:43.840)
It's very hard to predict.
Lex Fridman (20:45.880)
Many people think that we'll be flying around
Lex Fridman (20:47.700)
in the equivalent of flying cars, who knows?
Lex Fridman (20:51.160)
My own view, if I wanna go out on a limb,
Eric Schmidt (20:54.440)
is to say that we know a couple of things
Lex Fridman (20:56.840)
about 50 years from now.
Eric Schmidt (20:57.960)
We know that there'll be more people alive.
Lex Fridman (21:00.440)
We know that we'll have to have platforms
Eric Schmidt (21:02.160)
that are more sustainable because the earth is limited
Lex Fridman (21:05.680)
in the ways we all know and that the kind of platforms
Eric Schmidt (21:09.160)
that are gonna get built will be consistent
Lex Fridman (21:11.360)
with the principles that I've described.
Eric Schmidt (21:13.000)
They will be much more empowering of individuals.
Lex Fridman (21:15.720)
They'll be much more sensitive to the ecology
Eric Schmidt (21:17.720)
because they have to be, they just have to be.
Lex Fridman (21:20.520)
I also think that humans are gonna be a great deal smarter
Lex Fridman (21:23.760)
and I think they're gonna be a lot smarter
Lex Fridman (21:25.040)
because of the tools that I've discussed with you
Lex Fridman (21:27.720)
and of course, people will live longer.
Lex Fridman (21:29.160)
Life extension is continuing apace.
Eric Schmidt (21:32.160)
A baby born today has a reasonable chance
Lex Fridman (21:34.600)
of living to 100, which is pretty exciting.
Eric Schmidt (21:37.080)
It's well past the 21st century,
Lex Fridman (21:38.580)
so we better take care of them.
Lex Fridman (21:40.600)
And you mentioned an interesting statistic
Lex Fridman (21:42.600)
on some very large percentage, 60, 70% of people
Eric Schmidt (21:46.080)
may live in cities.
Lex Fridman (21:48.160)
Today, more than half the world lives in cities
Lex Fridman (21:50.460)
and one of the great stories of humanity
Lex Fridman (21:53.720)
in the last 20 years has been the rural to urban migration.
Eric Schmidt (21:57.440)
This has occurred in the United States,
Lex Fridman (21:59.200)
it's occurred in Europe, it's occurring in Asia
Lex Fridman (22:02.760)
and it's occurring in Africa.
Lex Fridman (22:04.660)
When people move to cities, the cities get more crowded,
Lex Fridman (22:07.760)
but believe it or not, their health gets better,
Lex Fridman (22:10.480)
their productivity gets better,
Eric Schmidt (22:12.280)
their IQ and educational capabilities improve.
Lex Fridman (22:15.440)
So it's good news that people are moving to cities,
Lex Fridman (22:18.500)
but we have to make them livable and safe.
Lex Fridman (22:20.820)
So you, first of all, you are,
Lex Fridman (22:25.860)
but you've also worked with some of the greatest leaders
Lex Fridman (22:28.300)
in the history of tech.
Lex Fridman (22:29.940)
What insights do you draw from the difference
Lex Fridman (22:32.940)
in leadership styles of yourself,
Eric Schmidt (22:35.660)
Steve Jobs, Elon Musk, Larry Page,
Lex Fridman (22:39.140)
now the new CEO, Sandra Pichai and others?
Eric Schmidt (22:42.740)
From the, I would say, calm sages to the mad geniuses.
Lex Fridman (22:47.740)
One of the things that I learned as a young executive
Eric Schmidt (22:50.660)
is that there's no single formula for leadership.
Lex Fridman (22:54.500)
They try to teach one, but that's not how it really works.
Eric Schmidt (22:58.380)
There are people who just understand what they need to do
Lex Fridman (23:01.020)
and they need to do it quickly.
Eric Schmidt (23:02.540)
Those people are often entrepreneurs.
Lex Fridman (23:05.060)
They just know and they move fast.
Eric Schmidt (23:07.340)
There are other people who are systems thinkers
Lex Fridman (23:09.100)
and planners, that's more who I am,
Eric Schmidt (23:11.420)
somewhat more conservative, more thorough in execution,
Lex Fridman (23:15.060)
a little bit more risk of risk.
Eric Schmidt (23:16.740)
A little bit more risk averse.
Lex Fridman (23:18.620)
There's also people who are sort of slightly insane,
Eric Schmidt (23:22.140)
in the sense that they are emphatic and charismatic
Lex Fridman (23:26.060)
and they feel it and they drive it and so forth.
Eric Schmidt (23:28.900)
There's no single formula to success.
Lex Fridman (23:31.340)
There is one thing that unifies all of the people
Eric Schmidt (23:33.620)
that you named, which is very high intelligence.
