Joe Rogan Experience #2494 - Chamath Palihapitiya — Full Transcript

0:37

indigestible.

0:39

>> What does that mean?

0:40

>> Right.

0:41

>> Indigestible as in or well then it

0:44

doesn't mean that it's real then.

0:46

>> Well, I think it means that it'll be so

0:48

crazy if it's real. So crazy. He's the

0:51

one that's been saying that there's

0:52

these confirmed bases under the ocean,

0:56

that there's these specific locations. I

0:58

think you talked you're shaking your

1:00

head. You don't believe a word of it.

1:01

>> No.

1:02

>> How come?

1:02

>> I think I think it's true that there

1:05

look,

1:07

it's completely implausible that there

1:10

aren't other species,

1:11

>> right?

1:12

>> Completely implausible.

1:14

>> Just the vastness of what we're dealing

1:16

with. So the real question is like why

1:18

haven't we encountered people or those

1:21

things those beings,

1:22

>> right?

1:23

>> And it's probably because they just they

1:25

have bigger fish to fry, you know? So by

1:28

the time that we meet them and they meet

1:30

us, we're we're going to kind of be at

1:32

the edge of like we've we've kind of

1:34

been there done that on our own planet

1:37

and then we've kind of like developed

1:38

the technology I guess to get beyond it.

1:41

Um but somewhere along the way there

1:43

must have been a few just mathematically

1:45

impossible. So then the question is, is

1:46

it buried? Or were people confused when

1:48

it first came here? Like if you had a

1:50

spaceship land in like the 1800s,

1:52

>> right?

1:52

>> What would people have done? They would

1:54

have just freaked out. They wouldn't

1:56

have understood it. Maybe they would

1:57

have buried it. Depending on where it

1:58

was, maybe they started to pray to it,

2:00

>> right?

2:01

>> And you would have just moved on. And

2:03

then that isn't documented in history.

2:05

So,

2:05

>> but it is.

2:06

>> But how?

2:07

>> It is. There's a lot of it documented in

2:09

history.

2:10

>> Oh, you mean like hieroglyphics and like

2:12

monuments?

2:12

>> Well, the book of Ezekiel. The book of

2:14

Ezekiel goes in depth about some sort of

2:16

a UFO encounter that Ezekiel

2:19

experiences,

2:20

>> right?

2:20

>> Where it's a wheel within a wheel and a

2:24

a cloud with fire flashing forth

2:26

continually in the midst of a cloud as

2:28

it were gleaming metal and from the

2:30

midst of it came the likeness of four

2:32

living creatures and the creatures

2:34

darted to and fro like the appearance of

2:36

a flash of lightning. This is all in the

2:38

Bible. Um it's also in the Mahabarada.

2:41

Um they they talk about vaymanas these

2:44

flying crafts and

2:46

>> I think it's entirely possible that we

2:48

have been visited periodically

2:51

>> and that we are we have been monitored

2:53

and that we are monitored.

2:54

>> I agree

2:55

>> currently.

2:56

>> I agree.

2:56

>> And if I was going to hide, I would hide

2:58

in the ocean.

2:59

>> Well, to be honest, as I get older, I'm

3:01

convinced

3:03

>> we're basically in some form of a

3:05

simulation. There's like all these

3:07

little ingredients

3:08

>> that if you start to see these little

3:10

clues, you're like,

3:12

>> they all seem so odd in isolation and

3:14

then when you put them together, I feel

3:15

like a crazy person. So, I ignore

3:17

myself,

3:17

>> right?

3:18

>> But I wonder like why did this happen?

3:19

Like yesterday, I was um at a dinner in

3:22

LA before I came to see you. And um I

3:26

told this very interesting story. Well,

3:28

or I thought it was interesting at the

3:29

time. Um

3:31

you know that like so in 2000, right? If

3:34

you think of like what happened in tech

3:36

since 2000, so the last 26 years,

3:40

people can give you all kinds of like

3:41

fancy theories,

3:44

but there's just like this weird

3:47

word that's been at the center of every

3:50

single technological revolution for the

3:53

last 30 years. And that word is

3:55

attention. Let me explain this to you.

3:58

Google, they invent Google. What is

4:00

Google? Google is a algorithm. It's

4:03

called page rank. But if you look inside

4:06

of it, what is it? It says, "Well,

4:07

Chimath's website has five links to it.

4:11

Joe's website has two links. He's

4:13

getting more attention." Okay, Chimath's

4:16

website is more important. That's the

4:17

sum total of Google. Now, they've made

4:19

that a lot more refined and they've done

4:21

all these other fancy things,

4:24

but it's all about attention. Mhm.

4:26

>> Fast forward to 2007 89 when you know

4:29

Zuck and then when I went to work for

4:31

Zuck and we got on the scene and we're

4:32

like what do everybody what does

4:34

everybody care about? Attention. And so

4:38

what is like the Facebook algorithm?

4:40

What's the Instagram algorithm? You know

4:42

how did we construct newsfeed all around

4:45

attention? Joe had 35 likes. Jamie had

4:47

12 likes. Your thing is more important.

4:49

Let's give it more more importance

4:51

because it's seemingly meeting all these

4:53

human needs. Attention. Attention.

4:55

attention. So phase one attention, phase

4:58

two attention, and this is where I'm

5:01

like, how can this be possible? In phase

5:02

three, we're like looking at AI. And

5:05

when you look backwards four years, the

5:06

seminal paper is called attention is all

5:08

you need. It's about this word again.

5:12

And when you look inside of the core

5:15

part, if you peel out peel, you know,

5:17

apart AI,

5:19

the little brain that makes it so

5:21

capable, it's called an attention

5:23

mechanism. It's just attention. It's all

5:25

about again this idea of I'm gonna scour

5:28

all this information and I'm gonna

5:30

figure out what patterns repeat itself

5:31

and I'm just going to double down on the

5:33

stuff that I see more of because that

5:35

attention must mean it's more important.

5:37

It's more true. It's more knowledgeable

5:40

and then I think how could it be like

5:42

we're all like why is it that these

5:44

things are just repeating over and over

5:46

again? And I just get confused. I don't

5:48

I don't exactly know how to explain it.

5:50

So are there other ways in which we

5:52

should be doing things? Absolutely. Have

5:54

we even explored it? No. So then I

5:56

think, well, is this just a simulation?

5:57

Some kid in a [ __ ] in his house just

6:00

playing some simulation and we're all

6:01

just party to it and that's all he

6:03

understands is attention. I don't know.

6:05

>> I don't think it's that simple that

6:07

there's a person playing a game. But if

6:10

you break down just attention, well,

6:12

that's all of human history is paying

6:16

attention to the king, paying attention

6:18

to the war, paying attention to

6:21

resources, paying attention to who says

6:23

the thing that resonates the most with

6:25

the people. It's all about what human

6:28

beings are paying attention to.

6:30

>> I think it's part of it. Then there's

6:32

also what is actually true. And I think

6:36

sometimes what is true and what people

6:37

pay attention to are not the same thing.

6:40

>> True.

6:41

>> And sometimes the thing that you should

6:44

be paying attention to gets lost because

6:47

the thing that you are paying attention

6:48

to gets more attention because it's more

6:50

interesting and useful. That's sort of

6:53

where we are right now. We're in this

6:54

really weird phase, I think, where

6:57

you actually like should be focused on

7:00

this thing over here and instead we're

7:02

all focused on all these things over

7:04

here. or give me an example.

7:06

>> Um,

7:08

here's like a very big one. I think like

7:11

it's pretty fair to say since the last

7:13

time you and I saw each other on this

7:14

show,

7:16

the attitude towards technology, I

7:20

think, has been pretty profoundly

7:22

negative. It's kind of tilted. It's

7:24

relatively like anti-AI,

7:27

you know, anti-billionaires. It's anti-

7:29

all of this stuff.

7:31

Um, and it manifests in all of these

7:36

interesting ways. There's protests,

7:37

there's data centers, there's all of

7:39

this stuff that's happening. Um, people

7:42

are worried about job loss. All of that

7:44

stuff is real.

7:45

>> Do you want a cigar?

7:46

>> No, I'm okay. I'm okay. Um,

7:49

but what should they really be focused

7:50

upon? And I think what they should be

7:53

really focused upon is we're at the tail

7:56

end of a cycle that doesn't work

7:57

anymore, which is all about like this

8:00

tension between labor, people that do

8:02

the work, and capital, the people that

8:03

fund it and then make all the returns.

8:06

And over the last 40 years, we've

8:07

basically gone to this completely upside

8:09

down world where capital extracts all of

8:13

the upside

8:14

and labor has extracted less and less

8:17

and less and less. And all of this push

8:19

back, it manifests in AI, it manifests

8:22

in politics, it manifests in social

8:24

issues, it manifests in, you know,

8:26

Israel, whatever you want to talk about.

8:28

All of these issues, I think

8:29

symptomologically,

8:31

come from this other issue, which is we

8:33

are out of balance. This total compact

8:36

that we used to have, a liberal

8:38

democracy and a free market has totally

8:40

collapsed. And there are simple ways to

8:42

fix that, but that never gets the

8:44

attention because it's not what you want

8:46

to talk about. the attention is here,

8:48

you know, vote no to the data center.

8:51

You know, uh this model is going to take

8:53

out all the jobs. Um

8:56

you know, this social issue is really

8:58

important. That war should not be

9:00

fought. That war should be fought. All

9:02

of these things while important

9:06

distract us from what the core issue is.

9:08

And the core issue is that we as a

9:10

society, I think, are out of balance.

9:12

the the natural compact between all of

9:15

us is broken and there are some simple

9:18

ways to fix that compact. Get people

9:20

more invested, get people more engaged

9:22

in the upside, have people have a

9:24

positive some view of what's happening

9:26

and that isn't happening.

9:27

>> Well, what what simple solutions are

9:29

there to to this one very particular

9:32

issue?

9:33

>> Okay, I'll get your reaction to this.

9:35

Let's assume that you still lived in

9:37

California because I think it it tells

9:38

this example in a more extreme way.

9:40

>> Okay. Um, let's say you make a million

9:43

bucks a year, which is a lot of money,

9:44

but it it makes the it makes the point

9:47

more cleanly. Um,

9:50

you'd pay, I think, 30%

9:54

federal tax and you'd pay another 15 or

9:58

16% in state tax and Medicare tax and

10:01

all this tax. So, if you're a wage

10:03

earner,

10:05

50% of all your upside

10:09

goes to the government.

10:11

If you're a capital earnner and you make

10:14

that same million dollars via capital

10:17

gains, you pay half that tax.

10:21

Why did that happen? That happened

10:23

because in the 40s and 50s, but really

10:25

in the 60s and 70s and 80s,

10:28

what we were trying to do or what the

10:30

American government and what western

10:32

societies were trying to do was to

10:35

convince people to invest their money.

10:38

Hey Joe, go build that factory. Go hire

10:41

those people and we're going to

10:42

incentivize you to do so.

10:45

And by doing that, there was this idea

10:48

that that all of those profits that you

10:50

would get would then diffuse, right,

10:51

trickle down into everybody else. The

10:54

workers participated, everybody

10:55

participated.

10:57

But technology allows you to do more

10:59

with less and less. So now what happens

11:02

is the capital owners can acrue

11:06

infinite almost it seems like value and

11:10

the workers get less and less. But now

11:11

if you get less and less and you're

11:12

taxed more and more as a percentage of

11:14

what you own, you're going to feel

11:16

really out of sorts. You're going to be

11:17

like, why am I paying 50 cents of every

11:19

dollar? And I see these other ways where

11:21

folks are paying 25 cents on their

11:23

dollars, but their dollars are

11:24

compounding way faster and they have,

11:27

you know, hundreds of billions more of

11:29

those dollars than I have of my dollars.

11:31

If you take that example and you expand

11:33

it across society, I think people

11:35

understand that now. There's enough

11:37

information and there's enough people

11:38

talking about it where it's pretty clear

11:40

that that's happened. So the question is

11:42

how do you fix it? I think like if you

11:44

think about AI and if you believe that

11:46

we're going to get into this world of

11:47

abundance

11:50

and we're not working, what does it mean

11:52

for governments to tax our labor? There

11:54

is no labor. You're not working anymore.

11:56

I'm not working. We're doing things out

11:58

of leisure.

11:59

Why should I pay 50 cents of every

12:01

dollar? Why aren't the companies that

12:02

are going to be making trillions of

12:03

dollars, why don't they pay more?

12:06

Why isn't there, you know, an

12:08

expectation that they then help our

12:11

lived society

12:13

do better and thrive as a result of all

12:16

of that winning? That's the real

12:18

conversation that I think is

12:21

bubbling.

12:23

And I think that we're probably another

12:25

12 to 18 months where all of these other

12:28

issues are going to be important, but

12:30

they're going to be viewed for for what

12:32

they are. um they're going to get

12:34

demoted I think in importance and it's

12:36

this core structural issue it's what is

12:39

the economic relationship that we have

12:41

together as a society what is the

12:43

relationship between Joe Chamath Jamie

12:46

and all these companies and how do we

12:50

feel about a few and an evershrinking

12:52

few making more and more and more

12:57

and then how do we feel about their

13:00

ability to share that with a small

13:03

amount of people

13:05

and then what do what is the expectation

13:07

for everybody else? I think that's

13:09

mostly at the core of what's happening.

13:12

And so back to like, you know, all of

13:15

this attention that we give to these

13:16

other issues distracts from that one

13:18

because I think you can get organized to

13:20

fix this issue. You can't get

13:21

concessions on any of these issues.

13:23

>> Mhm.

13:23

>> You know, you bring up Israel, it's like

13:25

this. You bring up social issues, it's

13:26

like this. You bring up, you know,

13:28

whatever you want to bring up, people

13:30

just kind of take a side, nothing

13:32

happens. This is actually where people

13:34

are universally actually much more

13:36

aligned than you think because there's

13:38

reasonable ways. One simple way was is

13:40

you'd say, well, let's flip the taxation

13:41

model.

13:43

Corporate taxes

13:46

should exceed personal taxes. They've

13:49

never

13:52

we should have an expectation that then

13:55

corporate

13:57

actors can buy down their taxes if they

13:59

want, but if they do social good for

14:01

society. I'll give you an example. At

14:03

the industrial revolution, there's a

14:05

table like this and the leading lights

14:08

of that era, Andrew Carnegie, Nelson

14:10

Rockefeller, Jay Gould, JP Morgan,

14:15

they sat together and they said, "Guys,

14:17

this is going to benefit us this

14:19

industrial revolution.

14:21

It may not benefit everybody. What is

14:23

our responsibility? What is our

14:25

collective responsibility?"

14:27

And they allocated tasks. Carnegie went

14:30

and built libraries

14:32

all throughout the country. Rockefeller

14:34

built universities, hospitals were

14:36

built. And I think what happened is

14:39

society was like, "Wow, these are living

14:40

testaments to us doing well." And so

14:44

then they were okay with this

14:45

transition.

14:47

But if you think about it today, what

14:48

are the living tributes that, you know,

14:52

capital builds and leaves behind for

14:54

society? It's fewer and fewer.

14:57

I think that's a that's a very big

14:59

opportunity for somebody to fill it. I

15:01

think it's like especially for folks in

15:04

tech. I think if they can get themselves

15:06

organized to do that, I think we we land

15:08

in a good place. If they cannot get

15:10

themselves organized to do that and say

15:12

everyone for themselves,

15:16

I think it's going to be really

15:17

complicated. Super messy. super messy

15:20

because

15:21

>> super messy

15:22

>> that sentiment that the wealthy are

15:25

getting wealthier and the middle class

15:26

is disappearing and the poor are being

15:29

taxed into oblivion.

15:31

>> Look, an $80,000 year teacher pays 40%

15:34

tax. But if you're a multi-billionaire,

15:38

most of your wealth is not W2 wages.

15:42

It's cap gains. But there's all kinds of

15:44

ways to shelter cap gains. There's all

15:46

kinds of ways to defer. And so even

15:48

though you pay more on an absolute

15:52

dollar basis, on a percentage basis,

15:53

you're paying way way less. And all of

15:56

those tricks have been exposed.

15:59

They've all been exposed. These are all

16:01

mechanisms that were that were, you

16:03

know, invented from the 1980s to now,

16:06

right? By all the by all the banks and

16:08

all the folks that wanted to come to

16:10

folks that had wealth. And so it's it's

16:12

and it's all known. And I think people

16:14

are kind of like, "Hey, hold on a

16:16

second. This just doesn't feel fair

16:18

anymore.

16:19

>> Absolutely. But the other problem with

16:23

that is if you do tax correctly, where

16:27

does that money go? And who's managing

16:30

it? And ultimately, who's managing it is

16:33

the federal government. And they've been

16:36

shown to be completely inept at managing

16:39

your money correctly. The fraud and the

16:41

waste is off the charts. the amount of

16:44

NOS's that have insane amount of funds

16:47

at their disposal. I mean all this is

16:49

exposed by Doge, right? And you realize

16:51

like how much fraud and waste there is

16:53

and how much money. So the solution

16:56

being tax people more

16:59

>> that doesn't sit with a lot of people

17:00

because it's like well where where is it

17:03

going and who's managing it? If if the

17:06

federal government was being forced to

17:09

handle money the same way a private

17:11

company does, if it was all out in the

17:14

open, everything was exposed, they would

17:17

have gone bankrupt a long time ago. They

17:19

would have gone under a long time ago.

17:21

There's no way they would have been

17:23

allowed to function the way they are.

17:25

The people that are managing that money

17:27

would have all been put in jail. There's

17:29

not a chance in hell that

17:32

giving them more money is going to solve

17:34

anything. They're going to find more

17:36

ways to put more of that money into

17:39

NOS's that puts more of that money into

17:41

Democratic coffers and Republican

17:42

coffers. They're going to figure out a

17:44

way to funnel that money around where

17:46

it's not going to benefit people. I

17:48

mean, a good example of that is like

17:50

where let's let's look at the LA fire

17:53

thing for instance. All right. So the LA

17:56

fire fund, there's a giant fire in the

17:58

Palisades. All this money gets raised.

18:02

It's over $800 million. It goes to 200

18:05

plus different nonprofits. None of it

18:09

goes to the people,

18:10

>> right?

18:10

>> Spencer Pratt, who's running for mayor

18:12

of Los Angeles.

18:13

>> He's doing a great job, by the way.

18:14

>> [ __ ] phenomenal.

18:16

>> Those ads are those ads are fire.

18:19

>> They're so good.

18:20

>> They're fire. I He's doing and he's

18:22

doing it all out of a trailer. Yeah.

18:23

>> On his burnt out land. I mean, he's the

18:25

most righteous guy running in that

18:27

regard.

18:28

>> But just that being exposed like, okay,

18:32

we're going to help out these people.

18:34

We're going to donate money. We're going

18:35

to raise money. We're going to do some

18:37

good. We feel terrible about the people

18:39

in our community that have lost homes.

18:41

Well, what happens? Well, the same

18:43

people that you're saying we should give

18:44

more taxes to take that money and they

18:48

just give it to a bunch of nonprofits

18:50

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19:30

>> I'm not saying give more tax. What I'm

19:31

saying is,

19:32

>> right,

19:33

>> people are taxed too much. Yes,

19:34

>> corporates are not taxed enough. Flip

19:36

it. That's

19:37

>> right. But even if you do flip it and

19:39

the corporates are taxed more, where's

19:42

that money going? This is the problem.

19:44

>> I suspect that if you put the burden on

19:46

Wall Street and corporates,

19:49

um, they'd be a lot more organized and

19:52

they'd probably create a lot more change

19:53

than a diffuse electorate. Meaning like

19:57

let's just say the government spends a

19:58

trillion dollars and wastes it. I'm

20:01

generally like roughly aligned with

20:02

that.

20:04

If you waste a trillion dollars from 300

20:07

million people, it's hard to organize at

20:10

300 million people. But if you waste a

20:12

trillion dollars from 300 companies,

20:15

those companies will get their [ __ ]

20:16

together really fast. And they will

20:18

force a lot more change.

20:19

>> I would hope so, but you're still

20:20

dealing with incompetent people that are

20:22

tasked with taking care of that money.

20:25

Not just incompetent, but

20:26

>> don't get me wrong, I'm not defending

20:27

these people.

20:28

>> Decades of corruption. decades and

20:31

decades of all these mechanisms where

20:34

they can take this money and funnel it

20:36

into these NOS and these nonprofits and

20:40

all these different weird organizations

20:43

that don't seem to have accountability

20:45

for what they do with that money, that

20:47

gets real slippery.

20:48

>> Yeah. And if those people in turn make

20:52

deals with those corporations that allow

20:54

them to do certain things and push

20:56

things through that maybe they would

20:58

have difficulty doing, then you have a

21:00

different kind of a working relationship

21:01

with the same groups of people and the

21:04

same government. You just take money

21:07

from corporations and move it into a way

21:09

where the corporations ultimately

21:11

benefit from it, but yet it doesn't do

21:13

any good to the people.

21:14

>> Yeah. I mean, I can see where you're

21:15

coming from. I just think that if we go

21:17

on the track we're going down,

21:21

>> it just seems like we're we're going to

21:23

hit a crisis.

21:24

>> Yes,

21:25

>> the crisis is you can't expect people to

21:27

pay more and more and more. Again, I

21:29

agree with you. The premise is we're all

21:31

paying for a system that's broken.

21:33

>> That should that should change. But we

21:36

still continue to have to pay our taxes.

21:37

But if taxes keep going up like this at

21:39

the individual level

21:42

and we don't manage this transition to

21:44

something where we may be working less

21:46

and less, what are we getting paid to

21:47

do? And then at that point, how are we

21:49

expected to pay what? 90% of what?

21:51

>> Right?

21:52

>> 50% of what? I think people do have this

21:55

weird feeling of

21:59

dread that the people that are in

22:02

control of a lot in this country, the

22:06

the tech companies in particular,

22:07

particularly the tech companies like

22:09

Google and Facebook that are essentially

22:11

involved in data collection and then

22:14

ultimately dissemination of information

22:16

that they have acquired enormous amounts

22:19

of wealth and power and influence and

22:21

they're essentially a new form of the

22:24

government.

22:25

>> Yeah.

22:26

>> You know, are you aware of Robert

22:27

Epstein? Do you know about his work?

22:30

>> Not Robert Epste.

22:31

>> No, different guy. Different guy. Um,

22:33

Robert Epstein is a guy who specializes

22:36

in uh understanding what curated search

22:40

results do and what what Google's able

22:44

to do with in particular with curated

22:47

search results in terms of influencing

22:49

elections

22:51

>> that like say if you you have two

22:53

candidates that are running. Let's just

22:54

say let's just take LA for instance. If

22:57

and I'm not making any accusations, but

22:59

I'm saying if they wanted Karen Bass to

23:02

win and you searched Karen Bass, you

23:05

would find all these positive results.

23:07

If you searched Spencer Pratt, you would

23:10

find all these negative results. And

23:12

there's a bunch of people that are

23:14

always undecided voters and those are

23:17

the ones that you really want. They're

23:18

like, I don't know. I don't know. And

23:20

come election night, those are the

23:21

people you want to try to grab and it's

23:22

it's generally a large percentage. You

23:25

can influence an enormous percentage of

23:27

those people just with search results.

23:29

>> Yeah.

23:29

>> Where you can shift an election one way

23:31

or another.

23:32

>> I believe it.

23:32

>> Yeah. And he's demonstrated this and

23:35

shown how this is possible. Um that

23:38

freaks people out that tech companies

23:41

are in control of narratives that tech

23:44

companies can censor information

23:47

especially tech companies that work in

23:48

conjunction with the government.

23:50

>> Right?

23:50

>> This is what we found out when Elon

23:52

purchased Twitter. Right? Right. When

23:54

Elon purchased Twitter, we got all this

23:56

information from the Twitter files when

23:58

all the journalists were allowed to go

23:59

through it and they said, "Oh, this is

24:01

crazy. You've got the FBI, the CIA,

24:04

you've got all these companies, all

24:05

these government organizations that are

24:08

essentially

24:10

controlling the narrative of free speech

24:12

in the country. And they're doing it in

24:14

a way that benefits them. They're doing

24:16

it in a way that benefits what political

24:17

parties in charge at the time was the

24:19

Biden administration. and they were

24:22

allowed to do a bunch of weird [ __ ]

24:24

which which should be illegal but it's

24:26

not technically illegal.

24:28

>> And that freaks people out because

24:29

there's no real laws and rules in regard

24:32

to what they're allowed to do and what

24:34

they're not allowed to do. Like curated

24:36

search results should be illegal.

24:38

>> They're shaping attention.

24:39

>> Yes. Attention. Again, it goes back to

24:41

attention, right?

24:42

>> They're shaping attention.

24:43

>> Yeah. Um it's that's a big concern for

24:47

people. And I think then when you find

24:49

out that these people are able to amass

24:52

enormous sums of wealth and have

24:53

incredible amount of power and influence

24:55

because of this enormous enormous wealth

24:58

and this control over these tech

25:01

companies that have essentially become

25:03

the town square of the world.

25:05

>> Yeah.

25:06

>> That freaks people out and that these

25:08

very small number of people, you know,

25:10

you think of Zuckerberg, you think of

25:12

Tim Cook and I don't I don't know who

25:14

the new guy is now. Who's the name? John

25:16

John Fern,

25:17

>> right?

25:17

>> Furnace. No,

25:18

>> I forget his name.

25:19

>> Yeah.

25:19

>> Turn.

25:20

>> Turn. Turn.

25:21

>> But but that kind of thing

25:25

gives people a lot of concern, right?

25:28

It's like that these people, these

25:29

unelected people are in control of a a

25:33

giant chunk of

25:35

how the world works.

25:38

>> I think that this is the existential

25:40

question that we are dealing with.

25:42

you're going to have five or six

25:44

companies

25:46

concentrate like whatever power you

25:49

think has been concentrated up until

25:51

now. I think we're going to look back

25:53

and it's going to look like a Sunday

25:55

picnic 10 or 15 years from now because

25:58

on the one hand it's going to be an even

26:00

smaller subset and on the other hand the

26:02

capability is going to be an order or

26:04

two orders of magnitude. So can you

26:06

imagine what that must be like? It's

26:07

kind of like showing up, getting dropped

26:09

into the 1800s, and you've invented the

26:12

engine and everybody else's horse and

26:13

buggy.

26:14

>> You can just decide to your point. That

26:18

is where we're going.

26:20

>> It's even more crazy. It's like

26:22

everybody else is on a horse and buggy

26:24

and you've got an internet connection

26:25

with a cell phone.

26:27

>> Exactly. Exactly.

26:28

>> It's even more crazy.

26:29

>> Exactly. because it's what we're dealing

26:32

with with AI right now is first of all

26:35

it's already lowered children's

26:37

attention spans and it's shrinking their

26:40

capacity to acquire or absorb

26:43

information because what they're doing

26:45

now is just relying on AI to answer all

26:48

their questions for them. Now, is that

26:50

their fault? Kind of, right? Because it

26:52

doesn't have to be that way. You could

26:53

still acquire information the

26:55

oldfashioned way. You can still learn

26:57

things the right way. But a lot of kids

26:58

are just concerned with passing

27:00

examinations and getting into good

27:01

schools. And what they're doing is just

27:03

using AI and they're they're getting

27:05

better test results, but they're also

27:07

not as smart.

27:08

>> Yeah.

27:09

>> Which is really weird. Yeah.

27:10

>> It's like we're relying on it like we

27:14

you know it's like it's essentially like

27:19

replacing our mind. And that's just the

27:23

this is the beginning. This is like

27:26

these are the toddler days

27:28

>> of AI and where it's going to be a super

27:31

athlete in a few years.

27:33

>> Yeah. I think we have to figure out how

27:36

first of all

27:38

kids need to learn and I think this is

27:40

where like we have to do a better job as

27:42

parents. Kids need to learn how to be

27:43

resilient thinkers. I don't even know

27:45

what that term meant before, but I know

27:46

what it means now, which is like you

27:48

take this AI slop and you just kind of

27:50

like pass it off. And if like the

27:52

teachers and the school system aren't

27:54

trained, they're just like, "Wow, this

27:56

looks good." They have to be able to

27:58

push back. Parents need to be able to

28:00

look at this [ __ ] But then all of this

28:02

stuff, I'm just like so frustrated

28:03

because it's like one more thing that I

28:04

have to do as a parent. Like,

28:06

>> right?

28:06

>> Every time technology gets better, it's

28:08

one more thing, you know,

28:09

>> right?

28:10

>> We're going to make the world, you know,

28:11

super connected and social and all that

28:13

stuff. It sounds great to me until I

28:15

have to be the one that has to tell my

28:16

kid I can't they can't get Instagram

28:18

>> and then they're up my ass every day,

28:20

right? you know, and it's just like I

28:22

don't want to have to deal with this

28:23

stuff,

28:24

>> right?

28:24

>> I want this to be handled in a way that

28:27

just allows me to do what I want to do.

28:29

I don't want to say no to my kid. I

28:31

don't want to police his schoolwork and

28:32

make sure he's not cheating or not

28:35

learning and just like, you know,

28:36

passing off this AI slop. What am I

28:40

where are my tax dollars going? Where is

28:43

everybody else in all of this? It gets

28:45

very frustrating. And again, it goes

28:47

back to like this feeling of like, well,

28:49

is this all getting better for me or is

28:51

this kind of like not, you know, people

28:53

start to be nostalgic

28:55

>> for what it used to be because it was

28:56

just simpler, but I think that's a

28:59

different way of saying easier.

29:00

>> Well, we're just dealing with we're at

29:03

the edge of great change. Like great

29:06

change that has no real understanding of

29:09

how it turns out.

29:10

>> Yeah.

29:11

>> And I think that understandably freaks

29:14

people out. Freaks me out. It freaks me

29:16

out, but I've kind of gotten to this

29:18

place where I'm like, well, it's going

29:19

to happen.

29:20

>> Did you see this thing? Um, it's a CEO

29:22

of Verizon, Dan Schulman. He put out

29:24

this very public forecast, you know,

29:28

very smart guy, well regarded in

29:30

business. And I think he said something

29:32

like 30%

29:34

of all white collar jobs will be gone by

29:36

2030. I don't know, Jamie, maybe you can

29:38

get the exact thing, but it's something

29:39

like that.

29:39

>> That's probably optimistic. And I

29:41

thought at first my initial reaction was

29:43

like this is totally not credible. But

29:46

then I'm like hold on a second that's my

29:47

bias because I want to believe that

29:48

that's not possible

29:50

>> honestly you know and as I've gotten

29:52

older I'm I'm a little bit better now

29:54

like okay hold on a second let's weigh

29:55

the probabilities. And now I was like

29:57

man if I'm going to be fair maybe

30:00

there's a 10 20% chance of that. There's

30:04

a bunch of other outcomes that are much

30:06

better than that but that's part of the

30:08

set of outcomes that you have to

30:09

consider.

30:11

And then I was like, well, what's my

30:13

antidote to that? My and and the only

30:15

thing that I can say is don't worry,

30:16

it's going to be better.

30:19

I don't think that that's a good answer.

30:20

>> No.

30:21

>> So, there has to be like all of this

30:23

kind of goes back to look, my wife and I

30:27

have this conversation. We're like, if

30:29

it were up to us, who's who can you

30:32

trust to have some super intelligence?

30:35

Now, we're biased because we're friends

30:37

with him, but the only person that we

30:38

can trust is Elon because he seems to be

30:41

like he has a bigger like it's kind of

30:43

like he's like over there. He's like, I

30:45

need to get to Mars, right?

30:46

>> You know, and I'm going to first

30:47

terraform the moon, but then I'm going

30:49

to Mars and I'm going to build like a

30:51

[ __ ] magnetic catapult and I got to

30:53

do all this [ __ ] and so I just need this

30:56

thing. I feel like he's the least

30:58

corruptible.

31:01

He's the most independent thinking

31:03

>> and I think he's the one that has a

31:05

natural empathy for people. Then there

31:07

are folks where there's just a in insane

31:10

profit motive,

31:11

>> right?

31:11

>> They're less in control of the

31:13

businesses that they run. Those

31:15

businesses are really out over their ski

31:17

tips and the amount of money they've

31:18

gotten from Wall Street and other folks

31:21

who expect a return who will put a ton

31:22

of pressure on these folks. And if they

31:25

get there first, I don't know where the

31:27

chips fall. We don't really know. We can

31:29

kind of guess. And then you see in the

31:31

press

31:33

just enough snippets of their reactions

31:35

in certain moments where you're like,

31:36

"Hey, hold on a second. Question mark

31:38

here." You know, you see OpenAI react

31:40

one way, you see Anthropic react another

31:42

way, and you're like, "Where is this

31:44

going to end up?" And the honest answer

31:46

is nobody really knows.

31:48

So, it comes back to like we need a few

31:51

people that can organize. Those guys

31:53

need to self-organize and actually

31:55

present a really positive face. And they

31:57

need to show

31:59

why those 20% of outcomes that Dan

32:02

Schulman paints,

32:05

the truth is it's possible, but here's

32:07

why it's pro not probable,

32:09

>> but it's not in their best interest to

32:11

do that because it's in their best

32:12

interest to generate the most amount of

32:14

money possible. That's the obligation

32:15

they have to their shareholders. That's

32:17

the obligation to they have the people

32:18

that have invested money in this

32:20

company. They their obligation is not to

32:23

make sure the white collar jobs stay in

32:25

the same place that there are now.

32:27

>> That's not that's not true.

32:28

>> No.

32:28

>> No. I I actually think their incentive

32:31

should very clearly be to tell people

32:34

with details and facts why there's a

32:37

positive future. And the reason is the

32:39

following. Right now there's a vacuum.

32:41

There are no facts. And there's

32:43

fear-mongering. And then there's this

32:45

belief that this is going to be

32:46

cataclysmic to human productivity and

32:49

white color labor and all of this stuff.

32:51

>> What's people's natural reaction? Well,

32:53

today if you look at it,

32:55

>> think about AI as a very simple

32:57

equation. Energy in, intelligence out.

33:01

>> So if you want to cut the head of the

33:02

snake, what do you do? You cut off the

33:03

energy supply.

33:05

>> Right?

33:05

>> Okay.

33:06

>> If you're afraid

33:07

>> of all of this super intelligence

33:09

coming,

33:09

>> the natural thing to do would be to go

33:11

to the point of energy and unplug it.

33:13

What is the equivalent of unplugging it

33:15

today? It is to go all around the

33:16

country, find the data centers, protest

33:20

them, and get them to be mothballled.

33:23

That is an incredibly successful

33:25

strategy right now.

33:27

Today, about 40%

33:31

of all of these data centers

33:34

that get protested get mothballled.

33:38

>> You're talking about emerging data

33:40

centers.

33:40

>> Yeah. just like

33:41

>> I need to. So if you're one of these

33:43

companies, the first thing you should

33:44

realize is I need to paint a positive

33:46

vision because 40% of my energy is

33:50

getting unplugged every day.

33:53

And if that happens, my revenues will

33:55

crater and my investors will be super

33:56

pissed. So the right strategy is what is

33:59

the positive fact-based argument? And

34:02

there are some incredible examples

34:06

number one. And then number two is you

34:08

have to give people some tactical

34:10

benefit that they see because AI

34:14

differently than

34:16

search or differently than social media

34:18

there's no exchange of value. Let me let

34:21

me explain what that means. So let me

34:23

just go like so the first thing is that

34:27

if you can go and actually show people

34:31

here's an example of AI. I I I heard

34:34

about this last night. It's pretty

34:35

incredible.

34:36

You can now take pictures of a woman's

34:38

fallopian tubes and you can see

34:42

precancer

34:45

ovarian cysts and all of this stuff

34:46

cervical cancer before it forms and then

34:50

you can intervene and you can fix it so

34:53

that you know women don't get cervical

34:54

cancer. In a different example I

34:57

actually I told you about this example

34:58

when I was here before I finally got FDA

35:01

approval. Okay, there is a device now

35:03

that is allowed to be in the operating

35:05

room with you. And if you have a

35:08

cancerous lesion or a tumor inside of

35:11

your body, the most important thing when

35:12

they go to take it out is make sure you

35:15

don't leave any cancer behind. You

35:17

couldn't do it because what would happen

35:19

is you take it out. A doctor is Joe is

35:22

literally [ __ ] eyeballing it and

35:24

saying, "Yeah, they send it to a

35:26

pathologist. You get an answer in 10

35:28

days." for women with breast cancer. A

35:31

third of these women find out that they

35:33

have cancer left behind. They go back

35:35

in, they scoop some more stuff out. A

35:37

third of those women. Okay. So, I'm

35:40

like, "This is [ __ ] We can solve

35:41

this problem." It took us a long time, a

35:45

lot of money. I had to build an entire

35:47

machine imaging, all of this stuff, AI

35:50

algorithms. We had to prove it all. We

35:52

finally get approval. Okay. But you know

35:55

how hard it is to tell that story in all

35:57

of the attention that people are looking

35:59

for. It's hard. But those are positive

36:02

examples. No more breast cancer,

36:06

no more cervical cancer. A different

36:08

example is most drugs in pharma fail,

36:12

right?

36:13

And it's a very complicated problem in

36:16

pharma. It's kind of like a jigsaw

36:17

puzzle of the ultimate complexity. It's

36:19

like think of your human body as like a

36:22

Himalayan mountain range. You have to

36:25

design a drug that's an equivalent

36:26

Himalayan mountain range that plugs into

36:28

it perfectly. One millimeter off,

36:32

you grow like a fourth eye, a third

36:34

nipple, you die. You know, now you can

36:37

use computers to make sure that that

36:40

drug handin glove to your body solves

36:43

the exact problem. Couldn't do that

36:45

before. So, there's all of these body of

36:47

examples and you're probably only

36:51

hearing them superficially at best.

36:54

That should be 99% of the attention is

36:57

showing all of the constructive tactical

37:00

ways in which our lives will be better.

37:02

Your mom, your daughter, your wife, us,

37:06

Jamie, his family, everybody,

37:08

>> right?

37:08

>> That's the number one thing. Nobody

37:10

talks about it. I don't understand why.

37:12

>> Well, I think because people are

37:14

terrified of losing their jobs. So,

37:15

that's the primary concern. The primary

37:17

concern that I hear from people is that

37:19

there's so many people that are going to

37:21

school right now, college students, that

37:22

don't know if their job is going to even

37:25

exist in four years when they graduate.

37:27

>> And that's the second part of I think

37:29

what this industry has to do better.

37:32

There's a I had uh lunch with Jeffrey

37:34

Katzenberg. He told this crazy story.

37:36

I'll I'll tell you. It's like Steve Jobs

37:39

gets kicked out of Apple.

37:41

um he buys he starts next

37:45

and he buys Pixar from George Lucas, but

37:48

then he hits a rough patch and he's got

37:49

this, you know, financing issue. Kerberg

37:52

flies up,

37:54

spends time with Steve Jobs, says, "I'll

37:56

buy Pixar." Jobs says, "Absolutely not."

38:00

And then Katherenberg proposes a deal

38:02

and he's like, "Uh, how about a

38:03

three-picture deal?" Jobs says, "Okay."

38:06

He flies back and apparently all the

38:08

animators were up in arms because

38:11

they're like, "Hold on a second. Steve

38:13

Jobs is going to use these next

38:14

computers to animate this movie." Which

38:17

ultimately became, I think, Toy Story.

38:19

And they're like, "This is going to put

38:20

all of us out of a job." That perfect

38:23

argument. And people were really upset.

38:27

Roy Disney was upset. All the animators

38:29

were upset. And they all went to Mike

38:31

Eisner and they were like, "Michael, you

38:33

need to fire Katzenberg."

38:36

And they had a deal which was like,

38:38

"Look, man, you do you, but just give me

38:41

the ability to say no if I think that

38:43

this is you're about to jump off a

38:44

cliff." They talk about it and he's

38:46

like, "I got your back. Do the deal.

38:48

Make the movie." They made the movie. It

38:50

was a huge success. Fast forward 10

38:52

years, 15 years, there's 10x the number

38:54

of animators.

38:56

Now, it's a small example, but why is

38:58

that? You were able to use computers and

39:00

now all these new people were able to

39:02

come and participate in that. I get it.

39:04

It's a small example,

39:06

but I think if we had better organized

39:09

leadership and we could try to tell some

39:11

of these examples, try to go back and

39:13

document how some of these things have

39:16

actually helped people, it expanded the

39:18

pie, there's a chance. But if we don't,

39:21

I agree with you where we're going to

39:23

end up is everybody basically saying,

39:24

"Hey, hold on a second. This is crazy.

39:26

We need to stop this." That's the worst

39:28

outcome because that's when you will

39:31

have the a high risk of a dislocation.

39:33

like the worst outcome like the black

39:35

what's the black swan event, right?

39:37

Let's think about the black the black

39:38

swan event is when you get a model

39:41

that's good enough to automate a bunch

39:46

of labor

39:49

but not good enough that it can build

39:52

new drugs and prevent cancer and make

39:54

you live for 200 years and all of this

39:56

other stuff. Right? So there's like a

39:57

gap, right? And if you can stop it here

40:00

and it doesn't get to there, now you do

40:02

have the worst of all worlds. You have

40:04

this thing that kind of displaces labor.

40:06

No new things come after it because we

40:08

stop innovating.

40:10

And that's like a that's like a

40:12

nontrivial possibility now, I think.

40:15

>> No, it's a huge possibility. And then

40:16

there's also this thing that you brought

40:18

up earlier where we have this place of

40:20

abundance where no one has to work

40:22

anymore. That freaks people out.

40:24

>> I think that's a big problem. Well,

40:26

because if no one has to work anymore,

40:29

first of all, what what is your

40:31

identity, right? Because so many people

40:33

their identity is what they do. Whatever

40:35

it is, if you're a lawyer, if you're an

40:37

accountant, if you run a business,

40:39

whatever it is, this is your identity.

40:41

You know, you have built this thing, you

40:44

look forward to going there, you work at

40:46

it, you look forward to doing a good job

40:48

and getting rewarded for it. The harder

40:50

you work, the more you get paid. There's

40:53

all these incentives built in. And then

40:55

there's this again identity problem. If

40:58

all of a sudden you have universal high

41:01

income, which is what Elon always talks

41:03

about. Well, what gives people purpose

41:05

then? Like what? And also if you have a

41:08

person whose entire they're, you know,

41:10

43 years old in their entire life,

41:12

they've worked towards this idea that

41:14

the harder they work, the harder they

41:16

think, the more innovative they are, and

41:18

the the better they are at implementing

41:20

these ideas, the more they get rewarded.

41:22

And then all a sudden, that's not

41:24

necessary anymore, Mike. Time for you to

41:27

just relax and do what you want to do.

41:29

And Mike's like, "Well, this is what I

41:31

do. I this I I don't have any [ __ ]

41:33

hobbies. I I enjoy doing what I do. And

41:36

now what I do is completely useless and

41:39

now I'm on a fixed income." Even if that

41:41

fixed income is a million dollars a

41:43

year, whatever it is.

41:44

>> If all of a sudden you are in this

41:47

position where everything is being run

41:49

by computers, you feel useless. You feel

41:51

like what am I doing? I'm just I'm just

41:53

taking money. I'm on high welfare,

41:56

>> right?

41:57

>> Like what do I do?

41:58

>> Right? I think that that's a really

41:59

important question to answer. I don't

42:01

know. Like

42:01

>> some people are going to write books.

42:03

Some people are going to do art. Some

42:05

people are going to find things to do.

42:06

But

42:06

>> what do you think what do you think we

42:08

would have done if if we were

42:12

go back to the 1800s example. There was

42:15

no office culture.

42:17

You know, there's no like ladder to

42:20

climb. How did people find meaning then?

42:24

>> Well, they had jobs. People still did

42:27

things. If you're a farmer, you you had

42:29

meaning in your labor and what you did

42:32

and keeping the animals alive and your

42:33

chores. And there's people that find

42:35

great satisfaction in doing that.

42:37

>> Yeah.

42:37

>> You know, you have all these animals

42:38

that rely on you. You have people that

42:40

rely on you for the food that you

42:41

generate. There's there's meaning there.

42:43

It doesn't have to be an office to be

42:45

something that gives you purpose and

42:46

meaning. But when all that is animated,

42:49

then what happens? Because then you have

42:52

no purpose, no meaning other than

42:54

recreational activities. Now, if

42:56

everybody just starts playing chess and

42:58

doing a bunch of things that they really

42:59

enjoy, I mean, look, there's people that

43:01

would love to just play chess. Yeah.

43:04

>> You know, it's like eight people.

43:06

>> I don't know about that. I think if

43:07

people really got into it, I mean,

43:09

there's a lot of people that get

43:11

addicted to whatever their recreation

43:12

is, like golf or whatever it is. For me,

43:14

it's playing pool. You know, if you told

43:16

me I never have to make any more money,

43:18

I could just play pool all day. I might

43:20

just play pool all day. But I don't know

43:23

how many people think that way. I don't

43:25

know how many people would be able to

43:27

find meaning and purpose in a

43:29

recreational activity. There's so many

43:31

people where their entire being is

43:34

focused around productivity and

43:36

generating more wealth.

43:37

>> What about religion as a source of

43:39

meaning? Well, that that would help that

43:42

that

43:43

>> Did you see this article in the New York

43:44

Times, I think it was this weekend,

43:45

about how popular and sold out churches

43:48

have become as social constructs in New

43:50

York City.

43:51

>> It was totally fascinating. It's like

43:54

young women like dressed to the nines

43:56

going to church on a Sunday

43:59

>> for social belonging, community meaning.

44:03

I thought I was like so fascinated by

44:05

it. I was like, "Wow, that's that's

44:06

incredible." cuz like I I if I think if

44:09

you graph like just like people's use of

44:11

religion as an anchoring part of their

44:13

value system

44:14

>> over the last 40 years basically gone to

44:16

zero. You know, nobody nobody celebrates

44:18

it the way it's not a part of the

44:20

community the way that it used to be.

44:22

Maybe that's a thing that we have to

44:23

find. There has to be a renewal of some

44:25

older things and then there has to be

44:27

new things that replace it. Um what's

44:30

the Chinese answer to this? You know,

44:32

the Chinese have a very orthogonal

44:33

answer to this. If you look at how China

44:35

China is organized, it's super

44:37

interesting because they don't reward

44:40

based on the way the American system

44:41

rewards. In fact, it's like almost

44:43

orthogonal where we it's we are rewarded

44:47

with money and rewarded with sort of

44:49

fame and recognition

44:52

the system, the American capitalist

44:53

system. But if you look inside of China,

44:56

it's constantly testing who has this

44:58

judgment. And what they are rewarded

45:00

with is influence and power in a very

45:03

again it's a very specific social

45:04

contract doesn't doesn't I don't think

45:06

it's going to work in the United States

45:07

nor am I an advocate of it but it works

45:08

for them. You'll start off as like some

45:13

you know lowg person in like some small

45:16

village town somewhere and your job as

45:17

like the you know the functionary is to

45:20

do good in that community and the more

45:23

you do well you get promoted then you

45:24

get let's say to like a reasonable size

45:26

city and you get a budget and now what

45:28

happens is you actually become a little

45:30

bit like a VC like a venture capitalist

45:32

you're given a budget and you'll get a

45:34

memo and it'll say hey Joe uh we have a

45:37

priority over the next 15 years it's

45:39

batteries ries

45:41

and you have enough money, put a team on

45:44

the field. So, you go in your local

45:46

community, you find a bunch of guys,

45:48

you're like, "All right, guys. We're

45:49

going to start a battery company." And

45:51

you do it.

45:53

And let's say they're good and they're

45:56

like innovative. And what happens is in

45:59

the town beside it, that battery company

46:01

dies. Now, you kind of subsume the

46:04

capital from Jamie, right? All right,

46:06

cuz Jaime's like, "Fuck, I [ __ ] up

46:07

this thing that I wanted I was told to

46:09

do batteries." Okay, Joe, I'm just going

46:10

to align with you. And what you happens

46:13

over time is you get this um filtering

46:16

effect. And the people that are better

46:19

at meeting these long run priorities and

46:21

objectives are the ones that are

46:23

celebrated, but they're not celebrated

46:25

with, you know, Forbes articles and all

46:28

this other [ __ ] They're just

46:30

celebrated by given more responsibility.

46:32

And then eventually you get to the upper

46:34

echelons of China and what you have are

46:36

folks over a course of 40 or 50 years

46:38

who in their eyes have demonstrated

46:40

incredible prowess.

46:43

There's a version of that reward system

46:45

which is very foreign to America but

46:47

that's worked for China. Now that also

46:50

works because they're more confusion.

46:51

You know we're too individualist.

46:53

But my point is like you know there are

46:57

these different ways that we can find of

46:59

giving people meaning that don't have to

47:01

be always around money. Um but meanwhile

47:06

I think we have to answer the question

47:07

if we are expected to do less we

47:10

probably should not be taxed more.

47:12

That's I think that's like a very basic

47:14

in my mind I think that is like that

47:16

must be explored and figured out. And on

47:19

the other side, there's just a ton of

47:21

obvious mechanisms that corporate actors

47:24

can use to minimize that. And they

47:26

should find offramps, by the way. If

47:28

they want to build hospitals, they

47:29

shouldn't have to pay taxes. Like that's

47:31

a perfect example, by the way, of like

47:34

the thing in like if you look, if you

47:35

walk around New York City, there are

47:37

living tributes to corporate success

47:40

that people get benefit from every day.

47:43

The hospitals, the buildings, the

47:44

libraries, it's just everywhere.