Lex Fridman (23:36.900)
At the end of the day, the thing that characterizes
Eric Schmidt (23:40.180)
all of them is that they saw the world quicker, faster,
Lex Fridman (23:43.620)
they processed information faster.
Eric Schmidt (23:45.700)
They didn't necessarily make the right decisions
Lex Fridman (23:47.300)
all the time, but they were on top of it.
Lex Fridman (23:49.940)
And the other thing that's interesting
Lex Fridman (23:51.180)
about all those people is they all started young.
Lex Fridman (23:54.140)
So think about Steve Jobs starting Apple
Lex Fridman (23:56.940)
roughly at 18 or 19.
Eric Schmidt (23:58.380)
Think about Bill Gates starting at roughly 20, 21.
Lex Fridman (24:01.620)
Think about by the time they were 30,
Eric Schmidt (24:03.700)
Mark Zuckerberg, a good example, at 19, 20.
Lex Fridman (24:06.900)
By the time they were 30, they had 10 years.
Eric Schmidt (24:10.620)
At 30 years old, they had 10 years of experience
Lex Fridman (24:13.700)
of dealing with people and products and shipments
Lex Fridman (24:16.940)
and the press and business and so forth.
Lex Fridman (24:19.740)
It's incredible how much experience they had
Eric Schmidt (24:22.740)
compared to the rest of us who were busy getting our PhDs.
Lex Fridman (24:25.220)
Yes, exactly.
Lex Fridman (24:26.060)
So we should celebrate these people
Lex Fridman (24:28.460)
because they've just had more life experience, right?
Lex Fridman (24:32.180)
And that helps inform the judgment.
Lex Fridman (24:34.340)
At the end of the day, when you're at the top
Eric Schmidt (24:38.220)
of these organizations, all the easy questions
Lex Fridman (24:41.380)
have been dealt with, right?
Lex Fridman (24:43.500)
How should we design the buildings?
Lex Fridman (24:45.620)
Where should we put the colors on our product?
Lex Fridman (24:48.180)
What should the box look like, right?
Lex Fridman (24:51.300)
The problems, that's why it's so interesting
Eric Schmidt (24:53.340)
to be in these rooms, the problems that they face, right,
Lex Fridman (24:56.420)
in terms of the way they operate,
Eric Schmidt (24:58.340)
the way they deal with their employees,
Lex Fridman (25:00.060)
their customers, their innovation,
Eric Schmidt (25:01.860)
are profoundly challenging.
Lex Fridman (25:03.900)
Each of the companies is demonstrably different culturally.
Eric Schmidt (25:09.340)
They are not, in fact, cut of the same.
Lex Fridman (25:11.700)
They behave differently based on input.
Eric Schmidt (25:14.180)
Their internal cultures are different.
Lex Fridman (25:15.820)
Their compensation schemes are different.
Eric Schmidt (25:17.460)
Their values are different.
Lex Fridman (25:19.340)
So there's proof that diversity works.
Eric Schmidt (25:24.700)
So, so when faced with a tough decision,
Lex Fridman (25:29.780)
in need of advice, it's been said that the best thing
Eric Schmidt (25:33.500)
one can do is to find the best person in the world
Lex Fridman (25:36.740)
who can give that advice and find a way to be
Eric Schmidt (25:40.780)
in a room with them, one on one and ask.
Lex Fridman (25:44.740)
So here we are, and let me ask in a long winded way,
Eric Schmidt (25:48.060)
I wrote this down.
Lex Fridman (25:50.740)
In 1998, there were many good search engines,
Eric Schmidt (25:53.420)
Lycos, Excite, AltaVista, Infoseek, Ask Jeeves maybe,
Lex Fridman (25:59.260)
Yahoo even.
Lex Fridman (26:01.860)
So Google stepped in and disrupted everything.
Lex Fridman (26:04.660)
They disrupted the nature of search,
Eric Schmidt (26:06.580)
the nature of our access to information,
Lex Fridman (26:08.860)
the way we discover new knowledge.
Lex Fridman (26:11.900)
So now it's 2018, actually 20 years later.
Lex Fridman (26:16.020)
There are many good personal AI assistants,
Eric Schmidt (26:18.740)
including, of course, the best from Google.
Lex Fridman (26:22.260)
So you've spoken in medical and education,
Eric Schmidt (26:25.540)
the impact of such an AI assistant could bring.
Lex Fridman (26:28.620)
So we arrive at this question.
Lex Fridman (26:30.340)
So it's a personal one for me,
Lex Fridman (26:32.180)
but I hope my situation represents that of many other,
Eric Schmidt (26:36.300)
as we said, dreamers and the crazy engineers.
Lex Fridman (26:40.580)
So my whole life, I've dreamed of creating
Eric Schmidt (26:43.900)
such an AI assistant.
Lex Fridman (26:45.860)
Every step I've taken has been towards that goal.