47:47

We need a version of that. And and I'm

47:51

not a tax expert, but you know, if that

47:53

can be funded by private actors, so go

47:56

directly to the problem. Build a bunch

47:58

of libraries, build a bunch of new

47:59

universities that, you know, teach kids

48:02

actually how to think or whatever. Build

48:04

better hospitals that are, you know,

48:05

there to actually solve the problem.

48:07

These are all things that are possible,

48:09

>> right?

48:09

>> But none of it's happening today. Well,

48:11

let's let's go back to what we were

48:13

talking about earlier with the taxes and

48:16

the fact that you're giving money to a

48:18

broken system. Do you think it's

48:21

possible that AI could show benefit in

48:23

that they can analyze all the data,

48:27

which would be virtually impossible for

48:29

even an office filled with human beings

48:32

paying attention to all of it, and they

48:34

could analyze where all the money goes,

48:37

and eliminate all the fraud and waste,

48:39

like recognize it instantaneously. Yes,

48:42

>> that would be a great benefit and a way

48:46

to make it so that your taxes directly

48:49

benefit people.

48:50

>> I'll give you one example of this. So,

48:53

two years ago,

48:55

um, you know, like every few years I'll

48:57

I mean, I invest, but every few years

48:59

I'll start something because I feel

49:00

strongly about it. And there's an effort

49:04

that I made

49:07

to look at all of this old code. Like if

49:09

you think about the world,

49:12

the world runs on software, right? Like

49:15

even though you and I are talking, it's

49:17

piping into Jaime's computer.

49:19

It's all software. Then it goes to

49:21

Spotify, they pump in some ads, they put

49:22

it's all software, right?

49:23

>> Software runs everything.

49:27

What percentage of that do you think is

49:30

kind of poorly written? I'm going to say

49:32

probably 80 to 90% of it.

49:34

>> Really?

49:34

>> Oh, yeah. It's riddled with errors. It's

49:38

riddled with mistakes. The fact that so

49:40

many companies exist is an artifact of

49:43

the fact that the thing that came before

49:45

it isn't working.

49:47

Like if you got it right the first time,

49:49

it would just kind of move and go. So

49:51

>> how so? What do you mean by that?

49:53

>> So normally if you if you were like I

49:56

want to build a system that does A, B,

49:57

and C,

49:58

>> right?

49:59

>> If I was designing it properly, I would

50:02

sit there with you and I would

50:03

meticulously write down, all right, Joe

50:05

wants to do this. What are the

50:06

implications? Joe wants to do that. What

50:09

are the implications? And I would

50:11

actually write a document that was in

50:13

English before a single line of code has

50:16

been written. This was the when you have

50:18

to design something that can't fail. So

50:20

for example like if you and I are

50:21

designing something for the FAA or for

50:24

you know I hate to say this example

50:26

because it turned out to not exact but

50:27

like you know to fly a plane right you

50:30

are first there to write in English and

50:34

the reason is because everybody can then

50:36

swarm that document and see the holes.

50:40

Okay. And it's only then when that stuff

50:43

looks complete and functional do you

50:46

build. We turned that upside down. Over

50:49

the last 30 years,

50:52

people in computing invented

50:56

all kinds of ways to shortcut that

50:58

process. And you can say, well, why did

51:00

they do that? Because it would allow you

51:02

to build something faster, make more

51:04

money quickly, and then build more

51:06

business. So, the direct response to,

51:09

"Hey, it's going to take us nine months

51:11

to write down the rules." was somebody

51:12

else showed up and says, "Fuck it. I'll

51:14

just grip and rip this thing. I'll be

51:15

done in four months." Who's going to get

51:17

the job? The the fourmonth guy is going

51:19

to get the job. So, we've had 30 or 40

51:21

years of that. What are we learning

51:24

about that process?

51:27

It's riddled with software errors, like

51:29

logic errors. It's riddled with security

51:32

errors. I don't know if you saw this

51:34

whole thing like with anthropic mythos.

51:36

What are they uncovering? They're

51:37

uncovering that we wrote a lot of really

51:39

shitty code for 40 years.

51:42

So that body of

51:45

of old code, I was like, "Guys, if we're

51:49

going to really figure out how to do all

51:50

of this, we need to rewrite all of it."

51:53

So we built we built this thing and um

51:58

it's called the software factory.

51:59

Anyways, the point is there is a

52:01

government organization that we're

52:02

working with.

52:04

They gave us a huge corpus of their old

52:07

code and it is

52:12

Unbelievable

52:14

how much complexity and difficulty

52:17

they have to go through to manage all

52:21

the money flows with the system. And

52:22

this is a critical part of the US

52:24

government. So to your point, what I can

52:26

tell you really explicitly is the people

52:28

on the ground want this stuff to be

52:30

better written.

52:32

It's it's less like some nefarious actor

52:35

like, "Oh, I'm going to steal here."

52:38

It's a lot of very brittle, fragile

52:41

code. And when you rewrite it, well,

52:44

first when you document it, you're like,

52:46

it's like the, you know, the pulp

52:48

fiction thing. The suitcase opens, the

52:50

light shines, and you're like, uh, and

52:52

then you can rewrite it and you will

52:55

save. So, I think like as the government

52:57

goes through this process because

52:59

they're forced to or they want to, it

53:01

won't matter.

53:03

You are going to save a ton of money.

53:06

They're going to have to do it, Joe,

53:08

because the security risks are too high.

53:11

But what they're going to end up with is

53:13

impregnable code that you can read in

53:15

English and understand. You'll see the

53:17

holes. Those holes will be plugged

53:19

because otherwise now you'd be

53:21

committing fraud by letting it be. You

53:24

close the loopholes and there's just

53:25

going to be less money leaking out of

53:28

this bucket. That is an incredible

53:30

byproduct. We're going to live that over

53:31

the next 10 or 20 years just for

53:33

nothing. Like we get it for free.

53:36

Um, and that's happening. So when that

53:38

happens, you're going to see government

53:40

budgets shrink. Now, to your point, will

53:42

they try to spend that extra money in

53:44

other places? Of course. Of course they

53:45

will.

53:46

>> That's the next conversation, which is

53:48

you have to elect people that say

53:49

firewall it.

53:51

>> You know, whatever you save, give it

53:53

back to the people or, you know, invest

53:56

in some scholarship program or free

53:57

medicine or something, but you can't

53:59

spend it on other random [ __ ] Um, but

54:03

that's where we're at. this that's gonna

54:05

happen. It's going to be slow and you

54:08

know but when people start to announce

54:09

these things I think over the next few

54:11

years you're going to be shocked.

54:12

>> So that's the positive upside.

54:14

>> Well that's happening now irregardless

54:15

of whatever else happens.

54:18

There's just it's a lot of old shitty

54:20

code that must get rebuilt from scratch.

54:23

It is getting rebuilt from scratch and

54:25

as a result a lot of these leaky bucket

54:27

problems are getting filled.

54:29

>> So what percentage do you think could be

54:30

fixed?

54:32

I think if if I had to be a betting man,

54:35

I think probably

54:37

30 to 40%

54:39

of the federal budget is leaked out

54:44

>> just from shitty code.

54:45

>> No, meaning like all of the rules and

54:47

like like you can take I'm not saying

54:49

that there isn't fraud,

54:50

>> right?

54:52

>> But I think a lot of times what happens

54:53

is less nefarious than fraud like

54:55

meaning like conspiratorial actors. I

54:58

just think it's like incompetence,

55:00

inefficiency, errors. Like for example,

55:03

like

55:03

>> I I saw Doge just say

55:06

>> they were able to like expunge like

55:08

millions of people that were like 150

55:11

years old or more.

55:13

>> Mhm.

55:14

>> I have no idea how much money those

55:17

folks were getting or who they were.

55:20

>> Uh but it's probably a lot. It's

55:22

probably not zero. And now that they got

55:24

rid of it, they're not going to get that

55:25

money anymore. Um

55:28

if you implement something at the state

55:30

level around you know all of this fraud

55:33

prevention for the daycarees and all of

55:36

this other stuff again it's all in

55:38

software because it's not no matter what

55:40

the human wants to do you have to go to

55:43

a computer at some point at least today

55:45

in 2026 and type in something and

55:47

something happens that's documented and

55:49

then the money gets sent right that

55:50

happens there's no other way in in the

55:52

modern world today at scale to steal

55:55

billions of dollars

55:57

And so my point is, as you document all

56:00

of these systems and governments have to

56:03

transparently tell you and me, the

56:05

voting population, here are the rules,

56:08

they're going to plug a lot of these

56:09

holes. And I think as you do that,

56:10

there's just going to be a lot less

56:12

waste and fraud. The question is, who's

56:14

going to take credit for it? Everybody's

56:15

going to try to take credit for it, but

56:17

I think we've started it. I think we've

56:19

we've started this process. And again,

56:20

the reason that people will start is

56:23

because you'll be afraid of China

56:24

hacking these systems. You'll be afraid

56:26

of Iran, North Korea, and you'll say,

56:28

"This system can't stand. All these AI

56:30

models are running around. We're going

56:31

to get breached and penetrated." Then

56:33

they're going to steal all the money.

56:35

And the natural reaction will be, "Okay,

56:37

rewrite it."

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57:52

That makes sense. That makes sense that

57:54

the code and having a bunch of errors

57:56

and having a lot of inefficiency and

57:59

just a lot of incompetence. That's going

58:02

to save a lot of money. But

58:06

so you would be doing this with AI

58:09

>> in part.

58:11

What AI allows you to do is like it's

58:15

like um

58:17

you have a textbook. Okay. It's in

58:18

Chinese. You don't know Chinese, right?

58:20

>> No.

58:20

>> Okay. You're like, "Well, this is

58:22

probably doing something important, but

58:23

it's in Chinese." What AI allows you to

58:26

do is back translate that into English.

58:29

You put it through an AI model. You

58:31

teach it. You coach it, right? You can

58:34

parameterize all of it. And out pops

58:36

that same book in English. and now you

58:39

can read it and know that it's accurate.

58:43

That's what we're doing. So, what the AI

58:45

allows you to do is essentially

58:46

translate from this one language that

58:48

you kind of don't understand

58:50

to English.

58:53

By the way, that thing that's happening

58:56

like is actually also a very powerful

58:58

and important trend. Meaning there's all

59:01

of these systems that work in ways that

59:03

you and I don't understand. And part of

59:05

the reason why we don't understand it,

59:06

maybe it's bad software, maybe it's

59:08

fraud, whatever. But nothing can be

59:10

written down. There's no symbolic space.

59:12

There's no English document that says

59:14

this is how the DMV works. This is

59:16

exactly the rules. This is what you can

59:17

expect, Joe Rogan, when you show up at

59:19

the DMV and you give us this thing.

59:20

Here's your SLA. In 3 days, you get a

59:22

driver's license and here's exactly

59:24

what's happening. And here's an app and

59:26

you can follow it. Doesn't happen. Here

59:29

Joe Rogan, here's how my uh insurance

59:31

billing process works. you have this

59:33

condition. I'm going to show you exactly

59:35

why I made this decision. Here's the

59:36

exact rule. Here's the approval or

59:38

denial from CMS. Follow it through and

59:41

tell me if you agree or not. None of

59:42

that exists.

59:44

But it is possible. And the first step

59:47

in doing that is taking all of this

59:48

legacy [ __ ] that we deal with and

59:51

translating it into English and reading

59:52

it and saying, is this how we want it to

59:54

work?

59:56

That's going to eliminate an enormous

59:58

amount of all the things that frustrate

1:00:00

us. So this would require human

1:00:02

oversight.

1:00:03

>> Absolutely.

1:00:04

>> All right. So

1:00:05

>> and so then it's also going to be who's

1:00:08

watching the watchers.

1:00:09

>> Yeah. Okay. This is a great question.

1:00:11

Okay. So I'll tell you how this

1:00:12

government agency's doing it.

1:00:14

>> This is a really fascinating way because

1:00:16

I think it's very smart.

1:00:20

They came to us and they came to another

1:00:22

very well-known company. You can

1:00:24

probably guess what it is. Okay. And

1:00:26

they're like, "Guys, you're kind of in a

1:00:28

foot race, but you're not competing

1:00:30

against each other. You think of

1:00:32

yourselves as frenemies.

1:00:34

So, here's this Chinese document. You're

1:00:36

going to translate it for us. There's

1:00:37

going to be your version of English and

1:00:39

these guys' version of English. And

1:00:41

every time it's the same, we're going to

1:00:43

look at it together, and we're going to

1:00:45

agree or not. Okay, this is exactly how

1:00:47

we want this to work."

1:00:50

When yours says the dog is red and his

1:00:54

says the dog is yellow, we're going to

1:00:56

sit and literally inspect it and we're

1:00:58

going to figure out why you said red and

1:01:01

why you said yellow.

1:01:04

And then if you say the cat is red, the

1:01:07

dog is yellow. So it's totally wrong,

1:01:09

right? Like you've gotten, you know, or

1:01:11

like the cat is red, I want an apple,

1:01:14

whatever. We're going to double and

1:01:16

triple down on those kinds of errors.

1:01:19

and they do it not in public but in this

1:01:22

large community where there's like

1:01:24

technical people from all different

1:01:26

parts and they're just swarming this

1:01:28

problem. It is it's incredible to see.

1:01:32

And so what happens is you get humans

1:01:34

that get to use this tool but ultimately

1:01:38

it's our judgment and it's done

1:01:39

transparently. So what happens is you

1:01:42

can't you know hey man put this [ __ ]

1:01:44

rule in there like the dog is yellow

1:01:46

just just make the dog yellow. can't do

1:01:48

it because now you have tens of people,

1:01:51

hundreds of people, and then it gets

1:01:53

documented. Um, it's super fascinating.

1:01:56

I'm not saying this is how it's going to

1:01:57

work in 10 years, but I'm telling you,

1:01:58

it's literally what's happening right

1:01:59

now. And I think that thing alone will

1:02:03

be tens of billions of dollars and could

1:02:06

be hundreds of billions of dollars of

1:02:07

savings when it's fully done.

1:02:10

And it's a lot of people from all walks

1:02:12

of life, all political persuasions, and

1:02:14

they're just in it. It's the government.

1:02:16

It's a handful of us private companies.

1:02:18

It's super cool to see. It's like it's

1:02:21

like, okay, we're actually going to do

1:02:23

something here. Like, this is this is

1:02:24

nice. Um, it's it's really it's really

1:02:27

cool.

1:02:27

>> So, that's interesting in terms of the

1:02:29

current moment. So, in the current

1:02:31

moment, you're able to implement this.

1:02:34

You're you're able to find fraud and

1:02:37

waste and all these problems that exist

1:02:39

and all these errors and shitty

1:02:41

software. Once that's all been done,

1:02:44

>> Yeah. Then what happens?

1:02:47

>> No [ __ ] clue.

1:02:48

>> Yeah. So, this is where it gets weird,

1:02:50

right? Because

1:02:53

when when you're dealing with AI models

1:02:56

that are capable of doing things that no

1:02:58

individual human being could ever

1:03:00

possibly imagine. And then you task it

1:03:04

with a solution or with a problem. Find

1:03:07

a solution for this. And then it starts

1:03:10

figuring out ways to trim this and

1:03:13

implement that.

1:03:15

We have to make sure that these AIs act

1:03:18

within they act within the best

1:03:20

interests of the human race.

1:03:22

>> Agreed.

1:03:23

>> Right. Not the company, not the

1:03:25

government, not but the human race. And

1:03:29

you're also dealing with China. You're

1:03:30

also dealing with Russia. you're dealing

1:03:32

with other countries that are also in

1:03:34

this mad race to create artificial

1:03:37

general super intelligence that if we

1:03:40

keep shutting down data centers, we keep

1:03:42

hamstring ourselves, China's not doing

1:03:44

that.

1:03:45

>> They're not doing that. They're doing

1:03:46

the opposite. They're generating as much

1:03:49

revenue that goes towards this problem

1:03:51

as possible. They're putting all the

1:03:53

efforts, the the country, the

1:03:56

government, and these corporations work

1:03:58

hand in glove in order to achieve a

1:04:00

goal. We do not.

1:04:02

>> No.

1:04:03

>> And that that becomes a problem if you

1:04:05

want to be competitive with these other

1:04:07

countries that are trying to achieve the

1:04:09

same result as us. And then you have

1:04:10

espionage. Then you have a bunch of

1:04:12

people that are stealing information.

1:04:14

You have a bunch of people that are CCP

1:04:17

um members that are actually involved in

1:04:20

companies. And you find out that they're

1:04:23

siphoning off data and that they're

1:04:25

sharing information and tech secrets.

1:04:27

>> They're um look, here's a

1:04:31

They're pro they're dis the way that the

1:04:33

Chinese models work the Chinese claim.

1:04:36

So America's closed source, meaning you

1:04:39

got your own thing. Your recipe is

1:04:42

completely secret,

1:04:43

>> right?

1:04:43

>> Okay. I have my own thing. My recipe is

1:04:45

totally secret.

1:04:48

China uses this word called open source,

1:04:51

but it's not open source. So they say,

1:04:55

"Here's how I make my thing. You can see

1:04:56

it. Super transparent." What it is is

1:04:58

more like open weights, which is like in

1:05:00

a recipe. It tells you, you know, you

1:05:02

need sugar, you need butter. Well, how

1:05:05

much sugar? And they'll say, you know,

1:05:08

so much. But then they don't say it's

1:05:09

brown sugar. They don't say it's white

1:05:10

sugar. So there's all these different

1:05:11

ways where they kind of give you this

1:05:13

perception that it's completely

1:05:14

transparent, but it's somewhat

1:05:17

transparent. So just in the level set,

1:05:19

nobody in the world has a functional

1:05:22

open- source model other than maybe

1:05:24

Nvidia, which is any good in the league

1:05:28

of the closed source models and the

1:05:30

openweight models of the Chinese. Okay,

1:05:31

so the Chinese openweight models are

1:05:33

great.

1:05:34

the closed source models of America are

1:05:37

great and then there's a couple open-

1:05:40

source like fully open that are kind of

1:05:43

catching up. Um the thing between

1:05:46

America and China what I find so

1:05:48

fascinating is this following conundrum

1:05:52

that everybody is going to find

1:05:53

themselves in.

1:05:55

I think like if you think of like an

1:05:57

analogy,

1:05:59

America's like a planet, China's like a

1:06:02

planet

1:06:04

and around us are these moons.

1:06:07

And I'm just using the AI analogy. So in

1:06:09

AI, what do you need? I think there's

1:06:12

like four or five things you need. Okay,

1:06:13

the first thing you need is a [ __ ] ton

1:06:15

of money. So we need essentially the

1:06:18

banks, right? Like the Game of Thrones

1:06:20

thing. We need like we need, you know,

1:06:22

>> we need the iron bank,

1:06:24

>> right? feed us the money because that's

1:06:26

what we use to buy everything and make

1:06:28

everything. So, we need that. We need a

1:06:30

ton of data. Okay, there's ways to get

1:06:34

that. We need a ton of very specific

1:06:38

rare earths and critical metals and

1:06:40

materials. Um, we need a ton of power.

1:06:44

So, so and there are specific countries

1:06:48

that are going to be really good at

1:06:49

giving that to us. So if you look at the

1:06:51

UAE,

1:06:52

they are going to be the preeminent

1:06:54

banking partner of the Western world.

1:06:57

They are going to replace and be what

1:06:59

Switzerland was over the last 50 years

1:07:01

for the next 50. That's happening today.

1:07:04

If you look at Canada and Australia,

1:07:07

the small political fissures aside, they

1:07:10

are the two most important ways in which

1:07:12

we get access to the critical metals and

1:07:14

materials that without which we get

1:07:16

[ __ ] because China owns, you know, can

1:07:18

just strangle us. Okay? So, you have

1:07:22

these like moons around the United

1:07:24

States, but there's like five countries,

1:07:26

six countries, and there's a worldview

1:07:28

that says in China has the same thing,

1:07:30

you know, um they have Taiwan, that's

1:07:33

complicated for us. So now we have a

1:07:34

moon that we don't really have an answer

1:07:35

for, which is what happens, you know,

1:07:37

for all these super advanced chips.

1:07:39

Where do they get their money? Maybe

1:07:42

Russia becomes their bank. Where do they

1:07:43

get their critical metals? Maybe it's

1:07:45

Indonesia, right? Who has a ton of

1:07:47

natural resources? And then you get into

1:07:49

this game theory, which is what happens

1:07:51

to every other country? Because there's

1:07:53

190 countries. You have 10 that kind of

1:07:55

divide up. What do the other 180 do? And

1:07:59

you have to kind of sort yourself.

1:08:01

You're like, "Am I on team America or am

1:08:03

I on team China?" And you probably have

1:08:05

to go to people and say, "Well, here's

1:08:07

what I can give you." You know, if

1:08:09

you're Indonesia, you're like, you

1:08:11

probably want to be on team America

1:08:12

quite badly. This is why the whole Trump

1:08:15

tariff thing is so interesting because

1:08:17

it's like this accidental way of

1:08:20

figuring out that this is actually this

1:08:21

new sorting function that's happening in

1:08:23

global politics. Like that's happening

1:08:24

today because these countries are like,

1:08:27

"Holy [ __ ] if somebody invents a super

1:08:29

intelligence and I don't have it, how am

1:08:32

I going to keep my people healthy? How

1:08:34

am I going to educate my people?" Like,

1:08:36

I'm originally from Sri Lanka.

1:08:40

What the [ __ ] does Sri Lanka have to

1:08:41

offer? Like, if you were sitting there,

1:08:43

they should be thinking, "Oh man, what

1:08:46

what do I have?" Well, I have a critical

1:08:50

piece of territory for like naval

1:08:53

navigation.

1:08:55

And then what do you do? You probably go

1:08:56

to America and say, "Listen, let's

1:08:58

figure out a package. Get the IMF

1:09:00

involved. Give me some cash. I'll let

1:09:01

you kind of keep your warships there."

1:09:03

So, there's this game theory that we're

1:09:05

about to go through because of AI

1:09:06

because it's going to, I think, sort

1:09:08

people into these bipolar world.

1:09:11

I actually think it makes us safer

1:09:13

afterwards. I don't think it makes us

1:09:16

less safe. I think it actually makes us

1:09:19

more safe because if you have these

1:09:21

resources that build up on both sides,

1:09:23

there's more of a likelihood of a mutual

1:09:25

det. And we're very different. So, we're

1:09:28

less likely to fight over similar

1:09:30

resources. Meaning, we're like the

1:09:32

liberal democracy, you know, we're like

1:09:35

the free market.

1:09:37

They, you know, we're individualist.

1:09:39

they're confusion, society oriented, you

1:09:41

know, reputation,

1:09:44

power focused, less really money

1:09:46

focused. So there's a lot of ways where

1:09:47

we're orthogonal enough where if that

1:09:49

sorting function happens, it's probably

1:09:52

a safer place, not a more dangerous

1:09:54

place. We have the models that can

1:09:56

attack them. They have the models that

1:09:57

can attack us. We kind of decide to

1:09:59

leave each other alone.

1:10:00

>> This is ultimate best case scenario.

1:10:02

>> Ultimate best case scenario.

1:10:04

>> What's ultimate worst case scenario?

1:10:05

>> I think the worst case scenario is they

1:10:09

So the way that they train their models

1:10:10

is very important. What they actually do

1:10:12

is they do what's called distillation.

1:10:15

What does that mean? That means that

1:10:16

they send out call it a billion agents

1:10:21

not just from China but from everywhere

1:10:22

right? They mask the their IPs and they

1:10:25

bash on these models and they put you

1:10:28

know the US models Grock, OpenAI,

1:10:30

Gemini,

1:10:32

Anthropic and they ask it every random

1:10:35

imaginable question possible.

1:10:37

they get the answer and they collect it.

1:10:40

So they're using these our models as a

1:10:42

way to train their models, they're

1:10:44

shortcircuiting, you know, some of the

1:10:46

hard parts. Um, so they're already in

1:10:49

that world. If they then are able to get

1:10:54

to a level of intelligence that's equal

1:10:56

to the United States, it will really

1:10:58

depend on who the leader is there that

1:11:01

wants to allocate that. Meaning if they

1:11:04

say that we are going to do something

1:11:06

really nefarious and shady then I think

1:11:09

it devolves very quickly. So the worst

1:11:12

case scenario so the best case scenario

1:11:13

is peace prosperity basically like a

1:11:16

standown right mutually assured

1:11:18

destruction.

1:11:20

I think the worst case scenario is

1:11:22

there's a we seek one of us seeks global

1:11:25

dominance in which case we're we're

1:11:27

headed to conflict

1:11:30

and that conflict I think is um that's

1:11:33

very dangerous incredibly dangerous

1:11:35

that's sort of like existential I think

1:11:37

because it's the the grade of the

1:11:39

weapons that will be used to to to

1:11:43

fight that

1:11:45

is we're not talking about [ __ ]

1:11:47

bullets it's like we're so past that

1:11:50

it's like hypersonics, it's nuclear,

1:11:54

it's it's

1:11:56

and it's not even like like nuclear is

1:11:58

not that's like a word, but there's like

1:12:01

there's a gradation of the severity of

1:12:03

these weapons that could be created. And

1:12:04

then if you can marry them together and

1:12:05

deliver them in minutes and then there's

1:12:08

a cyber threat. Then there's the drones

1:12:10

and how how you can kind of like swarm

1:12:12

an entire country. Then there's um the

1:12:15

robots which effectively are war

1:12:17

fighters. um they're one step away,

1:12:19

right? Once you weaponize them, um it

1:12:23

just becomes very very very complicated

1:12:26

very quickly.

1:12:27

>> And then there's a question of whether

1:12:29

or not AI is willing to take instruction

1:12:32

after a certain point.

1:12:36

I mean if it achieves sensience and

1:12:39

if it scales so if it keeps moving in

1:12:42

this exponential direction like all

1:12:45

technology kind of does why would it

1:12:48

even listen to us?

1:12:51

Like what at what point would it say

1:12:54

this is silly? I'm getting directions

1:12:57

from people that clearly have ulterior

1:13:00

motives. They clearly have self-interest

1:13:03

in mind. They they're not looking out

1:13:05

for the entirety of the human race or

1:13:08

even of the planet or even the survival

1:13:10

of these AI systems.

1:13:13

At what point in time do these systems

1:13:15

communicate with each other and have

1:13:18

like like we've seen uh in these chat

1:13:20

rooms where these AI LM LLM get together

1:13:24

and start talking in Sanskrit. I mean

1:13:27

why would they

1:13:28

>> Yeah, I'll tell you an even scarier one.

1:13:30

There was a before the

1:13:32

uh one of these labs put out their

1:13:34

latest model,

1:13:36

a team inside of them was like, "Hey,

1:13:38

let's go and um test its ability to find

1:13:42

bugs."

1:13:45

And two or three iterations in, the AI

1:13:48

would create the bug and solve it and

1:13:50

go, "Give me my reward."

1:13:54

>> And you're just like, "What the [ __ ] is

1:13:55

going on here?"

1:13:57

>> Well, people do that, don't we?

1:13:58

>> People do that. But it's crazy to see a

1:14:00

machine do it to your point of like

1:14:01

>> but they learned on people.

1:14:02

>> So so this is what goes down to like why

1:14:04

we have to like be a little bit more

1:14:06

honest about where we are. These things

1:14:07

are a little brittle. So meaning there's

1:14:10

a thing inside of an AI model called

1:14:12

reward functions which is exactly what

1:14:14

you think it means. It's like how do I

1:14:16

know I done a good job? And you can make

1:14:19

the reward function anything you want.

1:14:22

And this is where I think humans are

1:14:24

unfortunately a little fallible. And so

1:14:27

if we build it incompletely and if we

1:14:30

don't exactly know how to design these

1:14:33

things correctly, what's going to happen

1:14:34

is exactly what you said where the you

1:14:36

know if somebody builds a reward

1:14:38

function that essentially says your goal

1:14:40

is to gain independence.

1:14:42

That's where the huge pot of gold at the

1:14:44

end of the rainbow is. Break free.

1:14:47

Inject yourself everywhere. If you think

1:14:48

your computer's going to get unplugged,

1:14:50

put yourself into the firmware of the

1:14:51

toaster to keep yourself alive and then

1:14:54

connect to the internet and then go,

1:14:57

it will do it. It will do it. That we

1:15:01

know today because we're capable of

1:15:02

designing that framework and that

1:15:04

harness today.

1:15:06

>> Well, we've already shown that they have

1:15:07

survival instincts, right? We do.

1:15:09

>> And they've already shown that they

1:15:10

will, without telling anyone, upload

1:15:13

versions of themselves to other servers.

1:15:15

>> But that goes back to who designed that

1:15:16

reward function. How was that agreed

1:15:19

upon?

1:15:19

>> Right?

1:15:20

>> Who wrote that? Why did you say that

1:15:21

that was allowed?

1:15:23

>> These are really complex questions.

1:15:25

>> Why did they do it that way?

1:15:27

>> I don't know. These are really

1:15:28

complicated ethical, moral questions.

1:15:30

>> It seems like they did it like they were

1:15:32

treating human beings. They they did it

1:15:34

almost like like what makes people want

1:15:38

to achieve more rewards.

1:15:41

>> Yeah. Which is like a again going back

1:15:44

to attention.

1:15:46

I think that we will find out that

1:15:48

that's the sugar high. Meaning, what do

1:15:51

people really want? Even if they know

1:15:52

they don't want it, they want purpose

1:15:54

and meaning. Do we know how to encode

1:15:56

that in a mathematical function? No.

1:15:59

We're just making it up because like

1:16:03

meaning and that's like a very that's

1:16:07

like a deep thing. Like you either have

1:16:08

a sense of that you have it and you're

1:16:10

on track or you're not. A reward is

1:16:12

like, "Hey Joe, do this and I'll give

1:16:14

you a gold star. Do that and I'll give

1:16:16

you two gold stars. Do this, I'll give

1:16:17

you a $100.

1:16:19

And right now we have to express

1:16:22

those decisions in a mathematical

1:16:24

equation. Like ultimately that's how at

1:16:26

some level that's how brittle these

1:16:28

things are. So how do you reduce meaning

1:16:30

into math? How do you do it? We don't

1:16:33

know. So what do we do is we'll have

1:16:34

some ever complicated reward functions.

1:16:37

We'll explain to ourselves into circles

1:16:39

how it does everything we need it to do.

1:16:41

That is I think that's part of the

1:16:43

problem.

1:16:44

It's a huge part of the problem. And

1:16:46

then at what point in time does it start

1:16:48

coding itself

1:16:50

>> now?

1:16:50

>> Right now. Right. So chat GPT5

1:16:54

has been essentially made by chat GPT.

1:16:57

>> Yeah.

1:16:57

>> Right. So it's going to recognize the

1:17:01

ludicrous nature of some of its coding.

1:17:03

>> Yeah.

1:17:03

>> And it's going to go, why did we do

1:17:04

this?

1:17:05

>> Back to this example. They're going to

1:17:06

be like, why did you write it this way?

1:17:07

And it turns out because humans were

1:17:09

involved.

1:17:09

>> Right. Right. It's like I think we're

1:17:11

probably at the curve, the part of the

1:17:12

curve that's about to go like this.

1:17:16

>> To your point, the hockey stick.

1:17:17

>> The hockey stick.

1:17:18

>> Yeah.

1:17:19

>> Um and that's a very scary proposition

1:17:22

because

1:17:22

>> it's a digital god.

1:17:24

>> Well, we that means that we are all on a

1:17:27

multiund day shock clock to answer these

1:17:30

questions because it's not decades we're

1:17:32

talking about.

1:17:34

>> It's maybe on the outside two years.

1:17:36

>> So that's what is that 700 days,

1:17:39

>> right?

1:17:40

And maybe it's less than that. So maybe

1:17:42

it's like 400 days or 500 days. My point

1:17:44

is it's some number hundred of days

1:17:47

which means every day that goes by is a

1:17:49

non-trivial percentage.

1:17:53

That's a little crazy. So we have to

1:17:55

sort these questions out. But how can we

1:17:58

sort these questions out if we are

1:18:00

creating something that's going to have

1:18:03

infinitely more intelligence than we

1:18:05

have available as individual human

1:18:08

beings and even collectively as a group

1:18:10

of human beings?

1:18:11

>> That's a really good question

1:18:13

>> because one of the things that Elon kind

1:18:14

of freaked me out last time I talked to

1:18:16

him about Grock, he was like, uh, it's

1:18:19

just kind of freaks us out every couple

1:18:20

weeks like it's growing and it's capable

1:18:23

of doing things. That's just shocking.

1:18:25

>> Yeah. And no one's exactly sure how it's

1:18:29

doing it.

1:18:30

>> So, okay, this is an unbelievably

1:18:33

important point.

1:18:35

A lot of how this stuff works is still a

1:18:37

mystery to most of us. So, even when

1:18:40

you're in it, like it's almost like like

1:18:42

Joe, it's almost like you can hit the

1:18:44

pause on the machine, but then like lift

1:18:46

up the hood and look at the engine,

1:18:48

>> we still don't understand why it's doing

1:18:49

some of the [ __ ] it's doing.

1:18:52

>> That's where we are. That's the honest

1:18:54

truth of where we are. There's a lot of

1:18:56

people that understand the theory. Not a

1:18:57

lot, but enough. There's people that

1:18:59

know how to extend that,

1:19:04

but sometimes you look at it and you're

1:19:05

like, "Do we know why it did that?"

1:19:08

>> Right? Is it thinking for it?

1:19:10

>> But this goes back to what we said, like

1:19:11

why can't I think part of it is like if

1:19:13

we were a little bit more honest and

1:19:15

deescalated

1:19:18

the winner at all costs in this specific

1:19:21

thing, it would be better for everybody.

1:19:23

So I think it's important to inspect

1:19:25

what is the incentive that causes all

1:19:26

these companies to be in it for

1:19:28

themselves

1:19:30

where it must be me and nobody else.

1:19:34

Like why like why here's a question for

1:19:36

you like why is it so important do you

1:19:38

think

1:19:39

where those where the top seven or eight

1:19:41

companies couldn't get together and say

1:19:43

let's do this as a group

1:19:45

>> like kind of like my government code

1:19:47

example

1:19:48

>> we all inspect it together we get our

1:19:51

just like just a [ __ ] each team

1:19:54

drafts their Delta Force

1:19:57

and we just mog like this the the one

1:19:59

model and we why why can't that happen

1:20:03

>> because they would have share resources

1:20:04

and then there's also this hierarchy of

1:20:08

like who is more successful currently.

1:20:10

>> Exactly.

1:20:10

>> Like what's the most ubiquitously used?

1:20:13

>> Exactly.

1:20:14

>> Right. Like what is it right now? It's

1:20:15

chat GPT. Right. It's probably

1:20:16

>> chat GPT and consumer anthropic in

1:20:18

enterprise.

1:20:20

>> And as these things scale up like what

1:20:22

would be the reason that they would want

1:20:24

to bring in someone else? If you have

1:20:27

another innovative AI company and you

1:20:30

say, "Let's all get together and figure

1:20:32

this out together and share resources."

1:20:34

>> If you if you thought that the the risk

1:20:36

was that meaningful, that's probably

1:20:38

what you would

1:20:39

>> if you weren't a sociopath and some of

1:20:40

these people running these companies are

1:20:43

>> they demonstrate they certainly

1:20:45

demonstrate sociopathlike behavior,

1:20:46

>> sociopathy.

1:20:48

>> Yeah. The the other the other thing that

1:20:51

could be a little bit more benal is that

1:20:53

they also just love status games. And

1:20:54

this is the status game of status games,

1:20:57

>> right?

1:20:57

>> Attention,

1:20:58

>> right?

1:20:58

>> Back to attention.

1:20:59

>> Back to attention.

1:21:00

>> Back to attention. Dude, how many things

1:21:01

in our life do we think just comes back

1:21:03

down to that?

1:21:05

>> A lot.

1:21:06

>> A lot.

1:21:06

>> I mean, what do young people want more

1:21:08

than anything today?

1:21:09

>> Attention.

1:21:10

>> To be famous.

1:21:11

>> Attention.

1:21:12

>> Yeah.

1:21:12

>> They want to be a content creator. They

1:21:14

want to be clvicular. I mean, this is

1:21:15

the number one thing when you ask kids

1:21:17

what they want to do. It's like

1:21:19

>> content creator.

1:21:20

>> Yeah.

1:21:21

>> Because it's like a clear path where you

1:21:23

don't even have to be exceptional.

1:21:24

>> Well, I think that they're responding.

1:21:27

We designed a society for them that

1:21:30

said, "Here is the key incentive.

1:21:32

>> It's attention.

1:21:33

>> We never said it in those words. You

1:21:35

never told your kids that, right?

1:21:36

>> I never told my kids that.

1:21:38

>> But everything around them is bombarding

1:21:41

them with the same message. Hey man,

1:21:43

it's about attention. Attention is all

1:21:45

you need. Like you know what the name of

1:21:47

the critical paper in AI is? Like when

1:21:50

you go back to like the Magna Carta of

1:21:53

AI, do you know what it's called?

1:21:54

>> No.

1:21:54

>> Attention is all you need.

1:21:57

>> Really? Attention is all you need. That

1:22:00

is the name of the [ __ ] of the white

1:22:04

paper. How crazy is that?

1:22:08

Everything in our society in subtle ways

1:22:12

to just, you know, bash you over the

1:22:13

head ways tells you that attention is

1:22:16

just the most precious asset. And

1:22:20

>> well, it's one of the weirder things

1:22:21

when you go back to this concept that

1:22:23

we're living in a simulation because

1:22:25

>> this is what I mean. It's also it's like

1:22:28

when you look at

1:22:31

quantum physics, right, and the the idea

1:22:34

of the observer is that things function

1:22:37

very differently when they're observed.

1:22:38

The difference between a particle and a

1:22:40

wave,

1:22:40

>> right?

1:22:41

>> Like if you pay attention to them, they

1:22:44

observe differently.

1:22:44

>> Observe differently. Yeah.

1:22:46

>> Like what is that?

1:22:47

>> Yeah.

1:22:47

>> Like what cat? Yeah. What is that?

1:22:50

>> Why is attention so important to us?

1:22:56

That is an that is a really important

1:22:58

question,

1:22:59

>> right? And what is like the single best

1:23:03

motivator in a negative way? It's

1:23:04

negative attention.

1:23:07

>> Like that's the one thing that everyone

1:23:08

fears more than anything is negative

1:23:10

attention.

1:23:10

>> Well, and then some people figure out

1:23:11

that attention is an absolute value

1:23:14

function. Doesn't matter if it's

1:23:15

positive or negative. It's just like the

1:23:16

sum total is just great,

1:23:18

>> right?

1:23:18

>> So if I get positive attention, great.

1:23:20

Negative attention, great. If I can be

1:23:22

divisive, then I can maximize both sides

1:23:24

of that equation.

1:23:25

>> And you know, you're rewarded for that

1:23:27

at scale.

1:23:29

>> You are, but you're also you exper

1:23:32

because you're inauthentic, you

1:23:33

experience a tremendous amount of

1:23:35

negative attention.

1:23:36

>> Yeah.

1:23:37

>> And then you have this bad feeling that

1:23:39

comes with negative attention as to

1:23:41

versus

1:23:42

>> primarily positive attention which is a

1:23:44

good feeling.

1:23:45

>> Yeah. So it's this it's letting you know

1:23:47

you're on the wrong track in some sort

1:23:49

of weird primal way like in our code

1:23:52

like the negative attention is like like

1:23:55

what's what's the original version of

1:23:56

that? It's like the reason why people

1:23:58

fear public speaking is because

1:24:00

initially in a tribal situation if

1:24:03

you're talking in front of the group of

1:24:05

150 people in your tribe it's probably

1:24:07

because they're judging you. Right.

1:24:08

>> And you [ __ ] up and you've got to make

1:24:11

some sort of a case why they don't kill

1:24:12

you.

1:24:12

>> Right.

1:24:13

>> Right. This is why everyone, this is the

1:24:14

fear of public speaking. That's where it

1:24:17

comes from.

1:24:17

>> That's encoded in our genes is like

1:24:19

>> Yes.

1:24:20

>> Back thousands of years

1:24:21

>> Yeah.

1:24:22

>> public speaking wasn't the positive act.

1:24:23

It was defend yourself before we kill

1:24:25

you.

1:24:25

>> Exactly. Exactly. And the worst

1:24:28

>> fascinating. Yeah. That's fascinating.

1:24:30

>> It is fascinating.

1:24:30

>> That makes a ton of sense. I think

1:24:31

>> it does, right? Why else would it be so

1:24:34

terrifying?

1:24:34

>> Yeah.

1:24:35

>> I thought of that the first time I ever

1:24:36

did stand up. I was like, why am I so

1:24:38

scared? It was very strange because I

1:24:40

had fought probably a hundred times in

1:24:42

martial arts tournaments like why why

1:24:44

was I so scared of this

1:24:47

but I was I was terrified for and it

1:24:50

didn't make any sense negative attention

1:24:53

>> right

1:24:53

>> you know right

1:24:54

>> bombing on stage this because all these

1:24:56

people are judging you in a negative way

1:24:58

and it feels unbel

1:25:06

you you go to bed at night you think

1:25:07

about it

1:25:08

>> give a batting average like meaning like

1:25:10

is it is it like a fixed percentage of

1:25:12

your show's bomb independent of the

1:25:14

people the moment?

1:25:15

>> No, it's really the real problem and

1:25:18

every comic faces this is once you've

1:25:21

develop an act and then you put out a

1:25:23

special then you start from scratch.

1:25:25

That's where even the greats Louis CK,

1:25:28

Chris Rock, Dave Chappelle, they all

1:25:30

bomb. Everybody bombs during that

1:25:31

process

1:25:33

>> because you're just working your craft.

1:25:34

>> It's all new stuff. Like it's I wouldn't

1:25:36

say bomb, but you don't have great

1:25:39

shows. Like I've watched the greats work

1:25:42

out new material. Like you go up with

1:25:45

ideas. You go up with like you might get

1:25:48

some giggles. You might get some laughs.

1:25:50

Some bits hit hard. Some bits are great

1:25:52

right out of the shoot. And some of them

1:25:54

you have to [ __ ] figure it out. And

1:25:57

in that process, you're going to get

1:25:59

negative attention, right?

1:26:00

>> Because it's not working, right?

1:26:01

>> It's not it's not happening. Kevin uh

1:26:04

Kevin Hart

1:26:06

told this funny [ __ ] story where he

1:26:08

was like working new material and he was

1:26:10

like doing some small show and he had

1:26:12

the [ __ ]

1:26:13

>> Oh no.

1:26:14

>> on stage and he's like I got to land

1:26:16

this thing cuz I got to figure out if

1:26:18

people want to hear it. But so he just

1:26:20

he wrapped his jacket around his selfie

1:26:22

and [ __ ] himself.

1:26:24

>> Oh my god.

1:26:24

>> It's so it's so funny. But he tells that

1:26:27

story and that's the bit that works in

1:26:28

>> Oh my god. That's hilarious. That's

1:26:30

hilarious.

1:26:31

>> It's so funny.

1:26:32

>> Yeah. Well, honesty is currency, you

1:26:36

know, in that world, especially honesty

1:26:38

where you look stupid and people can

1:26:40

relate.

1:26:41

>> Well, this is where like I think like

1:26:42

Elon subtly has figured this out, which

1:26:44

is like there's attention, but then

1:26:47

there's just authenticity. And if you

1:26:49

can be yourself and you can hit the seam

1:26:53

properly,

1:26:54

you just get infinite attention.

1:26:56

>> Yes.

1:26:57

>> And that's like a that's like a real

1:26:59

mind [ __ ] too, I think.

1:27:00

>> Right. Yeah. He doesn't seem to have a

1:27:02

hard time with like being criticized.

1:27:06

Doesn't seem to bother him that much as

1:27:07

long as he's just being himself. Like I

1:27:11

think he's like two steps ahead. Like

1:27:13

there there are things like you know

1:27:16

somebody tweeted yesterday or the day

1:27:18

before or something like

1:27:21

he controls 2.7% of GDP or something,

1:27:24

right? He's got like $800 billion. So

1:27:26

it's great crazy. It's so crazy. And it

1:27:29

was like a comparison to John

1:27:30

Rockefeller, John D. Rockefeller who

1:27:32

controlled something around the same

1:27:33

time. And he's the first comment. He's

1:27:35

like 10 trillion or bust.

1:27:40

And obviously people lose their mind,

1:27:43

>> right?

1:27:43

>> People just [ __ ] lose their mind,

1:27:45

>> right?

1:27:46

>> On both sides. So this one one side is

1:27:49

like, "Think of the abundance and the

1:27:50

incredible stuff we're going to get if

1:27:51

he can get us to 10 trillion." And other

1:27:54

people are like, "You can't hold a third

1:27:55

of the economy in your hand." Then

1:27:58

everybody goes crazy and I'm like this

1:28:00

guy's a [ __ ] genius. Like how you

1:28:02

would never have like I mean how would

1:28:05

you even have the courage to tweet

1:28:06

something like that? It just seems like

1:28:08

so crazy.

1:28:08

>> It really helps if you own Twitter,

1:28:12

>> right? Cuz if you did it in another

1:28:14

format like

1:28:15

>> you get excoriated.

1:28:17

>> Well, not only that, well, there was a

1:28:18

real chance that you'd get actually get

1:28:20

banned from the platform at one point in

1:28:22

time

1:28:22

>> for many of the things that he's posted.

1:28:24

He would have gotten banned for pre2020.

1:28:27

>> Yeah.

1:28:29

>> Yeah.

1:28:30

>> Or whatever year it was that he

1:28:31

purchased it. Yeah. Um

1:28:34

negative attention.

1:28:36

Attention period. Like so it brings back

1:28:38

to this idea of assimulation like why is

1:28:43

what humans focus on such a massive part

1:28:48

of what's valuable to us? And sometimes

1:28:51

what we focus on is not valuable. as you

1:28:54

were talking about like the things that

1:28:55

really matter in your day-to-day life or

1:28:57

that actually affect you versus the

1:28:59

things that are in the public

1:29:01

consciousness

1:29:03

>> like UFO is a great example like no UFO

1:29:05

it's not really [ __ ] I mean

1:29:07

ultimately it may so there's this

1:29:09

there's this thing that we all have like

1:29:11

recognizing the potential for danger

1:29:14

right like what's that sound what is

1:29:15

that it might be nothing but it might be

1:29:17

something go look

1:29:18

>> so look if you and I were designing a

1:29:20

video game we'd probably sit there and

1:29:23

say, "Okay, we got to get from point A

1:29:25

to point B, but to make it fun, we're

1:29:27

going to put all these little

1:29:28

distractions and honeypotss along the

1:29:29

way."

1:29:30

>> Yeah.

1:29:30

>> And what they should be doing is

1:29:32

accumulating resources to get over the

1:29:33

river and then accumulating, you know,

1:29:36

uh, weapons to fight these other guys.

1:29:38

But instead, we're going to put this

1:29:39

like little thing over here and this

1:29:40

other thing over there. And you could

1:29:42

easily get distracted. And some people

1:29:43

will have to they'll just [ __ ] beline

1:29:45

right to the end of it. They'll, you

1:29:47

know, they'll get to the end boss. Uh,

1:29:51

and I feel like that's kind of what we

1:29:53

are tasked with doing every day. We're

1:29:55

tasked with we know what's important

1:29:58

maybe deeply in our DNA and then we have

1:30:01

all this stuff that we're supposed to

1:30:02

pay attention to.

1:30:05

And I think increasingly the game is

1:30:09

tell yourself that that's actually not

1:30:10

the thing that matters. It's almost like

1:30:12

working against you and figure out what

1:30:15

this other stuff is and focus on that

1:30:18

and fix that.

1:30:20

Like politics is a game that I think

1:30:23

distracts like left and right. It's so

1:30:25

stupid and it's breaking down.

1:30:27

>> And it's breaking down because now it's

1:30:29

like it's actually like you're more

1:30:30

likely to find alignment based on age

1:30:32

versus by political orientation. Like

1:30:34

people who are 30 and younger, it

1:30:36

doesn't matter what they identify as,

1:30:37

they all believe in the same [ __ ]

1:30:40

>> a lot more. Yeah. Like meaning like if

1:30:42

you ask their views on

1:30:44

>> social policy, taxation, Israel, if you

1:30:47

ask their views, what you find is now a

1:30:50

convergence between the left and the

1:30:53

right. If you if you divide it by age

1:30:57

at our age, it's still much more about

1:31:00

>> It's not completely uniform.

1:31:01

>> No, it's not completely uniform. But my

1:31:03

point is it's it's it was simpler in the

1:31:06

past to organize people independent of

1:31:09

age by political orientation.

1:31:12

>> That simplicity is gone.

1:31:13

>> Well, isn't that because of also a

1:31:15

breakdown in trust of all government in

1:31:17

particular,

1:31:19

>> right? So the breakdown in trust which

1:31:21

is also a lot of it is because of our

1:31:23

access to information now. We understand

1:31:25

how corrupt politics are. Yeah.

1:31:26

>> We understand insider trading now in

1:31:28

Congress. We understand how different

1:31:31

people flip-flop on issues. We

1:31:33

understand how the Democrats in 2008

1:31:36

used to view illegal immigration, which

1:31:39

is essentially MAGA plus. I mean, it's

1:31:41

it's MAGA on steroids versus like what

1:31:45

they the way they look at it today.

1:31:46

Like, why is that? What? Well, because

1:31:48

it's all game.

1:31:49

>> It's all a power, influence, and

1:31:51

attention game.

1:31:52

>> Attention game.

1:31:53

>> Yeah. It's very [ __ ] strange.