Eric Schmidt (26:48.420)
Now I'm a research scientist in human centered AI
Lex Fridman (26:51.060)
here at MIT.
Lex Fridman (26:52.300)
So the next step for me as I sit here,
Lex Fridman (26:54.860)
so facing my passion is to do what Larry and Sergey did
Eric Schmidt (26:59.860)
in 98, this simple startup.
Lex Fridman (27:04.180)
And so here's my simple question.
Eric Schmidt (27:06.820)
Given the low odds of success, the timing and luck required,
Lex Fridman (27:10.620)
the countless other factors that can't be controlled
Eric Schmidt (27:12.700)
or predicted, which is all the things
Lex Fridman (27:14.660)
that Larry and Sergey faced,
Eric Schmidt (27:16.460)
is there some calculation, some strategy
Lex Fridman (27:20.140)
to follow in this step?
Eric Schmidt (27:21.580)
Or do you simply follow the passion
Lex Fridman (27:23.700)
just because there's no other choice?
Eric Schmidt (27:26.580)
I think the people who are in universities
Lex Fridman (27:29.660)
are always trying to study
Eric Schmidt (27:31.860)
the extraordinarily chaotic nature of innovation
Lex Fridman (27:35.180)
and entrepreneurship.
Eric Schmidt (27:37.260)
My answer is that they didn't have that conversation.
Lex Fridman (27:41.180)
They just did it.
Eric Schmidt (27:42.820)
They sensed a moment when in the case of Google,
Lex Fridman (27:47.220)
there was all of this data that needed to be organized
Lex Fridman (27:49.700)
and they had a better algorithm.
Lex Fridman (27:51.300)
They had invented a better way.
Lex Fridman (27:53.780)
So today with human centered AI,
Lex Fridman (27:56.300)
which is your area of research,
Eric Schmidt (27:58.060)
there must be new approaches.
Lex Fridman (28:00.860)
It's such a big field.
Eric Schmidt (28:02.460)
There must be new approaches,
Lex Fridman (28:04.900)
different from what we and others are doing.
Eric Schmidt (28:07.220)
There must be startups to fund.
Lex Fridman (28:09.540)
There must be research projects to try.
Eric Schmidt (28:11.940)
There must be graduate students to work on new approaches.
Lex Fridman (28:15.020)
Here at MIT, there are people who are looking at learning
Eric Schmidt (28:18.180)
from the standpoint of looking at child learning.
Lex Fridman (28:20.580)
How do children learn starting at age one and two?
Lex Fridman (28:23.500)
And the work is fantastic.
Lex Fridman (28:25.340)
Those approaches are different from the approach
Eric Schmidt (28:28.180)
that most people are taking.
Lex Fridman (28:29.780)
Perhaps that's a bet that you should make
Eric Schmidt (28:31.940)
or perhaps there's another one.
Lex Fridman (28:33.820)
But at the end of the day,
Eric Schmidt (28:35.860)
the successful entrepreneurs are not as crazy as they sound.
Lex Fridman (28:40.100)
They see an opportunity based on what's happened.
Eric Schmidt (28:43.100)
Let's use Uber as an example.
Lex Fridman (28:45.300)
As Travis sells the story,
Eric Schmidt (28:46.740)
he and his co founder were sitting in Paris
Lex Fridman (28:48.940)
and they had this idea because they couldn't get a cab.
Lex Fridman (28:52.060)
And they said, we have smartphones and the rest is history.
Lex Fridman (28:56.660)
So what's the equivalent of that Travis Eiffel Tower,
Eric Schmidt (29:00.980)
where is a cab moment that you could,
Lex Fridman (29:03.980)
as an entrepreneur, take advantage of?
Eric Schmidt (29:05.940)
Whether it's in human centered AI or something else.
Lex Fridman (29:08.500)
That's the next great startup.
Lex Fridman (29:11.260)
And the psychology of that moment.
Lex Fridman (29:13.660)
So when Sergey and Larry talk about,
Lex Fridman (29:17.540)
and listen to a few interviews, it's very nonchalant.
Lex Fridman (29:20.180)
Well, here's the very fascinating web data
Lex Fridman (29:23.780)
and here's an algorithm we have for,
Lex Fridman (29:27.700)
we just kind of want to play around with that data.
Lex Fridman (29:29.420)
And it seems like that's a really nice way
Lex Fridman (29:31.020)
to organize this data.
Eric Schmidt (29:34.180)
I should say what happened to remember
Lex Fridman (29:35.580)
is that they were graduate students at Stanford
Lex Fridman (29:38.100)
and they thought this was interesting.
Lex Fridman (29:39.300)
So they built a search engine
Lex Fridman (29:40.540)
and they kept it in their room.