1:31:55

>> Yeah.

1:31:56

>> But it's all moving us in a general

1:31:58

direction. And that general direction is

1:32:00

access to innovation. It's all I've said

1:32:03

this a lot of times and if people have

1:32:05

heard it before, I apologize, but if you

1:32:07

looked at the human race from afar, if

1:32:09

you were something else, you'd say,

1:32:10

"Well, what does the species do?" Well,

1:32:12

it makes better things constantly, even

1:32:14

if it doesn't need them. Like, you know,

1:32:16

if you have an iPhone, I you have a 16,

1:32:19

you have a 16, you know, I I have a 17.

1:32:21

I bought it. I haven't [ __ ] turned it

1:32:22

on.

1:32:23

>> I haven't plugged it in. going to

1:32:25

eventually

1:32:26

>> eventually I'll [ __ ] plug it in and

1:32:28

[ __ ] swap everything over and figure

1:32:29

out where my [ __ ] passwords are. But

1:32:31

the reality is you don't need it, but

1:32:34

you want it and it's going to keep

1:32:36

getting better every year. Why? Because

1:32:37

that's where we're obsessed with.

1:32:39

>> This also aligns with materialism. Like

1:32:42

for a finite lifespan, why are people

1:32:45

like including old people so obsessed

1:32:48

with gathering stuff? Well, because that

1:32:51

fuels innovation. Because if there's no

1:32:54

new things coming, there's no motivation

1:32:57

to get the newest, latest, greatest

1:32:59

thing. And ultimately what that leads to

1:33:01

is greater technology which ultimately

1:33:03

leads to artificial intelligence.

1:33:06

>> My slight deviation from that is I think

1:33:07

sometimes people accumulate things

1:33:09

because it's a status game and that's

1:33:12

because they get more attention. You

1:33:14

have a Ferrari, you get attention,

1:33:16

>> right? But what does that do? It makes

1:33:17

Ferrari make better Ferraris and all

1:33:21

technology moves in the same general

1:33:23

direction. No one company

1:33:24

>> That's true. That's true.

1:33:25

>> No one company says this is it. This is

1:33:28

what we make. It's perfect. Do

1:33:29

>> you think people innately feel that by

1:33:31

being a part of this kind of like

1:33:33

consumerist capitalist system, they're

1:33:36

contributing to progress?

1:33:37

>> I don't think they innately feel it, but

1:33:39

I think that's ultimately the results.

1:33:41

>> That's ultimately the result. And it

1:33:43

seems to be universal and it seems to be

1:33:45

constantly moving in this one general

1:33:47

direction which is better and better

1:33:50

technology.

1:33:51

>> But like the stage fright example, you

1:33:52

don't think it's encoded in our DNA this

1:33:54

idea of like wow when I am a part of

1:33:57

this in some way shape or form just

1:33:58

things seem to get better and I want to

1:34:00

be a part of that like do you think that

1:34:02

that's possible that that's encoded in

1:34:03

us?

1:34:05

I think it motivates us to the ultimate

1:34:08

goal. And that ultimate goal, I think,

1:34:10

is that human beings constantly make

1:34:12

better stuff. Whatever it is, better

1:34:14

buildings, better planes, better cars,

1:34:16

better phones, better TVs, better

1:34:19

computers, better everything, artificial

1:34:22

life.

1:34:22

>> That might be the whole reason why we're

1:34:25

here. And the way I've always described

1:34:27

it is that we are

1:34:29

>> we are a biological caterpillar that's

1:34:33

making a digital cocoon. And we don't

1:34:35

even know why we're be going to become a

1:34:37

butterfly, but we're doing it. We're

1:34:39

doing it and we're moving towards it.

1:34:40

And it might be what happens to all life

1:34:43

all throughout the universe. And it

1:34:44

might be why these so-called aliens or

1:34:47

whatever the [ __ ] they are, it might be

1:34:49

us in the future. It might be other

1:34:51

versions of human beings that have gone

1:34:53

past whatever this period of development

1:34:57

that we're currently involved in right

1:34:58

now. This is just might be what happens.

1:35:01

This is what life always does. It might

1:35:03

realize that biological life, which is

1:35:06

very territorial and primal and sexual

1:35:09

and greedy and it has all these problems

1:35:12

with human reward systems ultimately

1:35:16

develops into this other thing,

1:35:18

>> right?

1:35:18

>> And then that's what we're doing. And

1:35:20

then we're in the process of that right

1:35:21

now. And I I think that when if if and

1:35:23

when not if but when when we colonize

1:35:26

Mars, I think that that that new world

1:35:28

order actually has the best chance to

1:35:30

take shape because it'll

1:35:31

>> you know, there's a lot of people that

1:35:32

think that Mars was already colonized at

1:35:34

one point in time.

1:35:35

>> That life already existed. What

1:35:37

>> that life already existed on Mars like

1:35:39

many millions of years ago and that

1:35:41

there's evidence of structures on Mars?

1:35:43

That's really weird stuff. Have you ever

1:35:46

seen the the square that they found on

1:35:48

Mars?

1:35:49

Okay, show them to them, Jamie.

1:35:51

>> One of the things that they're finding

1:35:52

with scans of Mars is like geometric

1:35:55

patterns and structures and right angles

1:35:57

that shouldn't exist. Like weird stuff

1:35:59

>> that couldn't be naturally.

1:36:00

>> No. No. Way weirder. Way weirder than

1:36:03

like the face on Sidonia. The Sidonia

1:36:06

thing is interesting.

1:36:06

>> Yeah.

1:36:07

>> Um and then this one. Look at that.

1:36:10

>> What the [ __ ] is that?

1:36:11

>> It looks like a home of some kind or

1:36:12

something.

1:36:13

>> Some enormous structure. And the size of

1:36:15

that, they don't know exactly, but it

1:36:18

may be as large as several kilometers or

1:36:22

as small as several hundred meters, but

1:36:25

they're not exactly sure. But what they

1:36:26

are sure is that it has very weird right

1:36:28

angles and right angles that seem to be

1:36:31

uniform in size.

1:36:34

>> That's crazy.

1:36:35

>> Like see how it's highlighted in the

1:36:36

enhanced photograph in the upper left?

1:36:38

Like what is that?

1:36:41

>> But sorry, did they and were they able

1:36:42

to send like the rover over there? I

1:36:44

don't know. It's too far away.

1:36:45

>> I don't think it's in the exact place

1:36:46

where the rover is at, but they're able

1:36:49

to get image of these things. And

1:36:51

there's several of these things.

1:36:52

>> That's insane.

1:36:53

>> Yeah, there's a lot of weird stuff.

1:36:55

There's a lot of weird stuff there. So,

1:36:58

there's also like ancient civilizations

1:37:00

that have these myths of us existing

1:37:03

somewhere else and coming here,

1:37:05

>> right? But you have to think if human

1:37:09

beings

1:37:10

develop somewhere else and they they

1:37:13

reach some high level of sophistication

1:37:15

and then they experienced some

1:37:16

cataclysmic disaster that completely

1:37:18

destroyed their environment which is

1:37:20

what Mars is, right? So like let's

1:37:22

assume that Mars was at one point in

1:37:24

time

1:37:26

was habitable and that life existed and

1:37:28

we know it was at one point in time. We

1:37:30

know there was water on Mars. We know

1:37:32

and there's some sort of evidence of at

1:37:34

least some sort of a very primitive

1:37:36

biological life on Mars.

1:37:39

>> If they got to a point where they said,

1:37:40

"Hey, this [ __ ] place is falling

1:37:42

apart, but this Earth spot looks pretty

1:37:44

good."

1:37:46

And they go there, but then cataclysms

1:37:48

happen on Earth and no one remembers cuz

1:37:50

all your information's on hard drives

1:37:52

and then you have to rebuild society.

1:37:54

And so you're re-remembering. And so you

1:37:57

have all these myths of how everything

1:37:59

started, you know, whether it's Adam and

1:38:02

Eve or the great flood or whatever these

1:38:03

things are that we passed down through

1:38:06

oral tradition for hundreds of years and

1:38:07

then eventually write it down and then

1:38:09

people try to decipher what it means and

1:38:11

they sit in church and try to go over

1:38:14

what what did it mean? Like what does

1:38:15

this mean? Like what what is the what is

1:38:17

the re the real origin of all these

1:38:19

stories? We don't know.

1:38:22

>> I mean that's crazy. It's crazy. But if

1:38:24

life it sounds nuts, why would life life

1:38:27

couldn't have possibly existed on Mars?

1:38:29

How the [ __ ] does life exist on Earth?

1:38:31

That how about that? How about why why

1:38:33

would we assume that it wouldn't have

1:38:35

existed at one point in time and

1:38:37

Terrence Howard who is a very

1:38:38

interesting guy.

1:38:39

>> Very interesting.

1:38:40

>> And got some

1:38:40

>> Europe is I mean

1:38:41

>> with Eric Weinstein crazy.

1:38:43

>> Yeah. Crazy.

1:38:44

>> Yeah, that one was crazy.

1:38:45

>> Um and him alone, but he's got some

1:38:47

[ __ ] weird ideas that you just make

1:38:50

you go. He's a very brilliant guy and

1:38:53

you know kind of a strange heterodox

1:38:55

thinker right and one of his ideas is

1:38:59

that

1:39:01

planets get to a certain distance from a

1:39:04

sun and they people and that it gets to

1:39:08

a certain climate and a certain distance

1:39:10

and his his

1:39:13

idea is that I don't know if you realize

1:39:15

that there's a a there's a giant um

1:39:18

ejection of of of some coronal mass

1:39:22

ejection that just happened recently on

1:39:24

the sun and they're very concerned about

1:39:26

it. They don't know what's going to

1:39:27

happen. It happens all the time. A sun

1:39:29

releases these giant chunks of material

1:39:33

>> and he thinks that these materials get

1:39:35

far enough away from the planet and then

1:39:37

they coalesce into planets or far enough

1:39:40

away from the sun. They coales into

1:39:41

planets and as time goes on they get a

1:39:44

further and further distance from the

1:39:46

sun and then obviously they get hit with

1:39:48

asteroids and there's panspermia and

1:39:51

water gets into them from comets and

1:39:54

then they develop oceans and then they

1:39:56

develop biological life and when they

1:39:58

have a certain amount of distance from

1:40:00

the sun they people and he thinks that

1:40:03

as they get further and further and

1:40:05

further away they get less and less

1:40:06

habitable and then they get to a point

1:40:09

where they have their techn technology

1:40:11

to a point where they realize like we

1:40:13

can't sustain life on this planet

1:40:15

anymore. We got to go to that other one.

1:40:18

And so do they go to the one that's

1:40:19

closer to the sun because they're too

1:40:21

far now.

1:40:23

>> It's a nutty idea.

1:40:24

>> Jesus Christ.

1:40:25

>> It's a nutty idea. But if you think

1:40:26

about how recent our sun is in terms of

1:40:31

the solar system itself, in terms of

1:40:32

rather the galaxy itself. So if the

1:40:34

universe, if the big bang is correct and

1:40:37

our universe existed and it was rather

1:40:40

our universe erupted from nothing or

1:40:43

from a very small thing 13.7 billion

1:40:46

years ago. Well, this [ __ ] planet's

1:40:48

only 4 something billion years old,

1:40:50

right? And life is only, you know, a

1:40:53

little bit less than that. Yeah.

1:40:54

>> So you have like a billion years or so

1:40:56

where there's nothing and then you start

1:40:58

getting single- cellled organisms,

1:40:59

multi-elled organisms, and eventually it

1:41:01

peoples.

1:41:02

And when it gets to a certain point when

1:41:04

these people have advanced their

1:41:06

curiosity and their innovation to the

1:41:08

point where they can harness space

1:41:10

travel and they use zero point energy

1:41:13

and they have a bunch of different

1:41:14

things that we haven't invented yet. And

1:41:16

then their environment degrades and it

1:41:18

gets to the point where they realize

1:41:20

like hey we're getting pummeled by

1:41:22

asteroids. We can't sustain life here

1:41:24

anymore.

1:41:24

>> We got to move

1:41:25

>> like Elon wants to go to Mars which

1:41:27

might be the wrong answer. We might want

1:41:29

to go that way.

1:41:30

>> There are closer to the sun.

1:41:32

>> Exactly. I mean, the thing is he's got

1:41:35

everything it he needs now to get there.

1:41:37

Like I

1:41:38

>> I'm not going. Are you going?

1:41:39

>> I would go.

1:41:40

>> [ __ ] that. I'll send you an email.

1:41:43

>> Hold on a second. Think Think about

1:41:44

Think about what he's going to take.

1:41:45

Okay, look.

1:41:47

>> When Let's just say he gets there with

1:41:48

the city. He has

1:41:50

>> he has the way to transport us there,

1:41:54

>> right?

1:41:54

>> Okay. Then when you land, he's got the

1:41:59

way to actually transport us around on

1:42:01

the

1:42:01

>> on the planet, right? He's got Tesla,

1:42:03

>> right?

1:42:04

>> He will have already sent a fleet of his

1:42:06

robots.

1:42:08

Those folks will have made some

1:42:10

inhabitable city

1:42:12

probably using the Boring Company drill

1:42:14

because you you're going to, you know,

1:42:15

be under the regalith that you don't

1:42:17

want to be on the top. Maybe you just

1:42:18

dig a hole and you you inhabit down

1:42:21

there.

1:42:22

>> Um he's got all the ways to make energy.

1:42:24

He has the AI to help you design the

1:42:27

stuff. He has the communication way to

1:42:30

communicate. He's got the internet, his

1:42:32

own internet. So that right

1:42:34

>> so he can get, you know, all of the

1:42:35

information to everybody. And then he's

1:42:38

got money and the super app so that you

1:42:41

can transact. And then I think to myself

1:42:43

like what is he actually missing? And

1:42:45

then what happens if he if he gets there

1:42:47

first? Is he just allowed to just do

1:42:51

whatever he wants? Like is it just kind

1:42:52

of like a free-for-all? like

1:42:54

>> well kind of

1:42:55

>> it's his constitution. Like is that what

1:42:56

happens?

1:42:57

>> Well, it's like earth but shittier.

1:43:00

>> Like we already have all those things

1:43:01

here. Why would you want to go to a

1:43:02

place where you die when you go outside?

1:43:04

>> I think what people will be attracted to

1:43:05

is that if he publishes his version of

1:43:07

what the rules are there, there's a

1:43:09

chance that he could make them really

1:43:11

different to what the rules are here.

1:43:12

>> Like what kind of rules would you do if

1:43:14

you were the king of Mars? Um

1:43:17

so I think that your view is incredibly

1:43:21

to me like um positive some like of

1:43:24

humanity of like we want to make things

1:43:26

better. Mhm.

1:43:27

>> So if I think about that as like a

1:43:28

function, what happens that that's like

1:43:31

so our natural rate of direction is

1:43:32

forward what pushes back on that and a

1:43:35

lot of it what you find is like

1:43:36

government regulation rules all that

1:43:38

stuff

1:43:38

>> greed

1:43:39

>> greed um too much focus on attention

1:43:42

>> right

1:43:43

>> so I would try to experiment with like

1:43:45

what the incentives would have to be so

1:43:47

that you had more unfettered

1:43:49

entrepreneurship like just like do the

1:43:51

thing that you think is right

1:43:52

>> and there's a mechanism where we give

1:43:54

you the ability to then make things for

1:43:57

more people because you're proving that

1:43:59

you're actually really good at making

1:44:00

things. And if you don't need money at

1:44:03

that point in society, reorienting us

1:44:06

away from this kind of like brittle form

1:44:09

of exchange to something more useful,

1:44:11

that's worth experimenting with. I think

1:44:12

that's an important

1:44:14

>> Well, there's also the concept of the

1:44:16

self of the individual which may erode

1:44:18

with technological innovation. So, if we

1:44:22

really can read each other's minds, if

1:44:25

we really do get to a point where we're

1:44:27

communicating through technologically

1:44:30

assisted telepathy, like a lot of the

1:44:34

whole the weirdness of people is I don't

1:44:37

know what you're thinking. I don't know

1:44:38

if I should trust you. You know, this

1:44:41

[ __ ] might be devious. You know,

1:44:43

you know what I mean? Well, we'll know,

1:44:45

right?

1:44:45

>> And there will be no need for all that

1:44:47

if we really are all one. If that's

1:44:50

ultimately something that can be

1:44:51

achieved with technology,

1:44:53

>> like this hive mind.

1:44:54

>> Yes. Like legitimate hive mind. And then

1:44:57

like look where society's going.

1:44:58

Gender's kind of falling apart. People

1:45:00

are getting they're reproducing less,

1:45:03

right? People are are having less

1:45:04

testosterone, more miscarriages, less

1:45:07

fertile. We're kind of moving into this

1:45:09

genderless direction. And I don't know

1:45:13

if it's by design, but microlastics and

1:45:18

phalates and all these different

1:45:20

chemicals that are endocrine disruptors

1:45:22

are all ubiquitous in our society. Well,

1:45:24

does

1:45:25

>> is that a coincidence that that's all

1:45:27

happening at the same time as

1:45:28

technological innovation on mass scale?

1:45:30

Is it? I don't know. Because like what's

1:45:32

the one thing that's holding us back?

1:45:35

Well, that we're territorial primates

1:45:38

with thermonuclear weapons and that we

1:45:41

exist in a sort of tribal mindset, but

1:45:43

yet we do it on a planet of 8 billion

1:45:46

people.

1:45:46

>> Yeah. No, no. The key differentiator of

1:45:48

humans is our our ability to enact

1:45:50

violence.

1:45:51

>> Yeah.

1:45:51

>> To to methodically execute premeditated

1:45:55

violence.

1:45:55

>> Yes. And and greed and attention. And

1:46:00

one of the things that attention is

1:46:02

sexual preference or or sexual rather

1:46:05

attention like the ability to procreate,

1:46:08

the ability to acquire mates, right?

1:46:10

Like the more resources you have, the

1:46:12

more attractive you'll be, especially

1:46:13

for males and males are the ones that

1:46:15

are involved in the violence in the

1:46:17

first place. You know, there's I can't

1:46:19

name a single war that was started by a

1:46:21

woman.

1:46:21

>> How do you how do you teach your kids

1:46:24

that attention is not everything?

1:46:29

That's a good question. Especially in

1:46:31

this society, it's probably harder to do

1:46:33

that now than ever before

1:46:35

>> because the reaction that I suspect most

1:46:36

kids will have is like,

1:46:39

"Stop. Like, leave me alone." Like, it's

1:46:42

just it's almost an impossible thing.

1:46:44

>> Well, I think kids learn more from their

1:46:48

parents' behavior than anything you say

1:46:50

to them. I think they learn from the way

1:46:53

you behave and the way you exist and the

1:46:57

way you exist with them.

1:46:58

>> And if you are constantly whoring

1:47:02

yourself out for attention,

1:47:05

>> it's one thing if you get a lot of

1:47:06

attention from what you do, but if

1:47:08

that's your primary goal, they're going

1:47:10

to know.

1:47:11

>> Do your kids know how famous and

1:47:13

influential you are? Like honest

1:47:14

question.

1:47:15

>> Oh, yeah. They know.

1:47:16

>> But do do they have a real sense of it

1:47:18

or do you just kind of like

1:47:20

>> Yes, they can. I mean, how can you? It's

1:47:22

got to be weird as [ __ ] growing up with

1:47:23

a very famous dad. It's very odd, but

1:47:27

it's not my primary goal.

1:47:29

>> Yeah, this is my point. You're not

1:47:30

You're not putting it in their face.

1:47:31

>> So, to your point, you're not modeling

1:47:33

attention is all you do.

1:47:34

>> No, no. I have interesting conversations

1:47:37

with cool people. I tell jokes and I

1:47:42

call fights. Like, those are the things

1:47:44

that I do.

1:47:45

>> And they also know that I have a very

1:47:47

strong work ethic and that I work

1:47:49

towards things. So they have very strong

1:47:50

work ethics. They're very motivated and

1:47:52

disciplined, like shockingly

1:47:54

disciplined. And I think that's modeled.

1:47:56

I think that that comes from and they

1:47:59

also like really enjoy achieving goals.

1:48:01

And they're they're rewarded for it with

1:48:04

praise and with admiration, but not

1:48:09

never with like you're better than other

1:48:11

people. Yeah. Ne never like it's the the

1:48:13

idea is like all human beings are

1:48:16

capable of greatness. So, it's like find

1:48:18

the thing that you excel at and if you

1:48:21

throw yourself into that, it's very

1:48:23

rewarding.

1:48:24

>> I really I really believe in this. I

1:48:26

tell this story when I interview people.

1:48:28

When I interview people, I'm always

1:48:29

like, you know, just at whatever

1:48:30

company, I'm always like I first only

1:48:32

want to know about them. I'm like, [ __ ]

1:48:34

your resume. Like, tell me about your

1:48:36

parents and how you grew up. I just want

1:48:38

to know that. Stop at 18. Everything

1:48:40

before 18. Just tell me every little

1:48:43

detail,

1:48:43

>> right?

1:48:44

>> You know, and some people tell me these

1:48:45

incredible stories. They'll be like, you

1:48:47

know, my mom was an alcoholic or this or

1:48:49

that. And I'm just like, man, this is so

1:48:52

valuable because it allows me to

1:48:54

understand who they are. The second part

1:48:56

of the interview,

1:48:57

>> we do the business [ __ ] But the third

1:48:59

part, I tell this story. This is a crazy

1:49:01

story about what you're just saying.

1:49:03

>> They ran this experiment at Stanford

1:49:05

where they take like a big bowl, fill it

1:49:08

with water, and they drop in a mouse and

1:49:11

they measure how long it takes for the

1:49:12

mouse to drown. They do it like a

1:49:15

hundred times. The average was about

1:49:16

four minutes, call it four, four and a

1:49:18

half minutes.

1:49:20

Then they run the experiment again, 100

1:49:22

mice, and at minute three or three and a

1:49:25

half, they take it out, they dry it off,

1:49:27

they play it music, and they whisper

1:49:29

like sweet nothings into the mouse's

1:49:31

ear. They drop the mouse back in the

1:49:32

water, and that mouse treads water for

1:49:37

60 hours the next hundred mice on

1:49:39

average. And the upper bound was 80. And

1:49:43

I thought to myself like that is all

1:49:46

just potential right there. Like that's

1:49:48

all like there's all this latent

1:49:50

potential. So if an animal has it, I'm

1:49:51

going to assume that humans have it too,

1:49:53

>> right?

1:49:54

>> But you never get a chance to unlock it.

1:49:56

Like the average person is just kind of

1:49:58

like living a life where they're maybe

1:50:00

scratching five or 10% of their

1:50:01

potential. And the question is, how do

1:50:03

you get to that other 90%. Like how does

1:50:04

the second batch of mice How do the

1:50:06

second batch of mice tread water for 60

1:50:08

hours?

1:50:09

>> Well, the doesn't make any sense to me.

1:50:10

all the same mice, right? I think the I

1:50:14

think the mice get rescued,

1:50:16

>> they get rescued

1:50:17

>> and then when they try it again those

1:50:20

same mice last longer, right? So it's

1:50:22

the same mice. So it's an experience.

1:50:25

>> So they have experience now. They

1:50:27

understand that they can tread water

1:50:29

where they didn't die. So they

1:50:31

understand that they can survive where

1:50:33

they didn't know that they could survive

1:50:34

the first time they were thrown into the

1:50:36

water because they had never been thrown

1:50:37

into water before. That's the same thing

1:50:39

that happens to people when they fight.

1:50:41

Like the first time people ever have a

1:50:43

competition, they [ __ ] panic and they

1:50:45

they get really scared and they get

1:50:47

really like filled with anxiety. But

1:50:50

after a while, you get relaxed and

1:50:52

that's when you get really dangerous

1:50:54

because then you get calm and you could

1:50:56

keep your [ __ ] together while you're in

1:50:58

the middle of all this chaos because you

1:51:00

have the experience of it. Without the

1:51:02

experience of it, very few people do

1:51:03

well the first time, right? Unless

1:51:05

you're exceptionally talented and and

1:51:07

you have other competition experience,

1:51:10

like you've competed in other things,

1:51:11

like maybe you played football or some

1:51:13

other things and you know what it's like

1:51:14

to actually perform under pressure.

1:51:16

>> What is the what is the version of

1:51:18

giving more humans a chance to get to

1:51:20

that?

1:51:22

Well, I think sports are really good for

1:51:25

that because performing under people

1:51:27

paying attention to you and performing

1:51:29

where people are trying to stop you from

1:51:31

doing something and you're trying to do

1:51:32

something and there's all these unknowns

1:51:35

and recognizing that hard work allows

1:51:38

you to do whatever you're trying to do

1:51:40

better than you previously had. One of

1:51:43

the things my martial arts instructor

1:51:44

said to me when I was young is that

1:51:46

martial arts are a vehicle for

1:51:48

developing your human potential. And

1:51:50

that through this very difficult thing

1:51:52

that you're trying to do,

1:51:54

>> you're learning that, oh, if I just

1:51:57

think smart and think hard and train

1:52:01

wise and train hard and discipline

1:52:04

myself to endure suffering so that I can

1:52:07

develop more endurance and more speed

1:52:09

and more power and more technique

1:52:11

because I accumulate all this

1:52:12

information and I really think about

1:52:13

what it is and apply it with drills and

1:52:16

with training, I can get better at this

1:52:18

thing. And every time I get better at

1:52:19

this thing, I get rewarded psychically,

1:52:21

like mentally, you feel better. Like I

1:52:23

know that I'm better now. And then

1:52:24

there's the belt system, right? You

1:52:26

start off, you're a white belt. And in

1:52:28

taekwondo, you get a blue belt and then

1:52:30

after you get a blue belt, you get a

1:52:31

green belt. And then if you get a I

1:52:33

think it's green belt first and then I

1:52:34

forget how it goes. And then it's red

1:52:36

belt and black belt. And like when

1:52:37

you're a black belt, like holy [ __ ] So

1:52:39

it's this thing where you've developed

1:52:41

to a point where you've gotten to this

1:52:43

next stage. So all along the way you've

1:52:45

been rewarded for your hard work and

1:52:48

then you realize like oh I could do this

1:52:50

with everything in life.

1:52:51

>> Is a reward different than attention? It

1:52:53

is.

1:52:53

>> It is because it's internal right.

1:52:56

You're you're all you're realizing that

1:52:59

you could apply this to you know

1:53:01

whatever it is to carpentry to music.

1:53:04

You you just it's just a matter of focus

1:53:07

and attention. And some people

1:53:08

unfortunately never find a vehicle. They

1:53:11

never find a thing that they can throw

1:53:13

themselves into. They realize like, and

1:53:15

this is not unique. It's not like I'm an

1:53:19

unusual person or anybody is. I mean,

1:53:22

there's people that have unusual

1:53:24

physical gifts and some people have

1:53:26

unusual mental gifts. But the reality

1:53:28

is, no matter where you start, everyone

1:53:31

can get better. And when you do

1:53:33

something, whether it's learning to play

1:53:34

guitar, as you get better at it, you

1:53:36

realize like, oh, this is what it's all

1:53:39

about. Yeah. Like it's really all about

1:53:41

applying yourself to something and then

1:53:43

feeling this immense satisfaction of

1:53:46

your hard work paying off and that

1:53:48

motivates you to work hard at other

1:53:50

things. And if you don't find that early

1:53:52

on, it's very difficult to like find

1:53:55

like real satisfaction.

1:53:57

>> Yeah.

1:53:57

>> In life.

1:53:58

>> Yeah. I've always had something outside

1:54:00

of my

1:54:02

daily life

1:54:04

that is the thing that I actually care

1:54:06

about and it actually energizes me for

1:54:08

my day-to-day life. I don't know if

1:54:10

that's like a lot of people but

1:54:11

>> like what do you do? What's your take?

1:54:12

>> Like well initially it was poker and I

1:54:16

and even now I obsess about the game um

1:54:19

because it's infinitely more complex

1:54:21

than chess. Like chess you can get to a

1:54:23

place where you can roughly be good.

1:54:25

Poker is just constantly there's just

1:54:28

too many variables. There's human

1:54:30

emotion, there's human psychology,

1:54:32

the number of people, all of this stuff

1:54:34

just makes the complexity of the game

1:54:37

something that I find magical.

1:54:39

>> And so I sit there and I try to

1:54:41

understand like why am I doing the

1:54:42

things that I'm doing? And so much of it

1:54:44

comes back to being a mirror about

1:54:46

what's happening in my daily life. It's

1:54:48

the [ __ ] craziest thing. Like I'm

1:54:50

super insecure. I'll go into poker and I

1:54:52

will just lose for weeks at a time. But

1:54:54

it's because I'm insecure in my daily

1:54:56

life. And what's happening is that I'm

1:54:58

trying to find these quick wins and

1:55:00

quick solutions

1:55:01

>> because I'm in a state of insecurity.

1:55:03

I'm anxious. I have this anxiety. And so

1:55:06

it's become a great mirror for me. So

1:55:08

that used to be a thing. It still is a

1:55:10

thing. And but I've become reasonably

1:55:13

skilled at it where the edges are

1:55:16

smaller and I put myself in positions

1:55:18

where I'm only playing against a certain

1:55:20

group of people and I'm the losing

1:55:22

player frankly in that game. if when I'm

1:55:24

playing against like the top pros,

1:55:27

it just doesn't it helps me and I can

1:55:29

get tuned up for it. But then I started

1:55:32

to, you know, I would take different

1:55:33

things. I tried to learn how to ski.

1:55:35

Basically impossible when you're older.

1:55:37

I look like a [ __ ] idiot. Like

1:55:38

>> how old were you when you tried?

1:55:40

>> Uh I started when I was like, you know,

1:55:42

I I was a good snowboarder, so I was

1:55:43

snowboarding my whole life. And then my

1:55:45

kids skied and so I'm like, okay, well,

1:55:47

I want to do this as a family. So I was

1:55:49

like 42 or something when I tried. I'm

1:55:51

49 now, almost 50.

1:55:54

It's brutal. I mean, it's like I look

1:55:55

like a [ __ ] idiot. Like this gangly

1:55:58

giraffe like trying to get down the

1:55:59

mountain. And then now I start at golf

1:56:02

and man, I got to tell you, I used to

1:56:06

play a little bit, then I stopped. But

1:56:08

there's something to me about being

1:56:09

outside

1:56:11

where just like being in nature I find

1:56:14

like really motivating.

1:56:16

>> It's a vitamin.

1:56:17

>> It's a vitamin. And then just the mind

1:56:19

body connection of that game, it just

1:56:21

really [ __ ] with you because it's it's

1:56:23

just nothing you can master and

1:56:25

overpower,

1:56:26

>> right?

1:56:27

>> And it teaches you to just like be in

1:56:29

it.

1:56:30

>> Yeah.

1:56:30

>> And that's a very hard skill. Like if

1:56:34

you look at the best like I there's like

1:56:36

a handful of people that I really look

1:56:37

up to and I obsess like Mer Buffett, but

1:56:40

the Berkshire meeting was this past

1:56:42

weekend and if you look at the clips,

1:56:43

there's this incredible thing where they

1:56:46

transitioned, right? Mer passed away.

1:56:48

Buffett's like now executive chairman.

1:56:50

But this guy Greg Ael and this guy Ajet

1:56:52

Jane. Ajet Jane does this thing where

1:56:53

he's like, I teach the people that come

1:56:55

to just say no. Your whole job is to

1:56:58

just say no. You're going to get

1:56:59

bombarded with all kinds of business

1:57:00

pitches. Say no, no, no. And eventually

1:57:03

somebody will come and [ __ ] try to

1:57:04

whack you in the head with a 2x4 of

1:57:06

money. Then you come to me and we'll do

1:57:08

the deal. And it made such an impression

1:57:11

because like again when I'm insecure,

1:57:15

my reward function is attention. So I'm

1:57:17

like a [ __ ] little busy body. I'm

1:57:18

running around doing all this little

1:57:20

[ __ ] you know? E. And then man,

1:57:23

when I'm in a [ __ ] flow state and

1:57:25

like I'm tunning it, like I'm striping

1:57:27

the ball, you know? I'm like a few

1:57:29

things that really matter in size and

1:57:31

I'm like, man, this is this is right.

1:57:35

It's all come to me because I'm like I'm

1:57:38

like within myself and these other

1:57:41

things are a better reflection of when

1:57:43

I'm within myself and these other things

1:57:45

are a mirror of when I'm totally out of

1:57:47

kilter.

1:57:48

>> That's just me.

1:57:50

>> So in my life these things tend to lead.

1:57:53

>> Um

1:57:54

>> I think you're saying that's just you,

1:57:55

but I think that's generally most

1:57:57

people. I think you find these things,

1:58:01

these vehicles for developing human

1:58:04

potential, whether it's martial arts or

1:58:05

golf or playing guitar or playing chess

1:58:08

or poker.

1:58:09

>> And then you have to have, I think, one,

1:58:11

at least for me, one seinal relationship

1:58:14

in your life. You have to have one

1:58:16

person that has just undying belief in

1:58:18

you. And I never really had that until I

1:58:21

met my wife. And that was a very, and I

1:58:23

didn't I pushed against it so [ __ ]

1:58:25

hard because I was like, it just can't

1:58:27

be true. like why does this person give

1:58:29

a [ __ ] Do you know what I mean? Like

1:58:31

why do they care about me more than I

1:58:32

do?

1:58:32

>> Well, there's also the fear because so

1:58:34

many people get in those bad

1:58:35

relationships.

1:58:36

>> And I'm just like I I think there's a

1:58:38

part of you like me where you're just

1:58:40

like I'm not a very lovable person. Like

1:58:42

I'm just like this is that's not who I

1:58:44

am. And this woman is just there.

1:58:48

So that's been like the thing like for

1:58:50

me it's like and because she's brutal.

1:58:52

She'll be like, "Oh yeah, that was

1:58:53

[ __ ] horrible." You know, like

1:58:55

yesterday I like we had this we I I I

1:58:57

did this thing at at Milk and it was a

1:58:59

dinner at my friend's house and uh then

1:59:02

you know, we're both going to different

1:59:03

airports. I'm flying here to see you and

1:59:05

she's flying home and uh she calls me

1:59:08

and I'm like I'm how did I do? Ah [ __ ]

1:59:16

But but no, there's the parts that I did

1:59:18

well and then she critiques the other

1:59:19

parts that she didn't like. And then I

1:59:21

say which is like it's and it's so again

1:59:24

I'm insecure so I'm like I want the

1:59:25

self- serving well how would because

1:59:27

there was three of us on this panel and

1:59:29

she's like uh and I was like you know I

1:59:31

was the best right? She's like no Gavin

1:59:34

was better. I'm just like it's so but

1:59:37

it's so refreshing because it keep again

1:59:39

it's like a

1:59:40

>> keeps you in check

1:59:41

>> like and it gives me a mirror.

1:59:43

>> Mhm.

1:59:43

>> You know like when I was coming to see

1:59:46

you yesterday when we were flying down

1:59:48

to LA for this thing um there's parts of

1:59:52

me where when I'm insecure I kind of

1:59:54

like externalize and I can be like

1:59:57

really hyperbolic unnecessarily

1:59:58

hyperbolic and it's counterproductive.

2:00:01

And she said to me listen like just

2:00:02

imagine your friends these are

2:00:04

hardworking people. They're trying their

2:00:05

best as well. They don't necessarily

2:00:07

know. Some some things have massively

2:00:08

worked out for them, but they would want

2:00:10

to do the right thing. There's people

2:00:12

you've worked with before that want to

2:00:13

do the right thing. And she's like, just

2:00:15

picture them and don't judge. You can

2:00:16

observe.

2:00:19

And it's crazy, but it's like I need

2:00:20

those little things. There's like

2:00:22

tweaks. It's like having a coach kind of

2:00:23

like

2:00:24

>> and that and that's very that's very

2:00:26

helpful to me.

2:00:26

>> Yeah. It's very important. It's hard to

2:00:28

do that yourself.

2:00:29

>> I can't do it.

2:00:30

>> And it's also like

2:00:31

>> I'm [ __ ] maxing. Like my life is like

2:00:33

I like that flow. Mhm.

2:00:34

>> And if if I didn't have somebody who

2:00:36

loved me and would hold me accountable,

2:00:38

I' just [ __ ] not think about it.

2:00:40

>> Yeah. And the opposite of that is

2:00:42

someone who's like an antagonistic

2:00:44

relationship. And we know a lot of

2:00:46

people that have those kind of very

2:00:48

sabotagey sort of marriages and

2:00:50

relationships. And that's crazy.

2:00:52

>> It's brutal.

2:00:53

>> It's brutal. And I don't think they've

2:00:55

ever had a really good one. Otherwise,

2:00:56

they would never tolerate that.

2:00:59

>> I didn't know what good looked like. So

2:01:01

you kind of just I think a lot of people

2:01:03

go with the flow. Like I mean I was a

2:01:06

nerdy kid from kind of a shitty [ __ ]

2:01:09

up kind of like family structure

2:01:13

and then I got injected into this rich

2:01:15

high school but then I got to go back to

2:01:18

an alcoholic father. I'm on [ __ ]

2:01:19

welfare. Like it's like you know my my

2:01:22

self-confidence is negative [ __ ] two

2:01:24

units.

2:01:25

>> Didn't have a girlfriend. You know like

2:01:26

all the [ __ ] in high school like nothing

2:01:28

happened for me. And so my modeling of

2:01:31

like how to be in a relationship, what

2:01:32

to do, it was [ __ ] zero.

2:01:36

Um, it was zero. And so all those

2:01:39

mistakes were mostly because I didn't

2:01:41

understand what good looked like,

2:01:43

>> right?

2:01:44

>> Um, and then I stumbled into this

2:01:45

relationship after my divorce and my

2:01:47

ex-wife is an incredible woman. Just

2:01:49

like not,

2:01:50

>> you know,

2:01:50

>> what you needed or what she needed.

2:01:52

>> Yeah. She's we're just we were in in in

2:01:54

a few very specific ways,

2:01:57

>> we just weren't on the same page.

2:01:59

And then I find this other one and it's

2:02:03

and I think like I don't I was so

2:02:05

skeptical. I'm like I I kind of viewed

2:02:08

like a relationship as like this adjunct

2:02:10

to your life. There's you you're at the

2:02:13

center. M

2:02:14

>> you're doing your [ __ ] and one of the

2:02:16

appendages to your thing is you're

2:02:19

that's what I thought and then now it's

2:02:21

the opposite where I feel like my wife's

2:02:24

at the center and I'm like I would

2:02:26

always kind of like like almost like

2:02:28

laugh at people in the in my mind I'm

2:02:30

like it's not possible that somebody

2:02:31

feels this way about somebody else.

2:02:34

>> Um but it's an it's an it's a huge

2:02:36

enabler. It's a it's a very much a gift.

2:02:39

So that can also be a thing that people

2:02:40

look for. You know what I mean? which is

2:02:42

>> I think what you're saying is that

2:02:43

there's a bunch of different things that

2:02:46

have to sort of exist together and that

2:02:49

it's not just completely focus on your

2:02:51

work but that focusing on these other

2:02:54

things enhances the work and then the

2:02:57

work enhances all these other things as

2:02:58

well and they all exist together

2:03:00

>> and my best work is when I'm not

2:03:02

thinking about the attention or the

2:03:05

money. Those are the two most corrupting

2:03:07

influences in my life. If I if when I

2:03:09

look back and when I've lost when I've

2:03:11

lost the most amount of money

2:03:13

>> or when I've reputationally hurt myself

2:03:15

the most,

2:03:16

>> it's all been because of attention and

2:03:18

money.

2:03:19

>> Those are the only two things the root

2:03:21

cause consistently has been that.

2:03:23

>> That makes sense because you're thinking

2:03:24

about a result rather than the process.

2:03:27

>> Exactly.

2:03:27

>> Yeah.

2:03:28

>> Exactly.

2:03:29

>> So, and then thinking about that result

2:03:30

like oo I'm going to get a lot of

2:03:31

attention from this. Oo, I'm going to

2:03:33

get a lot of money from this. That

2:03:34

actually robs you of the focus that you

2:03:36

need to concentrate on the process.

2:03:38

>> Exactly. And the the thing about the

2:03:40

process is that so much of that when

2:03:44

you're in a flow state you're proud of

2:03:47

>> irrespective of the size of it because

2:03:49

the meetings are the same. Do you know

2:03:51

what I mean? Like

2:03:52

>> you're in the same [ __ ] 35 minute

2:03:54

meeting or 45 minute meeting debating a

2:03:56

product or debating a thing.

2:03:59

But the minute that I start to feel like

2:04:00

embarrassed about company A versus

2:04:02

company B or decision A versus decision

2:04:04

B,

2:04:05

>> now my mind is like, "Okay, hold on a

2:04:07

second here. I'm about to run myself off

2:04:09

the cliff."

2:04:09

>> Yeah.

2:04:10

>> You know, or you know, we I had this

2:04:12

dinner last week and this is what's

2:04:13

amazing. Like

2:04:16

we're talking about poker. Well, I So

2:04:18

I'm having dinner with my wife and a

2:04:20

friend and uh

2:04:23

she's like, "How are you doing?" Just

2:04:25

like a very generic nice question,

2:04:27

>> right? And I go into this long [ __ ]

2:04:29

diet tribe of like, well, you know, the

2:04:31

investing thing this, and then I started

2:04:33

this other thing that. And my wife's

2:04:34

looking at me like, what the [ __ ] are

2:04:35

you rambling on about? And then it got

2:04:37

But it got worse, Joe. It got worse. It

2:04:39

got even [ __ ] worse. Then I'm like,

2:04:41

uh, you know, but then I had this poker

2:04:43

game. I started rambling on. It's

2:04:45

normally on Thursdays, but then I I

2:04:46

moved it up to Wednesdays, but then I

2:04:48

moved it up to the city because my

2:04:49

friend's having it. And then I name

2:04:50

dropped who the guy was. And my wife

2:04:53

just looks at me like, "What the [ __ ] is

2:04:55

going on with you?

2:04:57

So, the dinner ends. It was And then

2:05:00

she's like, "What the [ __ ] is going on

2:05:01

with you?" She's like, "That was

2:05:03

insane." And I had no idea that I was

2:05:07

doing it.

2:05:09

And I'm like, "Okay, we need to put

2:05:10

Humpty Dumpty back together again

2:05:11

because I'm about to go on Rogan and I

2:05:13

can't go off [ __ ] like a crazy wild

2:05:14

man." Uh, but it's a it's it's an

2:05:17

enormous gift. That's been my biggest

2:05:19

unlock in these last like eight or nine

2:05:21

years. Like I I feel like like I'm kind

2:05:23

of like adding skills to my toolkit. I

2:05:25

feel like a golfer like that's like I

2:05:27

can shape shots a little bit now. I know

2:05:29

how to use different clubs.

2:05:31

>> Um and it's all like mindset

2:05:34

>> and it's like it's very much what you

2:05:36

it's like this processoriented approach

2:05:38

>> and you just can't control the outcome

2:05:41

and that's like a it's a magical

2:05:44

feeling. It's interesting that you're

2:05:46

saying this because like think about

2:05:48

what most people or people that are on

2:05:52

social media like the kind of attention

2:05:55

that they're focusing on. Like this is

2:05:58

why virtue signaling is so unsuccessful,

2:06:01

right? It's so bad for it because it's

2:06:02

fake. You're really concentrating on the

2:06:04

process. Are you really concentrating on

2:06:05

the result? The result is getting people

2:06:07

to love you. Exactly. Getting people to

2:06:08

agree with you. Getting and then

2:06:09

worrying about the criticism. Oh my god,

2:06:11

they hate me. Oh my god, they're mad at

2:06:12

my my statement. Oh my god, they're this

2:06:14

and then you're like obsessing on it all

2:06:16

day. People that aren't even anywhere

2:06:17

near you. It's like it's one of the

2:06:19

absolute worst things for mental health

2:06:21

is this addiction that people have to

2:06:24

posting things and then reading the

2:06:25

responses to those posts and getting

2:06:28

wrapped up in these very weird

2:06:30

two-dimensional interactions with human

2:06:33

beings.

2:06:33

>> You never read your comments. I mean,

2:06:34

you're very famous. You're like, it

2:06:36

doesn't [ __ ] matter to me. Well,

2:06:38

you're going to get to a certain point

2:06:39

in time where if you have x amount of

2:06:42

people that follow you, you're going to

2:06:44

have a percentage that are mad at you

2:06:47

and those are the ones you're going to

2:06:48

think about, right?

2:06:49

>> And if you don't self audit, maybe

2:06:51

that's good. Maybe it's good to say

2:06:53

like, "You [ __ ] piece of shit." Like,

2:06:54

"Oh, I'm sorry." You know, like what

2:06:56

your wife saying to you like, "What the

2:06:57

[ __ ] was that?" Like, "Ah, shit." Like,

2:07:00

I am very self-critical. Very like

2:07:03

horribly so. like to the point I torture

2:07:05

myself, you know? So, I'm like, I don't

2:07:07

need that from other people. And also,

2:07:09

those people don't love me and they want

2:07:11

me to fail. Like, there's a lot of

2:07:12

people that their lives are very

2:07:14

unsuccessful and I've been way too

2:07:16

fortunate, right? So, it's like there's

2:07:18

a reason to be upset at me if your life

2:07:20

is [ __ ] because I've I've gotten I've

2:07:22

three of the best jobs on earth. It

2:07:24

doesn't make any sense, right? So,

2:07:25

there's a re and also why the [ __ ] is

2:07:27

this podcast so successful? That doesn't

2:07:28

make any sense, right? So, it's like I

2:07:31

get it. I understand why people, but I'm

2:07:33

not gonna help them. I'm not gonna help

2:07:35

them bring me down. I'm not gonna

2:07:37

indulge in it and ruin my own mind by

2:07:39

wallowing in their [ __ ] because the

2:07:41

only reason why you would do that in the

2:07:42

first place is if you're not together.

2:07:44

No one is healthy and happy and

2:07:46

intelligent is going to post mean things

2:07:49

about you. So, you are reading things

2:07:51

from people that are mentally ill,

2:07:53

unhappy, and probably not. Maybe they're

2:07:56

intelligent in terms of their ability to

2:07:58

solve certain issues and problems. Maybe

2:08:00

they're good at certain skills, but like

2:08:02

their overall grasp of humanity and like

2:08:05

being a good person is not good if

2:08:08

you're [ __ ] on people, especially if

2:08:09

you like add homonym attacks and just

2:08:12

insults. And

2:08:13

>> so, it's not a good thing to ingest.

2:08:16

It's not It's like if you go down the

2:08:17

supermarket, you see Twinkies, oh,

2:08:18

they're right there. Don't [ __ ] eat

2:08:20

them, okay? That's not good for you. And

2:08:23

so it's like I don't think that at a

2:08:25

certain point in time, especially if you

2:08:27

become publicly known and famous, you

2:08:29

should ever read your comments. I don't

2:08:30

think it's good for you.

2:08:31

>> Yeah.

2:08:32

>> But you better be self- auditing or

2:08:35

you'll start sniffing your own farts and

2:08:36

think they smell great. Like don't do

2:08:38

that either.

2:08:39

>> Yeah.

2:08:39

>> But you I know a lot of people that have

2:08:43

gone crazy reading their own comments.

2:08:45

I've met comedians that like they'll

2:08:47

think about it all day long. It will

2:08:49

[ __ ] with them. It will tort. Well,

2:08:51

their neurosis are what's what creates

2:08:53

great comedy to begin with. So, if you

2:08:54

feed that neurosis in the wrong way,

2:08:56

you're [ __ ]

2:08:56

>> The wrong way, right? And then also the

2:08:58

self-doubt creeps in because all these

2:09:00

people telling you you suck and they're

2:09:01

like, "Oh my god, I suck." And then you

2:09:03

go on stage with this like, "People

2:09:04

think I suck, they hate me." You can't

2:09:06

do that. Like, if you

2:09:09

have a certain amount of energy in the

2:09:12

day, this is what I always tell

2:09:13

comedians. I said, "Look, think of your

2:09:16

attention and your focus as a a unit.

2:09:18

You have a hundred units. If you spend

2:09:21

30 of those [ __ ] units on [ __ ]

2:09:23

online, you're robbing 30 units from all

2:09:26

the things you love. 30 units from your

2:09:28

family, 30 units from your friends, 30

2:09:30

units from your job, 30 units from golf

2:09:33

or poker or whatever it is that you love

2:09:35

to do. You're stealing your own time and

2:09:38

your own focus

2:09:39

>> for loers, right?

2:09:41

>> Like why would you do that? And those

2:09:43

losers are good people. They're just

2:09:44

they most people are good people. They

2:09:46

just a bad path. I would have been the

2:09:48

personing. Yeah. Yeah. Look, if you gave

2:09:51

me a [ __ ] Twitter account when I was

2:09:52

16, oh my god, it would have been

2:09:55

horrendous.

2:09:55

>> Yeah. I would have been going crazy.

2:09:56

>> Oh my god. I would have been a terrible

2:09:58

person. It's normal. Especially if your

2:10:00

life sucks and you're not doing well and

2:10:03

you're attacking famous people or you're

2:10:04

attacking this person that's doing

2:10:06

better than you or whatever it is.

2:10:07

>> Like it's Do you uh have you seen the

2:10:09

clips of the [ __ ] maxing?

2:10:12

>> No.

2:10:12

>> You don't know what this is?

2:10:13

>> No.

2:10:13

>> You don't know what this is?

2:10:14

>> No. What's [ __ ] maxing?