Lex Fridman (29:43.020)
And they had to get power from the room next door
Eric Schmidt (29:46.300)
because they were using too much power in the room.
Lex Fridman (29:48.020)
So they ran an extension cord over, right?
Lex Fridman (29:51.460)
And then they went and they found a house
Lex Fridman (29:53.500)
and they had Google world headquarters of five people,
Eric Schmidt (29:56.500)
right, to start the company.
Lex Fridman (29:57.540)
And they raised $100,000 from Andy Bechtolsheim,
Eric Schmidt (30:00.460)
who was the Sun founder to do this
Lex Fridman (30:02.220)
and Dave Cheriton and a few others.
Eric Schmidt (30:04.460)
The point is their beginnings were very simple
Lex Fridman (30:08.220)
but they were based on a powerful insight.
Eric Schmidt (30:11.700)
That is a replicable model for any startup.
Lex Fridman (30:14.860)
It has to be a powerful insight.
Eric Schmidt (30:16.500)
The beginnings are simple.
Lex Fridman (30:17.620)
And there has to be an innovation.
Eric Schmidt (30:19.860)
In Larry and Sergey's case, it was PageRank,
Lex Fridman (30:22.820)
which was a brilliant idea,
Eric Schmidt (30:23.980)
one of the most cited papers in the world today.
Lex Fridman (30:26.700)
What's the next one?
Lex Fridman (30:29.740)
So you're one of, if I may say,
Lex Fridman (30:33.500)
richest people in the world.
Lex Fridman (30:36.180)
And yet it seems that money is simply a side effect
Lex Fridman (30:38.700)
of your passions and not an inherent goal.
Lex Fridman (30:42.980)
But you're a fascinating person to ask.
Lex Fridman (30:48.220)
So much of our society at the individual level
Lex Fridman (30:51.540)
and at the company level and as nations
Lex Fridman (30:55.020)
is driven by the desire for wealth.
Lex Fridman (30:58.660)
What do you think about this drive?
Lex Fridman (31:01.100)
And what have you learned about,
Eric Schmidt (31:03.140)
if I may romanticize the notion,
Lex Fridman (31:05.020)
the meaning of life,
Lex Fridman (31:06.860)
having achieved success on so many dimensions?
Lex Fridman (31:10.420)
There have been many studies of human happiness
Lex Fridman (31:13.580)
and above some threshold,
Lex Fridman (31:16.340)
which is typically relatively low for this conversation,
Eric Schmidt (31:19.500)
there's no difference in happiness about money.
Lex Fridman (31:23.580)
The happiness is correlated with meaning and purpose,
Eric Schmidt (31:27.060)
a sense of family, a sense of impact.
Lex Fridman (31:30.020)
So if you organize your life,
Eric Schmidt (31:31.900)
assuming you have enough to get around
Lex Fridman (31:33.620)
and have a nice home and so forth,
Eric Schmidt (31:35.860)
you'll be far happier if you figure out
Lex Fridman (31:38.300)
what you care about and work on that.
Eric Schmidt (31:41.660)
It's often being in service to others.
Lex Fridman (31:44.580)
There's a great deal of evidence that people are happiest
Eric Schmidt (31:46.860)
when they're serving others and not themselves.
Lex Fridman (31:49.540)
This goes directly against the sort of
Eric Schmidt (31:52.540)
press induced excitement about
Lex Fridman (31:56.100)
powerful and wealthy leaders of one kind.
Lex Fridman (31:59.220)
And indeed these are consequential people.
Lex Fridman (32:01.700)
But if you are in a situation
Eric Schmidt (32:03.860)
where you've been very fortunate as I have,
Lex Fridman (32:06.100)
you also have to take that as a responsibility
Lex Fridman (32:09.020)
and you have to basically work both to educate others
Lex Fridman (32:12.180)
and give them that opportunity,
Lex Fridman (32:13.580)
but also use that wealth to advance human society.
Lex Fridman (32:16.700)
In my case, I'm particularly interested in
Eric Schmidt (32:18.540)
using the tools of artificial intelligence
Lex Fridman (32:20.580)
and machine learning to make society better.
Eric Schmidt (32:22.860)
I've mentioned education, I've mentioned inequality
Lex Fridman (32:26.020)
and middle class and things like this,
Eric Schmidt (32:28.060)
all of which are a passion of mine.
Lex Fridman (32:30.100)
It doesn't matter what you do,
Eric Schmidt (32:31.860)
it matters that you believe in it,
Lex Fridman (32:33.700)
that it's important to you,
Lex Fridman (32:35.380)
and that your life will be far more satisfying
Lex Fridman (32:38.100)
if you spend your life doing that.
Eric Schmidt (32:40.540)
I think there's no better place to end
Lex Fridman (32:43.460)
than a discussion of the meaning of life.
Eric Schmidt (32:45.220)
Eric, thank you so much.
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