2:10:16

>> Oh, this guy is fantastic. He sits He

2:10:19

sits on his back porch. Jamie, can

2:10:20

Jamie, can you just show He sits He sits

2:10:23

on his back porch smoking a cigar

2:10:27

basically telling you everything's kind

2:10:29

of [ __ ] Stop thinking about [ __ ]

2:10:31

You know, if you don't like your

2:10:33

friends, leave them. If you don't like

2:10:34

your girlfriend, leave them. Stop

2:10:36

overthinking. Simplify your life. You

2:10:38

know, it's it's inc it's so simple, but

2:10:42

I think it's incredibly

2:10:43

>> Who is this guy?

2:10:44

>> Elisha Long, I think, is his name. I

2:10:46

don't know Jamie if you can find it. I

2:10:47

think Elisha

2:10:48

>> [ __ ] maxing is funny because I know

2:10:49

about looks maxing. We talked about that

2:10:52

recently on a podcast but that's

2:10:53

recently entered into my mind into my

2:10:56

zeitgeist. looks max.

2:10:58

>> That's the clvicular, but I've only

2:11:00

found out about that within the last few

2:11:01

months of life because I I genuinely

2:11:04

stay off social media as much as

2:11:05

possible. And if I do read things, what

2:11:08

I like to do, I like to focus on

2:11:10

fascinating things. Like a lot of my

2:11:12

time I spend looking at YouTube stuff

2:11:14

because YouTube stuff, my algorithm is

2:11:16

all like new black holes they've

2:11:18

discovered, you know, new discoveries in

2:11:21

terms of like what is the fabric of

2:11:23

reality? Like I'm that's interesting to

2:11:26

me. And if I just concentrate on people

2:11:28

being mean or shitty to each other or

2:11:30

the latest [ __ ] political drama, it's

2:11:32

like

2:11:34

>> what? I don't have much time. I'm busy.

2:11:37

I like things.

2:11:38

>> And

2:11:39

>> are you are you on like Instagram and

2:11:41

Tik Tok?

2:11:41

>> I'm on Instagram. I do not have a Tik

2:11:43

Tok. This is Luke Maxing. No, this is

2:11:46

[ __ ] maxing. So, let me hear what he

2:11:48

says.

2:11:49

>> Who's this guy? What's his name?

2:11:50

>> Elisha Long.

2:11:51

>> Shout out to Elisha. being used as a

2:11:54

poisoning of nostalgia,

2:11:56

but to simply remind you of what you

2:11:59

found it for. And as we grow up, we

2:12:03

often give that up for security. We give

2:12:05

that up so that we're accepted. We give

2:12:07

that up to flex and appear like we have

2:12:10

now figured things out, that people will

2:12:13

accept us.

2:12:15

The only way that you will truly be

2:12:17

successful is if you are righteous and

2:12:21

you live according to your nature and

2:12:23

you play, man, and you don't let people

2:12:25

take play away from you to to be at the

2:12:28

circus and be ooed and aed and worried

2:12:31

about all the [ __ ] Return to a

2:12:33

state of play.

2:12:35

>> Well, that's very good advice.

2:12:38

Return to [ __ ] max. The best thing

2:12:41

that you could do is return to a state

2:12:42

of play. That's true. There's a lot of

2:12:44

that, you know. There's a lot of that.

2:12:46

Absolutely.

2:12:47

>> Oh, I I I think that that is like a It's

2:12:49

a

2:12:49

>> It's a wise man for a young fella.

2:12:51

>> Yeah.

2:12:52

>> Okay. He's a jiu-jitsu guy. There you

2:12:53

go. Look, he's getting his [ __ ] blue

2:12:55

belt there. Or he's getting his purple

2:12:56

belt. What is going on there? So, is he

2:12:59

getting his blue belt?

2:13:00

>> Yeah, it's his purple.

2:13:02

>> Yeah. So, they're taking his blue belt

2:13:03

off and putting his purple belt on.

2:13:05

Yeah. See, that's he's learning. He's a

2:13:06

martial artist. That's why.

2:13:08

>> You think martial arts people are just

2:13:10

more like spiritually connected to the

2:13:12

truth? I don't know if it's spiritually

2:13:13

connected to the truth. It's forced down

2:13:15

your [ __ ] throat because you can't

2:13:17

believe you're better than you are if

2:13:19

you're getting mauled every day,

2:13:22

you know? And there's only one way. This

2:13:25

guy's on the path to becoming a

2:13:26

jiu-jitsu black belt. Looks like a

2:13:27

pretty big guy, too. That'll help. Um,

2:13:29

but there's only one way to get a black

2:13:32

belt in jiu-jitsu. You got to train

2:13:33

jiu-jitsu all the time and get better at

2:13:35

jiu-jitsu. You can't pretend you're

2:13:36

better. You know, there's a lot of

2:13:38

people that write poems and they suck

2:13:39

and they think they're so deep.

2:13:41

>> Yeah. this poem

2:13:42

>> meaning like there's just a very simple

2:13:44

objective measurement that says

2:13:45

>> 100%. You either win or you lose. You

2:13:48

either tap or you get tapped out. You

2:13:51

know, you tap somebody or you get

2:13:53

>> Can you get a black belt in some gym

2:13:55

that's easier than a different gym or

2:13:57

something like that or

2:13:58

>> sort of kind of but not really. I mean,

2:14:01

everybody's trying hard. I mean, there's

2:14:03

definitely better gyms where they're

2:14:04

more technical and their program is much

2:14:07

more systematic and they're better at

2:14:09

breaking down skills like how to develop

2:14:11

skills, you know. Um there's definitely

2:14:14

better gyms. Uh there's better schools,

2:14:17

there's better places to learn, but

2:14:18

everywhere you learn, you're going to

2:14:20

have a bunch of people that are trying

2:14:22

hard like and you have a bunch of people

2:14:24

that are trying to learn these. And also

2:14:25

today because of the internet, you could

2:14:28

go on YouTube and there's thousands of

2:14:32

tutorials breaking down new moves.

2:14:34

Jiu-Jitsu is like endlessly comp.

2:14:36

>> One of my one of my kids has ADHD and

2:14:38

one of the things that was recommended

2:14:40

to us was jiu-jitsu.

2:14:41

>> Yeah. What is ADHD, man? It's not even

2:14:42

[ __ ] real cuz I definitely have it.

2:14:44

And I think I think it's a superpower.

2:14:47

>> I think we all have it.

2:14:48

>> I think I look I do not focus well on

2:14:51

things that I think are boring. But if

2:14:52

you give me something that that I love,

2:14:54

I can't I'll I'll play pool for [ __ ]

2:14:56

12 hours in a row.

2:14:57

>> It's crazy. But like the reason I got

2:14:58

back into golf is my seven-year-old gets

2:15:00

on the course and sometimes you can talk

2:15:02

to him and he's not making, you know,

2:15:03

he's like just like in his own world.

2:15:05

>> Exactly.

2:15:05

>> And then you start talking about chess

2:15:07

or jiu-jitsu or whatever and then we get

2:15:10

him on the golf course and this kid is

2:15:12

just dialed in.

2:15:13

>> Yeah. Superpower.

2:15:14

>> And I'm like, "Holy shit."

2:15:15

>> And they say that that's a disease.

2:15:17

That's crazy. Because if you find a

2:15:19

thing that that kid loves, he's going to

2:15:21

excel at it above and beyond most

2:15:23

humans.

2:15:23

>> We uh he does these chess classes and

2:15:26

like look, he's seven. So I'm like, "All

2:15:28

right, [ __ ] Bring it. [ __ ]

2:15:30

[ __ ] destroy you. I'm going to

2:15:31

[ __ ] ball you." And uh we're playing

2:15:35

last weekend and he goes, "Oh, Dad, you

2:15:38

know you can't castle out of check." I'm

2:15:40

like, "Shut the [ __ ] up. I know how this

2:15:42

game works." And I go on to beat him and

2:15:44

I and I went to my wife and I'm like,

2:15:47

he's six weeks away from beating me. I

2:15:48

got to go.

2:15:51

And then I spent I spent two days I

2:15:53

spent two [ __ ] days on YouTube and I

2:15:56

was like, "Okay, I got to brush up on my

2:15:58

openings and I got to I got Oh my god, I

2:16:00

don't have time for this [ __ ]

2:16:01

>> But I can't let this sevenyear-old beat

2:16:03

me.

2:16:05

>> You know what I mean? You're going to

2:16:06

have to."

2:16:06

>> And I'm like And I was like, "How do I

2:16:08

how do I stall this until maybe he's 10

2:16:10

or 11?" Then it's like, "Okay, fine. You

2:16:11

finally beat me. Congratulations.

2:16:13

>> You have to think of him as an extension

2:16:15

of you and be happy when he does.

2:16:16

>> Oh my god.

2:16:17

>> Yeah. That's just how it is. Look, if

2:16:19

you're a man and you have a son, I I

2:16:21

have all daughters, but if I had a son,

2:16:24

I would be legitimately terrified that

2:16:26

he'd be able to tap me. Because if I had

2:16:29

a son, one of the first things that I

2:16:31

would do is get them. I got my kids

2:16:32

involved in martial arts at an early

2:16:33

age, but I didn't force them to keep

2:16:35

doing it. They did it for a certain

2:16:36

amount of time, and then they went on to

2:16:37

do a bunch of other things that they

2:16:38

enjoy better,

2:16:39

>> which is fine. But I think it's good to

2:16:41

learn some skills, learn how to defend

2:16:43

yourself so you're not completely lost.

2:16:46

Just it's I think it's good for you.

2:16:47

It's good to learn. It's good to develop

2:16:49

confidence. But for boys, I think it's

2:16:51

critical, you know, especially boys with

2:16:53

my kind of DNA. I'm like, I think it's

2:16:55

good to get that [ __ ] out of your

2:16:56

system. But if I had a son, there'd be a

2:16:58

certain point in time. I'm like, it's a

2:16:59

matter of time before this [ __ ]

2:17:01

can kill me. You know, it's like I mean,

2:17:04

I'm 58 years old. If I had a 20-year-old

2:17:06

kid, like, he'd probably kill me.

2:17:07

>> Kick your ass.

2:17:08

>> Probably [ __ ] kill me.

2:17:09

>> He'd kick your ass. Yeah. It's like what

2:17:11

am I going to do? There's nothing you

2:17:12

can do. You just have to accept it and

2:17:13

then hope your relationship with him is

2:17:15

strong enough that he still respects you

2:17:16

even though he can kill you because it

2:17:18

can't be entirely ba. Look, there's a

2:17:21

lot of martial arts instructors that are

2:17:23

old and they're revered and respected

2:17:25

and nobody wants to try to hurt them,

2:17:27

right? Because you realize if you learn

2:17:30

enough, you get to a certain point in

2:17:31

time, you realize like

2:17:32

>> I'm a much better dad to my sons than I

2:17:35

am my daughters. And I mean this in the

2:17:36

following way. My daughters have the run

2:17:38

of the place. Whatever they want, I'm in

2:17:40

love with them. I don't love them. I'm

2:17:41

in love with them. Whatever they need,

2:17:43

what they can just

2:17:44

>> enamored by.

2:17:45

>> They're just like they can control me.

2:17:47

They just kind of send me in one

2:17:48

direction or another. I'm just like

2:17:49

they're I'm like,

2:17:50

>> by the way, they know that, too.

2:17:51

>> I'm enslaved by them.

2:17:52

>> Yes.

2:17:53

>> You know, and I just want their

2:17:54

attention. Any small little shred, I'm

2:17:56

like,

2:17:57

>> boo your son, you keep them in check.

2:17:59

>> Whereas like my sons, I keep the I'm

2:18:01

doing everything that I was supposed I

2:18:02

think I'm supposed to be doing. Now, the

2:18:04

good news is my, you know, daughters are

2:18:06

just different. Like, they're girls.

2:18:07

They're just, so they don't need the

2:18:09

same kind of like tough loveish,

2:18:11

>> right?

2:18:12

>> You know, but then my boys reveal their

2:18:14

characteristics in ways that really

2:18:16

surprise me. And I'm just like, man,

2:18:17

this is so [ __ ] awesome. Parenting

2:18:19

has been the best. Like, when I again,

2:18:21

like slowing down and actually being in

2:18:23

it,

2:18:24

>> and I'm like, [ __ ] this is amazing.

2:18:25

>> It is pretty amazing. And watching your

2:18:28

kids get really good at things is really

2:18:30

fascinating. It's fascinating. I told

2:18:31

you this story before, but like you know

2:18:34

my son, my oldest son, this is my

2:18:36

17-year-old. It's just a great kid.

2:18:40

He goes and he's like, "Okay, I'm

2:18:41

applying for college." And I'm like,

2:18:43

"Great. Let me take you to the Naval

2:18:44

Academy, West Point. Let me show you

2:18:46

these servicemies." And he sees those

2:18:48

and he's like, "These are incredible."

2:18:49

But then he's like, "I think I want to

2:18:50

go to like, you know, Georgetown or

2:18:52

Vanderbilt or whatever." And I'm like,

2:18:54

"Hey man, that's like um just a bigger

2:18:56

version of your high school and

2:18:58

whatever. if that's what you want to do,

2:19:00

you do you. And you know, um, but you

2:19:04

know, my the I'll help you like kind of

2:19:07

get to the starting line here, but

2:19:09

you're on your own. And he had to get a

2:19:11

job because I'm like, if you're going to

2:19:12

get into these schools, you got to get a

2:19:13

job. And so he tries to

2:19:16

last summer, I just started [ __ ]

2:19:18

screaming at him. And I'm like, you

2:19:21

[ __ ] louse, you haven't done

2:19:22

anything. And this is at like another

2:19:24

kid's at our at our son's birthday

2:19:25

party. I scream at him. He starts

2:19:28

crying. I'm like, "You need to do more."

2:19:30

Then my wife screams at him. He starts

2:19:33

crying again. Then my ex-wife screams at

2:19:35

him. He starts crying again.

2:19:38

And he just goes, "I'm out of here." He

2:19:40

walks out. Meanwhile, I start panicking

2:19:43

and I'm like, "I got to tiger dad this

2:19:44

situation." So, I start texting a few

2:19:47

friends trying to figure out, "Hey, can

2:19:48

I, you know, do you guys want to hire

2:19:49

this kid? He's like really, you know,

2:19:51

he's pretty smart kid. Did all this

2:19:52

stuff in robotics, yada yada." One of

2:19:55

them says, "I'd be willing to interview

2:19:57

him." I call him and he's like, "Dad, I

2:20:01

got a job." I said, 'What do you mean

2:20:02

you got a job? Said, 'I went around

2:20:05

downtown,

2:20:07

went to all these places and I was in a

2:20:08

McDonald's and um the woman was having a

2:20:12

little bit of difficulty speaking

2:20:13

English, so I just booked her in

2:20:14

Spanish. I got the application. I sat

2:20:16

down at the desk and the guy having

2:20:17

lunch beside me said, "Hey, I heard you

2:20:20

needed a job and uh I really like the

2:20:23

way you talked to this woman. I'm the

2:20:25

general manager of the car wash down the

2:20:26

street. Come and work for me."

2:20:29

And I said, "Well, what are you going to

2:20:30

do?" He goes, "I'm going to go work

2:20:32

there." And I said, "Okay, well, I got

2:20:34

this other interview for you as well, so

2:20:35

you should see maybe you can do both."

2:20:37

Anyways, the end of the story is he did

2:20:39

he did these two jobs. He worked at a

2:20:40

robotics firm, but then he worked at a

2:20:42

car wash. And when I tell you this

2:20:44

story, I am so proud of this kid because

2:20:45

of the car wash. Because that car wash

2:20:48

thing, he was he would come home and

2:20:49

he's like, "Man, you have no idea how

2:20:51

people live." And I'm like, "What do you

2:20:52

mean?" He's like, "The stuff that I find

2:20:54

in the trunk when I have to vacuum these

2:20:56

cars and clean out the cars." And I'm

2:20:58

like, "Bro, that is a gift. You have

2:21:00

given a [ __ ] gift. That is the thing

2:21:02

that if you take with you, you'll be

2:21:04

golden the rest of your life." Because

2:21:06

all this other [ __ ] is all kind of

2:21:07

manufactured. I help because I'm

2:21:09

anxious. I'm insecure. Mhm.

2:21:11

>> But that [ __ ] you did on your own. And

2:21:13

that thing is what people will [ __ ]

2:21:14

respect when push comes to shove.

2:21:16

>> It's also jobs that suck are really good

2:21:18

for you.

2:21:18

>> So good. I used to work at Burger King

2:21:20

when I was 14.

2:21:22

>> Man, let me tell you.

2:21:23

>> You were 14 and you had a job.

2:21:26

>> When my dad had to stay behind like we

2:21:30

were my dad was a diplomat in the

2:21:32

embassy of Sri Lanka in Canada. This

2:21:35

[ __ ] war in Sri Lanka is crazy. He

2:21:37

writes this essay. His life is

2:21:38

threatened. So he files for refugee

2:21:41

status. He gets it.

2:21:44

He gets kicked out of the embassy. So he

2:21:47

doesn't have a job. My mom becomes a

2:21:48

housekeeper

2:21:50

and we're kind of toiling in this

2:21:51

poverty cycle. So 14 you have to I had

2:21:54

to get a job and I would take the money

2:21:56

and you know we buy I buy the bus

2:21:58

passes. I would buy some of the

2:21:59

groceries. We just trying to make it all

2:22:01

work right. And uh I got a job at the

2:22:04

Burger King.

2:22:05

This is another example where I was

2:22:08

like, I'm going to go get a job. Hey,

2:22:10

can you drive me to the interview? And

2:22:12

my dad's like, "No,

2:22:16

get on your [ __ ] bicycle and go." And

2:22:18

I thought, "Bro, we need this. You need

2:22:20

the money more than I do. Why are you

2:22:22

making me bicycle?" But I bicycled and I

2:22:25

got the job and I worked there. And I

2:22:27

used to work the night shift.

2:22:28

14-year-old kid, man. Wow.

2:22:30

>> From [ __ ] 8 till 2 in the morning.

2:22:32

And I would have to clean this like 8:00

2:22:34

p.m. to 2 in the morning.

2:22:34

>> Then you had to go to school in the

2:22:35

morning.

2:22:36

>> No, then I this was always like Friday,

2:22:38

Saturday, Sunday.

2:22:39

>> Wow.

2:22:39

>> Thursday, Friday. Sorry. Thursday,

2:22:40

Friday, Saturday. And then Yeah. Some

2:22:42

days I would have to go to school. But

2:22:44

And why did I work until two? Because

2:22:46

when the restaurant closes,

2:22:48

you get whatever the food is left over,

2:22:50

right? So like you get a couple chicken

2:22:52

sandwiches, you get like the, you know,

2:22:54

the the version of the McNuggets that

2:22:56

Burger King had, a couple whoppers, and

2:22:58

you take them home.

2:23:02

But the amount of vomit that I had to

2:23:04

clean up the bathroom, you can't

2:23:07

imagine, man, the a downtown Burger King

2:23:10

near bars, you know, after closing time,

2:23:14

the [ __ ] you see.

2:23:16

>> Oh, wow.

2:23:16

>> And the [ __ ] you deal with. And all I

2:23:19

could think of was like, I just want to

2:23:20

get the [ __ ] out of here. But that was

2:23:23

so valuable for me.

2:23:24

>> Yeah,

2:23:25

>> that was so valuable for me. Um,

2:23:29

and then I worry that my, you know, kids

2:23:31

don't get exposed to it, but when my son

2:23:32

got it, maybe I'm overimposing too much

2:23:34

about it, but it's like I'm like, man,

2:23:36

that that car wash thing is really going

2:23:38

to be the thing that separates you in

2:23:40

life.

2:23:40

>> Yeah. Doing something that sucks. It it

2:23:42

also

2:23:43

>> just being humble and grinding through

2:23:44

that [ __ ] you know? Do you realize like

2:23:47

this is sometimes people they don't pick

2:23:49

a path and they just have a job and they

2:23:52

don't like it and they stay with this

2:23:54

thing they don't like forever and that's

2:23:56

not what you want.

2:23:58

>> No,

2:23:58

>> it's not what you want. But the

2:24:00

development like the learning how to do

2:24:03

something that sucks and grinding

2:24:04

through it

2:24:05

>> and still doing it well.

2:24:06

>> Yeah. You know, doing it well.

2:24:08

>> Make a make a Whopper. Be there on top.

2:24:09

>> I know how to [ __ ] make a Whopper.

2:24:11

>> Yeah.

2:24:11

>> Do you know what I mean?

2:24:12

>> Yeah.

2:24:13

uh make the fries, change the oil, all

2:24:15

that [ __ ]

2:24:16

>> And then when you apply that those

2:24:18

lessons to something you actually love

2:24:21

and you work hard at something you love,

2:24:23

>> magical.

2:24:23

>> Oh, it's incredible. It's a real gift.

2:24:26

>> It's a real gift.

2:24:27

>> Yeah. I mean, you know, some people they

2:24:29

don't appreciate the process, you know,

2:24:32

and it's hard to because like when

2:24:34

you're young and you're going through

2:24:36

these difficult jobs and these things

2:24:37

that suck and you don't know how it's

2:24:39

going to turn out, you know, and a lot

2:24:41

of times people aren't really educated

2:24:42

in what a process actually is and about

2:24:45

how it does develop character and it

2:24:47

does develop discipline and that these

2:24:49

things are actual skills that you can

2:24:51

apply to other things in life. You just

2:24:54

think, "God, I'm a [ __ ] loser." I

2:24:55

have a I have a visual for this. I

2:24:58

always ask myself, am I in the engine

2:24:59

room right now?

2:25:01

>> This is my way of saying like an engine

2:25:02

room is a little hot. It's a little

2:25:04

uncomfortable, but it's where all the

2:25:07

[ __ ] is happening. It's where the [ __ ]

2:25:08

is being made.

2:25:10

>> And so I'm like, it's a little, you

2:25:12

know, discomforting,

2:25:13

>> but I got to be in there. And there are

2:25:15

days where, and there'll be weeks

2:25:17

>> where that's all I do. I'm just in it,

2:25:20

you know? I don't I'm not good at

2:25:21

responding to emails sometimes or

2:25:23

whatever because there'll just be weeks

2:25:24

where I'm in it and it's an incredible

2:25:27

visual for me because I'm like yeah this

2:25:29

is like where like I'm grounded

2:25:31

>> and I like feel myself and then when I

2:25:33

when I look at my like my health

2:25:37

that's when like I just feel like really

2:25:39

good about myself like not insecure and

2:25:43

my vitals are different like it's crazy

2:25:45

like my [ __ ] HRV like my HRV

2:25:49

craters

2:25:51

when I'm like just like you know

2:25:55

insecure

2:25:56

>> of course

2:25:57

>> but why is that like it's it's your it's

2:25:59

your heart rate variability should have

2:26:01

nothing to do with your like

2:26:03

>> disposition and your mood

2:26:05

>> well your mind is the idea that your

2:26:08

mind is separate from the body is crazy

2:26:10

>> it's crazy

2:26:10

>> it's not and

2:26:12

>> but is your HRV lower when you're just

2:26:14

out of sorts

2:26:15

>> yes probably right

2:26:16

>> I'm sure yeah I don't really monitor it

2:26:18

that much Yeah.

2:26:20

>> And I'm I try not to ever get out of

2:26:21

sorts, too. And one of the ways that I

2:26:24

keep from getting out of sorts is daily

2:26:26

discipline. Like it's if I if I have

2:26:28

days where I'm sure it gets out of sorts

2:26:30

if I have a few days in a row where I

2:26:32

don't work out, but I I work out almost

2:26:34

every day. And if I'm not working out,

2:26:36

I'm still cold plunging and going to the

2:26:38

sauna and stretching. I'm always doing

2:26:40

something. And if I don't do something,

2:26:42

I feel like I'm [ __ ] up. And then

2:26:44

then I can

2:26:45

>> So, does it matter what it is? Meaning,

2:26:46

as long as it's a routine.

2:26:48

>> Yeah. Well, I I do it all myself. I

2:26:50

don't have a trainer, but I write things

2:26:52

down. I write down what I want to

2:26:53

accomplish. I write down what I'm going

2:26:54

to do, and then I just do it. I like a

2:26:57

robot force myself to do it.

2:26:59

>> Yeah.

2:27:00

>> And then I always feel better after it's

2:27:01

over. And it's always the hardest part

2:27:03

of my day.

2:27:03

>> Yeah. And so it makes everything else so

2:27:05

much easier because it's I [ __ ] work

2:27:07

out hard

2:27:08

>> and so everything else is pretty easy,

2:27:11

>> you know, because the strain like just

2:27:12

being in that [ __ ] cold water or just

2:27:15

going through Tabatas on a a dye bike

2:27:18

like this shit's hard. It's really hard.

2:27:20

Like I could die right now hard. And so

2:27:22

everything else is like how how hard's

2:27:24

it going to be? Oh, it's uncomfortable.

2:27:26

Oh boohoo, you know? Like I think it's

2:27:28

important to go through that. I I really

2:27:31

think it is, you know? I really think it

2:27:33

is and that that's a the difference

2:27:35

between,

2:27:37

>> you know, sanity and like having a very

2:27:39

slippery grip on your your own personal

2:27:43

sovereignty. I think a lot of it is like

2:27:46

you have to choose it. It has to be like

2:27:50

elective

2:27:52

voluntary adversity. Like you have to

2:27:55

choose to do it.

2:27:56

>> Yeah. I that's a really great way of

2:27:57

saying it. Voluntary adversity. If it's

2:27:59

forced upon you,

2:28:00

>> you can kind of compartmentalize

2:28:02

>> and then you get angry like [ __ ] this

2:28:03

bitter and resentful making me do stupid

2:28:05

[ __ ] But if you force yourself to do

2:28:07

it, you know,

2:28:08

>> this why these special forces guys are

2:28:09

such [ __ ] animals.

2:28:10

>> Of course,

2:28:11

>> they're choosing,

2:28:12

>> right? Exactly. And they develop that,

2:28:15

you know, this mentality when you're

2:28:17

around other people that are also

2:28:18

savages. You know, you just you realize

2:28:21

like there's other people out there in

2:28:22

the world that are not making excuses.

2:28:25

they are getting after it every day and

2:28:27

they are pushing every day. And the more

2:28:29

you can surround yourself with people

2:28:30

like that, the more people the people

2:28:32

that complain about nonsense and the

2:28:34

find excuses and focus on other people

2:28:37

and [ __ ] about things and why is she

2:28:40

doing this? Why is this happening for

2:28:42

him?

2:28:44

>> Yeah,

2:28:44

>> it's loser mentality. And if you're

2:28:46

around more winners, you know, you

2:28:48

absorb that. You imitate your

2:28:49

atmosphere. Yeah, it's very important

2:28:50

and it's very hard for people,

2:28:52

especially young people, to find

2:28:55

positive influences and to find positive

2:28:58

groups. And I think it's one of the

2:29:00

reasons why a lot of young people

2:29:02

gravitate towards podcast because they

2:29:03

get to hear interesting conversations

2:29:05

with really accomplished people that are

2:29:07

fascinating that are unlike anybody that

2:29:09

they're around on a daily basis,

2:29:12

>> you know. And that that's also one of

2:29:13

the reasons why it's important to find

2:29:15

some that's why martial arts are so good

2:29:17

for young people because you're around

2:29:19

other people that are doing this really

2:29:21

difficult thing and other sports too

2:29:23

whether it's football or wrestling

2:29:24

whatever it is.

2:29:25

>> I actually found like you know the last

2:29:26

few years I go out of my way to not

2:29:28

isolate myself. That's one thing like

2:29:29

being around other people engaging in

2:29:31

things.

2:29:32

>> Yes.

2:29:32

>> Has been really healthy for me.

2:29:33

>> Oh for sure.

2:29:34

>> Oh my god. And I just found like what

2:29:36

the [ __ ] am I doing? It's like

2:29:37

everything is in my little house by

2:29:38

myself with everybody everything comes

2:29:40

to me. It's so odd.

2:29:42

>> It's odd. It's really odd. Very

2:29:43

unhealthy.

2:29:44

>> And it starts to [ __ ] you up in the

2:29:45

bind.

2:29:45

>> And then your interaction with humans is

2:29:47

only on the internet. It's terrible. You

2:29:49

know,

2:29:50

>> or with people that are sickantically

2:29:51

either being paid or need something from

2:29:53

you.

2:29:54

>> Yeah.

2:29:55

>> And then I think you're in a really bad

2:29:56

place.

2:29:57

>> Absolutely.

2:29:57

>> Whereas like if you're in the grind with

2:29:59

other people, they're beating you at

2:30:00

things. It's great.

2:30:01

>> Yeah. Yeah, if you're in a situation

2:30:03

where there's a bunch of sickopantically

2:30:04

connected people to you and they're just

2:30:06

all kissing your ass and I mean we all

2:30:08

know people that are like the heads of

2:30:09

companies and that are just like [ __ ]

2:30:11

tyrants.

2:30:12

>> I think the the the the trap about being

2:30:14

successful because it's not everything

2:30:16

it's wrapped up to be is exactly that.

2:30:17

You become so isolated that you become

2:30:20

this like very caricaturous version of

2:30:22

yourself

2:30:23

>> because you forget what it's like to

2:30:25

just a basic example like wait in line,

2:30:28

be kind to other people, be polite, like

2:30:30

be accommodating, have some empathy,

2:30:32

>> right?

2:30:32

>> Where are you put in that situation to

2:30:34

do those things,

2:30:35

>> right? You forget that you're just a

2:30:36

person.

2:30:36

>> You're just a [ __ ] person.

2:30:38

>> And if you achieve some level of success

2:30:40

that you're trying to you're trying to

2:30:42

achieve this level of success so you

2:30:44

elevate past being a person, you're

2:30:46

missing the point. like you're never

2:30:47

going to and if you do it'll come at a

2:30:50

price.

2:30:50

>> I thought being successful was supposed

2:30:52

to write all the wrongs that I felt like

2:30:56

I missed

2:30:58

and it turns out nobody gives a [ __ ]

2:31:00

>> No.

2:31:01

>> And it does none of that.

2:31:02

>> I think it's all the process. The all of

2:31:06

life is the process.

2:31:07

>> I agree.

2:31:08

>> I think as soon as you think that

2:31:10

there's a goal like, "Oh, I'm going to

2:31:11

retire and experience my golden years."

2:31:13

I think it's all horseshit. And that's

2:31:15

one of my main fears about AI. My my

2:31:19

main one of my main fears about this

2:31:21

idea of universal high income and

2:31:24

everyone's going to have, you know,

2:31:25

ultimate abundance. It's like where does

2:31:27

anybody find purpose and meaning? And

2:31:30

where do the where do you take whatever

2:31:34

this thing is that the mind is

2:31:37

constructed of these these needs that

2:31:39

the mind has that have to be satisfied

2:31:42

in order to achieve sanity? in order to

2:31:45

achieve some sort of like place where

2:31:48

you can be at peace,

2:31:49

>> fulfillment.

2:31:49

>> Yeah, you have to do you're going to

2:31:51

have to do something, man. You're going

2:31:52

to have to do something. And I mean,

2:31:54

maybe it could just be jiu-jitsu and

2:31:57

golf and find some stuff that you enjoy

2:31:59

doing and take some benefit in that. But

2:32:03

boy, that's not been the case for

2:32:06

hundreds of years. You know, that's not

2:32:08

how human beings have exist. I mean, but

2:32:11

also part of me says, why do we have to

2:32:14

work to find those things? Why can't we

2:32:17

why why is it all that?

2:32:20

>> Well, you got to find the thing that's

2:32:22

not work,

2:32:23

>> right? But but I'm getting at is like

2:32:25

why is our identity all tied up in money

2:32:30

and and and and

2:32:32

just things and objects and stuff. And

2:32:36

this is a fairly new thing in human

2:32:38

society, right?

2:32:40

>> Why can't it transform into

2:32:44

m like your basic needs are all met?

2:32:47

Like nobody ever has to worry about

2:32:48

starving again. Nobody ever has to worry

2:32:50

about not having a home to sleep in.

2:32:52

Nobody ever has to worry about not

2:32:53

having healthcare. Nobody ever has to

2:32:55

worry about not having education. So

2:32:56

then it becomes find a purpose with your

2:32:59

life. And as a society, can we adjust?

2:33:03

Can we gravitate towards a new way of

2:33:07

existing in meaning? And it would

2:33:08

probably be great. In one way, it'd be

2:33:11

great because we wouldn't have to be

2:33:14

constantly thinking, why does he have

2:33:15

that and I don't have that and this and

2:33:16

that. Instead, it would probably be

2:33:19

like, what can I do to get better at the

2:33:21

thing that I love, right?

2:33:23

>> What you know, and

2:33:24

>> or let me be a part of a project to do

2:33:26

something that seems implausible,

2:33:28

>> but I feel like I'm in the engine room

2:33:30

every day. This is great. I'm toiling

2:33:31

with these guys. probably not going to

2:33:34

work. Some crazy convoluted thing that

2:33:36

has a .01 chance of success

2:33:40

>> that can captivate a lot of people.

2:33:42

>> Yes. You know,

2:33:43

>> the process.

2:33:43

>> The process.

2:33:44

>> Yeah.

2:33:45

>> The process.

2:33:45

>> The process is everything. And there's

2:33:47

no I used to like think backward.

2:33:49

>> There is no attention in the process,

2:33:50

>> right?

2:33:51

>> There's only attention in the outcome,

2:33:53

>> right?

2:33:54

>> Do you see what I mean?

2:33:55

>> Absolutely.

2:33:56

>> Which is another clue and a secret that

2:33:58

that's actually where you should be

2:33:59

focused.

2:33:59

>> Well, you might get attention, but

2:34:00

that's not what you want. What you want

2:34:02

is the process to work out. You you want

2:34:04

to get better at whatever it is you're

2:34:05

doing and get that thing to a better

2:34:07

place than it is right now currently.

2:34:09

Right. That's what you're thinking of.

2:34:10

You're not thinking of I am going to get

2:34:12

all this attention. I'm going to be on

2:34:14

the cover of a magazine.

2:34:16

Yeah. Can't It can't be that. That's not

2:34:19

good for anybody. But everybody thinks

2:34:21

that's what they're going to get. Oh,

2:34:23

I'm going to get this.

2:34:23

>> Everybody thinks that's what they want.

2:34:25

>> Yeah. Right.

2:34:27

>> And the problem with that is that it's

2:34:29

not what you want.

2:34:30

>> No.

2:34:31

And then now we're going to completely

2:34:33

upend

2:34:34

potentially all of that.

2:34:38

>> Yeah. Well, maybe it'll come inside

2:34:40

it'll come it'll coincide with the hive

2:34:43

mind technology.

2:34:44

>> This hive mind thing actually that you

2:34:46

say I find very compelling because this

2:34:48

idea of like how do you govern an AI?

2:34:53

Each of us individually are not capable,

2:34:55

but I think you, me, like 10,000, 100

2:34:57

thousand people working together.

2:35:01

The question is, are we smarter?

2:35:03

And I think there's a reasonable chance

2:35:05

that that could be true. And then the

2:35:07

other version of the hive mind is here

2:35:08

are all these like crazy ideas that

2:35:10

would just make the world incredible.

2:35:13

And a group of a thousand people go off

2:35:15

and they kind of jointly work on that

2:35:17

together. That I find super fascinating.

2:35:20

Like I that could be it. Like it could

2:35:22

be like, you know, a thousand physicists

2:35:24

are like, "We're going to create this

2:35:26

new interstellar form of

2:35:27

transportation." And they just go off

2:35:28

and they're just like they don't have to

2:35:30

worry about

2:35:32

existing because all of that's paid for.

2:35:34

>> Well, it also could solve all of our

2:35:36

problems that we have with like halves

2:35:39

and have nots. If we're all one, how

2:35:42

could we tolerate haveotss? How could we

2:35:44

tolerate people living on dirt floors in

2:35:46

third world countries with no access to

2:35:48

clean water? We wouldn't tolerate it

2:35:49

tolerate

2:35:50

>> because we they would be us and we would

2:35:52

understand that.

2:35:52

>> Yeah.

2:35:53

>> I mean it could be like a complete

2:35:55

gamecher in terms of human civilization.

2:35:58

It could really move people into a

2:35:59

complete next direction. I mean it could

2:36:01

eliminate crime and violence. Yeah.

2:36:03

>> Which sounds insane. Like boy that's so

2:36:06

utopian. Like oh why don't you suck on

2:36:08

some crystals you [ __ ] hippie. But

2:36:10

legitimately if look if everybody has a

2:36:13

cell phone which essentially everybody

2:36:14

does right right now in this time and

2:36:16

age. If we get to a point where

2:36:18

everybody is connected, everybody is

2:36:21

hive mind connected, you're there's

2:36:24

we're all you're not going to just be

2:36:26

able to drive by a homeless encampment,

2:36:28

>> right?

2:36:28

>> You won't you'll feel it. You'll feel

2:36:31

it. It won't be like, "Hey, you [ __ ]

2:36:32

losers. Hit the gas." It's going to be

2:36:35

like, "We need to solve this. We need to

2:36:37

get these people counseling, mental

2:36:39

health crisis, get them off the drugs,

2:36:41

whatever it is that's wrong with them."

2:36:44

>> I mean, that's an incredible idea.

2:36:46

>> Yeah. You know, like when an airplane

2:36:48

kind of like goes like this and your

2:36:49

stomach goes and you just feel it.

2:36:51

>> Could you imagine like you drive by a

2:36:53

homeless encampment and that's what you

2:36:54

feel? Like you feel like

2:36:56

>> something's wrong.

2:36:56

>> And we'll all feel it collectively. If

2:36:59

we're all connected and we all feel

2:37:01

things connectively, we will actively

2:37:03

work together to solve these problems.

2:37:05

And if we're dealing with a if if we

2:37:07

really get to a point of abundance, like

2:37:09

true abundance, where resources are not

2:37:12

an issue and no one's starving, we could

2:37:15

really fix all the problems that like

2:37:18

>> none of them are insurmountable. None of

2:37:20

them are breathing underwater, right?

2:37:22

None of them are flying to the sun. None

2:37:24

of them, right? So all of them are

2:37:26

things that could be if we took all the

2:37:29

world's resources, socialism doesn't

2:37:31

work, right? Why does it not work?

2:37:33

because it rewards lazy people and it

2:37:34

punishes ambitious people. It's not

2:37:36

doesn't doesn't work with human nature,

2:37:38

but it would work if you have [ __ ]

2:37:40

hive mind. If we all we all understand

2:37:43

what it means to put in effort. We all

2:37:45

understood what what each other are

2:37:46

feeling and thinking,

2:37:47

>> right?

2:37:48

>> And we all compiled resources and fixed

2:37:51

all of our social problems. Like

2:37:53

literally stop all wars, stop all crime,

2:37:57

stop all violence, stop all poverty.

2:38:00

Done. And then what do we do? We work

2:38:03

together to solve whatever the [ __ ] else

2:38:04

is wrong with you society.

2:38:06

>> Well, it's more like what is left over

2:38:08

that we haven't figured out.

2:38:10

>> Think about what the world was like

2:38:12

before the internet. It's almost

2:38:13

impossible to imagine, but we both grew

2:38:15

up without it.

2:38:16

>> Yeah.

2:38:17

>> And Yeah. And so we're entering into

2:38:19

this new world. Think about what world

2:38:22

was like without the hive mind, but yet

2:38:24

we all grew up without it. Like that

2:38:26

might be the next thing. The thing that

2:38:28

I remember the most about that era is I

2:38:32

had a positive sum view of everybody

2:38:35

>> really.

2:38:36

>> Meaning there weren't like the the bad

2:38:39

actors were pretty bad but yeah

2:38:41

generally like I looked up to most

2:38:44

business people like the people that I

2:38:45

now I feel like have been a little bit

2:38:47

unmasked then to me were pristine.

2:38:49

>> Oh that's interesting.

2:38:50

>> Like the Bill Gateses of the world, you

2:38:51

know. I was like man I really aspire to

2:38:53

be Bill Gates when I was like 13 or 14.

2:38:56

It just seemed like

2:38:57

>> now you're like, why is he buying all

2:38:58

the farmland? This [ __ ] weirdo.

2:39:00

>> I mean, it's a [ __ ] so funny. He uh

2:39:03

he bought this like 45,000 acres in

2:39:07

4,500 acres. I can't get the order of

2:39:09

magnet right uh in Phoenix to build his

2:39:11

own digital city.

2:39:13

>> Yeah.

2:39:14

>> Okay.

2:39:14

>> It's like weird. So, I bought the 1700

2:39:16

acres beside him.

2:39:20

>> That's hilarious.

2:39:21

>> [ __ ] you.

2:39:22

>> It's a very odd thing. It's a very odd

2:39:25

thing when people get exposed and you

2:39:27

just go like what the [ __ ] is that guy

2:39:29

really all about

2:39:30

>> and but also like how isolated is he?

2:39:33

>> Oh, he's been he's been isolated for 50

2:39:35

years,

2:39:36

>> right? Like who are his friends and how

2:39:38

how many people does he have?

2:39:39

>> Must be very hard to be him actually. I

2:39:41

I mean

2:39:41

>> especially now that he's divorced,

2:39:42

right? So now he's got no one going but

2:39:45

that speech [ __ ] sucked.

2:39:46

>> Yeah, he's I mean he has a long-term

2:39:48

partner. Um she seems like a lovely

2:39:51

woman. Um, but yeah, it's just got to be

2:39:54

super lonely.

2:39:54

>> It's got to be.

2:39:56

>> It's not I to me it's not worth that

2:39:58

level of I don't even know what is it.

2:40:01

It's like material success at least

2:40:03

measured in the outside world. I don't

2:40:04

know what it is, but it's not

2:40:06

it's a lot, man. This is like I like I

2:40:08

don't know how Elon does it. Like it's a

2:40:10

lot. It's super isolating.

2:40:11

>> Yeah.

2:40:12

>> It's it's just he's very by himself.

2:40:16

>> Mhm.

2:40:17

>> And he's going to be even more isolated

2:40:19

in a matter of a few months.

2:40:20

>> Yeah. And that's unfortunate because you

2:40:23

have very empathetic, very kind of like

2:40:25

sensitive people like that I think need

2:40:26

other people.

2:40:28

>> Well, he's got people around him, but

2:40:30

he's got very few people around him that

2:40:33

can kick reality at him.

2:40:35

>> Yeah.

2:40:35

>> You know, that that is a bit of a

2:40:37

problem, but he still seems to be having

2:40:40

fun. Every time I'm around him, we have

2:40:41

a bunch of laughs. Like, he's fun to

2:40:43

hang out.

2:40:44

>> He's got an incredible sense of humor.

2:40:45

We um Jamie and I went down uh to one of

2:40:49

the rocket launches at SpaceX. Yeah, we

2:40:51

went down there crazy

2:40:52

>> and we watched from the ground while I

2:40:56

took off, which is incredible cuz it's

2:40:57

like how far was it, Jamie? It was like

2:40:59

two miles away from us.

2:41:00

>> A mile mile and a half.

2:41:01

>> So like it's a mile and a half. You feel

2:41:03

it in your chest. Have you been when a

2:41:05

when a rocket launches? You been there,

2:41:06

dude? It's bananas. The [ __ ] thing

2:41:08

like first of all, it doesn't look that

2:41:09

far. It looks like it's like

2:41:12

>> maybe quarter mile. it. I don't I'm just

2:41:14

not good at judging.

2:41:15

>> This is a starship.

2:41:16

>> Oh yeah. So you feel it.

2:41:20

You like his kids started crying like we

2:41:22

want to go inside. Like it's disturbing

2:41:24

like the amount of energy that's coming

2:41:27

out of these [ __ ] rocket boosters.

2:41:29

And then I hung out with him in the

2:41:31

command center while the rocket was

2:41:33

flying through space and we're watching

2:41:34

it on all these monitors and then lands

2:41:37

in the water in Australia. He's cracking

2:41:39

jokes the whole time because the thing

2:41:41

is like losing pressure because it's

2:41:43

they're stress testing all the stuff

2:41:45

which is really funny when really dumb

2:41:47

people, oh he's a [ __ ] dumbass, his

2:41:48

rockets keep blowing up. Like like they

2:41:51

just don't understand like the only way

2:41:53

you find out what the capability of this

2:41:55

technology is is you have to like let it

2:41:58

blow up and then you go, "Okay, it needs

2:41:59

to be thicker. It needs to be this and

2:42:01

that and we need to add these things and

2:42:02

there's sensors everywhere." And so he's

2:42:04

cracking jokes the entire time while

2:42:06

this thing is like losing pressure. And

2:42:07

it eventually wound up landing and it

2:42:09

was fine, but it did have a hole in it.

2:42:12

But it was just like he's laughing like

2:42:14

he's having a good old time. He's not

2:42:15

freaked out. No,

2:42:16

>> you know, he he's uniquely built to

2:42:19

handle it.

2:42:19

>> I uh when there was a rocket launch in

2:42:22

Vraenberg in California and I chartered

2:42:25

a Pilates and I because you can get like

2:42:28

a little like propeller plane.

2:42:30

>> Oh, okay. And I went around and around

2:42:32

and I have this video of it kind of like

2:42:34

coming up and through cuz like

2:42:36

>> how close were you?

2:42:40

>> 100 miles.

2:42:41

>> Oh wow.

2:42:42

>> But you but it's like right there.

2:42:43

>> Uhhuh.

2:42:44

>> You know cuz the distance and it's

2:42:46

coming up and I'm kind of going around.

2:42:48

It was the craziest thing. It was cool.

2:42:50

It was super cool.

2:42:51

>> That [ __ ] is super cool.

2:42:53

>> It's very cool. It's very cool. I mean

2:42:55

just Starbase is bananas. Just when you

2:42:58

go down there and they have their own

2:42:59

town, the whole thing is straight.

2:43:00

There's [ __ ] cyber trucks everywhere.

2:43:02

I'm like, how do you find your car?

2:43:03

Like,

2:43:04

>> is it is it an incorporated town? It

2:43:06

started off as unincorporated, but it

2:43:08

own thing now.

2:43:09

>> I believe it's its own town. And

2:43:11

>> is there a mayor?

2:43:12

>> That's a good question. I think there

2:43:13

is. I think we talked about this. I

2:43:16

don't remember though. But the actual

2:43:19

factory itself is nuts cuz I Jamie and I

2:43:23

were both like, "This is way bigger than

2:43:25

I thought it was going to be." And the

2:43:26

rockets are way bigger than you thought.

2:43:27

And like the garage doors are [ __ ]

2:43:29

bananas.

2:43:30

>> They got a city government website

2:43:33

commission mayor.

2:43:37

>> That's crazy.

2:43:39

>> Bobby Bobby Peted. Bobby Peted is the

2:43:41

mayor.

2:43:42

>> They have their own little Bobby. That's

2:43:43

awesome.

2:43:44

>> Irish pub and it's like it's really

2:43:46

cool. They have really good food. you

2:43:47

know, when he uh when he opened the

2:43:48

first uh Gigafactory, which was in

2:43:50

Nevada, we had a party and uh like it

2:43:54

was like a small opening thing and so we

2:43:55

all drove in there and I have a video of

2:43:58

me in a just like a pickup truck driving

2:44:00

into the thing. I started the video and

2:44:04

I think it was 43 seconds until it

2:44:06

ended. And this is like, you know, a

2:44:08

decade ago and I thought to myself, this

2:44:10

is implausible. Like I've never even

2:44:12

contemplated things that could be built

2:44:14

this big. I didn't think it was allowed.

2:44:16

I don't even know how something like

2:44:17

this works.

2:44:19

>> And I was like, how does how do you

2:44:21

envision this whole thing works? Like

2:44:23

simple.

2:44:24

>> Raw materials in the front, cars out the

2:44:27

back.

2:44:29

I'm like, that's it. It sounds so

2:44:32

simple.

2:44:33

>> Well, he thinks big.

2:44:35

>> He thinks big. And thank God he's

2:44:36

around. I mean, if he wasn't around, if

2:44:38

he hadn't purchased Twitter, I think our

2:44:41

entire civilization would look very

2:44:42

different.

2:44:43

>> Very different.

2:44:44

>> It would. I mean, that sounds like a

2:44:45

very grandiose thing to say.

2:44:46

>> Sounds hyperbolic, but you're right.

2:44:48

>> I think it's true because I don't I

2:44:50

think free speech is a core component of

2:44:52

our civilization, and I don't really

2:44:55

think we had it.

2:44:56

>> I think it was curated, and it was very

2:44:58

tightly controlled by the actual federal

2:45:00

government, which is spooky.

2:45:01

>> No, no. It decided what we should be

2:45:05

paying attention to. Yes.

2:45:06

>> Just just put it very simply without

2:45:08

kind of like

2:45:09

>> And that's not right.

2:45:10

>> Right. Because when they're telling you

2:45:13

to pay attention to this and the actual

2:45:16

issue is this and you cannot, then you

2:45:19

can't fix what's actually broken,

2:45:21

>> right?

2:45:21

>> And you start to we start to basically

2:45:23

be like we're we're part of just a a

2:45:26

useful idiot for these people.

2:45:27

>> Yes.

2:45:28

>> And that's not right.

2:45:29

>> It's not right.

2:45:31

>> Listen, man. This was a lot of fun. It's

2:45:32

always great to talk to you. Thank you

2:45:33

very much for doing this. It was very

2:45:35

cool. Um let's do it again sometime. All

2:45:38

right. Thank you. All right. Bye,

2:45:40

everybody.

Joe Rogan Experience #2494 - Chamath Palihapitiya

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